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Forecasting

Forecasting

QUALITATIVE TECHNIQUES
QUANTITATIVE TECHNIQUES
ECONOMETRIC FORECASTING
EVALUATING FORECASTS
MAKING A FORECAST
BIBLIOGRAPHY

Forecasting involves the generation of a number, set of numbers, or scenario that corresponds to a future occurrence. It is absolutely essential to short-range and long-range planning. By definition, a forecast is based on past data, as opposed to a prediction, which is more subjective and based on instinct, gut feel, or guess. For example, the evening news gives the weather forecast, not the weather prediction. Therefore, forecasts should not be mistaken for predictions because forecasting is based on traceable and observable data and trends as opposed to mere assumptions. Properly prepared forecasts should be able to address blips that arise from one-off spread factors as well as other major seasonal factors. Spreadsheets can be used for analyzing past trends and determining forecasts.

Forecasting is based on a number of assumptions:

  1. The past will repeat itself. In other words, what has happened in the past will happen again in the future.
  2. As the forecast horizon shortens, forecast accuracy increases. For instance, a forecast for tomorrow will be more accurate than a forecast for next month; a forecast for next month will be more accurate than a forecast for next year; and a forecast for next year will be more accurate than a forecast for ten years in the future.
  3. Forecasting in the aggregate is more accurate than forecasting individual items. This means that a company will be able to forecast total demand over its entire spectrum of products more accurately than it will be able to forecast individual stock-keeping units. For example, General Motors can more accurately forecast the total number of cars needed for next year than the total number of white Chevrolet Impalas with a certain option package.
  4. Forecasts are seldom accurate and almost never totally accurate, although some are very close. Therefore, it is wise to offer a forecast range. If one were to forecast a demand of 100,000 units for the next month, it is extremely unlikely that demand would equal exactly 100,000. However, a forecast of 90,000 to 110,000 would provide a much larger target for planning.

William J. Stevenson lists a number of characteristics that are common to a good forecast:

  • Accuratesome degree of accuracy should be determined and stated so that comparison can be made to alternative forecasts.
  • Reliablethe forecast method should consistently provide a good forecast if the user is to establish some degree of confidence.
  • Timelya certain amount of time is needed to respond to the forecast so the forecasting horizon must allow for the time necessary to make changes.
  • Easy to use and understandusers of the forecast must be confident and comfortable working with it.
  • Cost-effectivethe cost of making the forecast should not outweigh the benefits obtained from the forecast.

Forecasting techniques range from the simple to the extremely complex. These techniques are usually classified as being qualitative or quantitative.

QUALITATIVE TECHNIQUES

Qualitative forecasting techniques are generally more subjective than quantitative forecasting techniques. Qualitative techniques are more useful in the earlier stages of the product life cycle, when less past data exists for use in quantitative methods. Qualitative methods include the Delphi technique, Nominal Group Technique (NGT), sales force opinions, executive opinions, and market research.

The Delphi Technique. The Delphi technique uses a panel of experts to produce a forecast. Each expert is asked to provide a forecast specific to the need at hand. After the initial forecasts are made, each expert reads what every other expert wrote and is influenced by their views. A subsequent forecast is then made by each expert. Each expert then reads again what every other expert wrote and is again influenced by the perceptions of the others. This process repeats itself until each expert nears agreement on the needed scenario or numbers.

Nominal Group Technique. The Nominal Group technique is similar to the Delphi technique in that it utilizes a group of participants, usually experts. After the participants respond to forecast-related questions, they rank their responses in order of perceived relative importance. Then the rankings are collected and aggregated. Eventually, the group should reach a consensus regarding the priorities of the ranked issues.

Sales Force Opinions. The sales staff is often a good source of information regarding future demand. The sales manager may ask for input from each salesperson and aggregate their responses into a sales force composite forecast. Caution should be exercised when using this technique as the members of the sales force may not be able to distinguish between what customers say and what they actually do. Also, if the forecasts will be used to establish sales quotas, the sales force may be tempted to provide lower estimates.

Executive Opinions. Sometimes upper-level managers meet and develop forecasts based on their knowledge of their areas of responsibility. This is sometimes referred to as a jury of executive opinion.

Market Research. In market research, consumer surveys are used to establish potential demand. Such market research usually involves constructing a questionnaire that solicits personal, demographic, economic, and marketing information. On occasion, market researchers collect such information in person at retail outlets and malls, where the consumer can experiencetaste, feel, smell, and seea particular product. The researcher must be careful that the sample of people surveyed is representative of the desired consumer target.

QUANTITATIVE TECHNIQUES

Quantitative forecasting techniques are generally more objective than qualitative forecasting methods. Quantitative forecasts can be time-series forecasts (i.e., a projection of the past into the future) or forecasts based on associative models (i.e., based on one or more explanatory variables). Time-series data may have underlying behaviors that need to be identified by the forecaster. In addition, the forecast may need to identify the causes of the behavior. Some of these behaviors may be patterns or simply random variations. Among the patterns are:

  • Trends, which are long-term movements (up or down) in the data.
  • Seasonality, which produces short-term variations that are usually related to the time of year, month, or even a particular day, as witnessed by retail sales at Christmas or the spikes in banking activity on the first of the month and on Fridays.
  • Cycles, which are wavelike variations lasting more than a year that are usually tied to economic or political conditions.
  • Irregular variations that do not reflect typical behavior, such as a period of extreme weather or a union strike.
  • Random variations, which encompass all non-typical behaviors not accounted for by the other classifications.
Table 1
Naïve Forecasting
Period Actual Demand (000's) Forecast (000's)
January 45  
February 60 45
March 72 60
April 58 72
May 40 58
June   40

Among the time-series models, the simplest is the naïve forecast. A naïve forecast simply uses the actual demand for the past period as the forecasted demand for the next period. This makes the assumption that the past will repeat. It also assumes that any trends, seasonality, or cycles are either reflected in the previous period's demand or do not exist. An example of naïve forecasting is presented in Table 1.

Another simple technique is the use of averaging. To make a forecast using averaging, one simply takes the average of some number of periods of past data by summing each period and dividing the result by the number of periods. This technique has been found to be very effective for short-range forecasting.

Variations of averaging include the moving average, the weighted average, and the weighted moving average. A moving average takes a predetermined number of periods, sums their actual demand, and divides by the number of periods to reach a forecast. For each subsequent period, the oldest period of data drops off and the latest period is added. Assuming a three-month moving average and using the data from Table 1, add 45 (January), 60 (February), and 72 (March) and divide by three to arrive at a forecast for April:

45 + 60 + 72 = 177 ÷ 3 = 59

To arrive at a forecast for May, drop January's demand from the equation and add the demand from April. Table 2

Table 2
Three Month Moving Average Forecast
Period Actual Demand (000's) Forecast(000's)
January 45  
February 60  
March 72  
April 58 59
May 40 63
June   57

presents an example of a three-month moving average forecast.

A weighted average applies a predetermined weight to each month of past data, sums the past data from each period, and divides by the total of the weights. If the forecaster adjusts the weights so that their sum is equal to 1, then the weights are multiplied by the actual demand of each applicable period. The results are then summed to achieve a weighted forecast. Generally, the more recent the data is, the higher the weight, and the older the data the smaller the weight. Using the demand example, a weighted average using weights of.4,.3,.2, and.1 would yield the forecast for June as:

60(.1) + 72(.2) + 58(.3) + 40(.4) = 53.8

Forecasters may also use a combination of the weighted average and moving average forecasts. A weighted moving average forecast assigns weights to a predetermined number of periods of actual data and computes the forecast the same way as described above. As with all moving forecasts, as each new period is added, the data from the oldest period is discarded. Table 3 shows a three-month weighted moving average forecast utilizing the weights.5,.3, and.2.

A more complex form of weighted moving average is exponential smoothing, so named because the weight falls off exponentially as the data ages. Exponential smoothing takes the previous period's forecast and adjusts it by a predetermined smoothing constant,α (called alpha; the value for alpha is less than one) multiplied by the difference in the previous forecast and the demand that actually occurred during the previously forecasted period (called forecast error). Exponential smoothing is expressed formulaically as such:

New forecast = previous forecast + alpha (actual demand previous forecast) F = F +ά (AF)

Exponential smoothing requires the forecaster to begin the forecast in a past period and work forward to the period for which a current forecast is needed. A substantial amount of past data and a beginning or initial forecast are also necessary. The initial forecast can be an actual forecast from a previous period, the actual demand from a previous period, or it can be estimated by averaging all or part of the past data. Some heuristics exist for computing an initial forecast. For example, the heuristic N = (2 ÷ α) 1 and an alpha of.5 would yield an N of 3, indicating the user would average the first three periods of data to get an initial forecast. However, the accuracy of the initial forecast is not critical if one is using large amounts of data, since exponential smoothing is self-correcting.

Table 3
Three-Month Weighted Moving Average Forecast
Period Actual Demand (000's) Forecast (000's)
January 45  
February 60  
March 72  
April 58 55
May 40 63
June   61

Given enough periods of past data, exponential smoothing will eventually make enough corrections to compensate for a reasonably inaccurate initial forecast. Using the data used in other examples, an initial forecast of 50, and an alpha of.7, a forecast for February is computed as such:

New forecast (February) = 50 +.7(45 50) = 41.5

Next, the forecast for March:

New forecast (March) = 41.5 +.7(60 41.5) = 54.45

This process continues until the forecaster reaches the desired period. In Table 4 this would be for the month of June, since the actual demand for June is not known.

An extension of exponential smoothing can be used when time-series data exhibits a linear trend. This method is known by several names: double smoothing; trend-adjusted exponential smoothing; forecast including trend; and Holt's Model. Without adjustment, simple exponential smoothing results will lag the trend; that is, the forecast will always be low if the trend is increasing, or high if the trend is decreasing. With this model there are two smoothing constants,α and β with β representing the trend component.

An extension of Holt's Model, called Holt-Winter's Method, takes into account both trend and seasonality.

Table 4
Period Actual Demand (000's) Forecast (000's)
January 45 50
February 60 41.5
March 72 54.45
April 58 66.74
May 40 60.62
June   46.19

There are two versions, multiplicative and additive, with the multiplicative being the most widely used. In the additive model, seasonality is expressed as a quantity to be added to or subtracted from the series average. The multiplicative model expresses seasonality as a percentageknown as seasonal relatives or seasonal indexesof the average (or trend). These are then multiplied times values in order to incorporate seasonality. A relative of 0.8 would indicate demand that is 80 percent of the average, while 1.10 would indicate demand that is 10 percent above the average. Detailed information regarding this method can be found in most operations management textbooks or one of a number of books on forecasting.

Associative or causal techniques involve the identification of variables that can be used to predict another variable of interest. For example, interest rates may be used to forecast the demand for home refinancing. Typically, this involves the use of linear regression, where the objective is to develop an equation that summarizes the effects of the predictor (independent) variables upon the forecasted (dependent) variable. If the predictor variable were plotted, the object would be to obtain an equation of a straight line that minimizes the sum of the squared deviations from the line (with deviation being the distance from each point to the line). The equation would appear as: y = a + bx, where y is the predicted (dependent) variable, x is the predictor (independent) variable, b is the slope of the line, and a is equal to the height of the line at the y-intercept. Once the equation is determined, the user can insert current values for the predictor (independent) variable to arrive at a forecast (dependent variable).

If there is more than one predictor variable or if the relationship between predictor and forecast is not linear, simple linear regression will be inadequate. For situations with multiple predictors, multiple regression should be employed, while non-linear relationships call for the use of curvilinear regression.

ECONOMETRIC FORECASTING

Econometric methods, such as autoregressive integrated moving-average model (ARIMA), use complex mathematical equations to show past relationships between demand and variables that influence the demand. An equation is derived and then tested and fine-tuned to ensure that it is as reliable a representation of the past relationship as possible. Once this is done, projected values of the influencing variables (income, prices, etc.) are inserted into the equation to make a forecast.

EVALUATING FORECASTS

Forecast accuracy can be determined by computing the bias, mean absolute deviation (MAD), mean square error

(MSE), or mean absolute percent error (MAPE) for the forecast using different values for alpha. Bias is the sum of the forecast errors [Σ(FE)]. For the exponential smoothing example above, the computed bias would be:

(60 41.5) + (72 54.45) + (58 66.74) + (40 60.62) = 6.69

If one assumes that a low bias indicates an overall low forecast error, one could compute the bias for a number of potential values of alpha and assume that the one with the lowest bias would be the most accurate. However, caution must be observed in that wildly inaccurate forecasts may yield a low bias if they tend to be both over forecast and under forecast (negative and positive). For example, over three periods a firm may use a particular value of alpha to over forecast by 75,000 units (-75,000), under forecast by 100,000 units (+100,000), and then over forecast by 25,000 units (-25,000), yielding a bias of zero (-75,000 + 100,000 25,000 = 0). By comparison, another alpha yielding over forecasts of 2,000 units, 1,000 units, and 3,000 units would result in a bias of 5,000 units. If normal demand was 100,000 units per period, the first alpha would yield forecasts that were off by as much as 100 percent while the second alpha would be off by a maximum of only 3 percent, even though the bias in the first forecast was zero.

A safer measure of forecast accuracy is the mean absolute deviation (MAD). To compute the MAD, the forecaster sums the absolute value of the forecast errors and then divides by the number of forecasts (Σ |FE| ÷N). By taking the absolute value of the forecast errors, the offsetting of positive and negative values are avoided. This means that both an over forecast of 50 and an under forecast of 50 are off by 50. Using the data from the exponential smoothing example, MAD can be computed as follows:

(|60 41.5| + |72 54.45| + |58 66.74| + |40 60.62|) ÷ 4 = 16.35

Therefore, the forecaster is off an average of 16.35 units per forecast. When compared to the result of other alphas, the forecaster will know that the alpha with the lowest MAD is yielding the most accurate forecast.

Mean square error (MSE) can also be utilized in the same fashion. MSE is the sum of the forecast errors squared divided by N-1 [Σ(P(FE)) ÷ (N-1)]. Squaring the forecast errors eliminates the possibility of offsetting negative numbers, since none of the results can be negative. Utilizing the same data as above, the MSE would be:

[(18.5) + (17.55) + (8.74) + (20.62)] ÷ 3 = 383.94

As with MAD, the forecaster may compare the MSE of forecasts derived using various values of alpha and assume the alpha with the lowest MSE is yielding the most accurate forecast.

The mean absolute percent error (MAPE) is the average absolute percent error. To arrive at the MAPE one must take the sum of the ratios between forecast error and actual demand times 100 (to get the percentage) and divide by N[(Σ | Actual demand forecast | ÷Actual demand) × 100 ÷ N]. Using the data from the exponential smoothing example, MAPE can be computed as follows:

[(18.5/60) + 17.55/72 + 8.74/58 + 20.62/48) × 100] ÷ 4 = 28.33%

As with MAD and MSE, the lower the relative error the more accurate the forecast.

It should be noted that in some cases the ability of the forecast to change quickly to respond to changes in data patterns is considered to be more important than accuracy. Therefore, one's choice of forecasting method should reflect the relative balance of importance between accuracy and responsiveness, as determined by the forecaster.

MAKING A FORECAST

William J. Stevenson lists the following as the basic steps in the forecasting process:

  • Determine the forecast's purpose. Factors such as how and when the forecast will be used, the degree of accuracy needed, and the level of detail desired determine the cost (time, money, employees) that can be dedicated to the forecast and the type of forecasting method to be utilized.
  • Establish a time horizon. This occurs after one has determined the purpose of the forecast. Longer-term forecasts require longer time horizons and vice versa. Accuracy is again a consideration.
  • Select a forecasting technique. The technique selected depends upon the purpose of the forecast, the time horizon desired, and the allowed cost.
  • Gather and analyze data. The amount and type of data needed is governed by the forecast's purpose, the forecasting technique selected, and any cost considerations.
  • Make the forecast.
  • Monitor the forecast. Evaluate the performance of the forecast and modify, if necessary.
  • Establish cause and effect relationships that add validation to a forecast.

SEE ALSO Futuring; Manufacturing Resources Planning; Planning; Sales Management

BIBLIOGRAPHY

Finch, Byron J. Operations Now: Profitability, Processes, Performance. 2nd ed. Boston: McGraw-Hill Irwin, 2006.

Forecasting Principles forecastingprinciples.com. Available from: http://www.forecastingprinciples.com.

Green, William H. Econometric Analysis. 5th ed. Upper Saddle River, NJ: Prentice Hall, 2003.

Hanke, John E. and Dean Wichern. Business Forecasting. 9th ed. Upper Saddle River, NJ: Prentice Hall, 2008.

Joppe, Dr. Marion. The Nominal Group Technique The Research Process. Available from: http://www.ryerson.ca/mjoppe/ResearchProcess/841TheNominalGroupTechnique.htm.

Stevenson, William J. Operations Management. 8th ed. Boston: McGraw-Hill Irwin, 2005.

Stutely, R. Definitive Guide to Business Finance: What Smart Managers Do with the Numbers. Prentice Hall: Upper Saddle River, New Jersey, 2007.

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Forecasting

Forecasting

Forecasting can be broadly considered as a method or a technique for estimating many future aspects of a business or other operation. Planning for the future is a critical aspect of managing any organization, and small business enterprises are no exception. Indeed, their typically modest capital resources make such planning particularly important. In fact, the long-term success of both small and large organizations is closely tied to how well the management of the organization is able to foresee its future and to develop appropriate strategies to deal with likely future scenarios. Intuition, good judgment, and an awareness of how well the industry and national economy are doing may give the manager of a business firm a sense of future market and economic trends. Nevertheless, it is not easy to convert a feeling about the future into a precise and useful number, such as next year's sales volume or the raw material cost per unit of output. Forecasting methods can help estimate many such future aspects of a business operation.

The goal of forecasting is to come as close to possible to an accurate picture of the future. But, as with other forms of fortune telling, it can never be fully accurate. There are simply too many interactive variables. A change in any one of these may cause the forecasted scenario to change. For example, unexpected shocks to the economy, as occurred after the terrorist attacks of 9/11, are extremely difficult to anticipate and plan around. Such extreme situations are, happily, very rare. But there are far more subtle events that may also cause major changes in the assumptions upon which a forecast is based, things like: sharply increased material costs resulting from storms or wars, the unexpected demise or buyout of a large competitor, and/or an increase in demand due to an unexpected fashion trend shift. Despite the fact that forecasting is an imprecise art, a company must do the best it can to plan for the future and an important part of this planning is forecasting.

The task of forecasting can be approached in a number of ways and the best forecasting outcomes are usually the result of applying several forecasting methods. To supplement their judgment, forecasters rely on a variety of data sources and forecasting methods. For example, forecasting may involve the use of econometric models that can take into account the interactions between economic variables. In other cases the forecaster may employ statistical techniques for analyzing sets of historical data referred to simply as time series. Other frequently used data sources are recent consumer surveys and forecasts produced by other institutionsindustry associations, investment banks, and economists generally.

FORECASTING AND ITS PRACTICAL APPLICATIONS

In an era where forecasts drive entire supply chain networks forecasting is an increasingly critical organizational capability. Forecasting the future may sound like a lofty and theoretical activity when in reality it is a practical business tool like many others. Here is an example. How should a business go about preparing the quarterly sales volume forecasts for their primary product, say, window-glass? The company will certainly want to review the actual sales data for window glass over the last few years. Suppose that the forecaster has access to actual sales data for each quarter over the 15-year period the firm has been in business. Using these historical data, the forecaster can see the general level of sales but more importantly, he or she can also determine what pattern the sales history produces, what trends are visible. A thorough review of the data may reveal some type of seasonal pattern, such as peak sales occurring in the spring as people do spring-cleaning and others prepare to sell their homes during the summer school break. In addition, if the forecaster is able to identify other factors that influence sales, like weather patterns or housing starts, historical data on these factors can also be used in generating forecasts of future sales volumes.

FORECASTING METHODS

Academics divide forecasting methods into two broad categories: qualitative and quantitative. The division of forecasting methods into qualitative forecasting and quantitative forecasting is based on the availability of historical time series data. If historical data and time series are available, than quantitative methods may be used. If not, qualitative methods are the only option.

Qualitative Forecasting Methods

Qualitative forecasting techniques generally employ the judgment of experts to generate forecasts. A key advantage of these procedures is that they can be applied in situations where historical data are simply not available. Even in situations where such data are available, quantitative forecasting methods are a useful addition to successful forecasting. Three important qualitative forecasting methods are: the Delphi method, scenario writing, and the subject approach.

Delphi Method

In the Delphi method, an attempt is made to develop forecasts through "group consensus."

A group of experts in a particular field participate. Usually, a panel of these experienced people is asked to respond to a series of questionnaires. The panel members, who should ideally come from a variety of backgrounds (marketing, production, management, finance, purchasing, etc.) are asked to respond to an initial questionnaire. A second questionnaire is then created which incorporates information and opinions gathered in the responses to the first questionnaire. The second questionnaire is then distributed. Each panelist is asked to reconsider and revise his or her initial response to the questions based on the new information. This process is continued until some degree of consensus among the panelists is reached. It should be noted that the objective of the Delphi method is not to produce a single answer at the end. Instead, it attempts to produce a relatively narrow range of opinionsa range into which most of the panelists' opinions fall.

Scenario Writing Method

Under the scenario writing approach, the forecaster starts with different sets of assumptions. For each set of assumptions, a likely scenario of the business outcome is charted. Thus, the forecaster generates several different future scenarios (corresponding to different sets of assumptions). The decision maker or business person is presented with the different scenarios, and has to decide which scenario is most likely to prevail.

A Subjective Approach Method

The subjective approach allows individuals participating in the forecasting decision to arrive at a forecast based on their feelings, ideas, and personal experiences. Many corporations in the United States have started to increasingly use the subjective approach. Internally, these subjective approaches sometimes take the form of "brainstorming sessions," in which managers, executives, and employees work together to develop new ideas or to solve complex problems. At other times, the subjective approach may take the form of a survey of the company's sales people. This approach, which is known as the sales force composite or grass roots method, is relied on because salespeople interact directly with purchasers and it is assumed therefore that they have a good feel for which products will or will not sell and in what quantities.

The advantage of using the salespeople's forecasts is that salespeople are highly qualified to explain the demand for products, especially in their own territories. The disadvantage is that salespeople may tend to be optimistic in their estimates since optimism is a characteristic often found in good salespeople. Also, those working in sales may fear that a low sales forecast will lead to layoffs in the sales area. The opinions of salespeople should not be relied on to the exclusion of all else for one additional reason. Salespeople may not be aware of impending changes in other related areas, such as availability of raw materials, national economic developments, or the arrival of a formidable new competitor.

Quantitative Forecasting Methods

Quantitative forecasting methods are used when historical data on variables of interest are availablethese methods are based on an analysis of historical data concerning the time series of the specific variable of interest. There are two quantitative forecasting methods. The first uses the past trend of a particular variable in order to make a future forecast of the variable. In recognition of this method's reliance on time series, it is commonly called the "time series method." The second quantitative forecasting method also uses historical data. This method is often referred to as the causal method because it relies on the use of several variables and their "cause-and-effect" relationships. Examples of variables that may have this cause-and-effect relationship are: 1) interest rate levels and levels of disposable income; 2) winter weather patterns and demand for heating oil; 3) increasing gas prices and a decline in demand for sports utility vehicles (SUVs). By studying the time series data on two or more variables that have a cause-and-effect relationship with the item for which a forecast is needed, effort is made to incorporate as many relevant factors as possible into the forecast.

In practice, most business people use some combination of these methods and techniques in trying to plan for the future and put together accurate forecasts. With each cycle of forecasting, more is learned about what factor to consider and how to weight their importance in projecting future events.

see also Business Planning; Sales Forecasts

BIBLIOGRAPHY

Aston, Adam, and Joseph Weber. "The Worst Isn't Over: Smarter science is helping companies and insurers plan for hurricanes. The Bad News: This year could be another doozy." Business Week. 16 January 2006.

Chase, Charles W. Jr. "Composite Forecasting: Combining Forecasts for Improved Accuracy." Journal of Business Forecasting. Summer 2000.

Engerman, Stanley. "On the Accuracy of Some Past and Present Forecasts." International Monetary Fund Staff Papers. Annual 2005.

Evans, Michael. Practical Business Forecasting. Blackwell Publishing, 2002.

Gaber, Tal, Jacob Goldenberg, Barak Libai, and Eitan Mullerray. "From Density to Destiny: Using spatial dimension of sales data for early prediction of new product success." Marketing Science. Summer 2004.

Gray, Andi. "How Forecasting Can Help the Bottom Line." Fairfield County Business Journal. 27 June 2005.

Jones, Vernon Dale, Stuart Bretschneider, and Wilpen L. Gorr. "Organization Pressures on Forecast Evaluation: Managerial, Political, and Procedural Influences." Journal of Forecasting. July 1997.

Mentzer, John T., and Mark A. Moon. Sales Forecasting Management. Sage Publications, Inc., 2004.

O'Connor, Marcus, William Remus, and Ken Griggs. "Going UpGoing Down: How Good are People at Forecasting Trends and Changes in Trends?" Journal of Forecasting. May 1997.

Sanders, Nada R., and Karl B. Manrodt. "The Efficacy of Using Judgmental versus Quantitative Forecasting Methods in Practice." Omega. December 2003.

Rasmussen, Rasmus. "On Time Series Data and Optimal Parameters." Omega. April 2004.

                             Hillstrom, Northern Lights

                               updated by Magee, ECDI

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forecast

fore·cast / ˈfôrˌkast/ • v. (past -cast or -cast·ed) [tr.] predict or estimate (a future event or trend): rain is forecast for eastern Ohio | [tr.] coal consumption is forecast to increase. • n. a prediction or estimate of future events, esp. coming weather or a financial trend. DERIVATIVES: fore·cast·er n.

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forecast

forecastaghast, avast, Belfast, blast, cast, caste, contrast, fast, last, mast, miscast, outlast, past, rat-arsed, unsurpassed, vast •steadfast • lightfast • holdfast •sunfast • colourfast • flabbergast •simulcast • telecast • typecast •forecast • broadcast • sportscast •downcast •outcast, outcaste •newscast • roughcast • upcast •opencast • worm cast • sandblast •Elastoplast • counterblast • mainmast •mizzenmast • topmast • foremast •fly-past

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Forecasting

Forecasting

What is a forecast?
Making your own forecast
State-of-the-art forecasting equipment
Understanding forecasts
Forecasting in the media
Using forecasts
The future of forecasting
For More Information

Weather forecasts assist people in many ways, such as helping them to decide when to plan a trip or when to plant their gardens. Predicting the weather, defined as the set of conditions of temperature, humidity, cloud cover, and wind speed at a given time, may also be a matter of life and death. Winter storms, hurricanes (the strongest form of tropical cyclones), tornadoes (violently rotating columns of air), and thunderstorms (small but intense storms) are all potential killers. A forecast can serve as a warning to those who are in the path of deadly weather.

Over the last century, meteorology and weather forecasting have made great advances. Meteorology is the scientific study of the atmosphere and atmospheric processes, especially weather and climate. Climate is the weather experienced by a given location, averaged over several decades. Meteorologists now have access to sophisticated technology and advanced methods of information gathering and analysis of atmospheric conditions, all of which make forecasting easier. The ability to make accurate forecasts is a sign that meteorology has entered the modern scientific era, not to mention every meteorologist's professional triumph.

What is a forecast?

A weather forecast is a prediction of what the weather will be like in the future, based on present and past conditions. Methods of forecasting range from very simple techniques based on wind speed and direction, temperature, cloud patterns, and experience, to very complex techniques using sophisticated computer modeling and large databases of historic information. Simple forecasting methods may be based on sayings, such as a "clear moon, frost soon"; or natural signs, such as the opening and closing of pinecones in response to humidity. Some of these sayings and so-called folk wisdom are useful, while others have no basis in fact.

On the other end of the forecasting scale are scientific methods, which involve the continuous measurement and analysis of atmospheric

WORDS TO KNOW

absolute humidity:
the amount of water vapor in the air, expressed as a ratio of the amount of water per unit of air.
agricultural report:
a specialized weather report tailored to the needs of farmers, which includes current temperature, precipitation, and wind speed and direction, as well as frost warnings and predictions of temperature and precipitation for the days to come.
air mass:
a large quantity of air throughout which temperature and moisture content are fairly constant.
air pressure:
the pressure exerted by the weight of air over a given area of Earth's surface. Also called atmospheric pressure or barometric pressure.
anemometer:
an instrument used to measure wind speed. A common type is the cup anemometer.
aneroid barometer:
a type of barometer that consists of a vacuum-sealed metal capsule, within which a spring expands or contracts with changing air pressure.
aviation report:
a specialized weather report tailored to the needs of pilots, which provides information on the height of the clouds, visibility, and storm systems.
backing wind:
a wind that shifts direction, rotating counterclockwise higher in the atmosphere.
barograph:
an aneroid barometer that records changes in air pressure over time on a rotating drum.
barometer:
an instrument used to measure air pressure.
blizzard:
the most severe type of winter storm, characterized by winds of 35 mph (56 kph) or greater, large quantities of snow, and temperatures of 20°F (−6°C) or lower.
chaos theory:
the theory that the weather, by its very nature, is unpredictable. Every time one atmospheric variable (such as heat, air pressure, or water) changes, every other variable also changes—but in ways that are out of proportion with the first variable's change.
climate:
the weather experienced by a given location, averaged over several decades.
cold front:
the line behind which a cold air mass is advancing, and in front of which a warm air mass is retreating.
dispersion:
the selective refraction of light that results in the separation of light into the spectrum of colors.
Doppler radar:
a sophisticated type of radar that relies on the Doppler effect, the change in frequency of waves emitted from a moving source, to determine wind speed and direction as well as the direction in which precipitation is moving.
drought:
an extended period of abnormal dryness.
El Niño:
means "the Christ child" in Spanish. A period of unusual warming of the Pacific Ocean waters off the coast of Peru and Ecuador. It usually starts around Christmas, which is how it got its name.
flash flood:
a sudden, intense, localized flooding caused by persistent heavy rainfall or the failure of a levee or dam.
fog:
a cloud that forms near or on the ground.
front:
the dividing line between two air masses.

conditions. With basic weather tools, local forecasts can easily be created. With today's high-tech instruments, professional meteorologists can create global forecasts with considerable accuracy.

Skilled versus unskilled forecasts

Anyone can guess at what the weather will be like tomorrow and have a fair chance of being correct. Since there is a limited range of possibilities for weather conditions at any season of the year, simple guesses will often match actual conditions. This is an example of an "unskilled" forecast. A "skilled" forecast, on the other hand, is based on observation and analysis of atmospheric conditions.

Skilled forecasting is not limited to professional meteorologists, however. Farmers and ranchers, whose livelihoods depend on the weather, can become quite skilled at predicting the weather over a twenty-four- to forty-eight-hour period, based on simple observations and experience.

When it comes to short-range weather forecasting, there are two principal types of unskilled forecasts. One is based on persistence and the other is based on long-range climatic predictions. The "persistence method" is simply predicting that tomorrow's weather will be the same as today's. If it has been hot and dry for several days, predicting another day of hot, dry weather is probably an accurate forecast. This method also works well in locations where the weather tends to be unchanging for days on end. Two examples are Los Angeles, California, where there tends to

be haze (high humidity and lots of airborne particles) in the morning and sunshine in the afternoon; and Seattle, Washington, where it is often cool and drizzling. Predicting mild and sunny weather for San Diego, California, is also a safe bet, since its weather is moderated by cold ocean currents.

Another type of unskilled forecast is created by studying weather information recorded over several decades to find the average conditions for a given location in a particular time of year. This is the kind of information often included in various almanacs. For example, the state of Michigan historically averages ten days of rain in September. Since there are thirty days in September this means that it rains, on average, on one-third of the days.

A skilled forecast, in contrast, is one that draws on global as well as local atmospheric observations. These observations include information not available to the average person, such as barometric pressure (the pressure exerted by the weight of air), winds at upper altitudes, dew point, and others. The forecasts given on television incorporate observations taken all over the world that have been processed by computers. The end result is a weather map showing temperatures, pressure highs and lows, precipitation (water falling to the ground), fronts (the dividing lines between air masses), and predictions as to how these conditions will change over the coming few days.

A skilled forecast is expected to be more accurate than an unskilled forecast. After all, wild guesses alone could produce forecasts that are accurate about half of the time. Thus the success rate of forecasting is not determined simply by how often the forecasts are correct, but by how far they exceed the success rate of unskilled forecasts.

Forecasting is a global endeavor

Modern-day forecasters look at weather as a global process. The reason for this approach is that the atmosphere, where weather occurs, forms a continuous blanket around the entire planet. Therefore, weather conditions in one part of the world may eventually affect conditions in another part of the world. Although it is not necessary to have information from all around the world to produce forecasts for the short term (a few days), such information becomes necessary when making longer-term forecasts.

As a general rule, simple observation of local atmospheric conditions will be useful for predicting the weather for the following few hours. To get a picture of what the weather will be tomorrow or the next day requires regional or statewide weather data. Accurate predictions for three or more days require information from the whole continent. For still longer periods global weather, observations are necessary.

International cooperation in data collection

The World Meteorological Organization (WMO) is responsible for organizing international cooperation in weather observations and reporting. This network of more than 180 national weather services, based in Geneva, Switzerland, is an agency of the United Nations. The WMO, through its World Weather Watch (WWW) program, oversees the worldwide collection and standardization of measurements of atmospheric conditions.

The WWW receives information from thousands of weather stations. About twelve thousand of these stations are on land, and another seven thousand are located at sea, on ships and oil rigs. Nearly one thousand more are radiosondes, instrument packages carried on board small weather balloons that take readings in the upper air. In addition, observations are collected from numerous aircraft, radar stations (stations that detect the location, movement and intensity of precipitation) and weather satellites, which are equipped with infrared and visible imaging equipment. Weather observers at land and sea stations are either weather professionals with government organizations or private industry, or trained nonprofessionals.

Who's Who: Hurd Willett

Hurd "Doc" Willett (1903–1992) was one of the most respected and skilled long-range forecasters of all time. Throughout his sixty-two-year career, Willett worked as a forecaster, teacher, and researcher. He authored over one hundred books and articles on meteorology and forecasting.

Willett's primary research topic was one that is still controversial within the meteorological community: the connection between sunspot cycles and long-range weather patterns. Astronomers have determined that the energy output of the sun varies somewhat with sunspot number. Willett theorized that climate change is linked to the sunspot cycles. This connection is known as the solar-climate relationship.

When Willett was nine years old he began recording winter storms and cold temperatures in a diary. Just before turning eleven, Willett knew what his future held: "In 10 years, one week, and three days, I will reach my majority," he wrote. "When I grow up, I want to be a weather man."

Willett began his career in weather science in 1925, when the discipline was still relatively undeveloped. He did much to advance the field. In the late 1920s and 1930s, Willett pushed for the integration of the polar front theory into U.S. meteorology. The polar front theory states that the storms of the middle latitudes are brought about by the mixing of cold, polar air from the north and warmer air from the south. The latitude at which this mixing occurs, approximately 60° north, is known as the polar front. Willett also developed some of the long-range forecasting principles that are now used in computer models.

Willett was made famous by his article, "Cold Weather Ahead," which was published in the Saturday Evening Post. In the article, Willett predicted that the series of devastating hurricanes that had pounded the East Coast from 1938 to 1955 would cease by 1965. He also predicted that after 1960, the Northwest, Rocky Mountains, and the Midwest would no longer experience droughts, except for a possible period of drought from about 1975 until 1980. Willett was astonishingly accurate. New England was free of major hurricanes from 1960 until 1985. The only drought to plague the northern United States between 1960 and the early 1980s lasted from 1976 to 1978.

Willett received the first-ever Distinguished Scientific Achievement Award from the American Meteorological Society in 1951 for his contributions to meteorology and to our understanding of the large-scale circulation patterns of the atmosphere.

Processing the information

Observers in the WWW network take measurements, at set time intervals, of temperature, humidity, precipitation, wind speed and direction, and air pressure. They also observe the clouds, noting their type, height, movement, and the amount of sky they cover. Observers send this information to local weather centers, where it is encoded, or translated into a type of shorthand using abbreviations and symbols. Those reports are then transferred to the three World Meteorological Centers of the WMO, located outside of Washington, D.C., in Moscow, Russia, and in Melbourne, Australia.

At the World Meteorological Centers, the reports are entered into supercomputers, which produce maps and charts representing a complete picture of the world's weather conditions. General weather forecasts are made from this information and sent out every six hours to national weather agencies. Next, these forecasts are sent to local weather agencies where they are used along with other data to create local forecasts. The local forecasts are then made available to the general public through the news media, such as newspapers, radio, television, and the Internet.

How data collection works in the United States

The collection of weather information in the United States is coordinated by the National Weather Service (NWS), an agency of the National Oceanic and Atmospheric Administration (NOAA). The NWS receives information from approximately one thousand land-based weather stations across the United States, most of which are located at airports. While many of these stations are operated by NWS staff, others are run by employees of other government agencies, such as the Federal Aviation Administration, or by private citizens. Weather conditions are also recorded on more than two thousand ships and over one hundred automated stations on oil rigs, lighthouses, or buoys. These stations are located on the Great Lakes and in parts of the oceans that influence weather in the United States. Over 125 radiosondes (electronic instrument packages used in weather balloons) measure temperature, air pressure, and relative humidity as they ascend from ground level to a maximum of about 20 miles (30 kilometers) above ground.

Measurements from land and sea stations are sent to the NWS every hour. Those from radiosondes are sent twice daily. The NWS also receives information from stations around the world every three hours. In addition, about twelve thousand volunteer weather-watchers send monthly logs to the NWS. These volunteers are private citizens who take daily readings of precipitation and maximum/minimum temperatures. Some volunteers work at cooperative weather stations with equipment supplied by the NWS. Information supplied to the NWS by volunteer weather-watchers is included in studies of long-term climatic change.

Short-, medium-, and long-range forecasts A forecast is considered

"short-range," "medium-range," or "long-range," depending on how far in the future its predictions extend. Short-range forecasts give detailed information about what to expect over the following twenty-four to forty-eight hours in terms of the temperature, wind speed and direction, cloud cover, and precipitation. Medium-range forecasts cover a period of two to ten days in the future. They predict the day-to-day temperature and precipitation up to five days in advance and describe likely temperature and precipitation averages for six to ten days in advance. Long-range forecasts make general weather predictions as far as three months in advance. These forecasts are limited to predicting whether rainfall and temperatures will be above or below average.

Short- and medium-range forecasts are produced by examining present atmospheric conditions. Long-range forecasts differ in that they are based on records of what the weather has been like, on average, for a particular climate at a particular time of year. Long-range forecasts are not intended to describe what the weather will be like from one day to the next, but are general guides as to what type of weather can be expected to dominate for that period, that is, warmer, colder, wetter, or drier than usual.

How accurate are forecasts?

Many people recall times that forecasts have been incorrect more readily than they recall times that forecasts have been correct. This may be the case because the memory of a ruined picnic is more vivid than the memory of outdoor activities undisturbed by the weather.

The reality is that, for most parts of the world, forecasts for twelve to twenty-four hours in advance are accurate about 87 percent of the time; twenty-four hours in advance they are accurate 80 percent of the time; and three to five days in advance they are accurate 65 percent of the time.

There is every reason to believe that forecasting will continue to become more accurate in the future, and yet, the accuracy of forecasting will always have its limits. The basic problem meteorologists have to deal with is the overwhelming complexity of the atmosphere. There are too many rapidly changing and erratic variables that affect weather patterns to get a complete and exact picture of the atmosphere.

Chaos theory and butterfly effect

In the early 1960s, Edward Lorenz made a discovery that has had a profound effect on weather forecasting. Lorenz's "chaos theory" explains that weather, by its very nature, is unpredictable. Lorenz used mathematical computer models to show that every time one atmospheric variable (e.g., heat, air pressure, water) changes, every other variable also changes. Furthermore, he found that even a slight change in one variable could produce significant changes in other variables. Thus, when Lorenz programmed two nearly identical sets of initial conditions into his computer model, he came up with two completely different forecasts.

Lorenz concluded that weather forecasting is chaotic because it is impossible to know, with absolute precision, every atmospheric condition at every moment. There will always be tiny discrepancies between the data used to create computerized forecasts and the actual atmospheric conditions. The effect of these discrepancies increases daily throughout a forecast so that by day ten a forecast may bear little resemblance to reality.

In theory, a small disturbance occurring in one part of the world can eventually have major implications in another part of the world. This condition is known as the butterfly effect. It gets its name from the idea that the flapping of a butterfly's wings in China, for instance, may trigger a storm system in New York.

The major conclusion of the chaos theory and the butterfly effect is that it will never be possible to predict, with complete certainty, the day-to-day weather for more than two weeks in advance.

Meteorologists first began to suspect that weather prediction would never be an exact science in the early 1950s. Computer modeling of weather patterns had revolutionized weather forecasting, and meteorologists believed that the new technology would rapidly and drastically improve the accuracy of forecasts. However, they were disappointed in the results. While the forecasts were improving, that improvement was painfully slow. It seemed that while the technology grew by leaps and bounds, the increased accuracy of forecasts barely inched along. This led mathematician and meteorologist Edward Lorenz (1917–), a professor at the Massachusetts Institute of Technology, to investigate the slow improvement rate of forecasts.

Making your own forecast

The concepts covered in the chapter, "Weather: An Introduction" together with the information contained in this section are sufficient to allow people to make very basic forecasts. Of course, these forecasts will not be as accurate as the National Weather Service and will not include global or long-range forecasts. But it may still be instructive to create short-range, local forecasts and compare their accuracy with those broadcast on television or printed in the newspaper.

Interpreting natural signs

Throughout the ages, people have associated all sorts of natural occurrences with approaching weather. These phenomena have included animal and plant behavior as well as the appearance of the sky and shifting winds. Some of these associations have proven accurate and are scientifically sound. That is not to say that animals and plants have predictive powers. Rather, they behave as they do because they are responding to current atmospheric conditions. These conditions happen to precede certain types of weather. Other aspects of natural forecasting, particularly those based on mythology and folklore, have been shown time and again to be invalid.

While natural signs alone will not provide everything needed to prepare forecasts, they can provide important clues. Animals and plants are generally more sensitive to environmental change than are humans. Clouds and winds are also reliable indicators of certain types of weather.

What can be forecast and when?

  • Forecasters predict the path of a quick and violent storm, such as a tornado, from a few minutes to an hour before it strikes.
  • Forecasters can warn of a large-scale storm system (such as a hurricane or heavy rain storm or snow storm) up to forty-eight hours before it arrives.
  • Forecasters can alert people to an approaching cold front three to five days in advance.
  • Forecasters can tell the average temperature and precipitation to expect for six to ten days into the future.

All other factors being equal, the forecaster with an understanding of natural signs is likely to enjoy a higher rate of success than one without that understanding. What follows are descriptions of some of the most

common natural signs of impending weather for the middle latitudes (including the United States and Canada), where weather patterns generally move from west to east.

Animals

Many animal species react to decreasing air pressure or increasing humidity, both of which are signs of rain. For instance, cows often lie down or huddle together in the grass before the rain comes. The reason for this behavior is not completely understood. One hypothesis for this behavior is that cows are preserving patches of dry grass, since they do not like to lie on wet grass. An alternate theory is that falling air pressure affects the digestive system of cows, making it more likely that they will choose to lie down rather than roam through the pasture grazing.

It is also common to see birds and bats flying at high altitudes before it rains. One proposed reason for this behavior is that they are chasing insects, which are carried upward by rising currents of warm air. This is a condition that typically precedes a thunderstorm.

A fisherman can sometimes tell that a storm is coming by the number of nibbles at his line. This pattern may be caused by fish trying to catch a meal before it is time to seek deeper, calmer waters. Rabbits, rattlesnakes, and other animal species are also known to intensify their food-gathering efforts before being driven to shelter by rain.

Other signs of rain are bees returning to their hives, gulls staying close to shore, and insects becoming more active. A whole chorus of animals seems to announce the rain: Frogs croak, geese honk, cicadas hum, and bees buzz, all more loudly than usual. Each of these types of behavior are responses to increasing humidity and/or decreasing air pressure.

One way to predict that a thunderstorm is on its way is to observe the behavior of pets. Animals are made uncomfortable by the static electricity in their fur, so a cat grooming itself constantly or a dog acting restless may indicate that a storm is approaching.

Plants

Pinecones close in response to rising humidity as do some flowers (tulips, African marigolds, scarlet pimpernels, dandelions, clover, and many others). One theory is that flowers close in response to moisture so the rain will not wash away their pollen. The leaves on trees may curl up in response to high humidity, something a person could notice as a sign of oncoming rain.

The sky

Two or three generations ago, people were much better at predicting the weather because they watched the sky much more than is common now. They especially watched cloud formations and learned how they could be used to predict weather. Cloud formations are probably the most reliable signs of an approaching storm or change in the weather. Far in advance of a warm front (the line behind which a warm air mass is moving), for example, the thin, high cirrus clouds known as "mare's tails" often appear in the sky. As the front gets closer, there may be an accumulation of high-level and or middle-level clouds as a possible indicator that a storm is brewing. The formation of low-level clouds after the middle- and high-level clouds have moved in means that rain or snow will soon follow.

An old weather proverb says: "Red sky at night, sailors' delight; red sky in morning, sailors take warning." This simple saying is often correct because weather patterns generally move from west to east. Thus, if skies are red at night, the sunlight, which is coming from the west where skies are clear, is reflecting off clouds to the east. However, if skies are red in the morning it is because the sunlight, in the east, is reflecting off clouds to the west. Clouds in the west may indicate that a storm is approaching.

Rainbows can be similarly interpreted. They are produced by the dispersion (selective bending) of sunlight through the rain. People can observe a rainbow only when the Sun is at their backs. If the rainbow is to the east, the rain has already passed. However, if a rainbow appears to the west of an observer, the rain is probably coming in her direction.

WORDS TO KNOW

frontal system:
a weather pattern that accompanies an advancing front.
frostbite:
the freezing of the skin.
geostationary satellite:
weather satellite that remains above a given point on Earth's equator, traveling at the same speed as Earth's rotation about 22,300 miles (35,900 kilometers) above the surface.
hair hygrometer:
an instrument that measures relative humidity. It uses hairs (human or horse), which grow longer and shorter in response to changing humidity.
halo:
a thin ring of light that appears around the Sun or the Moon, caused by the refraction of light by ice crystals.
haze:
the uniform, milky-white appearance of the sky that results when humidity is high and there are a large number of particles in the air.
heating-degree-days:
the number of degrees difference between the day's mean (average) temperature and the temperature at which most people set their thermostats. The total number of heating-degree-days in a season is an indicator of how much heating fuel has been consumed.
humiture index:
an index that combines temperature and relative humidity to determine how hot it actually feels and, consequently, how stressful outdoor activity will be. Also called temperature-humidity index or heat index.
hurricane:
the most intense form of tropical cyclone. A hurricane is a storm made up of a series of tightly coiled bands of thunderstorm clouds, with a well-defined pattern of rotating winds and maximum sustained winds greater than 74 mph (119 kph).
hygrometer:
an instrument used to measure relative humidity. It consists of a dry-bulb thermometer and a wet-bulb thermometer. Also called psychrometer.
isobar:
an imaginary line that connects areas of equal air pressure, after the air pressure measurements have been adjusted to sea level.
isotherm:
an imaginary line connecting areas of similar temperature.
jet stream:
the world's fastest upper-air winds. Jet streams travel in a west-to-east direction, at speeds between 80 to 190 mph (129 to 290 kph) around 30,000 feet (9,100 meters) above the ground. Jet streams occur where largest differences in air temperature and air pressure exist. (In North America, jet streams are typically found over central Canada and over the southern United States.)
latent heat:
the energy that is either absorbed by or released by a substance as it undergoes a phase change.
latitude:
an imaginary line encircling Earth, parallel to the equator, that tells one's position north or south on the globe.
marine forecast:
a specialized weather forecast of interest to coastal residents and mariners, which gives projections of the times of high and low tide, wave height, wind speed and direction, and visibility.
meteorology:
the scientific study of the atmosphere and atmospheric processes, namely weather and climate.
NEXRAD:
acronym for Next Generation Weather Radar, the network of high-powered Doppler radar units that cover the continental United States, Alaska, Hawaii, Guam, and South Korea.

A third reliable optical sign is a halo. A halo looks like a fuzzy white (or sometimes colored) ring of light around the Sun or Moon. It is produced by the refraction (bending) of sunlight or moonlight by ice crystals that have formed at high altitudes. These ice crystals are contained within thin, upper-level clouds that may mark the beginning of an approaching storm front. In general, the larger the halo, the closer the front, and the sooner it will rain. If the halo is small, the storm is far away. There are limitations to this method of prediction, however. Whether the halo is large or small, there is no telling if it will rain or if the storm will change directions before arriving in an area.

Wind

The movement of clouds at different altitudes moving in different directions is a sign that the weather is about to change. For example, when a cold front (the line behind which cold air is moving) reaches an area, winds shift in a counterclockwise direction (as viewed from above) producing a pattern known as a backing wind. A backing wind blows low-level clouds from the north, middle-level clouds from the northwest, and high-level clouds from the west. Since winds travel counterclockwise around a low-pressure system, and low pressure is associated with rainy or stormy weather, a backing wind can often be a sign of an approaching storm.

A key reference to: Fahrenheit and Celsius scales

Two main temperature scales are in use throughout the world: Fahrenheit and Celsius. The Fahrenheit scale was developed first, in 1714, by German-Dutch physicist Gabriel Fahrenheit (1686–1736). Fahrenheit also invented the first mercury thermometer. According to the way Fahrenheit arranged the gradations on his scale, fresh water freezes at 32°F and boils at 212°F, while saltwater freezes at approximately 0°F. The Fahrenheit scale is the one commonly used in the United States.

Anders Celsius (1701–1744), a Swedish astronomer, created his scale in 1742. Celsius felt it would be more convenient to use a system in which the freezing point of fresh water was designated as 0° and the boiling point as 100°. There was widespread agreement that these numbers were easier to work with, which prompted most of the world to adopt the Celsius scale.

A Celsius degree (°C)is larger than a Fahrenheit degree (°F). Specifically, one Celsius degree is equal to 1.8 Fahrenheit degrees. To convert from Celsius to Fahrenheit, multiply the degrees Celsius by 1.8, then add 32. To convert from Fahrenheit to Celsius, subtract 32 from the degrees Fahrenheit, then multiply by 0.56.

In other words:

°F = (1.8 × °C) + 32 OR °F = (9/5 × °C) + 32

°C = 0.56(°F − 32) OR °C = 5/9(°F − 32)

On the other hand, winds shift clockwise after a warm front has entered a region, producing a veering wind. An example of a veering wind is one that blows low-level clouds from the north, middle-level clouds from the northeast, and high-level clouds from the east. Since winds travel clockwise around a high-pressure system, and high pressure is associated with fair weather, a veering wind may signal the approach of warm, clear skies.

Instead of clockwise and counterclockwise rules, it may be easier to remember that a veering wind is changing its direction to your right as you face it while a backing wind changes directions to your left as you face it. Remember the old sailor's rule: "A veering wind will clear the sky; a backing wind says storms are nigh."

A systematic approach to data collection

To be an amateur weather forecaster requires more than observing the clues in nature about impending weather. It also necessary to measure and record specific atmospheric conditions daily. Using this information, which can be collected in a backyard, it is possible to create short-term, local forecasts, as well as to contribute to information meteorologists rely on in their study of long-term climatic conditions.

Installing your home weather center

The first step is to set up a station at home where you can make observations. A home weather station should include a number of basic instruments, such as a thermometer to measure temperature; a psychrometer or hygrometer to measure relative humidity; a barometer to measure air pressure; a wind sock to measure wind direction; an anemometer to measure wind speed; and a rain gauge to measure rainfall. While this equipment is relatively simple compared to the satellites and supercomputers used by forecasters at the National Weather Service, it is adequate for recording local weather conditions.

Choosing the best location

In order to make daily observations, you will need to establish a permanent outdoor location for your instruments. Ideally, the site should be at least 32 feet (10 meters) from trees or buildings and large enough to accommodate an instrument shelter plus other instruments. If this arrangement is not possible, choose any outdoor site to which you have access. Just keep in mind that trees and buildings may affect readings of wind and temperature. To test the adequacy of your location, compare your air temperature readings with those announced on your local weather station. The official readings announced at this station are usually taken at the closest airport.

The instrument shelter

The instrument shelter is also called a Stevenson screen or a weather shack. It is a place to store and protect instruments outdoors. Its other purpose is to provide standard conditions under which readings are taken. The shelter is essentially a ventilated wooden box on legs, about 4 feet (1.2 meters) above ground. It protects

the instruments from rain, direct sunlight, and wind, yet its slanted slats allow air to pass through the station. The roof of the shelter is double-layered, which helps prevent the sunlight from raising the temperature inside the shelter above that of the outside air. Finally, the whole shelter is painted white to reflect sunlight.

At a minimum, an instrument shelter should contain at least a thermometer, hygrometer, and barometer. It may also contain modified, automatically recording versions of these instruments as well as maximum and minimum thermometers. The other instruments—namely the wind sock, anemometer, and rain/snow gauge—should be placed near the instrument shelter, but far enough apart so that they do not interfere with each other's operation.

Where to get your instruments

Some of the instruments for your home weather center can be made, but others are more complex and should be purchased. Fortunately, all of the instruments can be purchased relatively inexpensively. Various models, however, range from the inexpensive to the very expensive. You can buy instruments at hardware stores, hobby shops, electronics stores, or catalogs. The best idea is to look into several catalogs to learn about the range of products and prices.

Measuring atmospheric conditions

Once the shelter is set up with the necessary instruments, you are ready to make measurements of weather conditions.

Temperature

Temperature is most commonly measured with a thermometer. A thermometer is a sealed narrow glass tube that has no air inside, with a bulb in the bottom containing a liquid. This liquid is usually mercury or red-dyed alcohol. When the surrounding air is warmed, the liquid expands and creeps upward through a tiny opening from the bulb into the tube. When the air is cooled, the liquid contracts and drops to a lower level in the tube. Tiny markings on the outside of the tube indicate the degree to which the liquid has risen or fallen—the temperature.

A type of thermometer that continually records the temperature is called a thermograph. This instrument has a needle that makes marks on a rotating drum covered with graph paper. A thermograph works by the expansion and contraction of two metal strips (usually iron and brass), welded together. When the temperature increases, each strip expands, but by different amounts. This expansion produces a slight bending of the strips, which causes a series of levers to move. The levers lead to the needle that etches on the drum.

Maximum and minimum thermometers tell the highest and lowest temperatures during an observation period (usually one day). The liquid within the tube rises in the maximum thermometer as long as the air temperature increases. The hole that connects the bulb to the tube, however, is narrower than in a regular thermometer. It is wide enough to allow the liquid to rise through it, however it prevents the liquid from passing back into the bulb. The liquid remains "stuck" at the maximum temperature.

A maximum thermometer can be reset by spinning or shaking it. In this respect, a maximum thermometer is similar to the old-fashioned, non-digital type of thermometer used to take a sick person's temperature.

A minimum thermometer usually contains alcohol, since alcohol has a much lower freezing point than mercury (−91°F [−71°C] for alcohol and −40°F [−40°C] for mercury). It looks like a regular thermometer,

except it is mounted horizontally. The minimum temperature is marked in this thermometer by a small dumbbell-shaped glass bar within the bore of the thermometer.

As the air temperature cools and the liquid contracts back into the bulb, surface tension drags the bar with it. However, when the temperature warms and the alcohol expands, it flows past the bar. (Surface tension causes the bar to move only when it is at the surface of the column of liquid.) The bar remains stationary, indicating the minimum temperature. This thermometer can be reset by turning it upside down, so that gravity pulls the bar to the surface of the column of alcohol.

Maximum and minimum thermometers come in other forms as well. One form is a U-shaped maximum-minimum thermometer with two temperature scales, one on each of the vertical branches. In this instrument, columns of liquid move small bars that mark the high and low temperatures. Digital thermometers with built-in memory can also serve as maximum-minimum thermometers.

Minimum temperature is the best standard by which to compare daily temperatures, since the day's low is usually reached after the sun goes down. When sunlight strikes a thermometer, the thermometer not only measures the energy of the surrounding air molecules (the true temperature), but it also measures the radiant energy from the Sun. This effect produces a higher temperature reading than the actual air temperature. Temperature readings during the day are much more

Dew-Point Temperature Wet-bulb depression
Current Temperature 1.8°F
(1.0°C)
3.6°F
(2.0°C)
5.4°F
(3.0°C)
7.2°F
(4.0°C)
9.0°F
(5.0°C)
14.0°F
(−10.0°C)
5.9°F
(−14.5°C)
−6.3°F
(−21.3°C)
−33.3°F
(−36.3°C)
18.5°F
(−7.5°C)
11.5°F
(−11.4°C)
1.9°F
(−16.7°C)
−13.9°F
(−25.5°C)
23.0°F
(−5.0°C)
16.9°F
(−8.4°C)
9.0°F
(−12.8°C)
−2−2°F
(−19.0°C)
−24.3°F
(−31.3°C)
27.5°F
(−2.5°C)
22.1°F
(−5.5°C)
15.4°F
(−9.2°C)
6.6°F
(−14.1°C)
−6.7°F
(−21.5°C)
−42.3°F
(−41.3°C)
32.0°F
(0.0°C)
27.1°F
(−2.7°C)
21.4°F
(−5.9°C)
14.4°F
(−9.8°C)
4.6°F
(−15.2°C)
−11.0°F
(−23.9°C)
36.5°F
(2.5°C)
32.2°F
(0.1°C)
27.1°F
(−2.7°C)
21.0°F
(−6.1°C)
13.5°F
(−10.3°C)
3.0°F
(3.0°C)
41.0°F
(5.0°C)
37.0°F
(2.8°C)
32.5°F
(0.3°C)
27.3°F
(−2.6°C)
21.0°F
(−6.1°C)
13.3°F
(−10.4°C)
45.5°F
(7.5°C)
41.9°F
(5.5°C)
37.8°F
(3.2°C)
33.3°F
(0.7°C)
27.9°F
(−2.3°C)
21.6°F
(−5.8°C)
50.0°F
(10.0°C)
46.6°F
(8.1°C)
42.8°F
(6.0°C)
38.8°F
(3.8°C)
34.2°F
(1.2°C)
28.8°F
(−1.8°C)
54.5°F
(12.5°C)
51.3°F
(10.7°C)
47.8°F
(8.8°C)
44.1°F
(6.7°C)
40.1°F
(4.5°C)
35.4°F
(1.9°C)
59.0°F
(15.0°C)
55.9°F
(13.3°C)
52.9°F
(11.6°C)
49.2°F
(9.6°C)
45.7°F
(7.6°C)
41.5°F
(5.3°C)
63.5°F
(17.5°C)
60.6°F
(15.9°C)
57.7°F
(14.3°C)
54.5°F
(12.5°C)
51.1°F
(10.6°C)
47.3°F
(8.5°C)
68.0°F
(20.0°C)
65.3°F
(18.5°C)
62.4°F
(16.9°C)
59.5°F
(15.3°C)
56.3°F
(13.5°C)
52.9°F
(11.6°C)
72.5°F
(22.5°C)
70.0°F
(21.1°C)
67.3°F
(19.6°C)
64.4°F
(18.0°C)
61.3°F
(16.4°C)
58.3°F
(14.6°C)
77.0°F
(25.0°C)
75.7°F
(24.3°C)
72.0°F
(22.2°C)
69.3°F
(20.7°C)
66.3°F
(19.1°C)
63.5°F
(17.5°C)
81.5°F
(27.5°C)
79.2°F
(26.2°C)
76.6°F
(24.8°C)
73.9°F
(23.3°C)
71.4°F
(21.9°C)
68.5°F
(20.3°C)
86.0°F
(30.0°C)
83.7°F
(28.7°C)
81.3°F
(27.4°C)
78.8°F
(26.0°C)
76.3°F
(24.6°C)
73.6°F
(23.1°C)
90.5°F
(32.5°C)
88.2°F
(31.2°C)
85.8°F
(29.9°C)
83.5°F
(28.6°C)
81.0°F
(27.2°C)
78.4°F
(25.8°C)
95.0°F
(35.0°C)
92.8°F
(33.8°C)
90.5°F
(32.5°C)
88.2°F
(31.2°C)
85.8°F
(29.9°C)
83.3°F
(28.5°C)
99.5°F
(37.5°C)
97.3°F
(36.3°C)
95.2°F
(35.1°C)
92.8°F
(33.8°C)
90.5°F
(32.5°C)
88.2°F
(31.2°C)
104.0°F
(40.0°C)
101.8°F
(38.8°C)
99.7°F
(37.6°C)
97.5°F
(36.4°C)
95.2°F
(35.1°C)
93.0°F
(33.9°C)
Relative Humidity Wet-bulb depression
Current Temperature 2.0°F
(1°C)
3.6°F
(2°C)
5.4°F
(3°C)
7.2°F
(4°C)
9.0°F
(5°C)
14.0°F (−10.0°C)69%39%10%
18.5°F  (−7.5°C)73%48%32%
23.0°F  (−5.0°C)77%54%32%11%
27.5°F (−2.5°C)80%60%41%22%3%
32.0°F    (0.0°C)82%65%47%31%15%
36.5°F    (2.5°C)84%68%53%38%24%
41.0°F    (5.0°C)86%71%58%45%32%
45.5°F    (7.5°C)87%74%62%50%38%
50.0°F    (10.0°C)88%76%65%54%44%
54.5°F    (12.5°C)89%78%68%58%48%
59.0°F    (15.0°C)90%80%70%61%52%
63.5°F    (17.5°C)90%81%72%64%55%
68.0°F    (20.0°C)91%82%74%66%58%
72.5°F    (22.5°C)92%83%76%68%61%
 77.0°F    (25.0°C)92%84%77%70%63%
81.5°F    (27.5°C)92%85%78%71%65%
86.0°F    (30.0°C)93%86%79%73%67%
90.5°F    (32.5°C)93%86%80%74%68%
95.0°F    (35.0°C)93%87%81%75%69%
99.5°F    (37.5°C)94%87%82%76%70%
104.0°F    (40.0°C)94%88%82%77%72%

accurate when taken in the shade than in the sun. However, even indirect sunlight alters the actual air temperature somewhat.

Humidity

The most useful measure of humidity is the relative humidity. Relative humidity is a measure of the amount of water in air compared to the total amount of water the air can hold at a given temperature. Remember that warm air can hold more water than cold air. Relative humidity is expressed as a percentage and tells how wet the air feels.

The simplest way to find the relative humidity is with a psychrometer, an instrument that consists of a dry-bulb thermometer and a wet-bulb thermometer. The dry-bulb thermometer tells the actual air temperature and the wet-bulb thermometer tells the saturated air temperature. The difference between these two temperatures is called the wet-bulb depression. Once you know the actual air temperature and the wet-bulb depression, you can refer to a standardized chart to find the relative humidity.

A dry-bulb thermometer is a regular thermometer, as described above. A wet-bulb thermometer is a thermometer with wet fabric placed around the bulb. An ideal fabric is a cotton weave called muslin, which retains moisture well. The wet cloth around the bulb provides an environment comparable to that of saturated air.

The wet-bulb thermometer almost always gives a lower temperature reading than the dry-bulb thermometer. The reason is that water from the cloth evaporates and absorbs latent heat from the bulb of the thermometer, thus cooling the thermometer. Latent heat is the heat released during the phase change, as the water turns from liquid to gas. The only exception to this is when wet-bulb and dry-bulb thermometers give equivalent readings, which occurs when water ceases to evaporate from the cloth. At this point the surrounding air is at its saturation point, meaning there is 100 percent relative humidity. The temperature at which both thermometers give the same reading is the dew point, which is the temperature at which any moisture in the air will condense and fall as snow or rain. You can determine the dew point from a standardized chart if you know the actual air temperature and the wet-bulb depression.

The greater the difference between the two temperatures (wet-bulb depression), the more water evaporates into the air, and the lower the relative humidity. A small wet-bulb depression indicates that little water is evaporating into the air, hence the relative humidity is high.

A variation on this instrument is the sling psychrometer. It consists of a dry-bulb thermometer and a wet-bulb thermometer mounted side by side on a metal strip, which rotates on a handle at one end. Operate it by holding the handle and spinning the metal strip in circles. This speeds up evaporation at the wet bulb, resulting in a quicker wet-bulb temperature reading.

Another tool for measuring humidity is the hair hygrometer. This instrument uses hairs (human or horse), which expand and contract in response to changing humidity. When there is more water in the air, the hair absorbs moisture and becomes longer. Conversely, when the air is drier, the hair loses moisture and becomes shorter. In fact, hair length changes by as much as 2.5 percent depending on the humidity. The same principle on which a hair hygrometer works can be observed in people's hair. Straight hair becomes limp in high humidity, and curly hair needs extra moisture to combat frizziness.

The hair hygrometer looks something like a thermograph in that its moving needle etches marks on a paper-covered, clock-driven, rotating drum. It works like this: Several hairs are attached to a system of levers. When the hair length changes, it causes the levers to shift. The last lever is attached to the needle, which records the motion. The paper on the moving drum is imprinted with horizontal lines representing percentages of relative humidity. The up-and-down motion of the needle is calibrated with this scale, so the markings tell the relative humidity over time.

Experiment: Make your own paper hygrometer

Paper can be used instead of hair to measure relative humidity, since it also absorbs water in the air. Using the following basic materials, you can create your own paper hygrometer: a piece of paper, a drinking straw, a small ball of modeling clay, a cardboard box at least one foot wide, a piece of poster board, and a toothpick.

  1. To make the pointer, cut out five paper squares, each about 2 inches (5 centimeters) across. Use a hole-punch to make a hole through the center of each square. Push the straw through the holes so that the paper squares are grouped together on one end of the straw.
  2. On the other end of the straw, affix a small ball of clay. Poke a toothpick into the clay, so that it extends in the line of the straw.
  3. To make the pivot, cut a strip out of the poster board that is 6 inches (15 centimeters) long by 2 inches (5 centimeters) wide. Fold it twice into three squares. Unfold it to form a three-sided box and place the middle portion flat on the table, with the other two portions sticking straight up. Cut a small notch at the top-center of each of the two vertical sides.
  4. To create the scale, cut an isosceles triangle (a triangle with at least two equal sides) out of the poster board that is 4 inches (10 centimeters) at the base and 6 inches (15 centimeters) tall. Fold it in half lengthwise. Draw a series of evenly spaced dashes on one side of the fold that are perpendicular to the fold.
  5. Position the triangle scale at one end of the box top, so that the base is on the surface and the fold extends straight upward. The fold should point toward the opposite end of the box top. Position the pivot at the other end, across from the scale. Glue the pivot and scale into place.
  6. Stick a pin through the straw, about two-thirds of the way toward the back of the straw (it should be closer to the paper than the toothpick). Balance the pointer by resting the edges of the pin in the notches of the pivot. You may have to adjust the position of the paper squares to get the pointer to balance.

When the relative humidity is high, the paper squares will absorb water and become heavier, making the pointer aim higher on the scale. When the relative humidity is low, the paper squares will be lighter and the pointer will aim lower.

Air pressure

Air pressure, also called "atmospheric pressure" or "barometric pressure," is measured with a barometer. This tool was invented by Italian mathematician Evangelista Torricelli (1608–1647) in 1643. Torricelli filled a small glass tube with one sealed end with mercury. He then

turned the tube upside down and placed the open end in a dish of mercury. The level of mercury in the tube began dropping. It stabilized when the weight of the mercury in the tube equaled the weight of the air pushing down on the surface of the mercury in the dish. The stable mercury level in the tube gave a way to describe the air pressure.

Mercury barometers still provide the most accurate method of measuring of air pressure. One drawback to using them, however, is that they must be "reduced" to sea level by calibrating the barometer so that it gives readings as if at sea level, compensating for differences caused by altitude. To calibrate a barometer to your altitude above sea level, call your local weather service office for an official reading. It is also necessary to adjust this type of barometer regularly to account for the expansion and contraction of the mercury in response to temperature change.

While the aneroid barometer is not as accurate as the mercury barometer, it needs no adjustment, making it the most convenient tool for the job. In addition, aneroid barometers are smaller and easier to transport than mercury barometers. It is also possible to use an aneroid barometer in a recording device called a barograph. Aneroid barometers are the more widely used variety today.

The aneroid barometer has a vacuum-sealed capsule made of steel or beryllium alloy. The capsule contains a spring that changes in size with air pressure. When the pressure falls the capsule expands, and when the pressure rises the capsule contracts. This movement triggers a series of levers that are connected to a pointer. This pointer indicates the air pressure on a dial.

The dial of an aneroid barometer, in addition to units of atmospheric pressure, may have zones designated "rain," "change," and "fair." These terms should not be taken literally. Just because the air pressure is low does not necessarily mean it will rain. A much more useful indication of future weather is how air pressure rises or falls over time. Falling air pressure is a sign of rain and rising air pressure is a sign of clearing skies.

Mercury and aneroid barometers can be placed indoors or outdoors, since indoor air pressure adjusts very quickly to outdoor air pressure. The barometer should be mounted vertically and kept out of direct sunlight.

A variation on the aneroid barometer is the barograph. It works the same way as an aneroid barometer except in the barograph (similar to the thermograph or hair hygrometer), the levers are connected to a needle that etches its movements onto a paper-covered, rotating drum. A barograph measures changes in air pressure over time.

Air pressure can be described in units of length or pressure

Units of length:

inches (in)

millimeters (mm)

(These units refer to the height of the column of mercury in a barometer)

Units of pressure:

pascals (Pa)

millibars (mb)

(These units describe air pressure specifically)

Air pressure at sea level:

between 28.64 and 30.71 in (727.45 and 780.03 mm)

between 970 and 1040 mb

Average air pressure at sea level:

29.92 in (760 mm)

1013.25 mb

Wind direction

Wind socks and wind vanes are both simple instruments used to determine the direction of the wind. A wind sock is a cone-shaped cloth bag, open on both ends, mounted on a pole. The wind enters through the wide end and exits through the narrow end. Thus, the wide end points to the direction from which the wind is coming. (Note: the "wind direction" in weather reports is the direction from which the wind comes, as opposed to the direction it is heading. For example, an "east wind" is one that is coming out of the east and moving to the west.)

You can buy a wind sock at a hardware store or construct your own. The sock is made by stretching a piece of weatherproof material over a series of increasingly larger metal rings, to form a cone-shape. The metal rings can be made from sturdy metal wire or cable that is cut into progressively longer pieces and twisted or clamped together at the ends. The sock is then attached to a tall, lightweight pole by a freely rotating metal ring.

Choose a place as far as possible from buildings and trees to erect the pole. The sock should be up high enough so that surface features do not interfere with the direction of the wind (10 feet or higher is ideal). Once your wind sock is up and working, you can use a compass to determine the direction the wind is blowing. When the wind is calm, it is recorded as "zero degrees." An east wind is 90 degrees, a south wind is 180 degrees, a west wind is 270 degrees, and a north wind is 360 degrees.

Another tool for measuring wind direction is a wind vane, or "weather vane." A wind vane is a free-swinging horizontal metal bar with a vertically oriented, flat metal sheet (often in the shape of a rooster or other animal) serving as a weight at one end of the bar and an arrow weighing down the other end. The arrow always points into the wind, toward the direction the wind is coming from.

On some weather vanes, a stationary, horizontal metal cross is positioned beneath the swinging bar, with the cardinal directions (north, south, east, and west) inscribed on the four ends. You can tell the wind direction with this type of wind vane by comparing the position of the arrow on the swinging bar with the directional cross beneath it. When there is only the swinging bar, you must use a compass to determine the direction in which the arrow is pointing. (Sometimes the wind is blowing too lightly to move a wind vane. If that is the case, use an

alternate method, such as looking at a wind sock or flag, to determine wind direction.)

Wind speed

Wind speed is measured by a tool called a cup anemometer. This device works like a speedometer. It consists of three or four cups, positioned on their sides, connected to a cap by horizontal spokes. The cap sits on top of a pole. The cap/spokes/cups unit rotates freely on the pole. The faster the wind blows, the faster the cups spin. This motion generates a weak electric current which is measured and displayed on a dial. To obtain an accurate measurement, the observer should check the wind speed several times over one minute and take the average value.

Wind speed is usually measured in units of miles per hour (mph) or kilometers per hour (kph). One kilometer is equal to 0.62 miles. The speed of wind over the water is commonly given in knots. One knot equals 1.15 mph (1.85 kph).

It is best to mount an anemometer away from buildings and trees. Place it as high as possible, but do not put it on a rooftop because winds accelerate over rooftops. If you do not have access to a suitable outdoor location, use a handheld anemometer. This device is a small instrument you can carry into a clearing to check the wind speed.

Precipitation

The final condition to monitor in your home weather station is precipitation; that is, rainfall and snowfall. This measurement is relatively easy to make and, best of all, requires no equipment purchase. A rain gauge is simply a container that catches the rain. Any transparent container with a flat bottom and straight sides (like a drinking glass) can be used. Once or twice a day, take a ruler and measure (in inches or millimeters) the height of the water in the container. Then empty the container and set it up again.

This device will give you a rough idea of the amount of rainfall. For a more accurate and precise measure of precipitation, you can invest in the type of rain gauge used by the National Weather Service. This instrument consists of two nested cylinders (a smaller one that fits inside of a larger one), with a funnel that fits over the outer cylinder and directs water into

the inner cylinder. The diameter of the mouth of the funnel will be several times wider than the diameter of the inner cylinder. If the diameter of the mouth of the funnel is ten times the diameter of the inner cylinder, than the area will be one hundred times greater. Thus, when an inch of water accumulates in the inner cylinder, it indicates that one-hundredth of an inch of rain has actually fallen.

If you want to get highly precise measurements, you can purchase a rain gauge that records patterns of precipitation over time. There are numerous varieties of this type of device, such as weighing-bucket rain gauges and tipping-bucket rain gauges. They are each driven by different mechanisms, but the outcome is the same: The rainfall is recorded on a paper-covered rotating drum.

Your rain gauge should be situated far from trees and buildings. If possible, follow this rule: Do not place the rain gauge closer to an obstacle than a distance equal to four times the height of that obstacle. For example, the rain gauge should be set up at least sixteen feet away from a four-foot-tall shrub. To prevent your rain gauge from tipping over, dig a small hole (a few inches deep) in the ground that is the width of your container and set the rain gauge in this depression.

Snow is easier to measure than rain. Just stick a ruler down through the snow until it hits the ground and take a reading. For best results, record the average of several readings taken around your weather station. If you want to find how much new snow has fallen in a given time

period, set a board on top of the old snow and measure the snow that falls on the board.

Meteorologists are also interested in the water content of snow, called the meltwater equivalent. There are various, somewhat complicated methods of finding the meltwater equivalent. Some require the use of a modified rain gauge and antifreeze. On average, ten inches of snow equals one inch of liquid water. This value varies greatly, however, depending on how cold and dry, or warm and wet, the snow is. In fact, very dry snow can be as little as be as one-thirtieth meltwater by volume and very wet snow can be as much as one-third meltwater by volume.

Recording observations

Daily measurements that have been made over a long period are the most useful type of information about local weather conditions. Standard daily weather log sheets (such as those provided by the National Weather Service) may be quite detailed. They generally include columns for sky condition (type and amount of cloud cover); wind direction; wind speed; visibility (how far you can see due to presence or absence of haze or fog, which is just a cloud at ground level); relative humidity (recorded as wet-bulb and dry-bulb temperatures); maximum and minimum temperatures; snowfall; rainfall; soil temperatures at various depths; and hours of sunshine throughout the day. They also have

space for notes about significant weather occurrences (such as a hailstorm) and general conditions of the day.

To record your observations, fashion your own log sheet, on which you can record the conditions you are able to measure. You do not want to create an impossible task for yourself. It is better to make once- or twice-daily recordings of a limited number of conditions than to make occasional recordings of many conditions.

Try to take your readings at the same time (or times) each day, ideally each morning and afternoon. Temperature should be consistently recorded either in degrees Fahrenheit or degrees Celsius. Readings of air pressure should include the current air pressure, the change in pressure since the last reading, and whether the pressure is rising or falling (pressure tendency).

Wind direction, to the nearest 10 degrees, should be measured with a compass. Wind speed can be recorded in miles per hour or kilometers per hour if you have an anemometer, otherwise use the Beaufort scale.

Visibility is a measure of how far you can see. The best way to assess visibility is to determine the distance to certain landmarks, and note each day which ones you can see from your weather station. Cloud cover can be noted as one of four categories: overcast (covering more than 90 percent of the sky); mostly cloudy (covering 50-90 percent of the sky); partly cloudy (covering 10-50 percent of the sky); or clear (covering less than 10 percent of the sky).

Your notes will be briefer and more orderly if you use international weather symbols to describe wind speed, current weather conditions, and clouds. Your weather journal should have plenty of room for notes, where you can record any general or specific weather observations for the day—such as the opening or closing of pinecones, the location of a rainbow (to the east or west) in the sky, the arrival of migrating birds, or the impact of the fall's first frost on a garden. It is also helpful to supplement your written notes with drawings or photographs of clouds, frost patterns on your windshield, or icicles dripping from trees, for instance.

Making forecasts

The information you record at your home weather station will enable you to give a weather report of current conditions, but predicting the future is a more complex task. Before you try your hand at producing forecasts, it is best to just record daily observations until you have become familiar with the instruments and the methods of measuring specific conditions. It also helps to review your journal after several days or weeks, looking for any weather trends. Once you are comfortable with the whole process, you are likely to have greater success at forecasting.

A homemade forecast for one day in advance may include elements such as the expected cloud cover, precipitation, and what the minimum temperature for the night will be. While there are standard procedures for predicting these conditions, keep in mind that forecasting, as a whole, is greater than the sum of its parts. In other words, an overall description of what the next day's weather may bring takes more than plugging each measurement into some equation. It requires the ability to notice subtle changes in the natural world, as well as monitoring atmospheric conditions with your instruments.

Certain types of predictions and general assessments about the weather can be made by looking at your measurements or by taking note of general conditions. For example:

  • Falling air pressure indicates that a storm may be moving in, while rising air pressure suggests skies will clear.
  • Feathery, high-level clouds are a sign that, while current conditions may be fair, a storm may be approaching. Thick, low-level clouds are a sign that precipitation is imminent.
  • The appearance of a line of dark, middle-level clouds on the horizon indicates that precipitation is likely.
  • Cloud formation is more likely when relative humidity is high than when it is low.
  • Clear weather is likely forthcoming when fog burns off before noon, the percentage of cloud cover decreases, or "cracks" develop in a sheet of clouds.
  • The air temperature will dip lower on a clear night than on a cloudy night, everything else being equal.
  • The lowest nighttime temperatures occur when there are clear skies, light winds, and snow on the ground.
  • When the dew point is below 32°F (0°C), you will get frost rather than dew.
  • A veering wind (clockwise shift with height) is a sign of clearing skies and rising temperatures.
  • A backing wind (counterclockwise shift with height) is a sign of stormy weather and falling temperatures.

To answer more complex questions about the weather, however, you must take into account a whole host of observations. Here are some examples of how to make general assessments and predictions about the weather by looking at several atmospheric conditions simultaneously.

A key reference to: The Beaufort scale

In the early 1800s British Navy commander Sir Francis Beaufort developed a scale for estimating wind speed. The Beaufort Scale of Wind Force looks at the effect of the wind on water, trees, and other flexible objects on land. Beaufort's intention was to create a standard method of assessing wind speed, based on descriptions commonly used by sailors.

His scale was officially adopted by the British Navy in 1838 and became the international mariner standard in 1853. In 1926, the scale was modified so it could also be used on land. Many sailors still use the Beaufort method to measure wind speed.

The scale ranges from 0 to 12, with 0 for still conditions and 12 for hurricane-force winds. Try using the Beaufort scale provided here in various weather conditions to approximate the wind speed. Compare your results with the official wind speed reported by your local weather service.

Will it rain? Will it snow?

A prediction of rain or snow is made by examining three specific atmospheric conditions: air pressure, sky conditions, and temperature. First, look at your last few readings of air pressure. Is it rising, falling, or staying the same? If it is rising or staying the same, precipitation is unlikely. Falling barometric pressure is often a signal of changing weather.

Beaufort Wind Scale
Wind Speed (mph) Beaufort Number Wind Effect on Land Official Description
Less than 10Calm; smoke rises vertically.CALM
1-31Wind direction is seen in direction of smoke; but is not revealed by weather vane.LIGHT AIR
4-72Wind can be felt on face; leaves rustle; wind vane moves.LIGHT BREEZE
8-123Leaves and small twigs in motion; wind extends light flag.GENTLE BREEZE
13-184Wind raises dust and loose papers. Small branches move.MODERATE BREEZE
19-245Small trees with leaves begin to sway; crested wavelets appear on inland waters.FRESH BREEZE
25-316Large branches move; telegraph wires whistle; Unbrellas become difficult to control.STRONG BREEZE
32-387Whole trees sway and walking into the wind becomes difficult.NEAR GALE
39-468Twigs break off trees; cars veer on roads.GALE
47-549Slight structural damage occurs (roof slates may blow away, etc.).STRONG GALE
55-6310Trees are uprooted; considerable structural damage is caused.STORM
64-7211Widespread damage is caused.VIOLENT STORM
73 or more12WIdespread damage is caused.HURRICANE

The next factor to examine is sky conditions. If skies are clear, clouds are few, or only smooth, low-level clouds exist, then chances of rain are small. However, the presence of dark, low-lying clouds or development of upper-level clouds to the west, in conjunction with falling air pressure, indicates that precipitation is likely.

To determine whether that precipitation will fall to the ground as rain or snow, check the temperature. If it is above 37°F (3°C), rain is likely. However, if the temperature is 37°F or below, you can expect sleet or snow.

How cold will it get tonight?

This question is one people often ask when trying to decide whether it is safe to leave their pet or plants outside for the night. By checking a minimum thermometer in the morning, you can learn the previous night's low temperature. But predicting the upcoming night's low is a more involved process that requires checking the outdoor temperature twice after the Sun goes down, and using an equation to find the answer. Bear in mind that since cloud cover and wind distort the amount of heat lost at night, this method works only under clear, calm conditions.

The first step is to find out what time the Sun will set in the evening and rise the next morning. This information is published in most local newspapers. The time of your first temperature reading depends on the month. In December or January wait one hour after sunset; in October, November, or February wait one-and-a-half hours after sunset; and in any other month wait two hours after sunset. This rule only applies to the Northern Hemisphere.

You must wait a certain length of time before taking measurements, because once the Sun sets, heat from the ground begins to radiate upward, into space. After a given period, the temperature at the surface will fall at a constant hourly rate. The length of time it takes for the temperature to begin dropping at the constant rate is shorter in the colder months and longer in the warmer months.

Assume the month is September. Two hours after sunset, go out to your instrument shelter, read the thermometer, and record the temperature. One hour later, go back and record the temperature again. The difference between the two temperatures is the "hourly drop." Next, count the hours that remain until one hour before sunrise. Multiply that number by the hourly drop. Subtract that figure from your second temperature reading and you will get the night's likely minimum temperature.

Will dew or frost form?

To answer this question you must determine the dew point and the night's predicted low temperature. The dew point depends on temperature and relative humidity. Specifically, the dew point is the temperature at which the air is saturated, resulting in the formation of dew or frost. Using wet-bulb and dry-bulb thermometers you can find the wet-bulb depression. Once you know the wet-bulb depression and the actual air temperature, you can find the dew point from the dew-point chart.

After you determine the dew point, two questions remain: Will the air become cold enough to reach the dew point and is the dew point above or below freezing? To answer the first question, use the method described above for determining minimum temperature. If the predicted minimum temperature is at or below the dew point, moisture will form on the ground. If the predicted minimum temperature is above freezing, the moisture will take the form of dew. However, if it is at or below freezing, you can expect frost.

Is the day hot or cold for the time of year?

Imagine that it is March 1 and it is very cold outside. How do you know if it just seems colder than normal because you are tired of the long winter or if it really is colder than normal? Here is a way to find out.

To determine whether the day is hot, cold, or normal for the time of year, you must look at a number of factors. These include identifying the existing air mass; comparing the day's maximum temperature with the average maximum temperature for the time of year in your locality; and recording the current wind speed and sky conditions. Then you can plot all of these variables on a chart to find out how the day compares to the norm.

The first step is to determine what type of air mass is in your area. An air mass is a large body of air that has fairly consistent temperature and moisture content. There are several clues that will help you identify whether you are within a tropical air mass or a polar air mass. The first is the season. In the United States, tropical air masses tend to dominate in the summer and polar air masses tend to dominate in the winter.

Here are other clues: polar air masses range from cool to extremely cold. One may bring bitterly cold temperatures to Montana (−10°F, or −20°C), yet on the rare occasion when it moves as far south as Florida, it may warm up to 50°F (10°C). Tropical air masses, on the other hand, range from warm to very hot. In the winter, they are generally limited to the southern states. If a tropical air mass makes it to the northern United States, it brings unseasonably mild temperatures.

The second step is to record the maximum temperature for the day. Then you must find the average maximum temperature for your location at the particular time of year. This information can be found at your local public library or weather service office. Records are generally kept for ten-year periods. One you have taken a reading of the day's maximum temperature, compare it to the average maximum temperature. Note whether it is higher or lower than the average, and by how many degrees.

The next step is to observe today's weather: Is it overcast or partly-to-mostly sunny? Are the winds calm-to-light or strong?

Putting your weather observations to use

One way to put your daily weather records to use is to become an official observer for the National Weather Service. This requires sending copies of your records to the NWS, where they will be added to the pool of data used by professional meteorologists. To learn how to do this, contact the weather service office in your area. Local radio and television stations also often receive reports from amateur observers.

State-of-the-art forecasting equipment

To complete the global atmospheric picture, a survey of the upper air is also necessary. Meteorologists rely on extremely sophisticated equipment

to supply information about atmospheric conditions at various levels of the troposphere (the lowest part of Earth's atmosphere). This section will describe this equipment plus the supercomputers that analyze the mountains of data and produce forecasts at incredible speeds.

Weather balloons

The very first upper air measurements were obtained by standing on mountaintops or by sending up instruments attached to kites. Then came the days when scientists would ride in hot air balloons and take readings. Pioneering balloonists risked their lives, ascending thousands of feet above ground where the air is dangerously thin and cold. Modern weather balloons filled with hydrogen or helium carry electronic instrument packages called radiosondes. These unpiloted balloons can safely climb to far greater heights than their piloted predecessors.

The instruments in radiosondes measure temperature, air pressure, and relative humidity as they ascend to a maximum of 20 miles (30 kilometers) above ground. Radiosondes are equipped with radio transmitters that continuously relay measurements to stations on the ground. Rawinsondes are radiosondes that emit a signal so that their location can be tracked by radar on the ground. From the path of a rawinsonde, one can determine how wind speed and direction changes with altitude.

About 1,000 radiosonde stations have been established worldwide, approximately 125 of them in the United States. About 500 radiosondes are launched at the same time around the world twice each day. These launches take place at noon and midnight Greenwich Mean Time, which is 7:00 am and 7:00 pm Eastern Standard Time. A balloon takes forty-five to ninety minutes to reach its maximum height. At that point the balloon bursts.

In the United States, radiosondes are equipped with parachutes so they can reach the ground intact. Each one comes with a prepaid mail bag and instructions, so the finder can return it to the National Weather Service. About one-third of all radiosondes launched are returned in this way and reused.

A variation on the radiosonde is the dropwindsonde. This instrument package is released at high altitude by an aircraft rather than being carried aloft by a balloon. It parachutes to Earth at a speed of 11 mph (18 kph), radioing back atmospheric measurements every few seconds. Dropwindsondes are used primarily over oceans, where there are very few surface stations for launching radiosondes.

Weather aircraft

Weather aircraft also contribute to the collection of data in upper levels of the troposphere. They are used primarily to probe storm clouds, within which they measure temperature, air pressure, and wind speed, and direction. These airplanes have reinforced wings and bodies in order to withstand the hail, ice, and strong winds they encounter inside the clouds. The weather instruments are carried in pods beneath the plane's wings or attached to its nose cone. Weather aircraft are employed in small numbers by most of the world's leading meteorological agencies.

Weather aircraft have contributed greatly to our understanding of hurricanes and other tropical storms. In the fall of 1996 NOAA acquired a jet, called the Gulfstream IV-SP, specifically for studying hurricanes. The jet can cruise right through these storms at heights of up to 45,000 feet (8.5 miles or 14 kilometers). The NOAA jet contains sensors that measure air pressure, temperature, humidity, and wind speed at the edges and the core of the storm. It is just one of the eight types of research aircraft in use by NOAA.

Who's who: Tom Kudloo, aerologist

Tom Kudloo operates a weather station in the Arctic, one of the thousands of weather stations across North America. He is an aerologist, someone who observes and gives reports of local atmospheric conditions. Kudloo uses weather balloons to take readings of upper-air conditions twice daily.

"I attach weather instruments and a tiny radio transmitter to the balloon," says Kudloo. "A cardboard box holds the radio transmitter and a sensor to measure air temperature, air pressure, and humidity. As the balloon rises, the sensor also measures the balloon's speed and direction. This helps me calculate the wind speed and direction. As the balloon goes up, the radio transmitter sends me information about the air masses above me."

This information is entered directly into a computer, which prints out a report. Kudloo analyzes this report and sends the results to forecast offices in several major cities.

He sends up balloons at 5:15 am and 5:15 pm, local time, each day. These times coincide with balloon testing carried out at many other weather stations around the world. In this way, Kudloo's results can be coordinated to achieve a global picture of the atmosphere at particular times.

The reason for upper-air hurricane research was explained by Commander Ron Philippsborn, one of four pilots to fly the NOAA jet, in the August/September 1996 issue of Weatherwise magazine: "We want to get almost to the base of the stratosphere if we can, up to the outflow regions of the hurricane," said Philippsborn. "If we do that, we will finally be able to look at the entire air column throughout the environment of the hurricane, as well as the steering currents. This data will be fed into sophisticated computer models to improve forecasters' ability to figure out where these things are going to go."

The information collected by the jet is combined with readings taken at ground stations, in order to better assess where a hurricane is headed. In this way, it is possible to provide more advance warning to communities in the hurricane's path.

Other research platforms

In addition to weather aircraft, NOAA also operates several other weather data-gathering systems. The NOAA ship the Ronald H. Brown is a state-of-the-art oceanographic and atmospheric research platform, sailing out of Charleston, South Carolina. It was commissioned in 1997, and as of 2007, is the largest vessel in the NOAA fleet. The Ronald H. Brown carries a wide variety of highly advanced instruments and sensors, and can travel worldwide supporting scientific studies to increase our understanding of the world's oceans and climate. NOAA also operates nineteen other vessels based in ports around the world, from which they conduct oceanographic and atmospheric research.

Radar

Since its development during World War II (1939–1945), radar has become an indispensable tool for forecasting precipitation. Conventional radar (versus Doppler radar, discussed below) detects the location, movement, and intensity of precipitation, and gives indications about the type of precipitation present in a weather system. Since radar continuously scans a large region, it can detect isolated areas of precipitation that are often missed by instruments at widely spaced weather stations. For this reason, radar is particularly valuable for monitoring severe weather systems that are concentrated over small areas, such as thunderstorms. Radar is also valuable for assessing the intensity of larger severe weather systems, such as hurricanes.

Radar is an abbreviation for "Ra dio D etection a nd R anging." Conventional radar operates by emitting short-wavelength radio waves in the microwave portion of the radio spectrum. The microwaves are reflected by precipitation but not by the tiny droplets of water or ice that make up clouds. In this way, radar distinguishes between precipitation, which it "sees," and clouds, which it does not "see."

Precipitation scatters the microwaves, sending a portion of them—a "radar echo"—back to a receiver. The radar echo shows up as pulses on a cathode-ray monitor, which is similar to an older-style television screen. The radar continuously rotates, scanning a complete circle with a radius of up to 250 miles (400 kilometers) surrounding the station. It sends out and receives hundreds of signals each second.

Since radar waves travel at the speed of light, the distance of the precipitation from the radar station can be determined by the length of time between the emission and reception of a signal. The intensity of precipitation, or "echo intensity," is determined by the strength of the radar echo. This echo is portrayed on the monitor where intensities are color-coded. For example, large raindrops and hailstones, which have the greatest echo intensity, show up as red or purple, while light rain shows up as green.

In the mid-1970s a new, vastly improved type of radar, called Doppler radar, was developed. Doppler radar is based on the Doppler effect, discovered in 1842 by Austrian physicist Christian Doppler (1803–1853). The Doppler effect is the change in frequency of sound waves emitted from a moving source.

Waves bunch up as they approach their target and spread out as they move away from their target. An example of this effect is that the whistle of a train moving toward an observer sounds with a higher frequency than does the whistle of a train moving away from the observer. Similarly, a storm approaching a radar station reflects radar waves with a higher frequency than a storm moving away from a radar station.

Doppler radar can perform all of the functions of conventional radar plus it can determine the direction in which precipitation is moving, as well as wind speed and direction. Doppler can even estimate rainfall rates, which is important in foretelling floods. It can also locate fronts and wind shifts even in the absence of precipitation.

Doppler radar can look within a storm system and map out the air circulation patterns. This information allows forecasters to witness the earliest stages of a thunderstorm or tornado. While conventional radar can predict a

tornado only two minutes before it is fully formed, Doppler radar gives twenty minutes's advance warning. Doppler radar gives a much sharper overall picture of precipitation and wind patterns than does conventional radar.

Aircraft pilots are particularly grateful for Doppler radar. Doppler radar can measure the velocity (speed and direction) of winds, giving advance warning of wind shear, which is a quick change in the direction or speed of the wind. A strong, downward wind that is the result of a wind shear, called a microburst, has been responsible for many plane crashes.

In the mid-1990s, the National Weather Service began replacing its conventional radars with Doppler radars. Between 1992 and 1997, 158 high-powered Doppler radars were installed. Each one can detect precipitation up to about 285 miles (460 kilometers) away and can measure winds up to about 150 miles (240 kilometers) away. These radars, which cover the continental United States, Alaska, Hawaii, Guam, and Korea, make up the NEXRAD (Next Generation Weather Radar) system, a joint project of the National Weather Service, the U.S. Air Force, and the Federal Aviation Administration. Additional Doppler radars known as Terminal Doppler Weather Radar (TDWR) were installed at major airports, specifically to watch for thunderstorms and microbursts.

Since Doppler radars have come into use, the success rate of identifying damaging thunderstorms and tornadoes has increased sharply. At the same time, the number of false alarms has been cut in half. The advance warning provided by Doppler radar has saved many lives.

Wind profilers

A wind profiler is a specialized Doppler radar that probes the upper levels of the troposphere (the lowest part of Earth's atmosphere). Resembling a giant metal checkerboard, a wind profiler is a 40-foot-by-40-foot (12-meter-by-12-meter) wire mesh antenna mounted on Earth's surface. It is aimed straight up toward the sky and measures the speed and direction of winds aloft.

The technical name for a wind profiler is a "phased array antenna." It works by sending radar waves into the air. As the radio waves encounter changes in air density (caused by differences in temperature and humidity), they are reflected back to the antenna at varying intensities. A computer analyzes the data and calculates wind speeds and directions at seventy-two different levels of the atmosphere, to a maximum of 10 miles (16 kilometers) up. From that, average hourly wind speeds are calculated. This information is then sent to out to local offices of the National Weather Service and used in the creation of local forecasts.

The advantage of wind profilers over radiosondes or rawinsondes is that while rawinsondes take measurements only twice a day, wind profilers take readings every six minutes. Rawinsondes, however, measure temperature, air pressure, and humidity, as well as wind speed and direction. Wind profilers are used to complement the data collected by rawinsondes.

In 1992 the first network of twenty-nine wind profilers was erected in sixteen states throughout the Midwest. Scientists anticipated that the data they provided would assist in producing more accurate short-term weather forecasts. Up-to-the-minute information about winds aloft is particularly useful for plotting the course of a storm and for pilots who are planning flight paths. By 2004, thirty-five wind profilers had been installed in the central plains of the United States and Alaska.

Weather satellites

The weather forecaster's most valuable tool for creating long-term forecasts is the weather satellite. Weather satellites make it possible to view storms from space and to monitor weather conditions continuously around the planet. Weather satellites also provide meteorologists with pictures and other information about hurricanes and tropical storms that occur over the oceans and points on land that are beyond the range of surface weather stations.

The first weather satellite, launched in April 1960, was TIROS 1. TIROS stands for Television Infrared Observation Satellite. It took twenty-three thousand pictures of global cloud cover over a period of seventy-eight days, exceeding the expectations of meteorologists. In September 1961, the value of weather satellites hit home with the images sent back of Hurricane Carla. That information resulted in the first widespread evacuation in the United States. About 350,000 people along the Gulf coast were removed from the path of the killer hurricane.

Today, several nations operate weather satellites. In addition to the United States, these include member nations of the European Satellite Agency, as well as Japan, India, and Russia.

Weather satellites do more than photograph clouds

For most people, the words "weather satellite" conjure up images of swirling clouds seen from space. While weather satellites do produce such photos, their function is far more extensive. Weather satellites determine the temperature at various atmospheric levels, from cloud tops down to the land and oceans. They also measure humidity and wind speeds in the upper air and even track plumes (shifting regions) of invisible water vapor. In addition, satellites relay information from one ground station to another and pick up and transmit distress signals from vessels in the air and at sea.

Imaging equipment on board satellites is capable of receiving two types of radiation from Earth: visible and several channels of infrared. Visible radiation is reflected sunlight. Sensors on board satellites take what is essentially a black-and-white photo of the visible radiation. These pictures show cloud patterns as well as surface features larger than about a half-mile (a kilometer) across that are situated under clear skies. Therefore, it is possible to distinguish storm systems, fronts, thunderstorms, hurricanes, topographical landmarks, and even snow cover on land.

Infrared radiation is heat that is radiated by or reflected from Earth's surface. The picture produced by infrared sensors is essentially a road map of the temperatures of the cloud tops. Temperature varies with height—generally, the higher the cloud top, the lower the temperature. An infrared image also shows the location and intensity of thunderstorms. Thunderstorms are produced by towering clouds. The higher the cloud top, the greater the intensity of the thunderstorm.

The intensity of infrared radiation is also a measure of the amount of water vapor in the air. Since rising air carries moisture aloft, areas of vertical motion can be also be assumed to have high humidity. The presence of water vapor in the air, measured on what is known as the satellite's "vapor channel," has been recognized as an important factor in the development of thunderstorms at locations far from the vapor plume itself.

The instruments on board satellites analyze the visible and infrared radiation they receive and produce soundings. Soundings are analyses of temperature and humidity at different atmospheric heights. Satellites transmit these data by radio to weather forecasting centers several times daily.

Geostationary and polar-orbiting satellites

The United States' fleet of weather satellites is operated jointly by NOAA and the National Aeronautics and Space Administration (NASA). Generally, weather satellites are either geostationary or polar-orbiting. Geostationary satellites orbit at an altitude above Earth's equator, about 22,300 miles (35,000 kilometers), that gives them the same orbital period as Earth's rotation period. Consequently, they appear to be "parked" above a given point on Earth's equator. Polar-orbiting satellites, on the other hand, travel north-south routes, crossing over both poles just 500 to 620 miles (800 to 1,000 kilometers) above Earth's surface. Together, geostationary and polar-orbiting satellites constitute a complete global weather monitoring system.

The current series of U.S. geostationary satellites is called Geostationary Operational Environmental Satellite (GOES). The first satellite in this series was launched in 1975. In late 2006, NOAA had four operational geostationary satellites. GOES-11 and GOES-12 are positioned to view the United States. Together, they provide complete scans every thirty minutes. GOES-10 has been positioned to scan much of South America. GOES-13 is operational, but has been placed in reserve (or storage) until needed.

Because of its high altitude, a geostationary satellite is able to scan nearly one-third of Earth's surface at a time, producing a picture of all of North America every thirty minutes. Most of North America is scanned by two different satellites, sometimes called GOES East and GOES West. Among other data collected by these satellites, they can detect developments in the atmosphere (which meteorologists call "triggers") that may lead to severe weather events, such as tornadoes, flash floods (sudden localized floodings), and hurricanes. Once the satellite detects a trigger, it tracks the storm's movements closely.

NOAA also operates several polar-orbiting satellites. The two oldest operational satellites are named NOAA-12 and NOAA-14. They were

launched in May 1991 and December 1994, respectively. While still operational, they are currently considered on standby status. Launched between 1998 and 2005, NOAA-15, 16, 17, and 18 are a newer and heavier design with enhanced capabilities.

Each satellite completes just over fourteen orbits in a twenty-four-hour period. Consequently, each satellite flies over a given point on Earth's surface approximately twice each day. Between the two satellites, every place on Earth is observed four times each day, twice in the morning and twice in the afternoon. Measurements of atmospheric conditions are therefore updated every six hours for each location. A lower flying polar-orbiting satellite collects highly detailed information from 100-mile-wide (60-kilometer-wide) sections of Earth's surface at a time. The polar-orbiters, in addition to monitoring temperature, cloud cover, and humidity, are equipped with ultraviolet sensors. These sensors measure ozone levels in the atmosphere and monitor the ozone hole, where ozone gets low in the upper atmosphere, that develops over Antarctica each fall.

The most recent entry in the fleet of polar-orbiting satellites is NOAA-18, which was developed by NASA for NOAA. It collects information about Earth's atmosphere and environment to improve weather prediction and climate research across the globe. NOAA-18 has the capability to detect severe weather and report to it the National Weather

Service, which broadcasts the findings to the global community. Early warning can mitigate the effects of catastrophic weather.

NOAA-18 also has instruments to support an international search-and-rescue program. The Search and Rescue Satellite-Aided Tracking System transmits to ground stations the location of emergency beacons from ships, aircraft, and people in distress around the world. The program, in place since 1982, has saved about eighteen thousand lives. NOAA-18 is also the first in a series of polar-orbiting satellites to be part of a joint cooperation project with the European Organization for the Exploitation of Meteorological Satellites.

Oceanographic satellites

NOAA at one time also operated satellites specifically designed for surveying the oceans. The first of these, called Seasat, was launched in June 1978. After just one hundred days of operation, it ceased operation due to a power failure. While in orbit, Seasat used radar wave, visual, and infrared sensors to determine water surface temperature, wind speed, wind direction, wave height, and weather conditions on the seas.

The data collected by Seasat was used in the creation of the next oceanographic satellite, called the Ocean Topography Experiment, or TOPEX. (Topography is the shape and height of Earth's surface features.) The U.S. TOPEX, together with the French satellite Poseidon, was launched in 1992. The TOPEX/Poseidon data was used to create near-perfect maps of ocean topography, complete with ice floes (chunks of floating ice), wind, and waves.

In December of 2001, TOPEX/Poseidon was operationally replaced by Jason-1, a joint program of NASA and the French Centre National d'Etudes Spatiales. Jason-1 has vastly improved understanding of ocean circulation and its effect on global climate. This new system completed its fifth year in orbit on December 7, 2006. From its vantage point 860 miles (1,330 kilometers) above Earth, Jason-1 has provided measurements of the surface height of the world's oceans to an accuracy of 1.3 inches (3.3 centimeters).

Computer forecasting models

Due to the complex and partly chaotic nature of weather forecasting, the National Weather Service has come to depend on computers to store and analyze the vast quantities of data received from surface weather stations, weather balloons, aircraft, radar, wind profilers, and satellites.

Before the use of computers in forecasting, which began in the mid-1950s, day-to-day forecasts could be made only thirty-six hours in advance. Now that computers have been developed to perform numerical forecasting, daily forecasts can be made for six to ten days in advance. Numerical forecasting is the use of mathematical equations and computer models to predict the weather.

The National Weather Service has contracted with IBM to provide supercomputer facilities to aid in hurricane forecasting through 2012. The computer system is a cluster of forty-four IBM eServer p690 servers located in Gaithersburg, Maryland. All together the system is capable of 7.3 trillion calculations per second. This improved forecasting was put to a severe test during the 2005 hurricane season, but it aided the NWS in making accurate landfall predictions for hurricanes Katrina and Rita. It also revealed gaps in our basic understanding of the forces controlling hurricanes.

NOAA and the NWS continue to upgrade and develop computer systems to improve the range and accuracy of forecasts. A wide variety of computer systems are used to run a variety of different numerical and dynamical models to provide local, aviation (for pilots), marine (for sailors), and other forecasts.

WORDS TO KNOW

occluded front:
a front formed by the interaction of three air masses: one cold, one cool, and one warm. The result is a multi-tiered air system, with cold air wedged on the bottom, cool air resting partially on top of the cold air, and warm air on the very top.
ozone hole:
the region above Antarctica where the ozone concentration in the upper atmosphere gets very low at the end of each winter.
ozone layer:
the layer of Earth's atmosphere, between 25 and 40 miles (40 and 65 kilometers) above ground, that filters out the Sun's harmful rays. It contains a higher concentration of ozone, which is a form of oxygen that has three atoms per molecule.
polar front:
the region or boundary separating air masses of polar origin from those of tropical or subtropical origin.
polar orbiting satellite:
a weather satellite that travels in a north-south path, crossing over both poles just 500 to 625 miles (800 to 1,000 kilometers) above Earth's surface.
precipitation:
water particles that originate in the atmosphere (usually referring to water particles that form in clouds) and fall to the ground.
psychrometer:
an instrument used to measure relative humidity. It consists of a dry-bulb thermometer and a wet-bulb thermometer. Also called hygrometer.
radar:
an instrument that detects the location, movement, and intensity of precipitation, and gives indications about the type of precipitation. It operates by emitting microwaves, which are reflected by precipitation. It is an abbreviation for Ra dio D etection a nd R anging. Radar may be called conventional radar to distinguish it from Doppler radar.
radiosonde:
an instrument package carried aloft on a small helium- or hydrogen-filled balloon. It measures temperature, air pressure, and relative humidity from the ground to a maximum height of 19 miles (30 kilometers).
rain gauge:
a container that catches rain and measures the amount of rainfall.
rainbow:
an arc of light, separated into its constituent colors, that stretches across the sky.
refraction:
the bending of light as it is transmitted between two transparent media of different densities.
relative humidity:
a measure of humidity as a percentage of the total moisture that a given volume of air, at a particular temperature, can hold.
shower:
a brief spell of localized rainfall, possibly heavy, that only occurs in warm weather.
sling psychrometer:
an instrument that measures relative humidity. It consists of a dry-bulb thermometer and a wet-bulb thermometer mounted side by side on a metal strip, which rotates on a handle at one end.

In addition, NOAA is developing an extensive system for storing and analyzing data. Two NOAA sites began using the system, called the Comprehensive Large Array-data Stewardship System (CLASS), in 2004. It provides researchers and policy-makers access to NOAA environmental data and products, obtained either from spacecraft or ground-based observations.

These national and global forecasts and maps are then handed down to local weather agencies and private meteorologists in the media and at airlines. Local weather forecast offices use this information, in combination with other data, to produce basic public forecasts (including warnings of hazardous weather such as floods, thunderstorms, thick fog, or high winds) and aviation reports. Weather offices on the coasts also provide marine forecasts.

Understanding forecasts

The final product of the measurement is a weather forecast. The basic elements of a professional, local forecast are presented in a straightforward way that can easily be understood. Rather than page after page of data, daily forecasts use a type of shorthand consisting of internationally recognized weather symbols and weather maps. Learning this weather "language" makes it possible to understand professional forecasts, and will also be a handy tool to use in a weather journal.

Who's who: Lewis Fry Richardson, forecaster by the numbers

British mathematician Lewis Fry Richardson (1881–1953) introduced the use of mathematical equations in forecasting with his 1922 report "Weather Prediction by Numerical Process." It took Richardson many months to devise a set of calculations that could represent the behavior of the various atmospheric processes necessary to create a sample twenty-four hour forecast. Although his calculations were far from perfect and his results quite inaccurate, he had set the stage for the development of the computer models which generate our forecasts today.

Richardson demonstrated that an enormous number of calculations would have to be made very quickly to produce accurate numerical predictions. In fact, he estimated that the creation of forecasts by his numerical process would require the efforts of sixty-four thousand mathematicians with calculators working around the clock every day of the year. Only with the advent of microcomputers did numerical prediction become feasible. With today's sophisticated equations that more closely model the behavior of the atmosphere, numerical prediction using computer models continues to produce increasingly reliable forecasts.

What a forecast says

A typical local forecast found in a newspaper, on the radio, television, or on the Internet will include information on at least the following conditions: temperature, humidity, air pressure, winds, sky conditions, and precipitation. On particular days, or in certain locations, forecasts may include additional information, such as storm warnings, marine advisories, aviation forecasts, and air quality reports. Forecasts may also give the times of sunrise and sunset and tell the phase (how much of the Moon is visible from Earth; how "full" it is) of the Moon.

Temperature

In addition to giving the current temperature, most weather forecasts include the high and low temperatures for the preceding twenty-four hours. By way of comparison, they also include the normal high and low temperatures, as well as the record high and low temperatures, for that location on that date.

In winter or in cold climates, where the danger of frostbite (freezing skin) exists, weather forecasters include an index called the windchill equivalent temperature (WET), or windchill index, or just windchill. It is a measure of how cold the air feels, due to the interaction of wind and temperature. The WET is the temperature at which the body would lose an equivalent amount of heat if there were no wind. For instance, if it were 30°F (−1°C) with winds blowing at 15 mph (24 kph), the WET would be 9°F (−13°C).

During winter, or in any place where it is cold enough to require home heating, local weather forecasts may include a measurement called heating-degree-days. A degree-day is the number of degrees' difference between the day's mean (average) temperature and a temperature selected to represent the temperature at which most people set their thermostats. By tallying the total number of degree-days throughout a season officials can get a good idea of how cold the period has been and, consequently, how much heating fuel has been consumed.

To calculate the mean temperature, add together the day's high and low temperatures and divide by two. For example, say the high temperature for the day is 50°F (10°C) and the low is 20°F (6°C). The mean temperature is 35°F (50°F + 20°F, divided by 2). Now assume that in an average home the thermostat is set at 65°F (18°C). For this particular day, subtract the mean temperature, 35°F, from 65°F and come up with 30 degree-days. The colder the climate and the more severe the winter, the greater the number of heating-degree-days for the season.

Humidity

What is referred to as "humidity" in forecasts is actually the relative humidity. It is expressed as a percentage of the amount of moisture in the air compared to the total moisture the air is capable of holding at that temperature. This measurement will not necessarily tell how wet or muggy the air will feel, since that is greatly dependent on temperature. For instance, 85 percent relative humidity will feel much more uncomfortable when it is 90°F (32°C) than when it is 50°F (10°C).

One way to determine "mugginess" is to look at the wet-bulb temperature. A wet-bulb thermometer will always give a reading that is lower than the actual air temperature except when the outside air has 100 percent relative humidity. When it is hot out, the lower the wet-bulb reading, the faster sweat evaporates, and the less muggy it feels. As the wet-bulb temperature approaches the air temperature, the slower sweat evaporates and the muggier it feels.

The temperature at which the wet-bulb temperature equals the actual air temperature is the dew point. The dew point, the temperature at which moisture condenses out of the air (because the air is saturated), can be used as a measure of mugginess or comfort. In general, if the dew point is below 40°F (4°C), the air feels dry. If it is between 40°F and 59°F (15°C), the air feels comfortable. If the dew point is higher than 59°F, the air feels muggy.

Air pressure

Measurements of air pressure always include the pressure itself (which may be given in a variety of different units) and whether the pressure is rising or falling. The latter piece of information is more significant than the former, since it is the change in air pressure that gives clues about weather patterns. Recall that rising pressure generally means fair weather and falling pressure means changing weather.

There are no set values defining "high pressure" and "low pressure," since these are meaningful only when two pressures are compared to one another. That is, air pressure is "high" only if it is higher than an adjacent system or "low" if it is lower than an adjacent system.

At sea level, the average air pressure is 29.92 inches (1013 millibars). While it is tempting to categorize anything above that as "high" and anything below that as "low," consider this: The air pressure at one location may be 30.12 inches (1020 millibars) adjusted to sea level, considerably higher than average. Yet that location may be situated within a high-pressure belt where the average pressure is 30.25 inches (1024 millibars). In light of this information, is that air pressure "high" or "low"?

Winds

Most weather forecasts provide two pieces of data about the wind: speed and direction. The speed describes current conditions, while the direction is most valuable as an indicator of what is to come.

Here is a general guideline for categorizing how windy a day is: From 0 to 10 mph (0 to 16 kph) the wind is somewhere between still and gentle; from 10 to 20 mph (16 to 32 kph) the wind is moderate or "breezy"; from 20 to 30 mph (32 to 48 kph) the wind is strong; and anything above 30 mph (48 kph) is a gale-force wind.

Wind direction often provides a clue as to what type of weather is coming, although the specifics vary from location to location. See if you can draw a connection between wind direction and weather patterns in your area by examining trends in your weather journal.

Sky conditions

This section of the forecast includes information on the amount and type of cloud cover, as well as fog and haze, when relevant. It also includes changes in conditions, such as "increasing cloudiness," "decreasing cloudiness," "clearing," or "fog lifting before noon." In general, increasing cloudiness indicates a greater chance of precipitation while decreasing cloudiness and lifting fog indicate that fair weather is in store.

Precipitation

This category contains information on the amount of rain or snow that has fallen within the previous twenty-four hours and amount predicted to fall during the coming twenty-four hours. In the United States, rainfall and snowfall are generally measured in inches. Any rainfall over one-half inch (about one centimeter) in one day is considered heavy. It takes about five or six inches (about fifteen centimeters) of snow to be considered a heavy snowfall. Snow occupies roughly ten times the volume of its melt-water equivalent although this varies with temperature. The warmer and wetter the snow, the higher the meltwater equivalent, and the colder and drier the snow, the lower the melt-water equivalent.

Most forecasts state that there is a certain percent chance that rain or snow will fall during the coming twenty-four hours. Alternatively, the probability of precipitation may be characterized by terms such as "chance of rain" or "slight chance of snow."

The percentages are determined by examining ten days in the past which had weather conditions comparable to the present day. The first step is to tally up how many of those ten days had at least 0.01 inch of rainfall or the meltwater equivalent of snowfall. Then that number is divided by ten and multiplied by 100 percent. Thus, if precipitation occurred on four out of ten similar days, there is a 40 percent chance of precipitation for the present day.

A key reference to: The humiture index

The humiture index, also known as the "temperature-humidity index," is another way to measure how hot and muggy it feels and consequently how stressful outdoor activity will be. The index is based on the same principle as the wet-bulb temperature, namely that the faster water (or sweat) evaporates, the less muggy it is (and the cooler people feel), and vice versa.

The humiture index is most useful during the hottest part of the day. The value for any given set of conditions can be determined by solving a rather complex equation for given values of temperature and relative humidity. Fortunately, there is a chart that serves the same purpose. The lower the humiture index, the more comfortable the air feels. Any value over 89 on the chart is in the "uncomfortably hot and muggy" range.

Most television and newspaper weather forecasts include some form of humiture index when conditions are so hot and muggy that people are in danger of suffering heat stroke. This index may be listed as a "heat-stress index" or "apparent temperature." It generally includes one of the following four danger categories: caution, extreme caution, danger, or extreme danger.

Many forecasters prefer to use phrases to describe the chance of rain or snow. Here is a key to understanding those phrases, as well as some other forecasting language relating to precipitation:

  • slight chance of precipitation—10 or 20 percent chance
  • chance of precipitation—30 to 50 percent chance
  • occasional precipitation—over 50 percent chance (but will last less than half of the forecast period)
  • showers—localized, brief rainfall ("snow showers" refers to snowfall)
  • rain—steady rainfall covering a wider area
  • isolated showers—showers that fall on less than 10 percent of the forecast area
  • scattered showers—showers that fall on 10 to 50 percent of the forecast area
  • numerous showers—showers that fall on the majority of the forecast area
  • periods of rain (or snow)—on-and-off rain (or snow) throughout the whole area, for the duration the forecast period
  • snow squall—very heavy, brief snowfall
  • snow flurries—very light snowfall that results in little or no accumulation
  • heavy snow—snow that is accumulating at a rate of at least 1 inch per hour, with visibility less than 5/16 of a mile

International weather symbols

The set of weather symbols in use today was developed as a way to standardize the data collected by the thousands of weather stations around the globe. Using this universal shorthand, a weather station can describe many conditions—winds, temperature, visibility, present weather conditions, dew point, cloud cover, precipitation, and air pressure—for each time period (usually every three hours) in a space the size of a postage stamp. Forecasters also use symbols for fronts, pressure highs and lows, and regions of equal pressure, in the creation of weather maps. A weather station entry, sometimes called a station circle, is the form in which information is summarized by each individual weather station and sent to regional offices. A forecaster, by glancing at a station circle, can quickly discern the overall conditions at a given station.

Weather maps

A weather map, also called a surface analysis, is created by national or regional weather agencies and is intended for use by forecasters. Weather maps generally encompass an entire nation or group of nations. In North America, the basic map before weather patterns are added shows state/provincial borders, large cities, major rivers, and other important topographical features.

Station circles are plotted on the map at their appropriate locations. The collection of local data is then examined for patterns of air pressure and temperature. From this, meteorologists can determine the locations of fronts, regions of high and low pressure, the dividing line between

temperatures below freezing and above freezing, and the movement of storm systems. Each of these patterns is labeled on the map using symbols. The weather maps on television or in the newspaper are greatly simplified versions of the type used by forecasters.

A set of features found on many weather maps is a series of lines known as isobars. Isobars are lines that connect points of equal air pressure. On some maps, an air pressure value is tagged on each isobar. Closed isobar curves represent centers of high and low pressure. These areas are usually marked on a map with a capital "H" or "L." The isobars in the figure form concentric circles of increasingly high pressure. Between the high pressure areas are isobars of low pressure, where the lowest pressure is along the circle at the center.

Isobars are also guides to wind speed and direction. First, the closer the isobars are to one another, the steeper the pressure gradient and hence, the stronger the winds. Second, remember that winds do not flow into the center of high- and low-pressure areas, but around them. In the Northern Hemisphere, winds flow counterclockwise around the lows and clockwise around the highs. Isobars are generally closer together as they approach low-pressure areas, where winds also tend to be strong. Conversely, isobars are generally farther apart as they approach high-pressure areas, where winds are relatively calm.

Fronts, the boundaries between relatively warm and cold air masses, are also labeled on a weather map. The locations of fronts are determined by using both surface data and satellite images. Clues to the position of a front are found in surface readings for wind direction, dew point, sky conditions, and precipitation. The locations of temperature differentials on satellite images also help identify where air masses begin and end.

As illustrated in the national weather map, a line with triangles represents a cold front and line with half-circles represents a warm front. The triangles and half-circles point in the direction the air mass is heading. A line with triangles on one side and half-circles on the other represents a stationary front (the line between a cold and a warm air mass,

neither of which is moving) and a line with triangles and half-circles both on the same side represents an occluded front (a front formed by three air masses).

Satellite and radar images also indicate where precipitation is falling. These areas are marked on weather maps with certain colors or gray shading, or are superimposed with diagonal lines. The maps also indicate temperature by applying different shades of gray or colors to areas that fall within given temperature ranges.

Weather maps are also created for the upper levels of the atmosphere, using information provided by radar, weather aircraft, weather satellites, and radiosondes. These maps differ from surface maps in that they are constructed along an imaginary surface of equal pressure (i.e., 500 millibars, where the atmosphere is at half its sea-level pressure). Air pressure varies with altitude, primarily due to temperature differences. Air pressure drops with altitude at a faster rate in cold air masses than it does in warm air masses.

People can also discern the pattern of upper-air winds from upper-air maps. This information is valuable because the motion of winds aloft is a key component in the development of weather patterns at the surface.

Forecasting in the media

What most people know about the weather is based solely on reports they see on television, read in the newspaper, hear on the radio, or find on the Internet. These reports include general information about the nation's weather as well as more detailed analyses and predictions for the local area.

Television weathercasts

Television is the medium from which most people today get their weather information. Weather is an element of practically every local and national television news show, and the true weather fanatic with cable television can tune in to it twenty-four hours a day.

In addition to providing the basic information that helps people decide how to dress in the morning, TV weather can be quite educational. Television weathercasts have featured lessons on the dynamics of frontal systems, jet streams (the fastest upper-air winds), El Niño (strong episodes of Pacific warming), highs and lows, hurricanes, tornadoes, and other phenomena.

Weather reports first appeared on television in the early 1940s. The original broadcasts were extremely primitive, even laughable by today's standards. To assure some measure of professionalism in TV forecasts, the American Meteorological Society began issuing its Seal of Approval in 1959 to those weather shows it deemed trustworthy. A similar system of offering credentials was adopted by the National Weather Association in 1982.

In the early years, television weathercasters drew fronts, highs and lows, and other information by hand, or placed stick-on symbols onto large maps, as they gave their reports. In the early 1980s these methods were replaced by computer-generated color graphics. Coupled with images provided by geostationary satellites, which first began appearing on TV screens in the mid-1970s, television weathercasts became an impressive visual presentation.

The five-minute weather presentation seen during a TV news show may appear simple, but producing the segment is actually quite a laborious task. It begins about five hours before the broadcast, when the weather reporter pores through the stacks of computer-generated forecasts

provided by the National Weather Service, as well as radar and satellite images. It is the weather reporter's task to make sense of it all, condense it into a short report, and choose satellite images to go along with it.

Next comes the creation of weather graphics, including maps, forecasts, and animated satellite images. These animated images are actually a string of satellite pictures shown in quick succession, so it looks as if they are moving. While many television stations rely on private weather graphics firms to design the visuals for their weather shows, some stations, including The Weather Channel, design their own computerized graphics.

Then, just before the show, the weather reporter must get all the information in order, check for any last-minute changes in conditions, and rehearse the report. Finally, it's show time—five minutes later, it is over.

Newspaper weathercasts

There is no such thing as a standard newspaper weather report. Newspaper weather pages are often colorful, with easy-to-understand symbols (such as pictures of sun and clouds), and they contain a great variety of information presented in many different ways. For instance, newspapers may feature a large weather map of the entire nation, a local map, or both.

Regardless of the differences, some basic ingredients show up in one form or another in weather pages of most newspapers, particularly large ones. These include a weather map, a local report, national and local forecasts, a list of high and low temperatures for select cities in the North America, and, in some cases, around the world. Most weather maps include fronts and pressure systems. While many weather maps display isobars, an even greater number display isotherms, which are bands representing areas of similar temperature.

Most weather pages contain information that goes beyond the basic report. The specifics of those supplements generally depend on the economic, geographic, and recreational interests of the inhabitants of the locality. For instance, a weather page may contain a ski report, a marine forecast, a farm and garden report, or an air quality index. Some weather pages also contain sections for children, including pictures, activities, or "fun facts." Others may contain satellite photos, an analysis of the jet stream, or a tally of heating-degree-days.

Radio weathercasts

Without the aid of weather maps and other visuals, weather reporting is quite challenging. Thus, most commercial and public radio stations present only general current weather information and what listeners may expect over the next twenty-four hours. Other information, such as shipping reports or agricultural reports (generated especially for farmers), are broadcast in locations where they are relevant.

One source of extensive, local weather information on the radio, available all across the United States, is provided by the National Oceanic and Atmospheric Administration. NOAA Weather Radio is transmitted on seven different high-band FM frequencies, ranging from 162.400 to 162.550 megahertz. To hear this transmission, listeners may need a special receiver called a "weather radio." In some places, NOAA Weather Radio comes in on special radio bands such as the weather band, citizens' band, and some automobile, aircraft, and marine bands. In a few areas the transmission can be picked up on standard AM/FM radios.

Weather report: Wooly Lamb—the first weather reporter

The very first televised weather report was shown on October 14, 1941, on WNBT (later WNBC) in New York City. The report was presented by a cartoon character named "Wooly Lamb." The little lamb began each report by first looking at the sky through a telescope, then facing the camera and singing this song: "It' hot, it's cold. It's rain, it's fair. It's all mixed up together. But I, as Botany's Wooly Lamb, predict tomorrow's weather." ("Botany" referred to the show's sponsor, Botany's Wrinkle-Proof ties.) A written forecast for the next day's weather then appeared on the screen. Even more amazing than the notion of a cartoon lamb presenting the weather, is the fact that Wooly Lamb kept its job for seven years!

NOAA Weather Radio continuously broadcasts the latest weather information, twenty-four hours a day. Reports are usually four to six minutes long and are updated about every one to three hours. Reports are changed more frequently during rapidly changing or severe weather.

In response to hazardous weather, NOAA Weather Radio will sound an alarm that alerts listeners to turn up the radio and stay tuned. Some receivers are programmed to turn on whenever a hazardous-weather alarm is activated. NOAA Weather Radio also broadcasts reports from local weather service offices that are relevant to the region. For instance, one may offer marine reports while another offers agricultural reports and climatological forecasts.

NOAA Weather Radio broadcasts are prepared by local offices of the National Weather Service (NWS) and sent out from four hundred transmitters throughout the United States, Puerto Rico, Guam, and Saipan. Each station transmits to a radius of only 40 miles (64 kilometers), an area covered by the report. Presently, NOAA Weather Radio can be received by 80 to 95 percent of the U.S. population, provided they have a radio.

Weather on the Internet

The Internet serves as a link between the general public and just about every type of weather information imaginable. It is a valuable resource for professional meteorologists, the media, and weather enthusiasts alike. On the Internet, users can find satellite and radar images, photos of storms and storm-related damage, the predicted courses of hurricanes and inland storms, detailed forecasts for particular regions, reports tailored to specific interest groups (e.g., mountain climbers, boaters, and skiers), and much more.

A key reference to: The marvelous chroma key

Television weather reporters do not see what viewers see. The colorful weather map so familiar to TV audiences, to which the reporter appears to point as he or she describes the weather, does not show up in the studio. Instead, the background seen by the reporter is a single color, typically green or blue. The reporter relies on monitors on either side of the screen to determine the position his or her hands or body relative to the map.

The color images viewers see on a TV weathercast are produced by a process called "chroma key," or "color-separation overlay." A computer in the station's control booth electronically superimposes single-color portions of a graphic on top of one another, producing a full-color image. When the forecaster gives a verbal cue or when the color of the screen behind the reporter (the "chroma key") changes, a new graphic is appears.

National Oceanic and Atmospheric Administration

The most extensive and most reliable source of weather information on the Internet is from the National Oceanic and Atmospheric Administration. Much more than weather information is available: NOAA also covers fisheries, navigation, and other topics related to the oceans. It does, however, give

WORDS TO KNOW

stationary front:
the dividing line between two stationary air masses. It occurs when a cold air mass comes in contact with a warm air mass, with neither air mass moving.
sunspot:
an area of magnetic disturbance on the surface of the Sun, sometimes referred to as a sun storm.
thermograph:
an instrument consisting of a thermometer and a needle that etches on a rotating drum, continually recording the temperature.
thermometer:
an instrument used to measure temperature. It consists of a vacuum-sealed narrow glass tube with a bulb in the bottom containing mercury or red-dyed alcohol. Also called dry-bulb thermometer.
thunderstorm:
a relatively small but intense storm system, that produces moderate-to-strong winds, heavy rain, and lightning, sometimes with hail and tornadoes.
topography:
the shape and height of Earth's surface features.
tornado:
a rapidly spinning column of air that extends from a thunderstorm cloud to the ground. Also called a twister.
veering wind:
a wind that shifts direction, turning clockwise as it moves higher.
warm front:
the line behind which a warm air mass is advancing, and in front of which a cold air mass is retreating.
warning:
a severe weather advisory that means that a storm has been sighted and may strike a specific area.
watch:
a severe weather advisory that means that while a storm does not yet exist, conditions are ripe for one to develop.
weather:
the set of conditions of temperature, humidity, cloud cover, and wind speed at a given time.
weather aircraft:
aircraft that carry weather instruments and collect data in the upper levels of the troposphere. They are primarily used to probe storm clouds, within which they measure temperature, air pressure, and wind speed and direction.
weather forecast:
a prediction of what the weather will be like in the future, based on present and past conditions.
weather map:
a map of a large geographic region, on which weather station entries are plotted. By looking at a weather map, a meteorologist can determine the locations of fronts, regions of high and low pressure, the dividing line between temperatures below freezing and above freezing, and the movement of storm systems. Also called surface analysis.
weather satellite:
a satellite equipped with infrared and visible imaging equipment that provides views of storms and continuously monitors weather conditions around the planet.
wind sock:
a cone-shaped cloth bag open on both ends, through which wind flows that is used to determine the direction and estimate the speed of the wind.
wind speed:
the rate at which air is moving relative to the ground.
windchill equivalent temperature:
the temperature at which the body would lose an equivalent amount of heat, if there were no wind. Also called windchill index.

in-depth information on satellites (weather and others) and provide a link to the National Weather Service, which is a branch of NOAA.

Using forecasts

Most people listen to or read a forecast to decide how to dress the next day or whether to set up their party indoors or outdoors. But forecasts take on much greater significance when the weather is severe. Warnings of an approaching storm are intended to give local inhabitants time to take safety precautions and, if possible, secure their property. Forecasts take on economic significance for people who make their living outdoors or at sea.

Improving on forecasts

Understanding the basics of weather enables one to make greater use of forecasts. With knowledge of how the landscape (mountains, valleys, lakes, buildings, trees, etc.) affects weather conditions surrounding a locality, a local forecast can be customized to fit. For instance, in a city, the temperature, on average, may be a few degrees warmer than at the airport weather station. Large buildings block the wind, making it slower than what is reported.

Knowing how weather works, ordinary people can check the accuracy of a forecast. Remember that weather reports sent out through the media are generally based on information that is at least two hours old, and the weather is notorious for its quick changes. A cold front, for example, may advance more rapidly or more slowly than predicted, or a completely new weather system may develop quickly.

Severe weather warnings

One of weather forecasters' most important duties is to alert the public to approaching severe weather. In recent years, the amount of time between the warning of a potential disaster and its actual occurrence has greatly increased. This improvement is due primarily to better computer forecasting models. In fact, major storms such as hurricanes, blizzards (the most severe type of winter storm), and heavy rains can now be predicted by computer even before the weather conditions they produce are detected by weather stations.

Tools such as computer modeling, Doppler radar, and weather satellites have significantly improved the accuracy with which the course of severe storms can be predicted. This process is important because forecasters do not want to initiate evacuations of people who are not really in a storm's path. Evacuations, which are often carried out in advance of a hurricane, are very expensive. People spend money boarding up their houses and purchasing supplies. Businesses lose money when they are forced to close. More importantly, when people are evacuated without reason, they tend to lose faith in weather warnings. The next time a warning is issued, they may decide there is no reason to leave, even though that time they may really be in harm's way.

Far more challenging than predicting when a major storm will strike is predicting the approximately ten thousand violent thunderstorms and one thousand tornadoes that occur in the United States each year. In recent years, only modest gains have been made in this area. One reason why it is much more difficult to forecast small-scale storms than it is to forecast large-scale storms is that small, localized patterns are usually not predicted by computer models. The warning signs of tornadoes and thunderstorms must be picked up at weather stations before any type of advisory can be issued—and then there is usually not much time before the storm strikes.

Thanks to Doppler radar, recent improvements have been made in determining when thunderstorms become severe, as well as assessing the course of tornadoes. This technology, which gathers information from the heart of the storm, is responsible for increasing the warning times for violent thunderstorms, as well as halving the number of false alarms.

Meteorologists make use of two main categories of severe weather advisories: watches and warnings. A "watch" means that while a storm does not yet exist, conditions are ripe for one to develop. A "warning" is more serious. This message indicates that a storm has been sighted and may strike a given area. While numerous subsets of these categories are issued for each type of storm, these two words alone provide important clues about the status of a storm and how to respond appropriately. It is important to stay tuned to forecasts and heed all warnings. While some storms are merely exciting spectacles that cause little damage, others may create life-threatening conditions.

Specialized forecasts

Specialized forecasts are generated for particular geographic areas and are tailored to the interests of specific groups of people, such as pilots, boaters, travelers, and farmers.

Aviation reports provide information on the height of clouds, visibility, and storm systems. In response to reports of storms or poor visibility, a pilot may change his or her course and fly around a storm. Reports of poor conditions at an airport may force a pilot to delay landing or to proceed to a different airport. The National Weather Service operates a toll-free telephone information line to help keep pilots informed.

Marine forecasts are issued for areas along the coastlines of North America. Such forecasts are of interest to the nearly two-thirds of the population who live within 50 miles (80 kilometers) of a coast. These forecasts give projections of the times of high and low tides, wave heights, wind speed and direction, and visibility. When rough weather is brewing over the water, the NWS issues small-craft advisories and other warnings that may affect fishermen and other boaters, as well as workers on oil rigs.

Agricultural reports include current temperature, precipitation, and wind speed and direction, as well as predictions of temperature and precipitation for the days to come. One example of how farmers use this information is in deciding when to apply pesticides. The temperature projections help a farmer determine which insects will likely pose a threat to which crops. If a pesticide is deemed necessary but rain is predicted, a farmer will delay applying chemicals since rain will wash the chemicals off before they take effect. The farmer also takes into account the current wind information, as a safety measure, before spraying.

Another element of an agricultural forecast is a frost warning, which is issued to warn farmers of the danger to their crops. Decisions about when to irrigate, obviously, are also dependent on predicted rainfall. So is cutting hay, since fresh hay needs at least two days to dry once it has been cut.

Travelers' reports tell what the weather is like at a traveler's destination. Some TV or newspaper weather sources regularly include forecasts for popular vacation spots, while others list temperature highs and lows and general conditions for major cities around the world. Some travelers' reports indicate whether or not airlines are operating on schedule at airports in major travel destinations.

Ski reports, which describe conditions of interest to skiers, generally list forecasts for popular ski destinations.

The future of forecasting

In the early 1960s Edward Lorenz demonstrated that it may never be possible to predict the weather with perfect accuracy; just how close to perfection forecasting can come is still not known. However, the meteorological community is determined to push the success rate of forecasting to the theoretical limit, whatever that may be. With that goal in mind, meteorologists are pursuing various strategies, including achieving a greater understanding of the forces at work in creating weather, obtaining higher quality observational data, and improving computer capabilities.

Toward a greater atmospheric understanding

During the World War I era (1914–1918), the discovery of fronts, air masses, and upper-air patterns revolutionized how we look at weather. It sparked the rapid development that the field of meteorology continues to enjoy to this day. Along with increased knowledge of how weather works, however, has come the realization that there is still much to learn.

New facets of atmospheric science are continually being discovered and probed. Some topics currently under study include interaction between the ocean currents and temperatures and atmospheric circulation; the role of the stratosphere (the layer of Earth's atmosphere above the troposphere); the effect of plumes of water vapor in the air; the effect of ice particles in thunderstorm clouds, and lightning above the clouds, on the global electrical circuit; and the interaction of winds and clouds in the formation of storms.

As meteorologists learn how these factors fit with other pieces of the atmospheric puzzle, they can incorporate them into computer forecasting models. While technological advances in recent years have greatly improved the abilities of computers to process information, in the end, a computer merely does what it is programmed to do. The quality of the results depends on the sophistication of the program. The sophistication of the program, in turn, is a reflection of the programmer's understanding of atmospheric processes.

Weather report: Marine forecast

The following is an example of a marine forecast taken from NOAA on March 7, 2007: "Point Arena, California: Tonight: west winds 5 to 10 knots switching northwest late. Wind waves 1 to 2 feet with swell 4 to 6 feet at 11 seconds. Thursday: northwest winds 10 knots. Wind waves 1 to 2 feet with swell 5 to 7 ft at 10 seconds." A marine forecast for Plymouth, Massachusetts, on the same day reads follows: "SMALL CRAFT ADVISORY IN EFFECT FROM THURSDAY MORNING THROUGH THURSDAY EVENING. Tonight: west winds 15 to 20 knots. Seas 2 to 4 feet. A slight chance of snow showers after midnight. Light freezing spray after midnight with visibility 1 to 3 nautical miles. Thursday: west winds 20 to 25 knots, becoming northwest 25 to 30 knots. Seas 4 to 6 feet. Light freezing spray. A chance of snow showers in the morning. Visibility 1 to 3 nautical miles."

More and better observations

Another way that meteorologists are working to improve the accuracy of weather forecasts is by collecting more detailed data, with greater frequency. If they start out with incorrect, incomplete, or out-of-date data, it does not matter how good their computer model is—the results will be skewed. When more precise and current data are entered in a computer model, more accurate forecasts are produced.

One problem that forecasters are working to overcome is that in some parts of the world, such as sparsely populated lands and the oceans, observations are scant. An increase in the number of automated weather stations and weather satellites, anticipated to become operational over the next several years, will help remedy this shortfall.

The quality of observational instruments is also being improved. Older equipment is undergoing modernization and greater numbers of newer, high-tech instruments (particularly Doppler radar, wind profilers, and satellites) are being deployed.

Improving computer capabilities

Along with improvements in data collection, the future will also see more effective computers. The National Weather Service's supercomputers will certainly be replaced with newer, faster, and more powerful models that are capable of processing an increased volume of data. They will be programmed with more complex and sophisticated models and will produce forecasts with greater range and accuracy.

Another important criterion in a computer's performance is resolution. Resolution refers to the number of squares that make up the computer's grid system. The entire area under study, such as the continental United States, is divided into squares. The computer produces one forecast for each square in the grid by averaging conditions at all points throughout that square.

The number of squares in a grid is inversely proportional to the size of each square. The greater the number of squares, the smaller each square is. Likewise, as the square size decreases, the resolution increases and the more precise the forecast becomes.

Consider a low-resolution grid in which each square is 100 miles (161 km) across. Conditions can vary greatly over this 100-square-mile (260-square-kilometer) area. For example, temperatures may differ by 15°F (8°C) or more. Thus, a forecast based on average conditions will not be relevant for many points within the square.

Meteorologists have a goal to increase resolution so that each square within a grid is as small as 4 square miles (10 square kilometers). In that way, the variation of conditions within a square will be much lower and forecasts will become more accurate for every point within the square.

Ensemble forecasting

Meteorologists are currently experimenting with a new method of forecasting called ensemble forecasting. This method takes into account the predictability of the behavior of the atmosphere at the time a forecast is made. If the atmosphere shows signs of stability, the forecast is more likely to be correct than when atmospheric conditions are showing signs of rapid and erratic change.

The predictability of the atmosphere can be determined by running a series of computer simulations, starting with slightly different atmospheric variables each time. If the forecasts generated for ten days in advance in each simulation are similar to one another, then the atmosphere is in a predictable phase. However, if the forecasts start to differ from one another by day three, then the atmosphere is unpredictable.

The predictability of the atmosphere influences how accurate a forecast will be beyond a few days. Thus, using the ensemble method, a forecaster can determine the probability that his or her forecast will be correct. When the atmosphere is unpredictable, a forecaster may decide to limit a forecast to three days ahead. However, when the atmosphere is predictable, a ten-day forecast could be made with confidence.

[See AlsoClimate; Clouds; Human Influences on Weather and Climate; Hurricane; Precipitation; Weather: An Introduction ]

For More Information

BOOKS

Aguado, Edward, and James Burt. Understanding Weather and Climate. 4th ed. Englewood Cliffs, NJ: Prentice Hall, 2006.

Ahrens, C. Donald. Meteorology Today: An Introduction to Weather, Climate, and the Environment. 7th ed. Belmont, CA: Thomson Brooks/Cole, 2006.

Hodgson, Michael. Basic Essentials. Weather Forecasting. 3rd ed. Guilford, CT: Globe Pequot Press, 2007.

Kahl, Jonathan D. W. Weather Watch: Forecasting the Weather. Toronto, Ontario, Canada: Monarch Books of Canada Limited, 2002.

Vasquez, Tim. Weather Forecasting Handbook. 5th ed. Garland, TX: Weather Graphics Technologies, 2002.

WEB SITES

"Do-It-Yourself Weather Forecasting." Weather Michigan. 〈http://www.weathermichigan.com/u_do_it.htm〉 (accessed March 25, 2007).

"Official Weather Forecasts and Warnings." The World Meteorological Organization. 〈http://www.wmo.int/〉 (accessed March 25, 2007).

"Weather." National Oceanic and Atmospheric Administration. 〈http://www.noaa.gov/wx.html〉 (accessed March 24, 2007).

"Weather Office." Environment Canada. 〈http://weatheroffice.ec.gc.ca/canada_e.html〉 (accessed March 25, 2007).

"Welcome to the Weather Underground," Weather Underground〈http://www.wunderground.com/〉 (accessed March 25, 2007).

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