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- Author or Editor: Dennis M. Driscoll x
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Abstract
Abstract
Abstract
This investigation was undertaken to determine how different the weather forecasts of telecasters are from those of the National Weather Service for the same areas and times, and the sources of information telecasters use when they modify the NWS forecast or develop their own. Questionnaires were mailed to 453 television weatherpersons, most of whom were seal holders of the AMS; 67 percent were returned. It was determined that 1) only 6% of all respondents do not consider the NWS forecast at all, whereas for almost 60% this consideration is moderate or heavy; 2) the percentages of those who transmit a.forecast different from that of the NWS 0–10%, 40–60% and 90–100% of the time are 16, 30 and 8, respectively; 3) when the forecast issued was different from that of the NWS, the elements most likely to be different were precipitation (84%), temperature (82), state of sky (66), and wind speed and direction (34); 4) the factors that influence the telecaster to issue a different forecast are, in order, current weather, local conditions, the telecaster's own analysis of forecast models, the telecaster's experience, satellite photographs, radar, and colleagues. The responses to each of these four items were further stratified by whether or not the respondent held the AMS Seal of Approval, whether he/she had a bachelor's degree, years as a telecaster, and the size of the market area. The division of responses by the first two of these stratifiers produced the largest changes from the percentages for all respondents given in 1 and 2 above and also produced relatively large differences within that stratifier. For example, forecasters who are least likely to consider the NWS forecast, and who issue a forecast different from that of the NWS a large percentage of the time, are seal holders with a degree and 6 to 10 yr experience who work in one of the top twenty market areas.
Abstract
This investigation was undertaken to determine how different the weather forecasts of telecasters are from those of the National Weather Service for the same areas and times, and the sources of information telecasters use when they modify the NWS forecast or develop their own. Questionnaires were mailed to 453 television weatherpersons, most of whom were seal holders of the AMS; 67 percent were returned. It was determined that 1) only 6% of all respondents do not consider the NWS forecast at all, whereas for almost 60% this consideration is moderate or heavy; 2) the percentages of those who transmit a.forecast different from that of the NWS 0–10%, 40–60% and 90–100% of the time are 16, 30 and 8, respectively; 3) when the forecast issued was different from that of the NWS, the elements most likely to be different were precipitation (84%), temperature (82), state of sky (66), and wind speed and direction (34); 4) the factors that influence the telecaster to issue a different forecast are, in order, current weather, local conditions, the telecaster's own analysis of forecast models, the telecaster's experience, satellite photographs, radar, and colleagues. The responses to each of these four items were further stratified by whether or not the respondent held the AMS Seal of Approval, whether he/she had a bachelor's degree, years as a telecaster, and the size of the market area. The division of responses by the first two of these stratifiers produced the largest changes from the percentages for all respondents given in 1 and 2 above and also produced relatively large differences within that stratifier. For example, forecasters who are least likely to consider the NWS forecast, and who issue a forecast different from that of the NWS a large percentage of the time, are seal holders with a degree and 6 to 10 yr experience who work in one of the top twenty market areas.
Abstract
Late evening weather forecasts by telecasters at major network television stations in seven United States cities, and corresponding forecasts from the National Weather Service, were monitored by meteorology students for 6 months in 1985–86. These forecasts were of temperature and precipitation for the three periods of “tonight,” “tomorrow,” and “tomorrow night.” The accuracy of temperature forecasts was evaluated with three indexes: mean absolute error, root mean square error, and percentage of errors over 10°F. For precipitation, the indexes were Brier score (accuracy) and reliability.
The accuracy of temperature forecasts was not greatly different for the telecasters and the NWS. Three of 20 pairings show a statistically significant difference according to the sign test; this is not much more than would be expected by chance. For precipitation similar results were obtained: only 1 of 20 Brier score pairings is statistically significant. The NWS has higher reliability scores, although no test exists for determining the statistical significance of this difference.
Abstract
Late evening weather forecasts by telecasters at major network television stations in seven United States cities, and corresponding forecasts from the National Weather Service, were monitored by meteorology students for 6 months in 1985–86. These forecasts were of temperature and precipitation for the three periods of “tonight,” “tomorrow,” and “tomorrow night.” The accuracy of temperature forecasts was evaluated with three indexes: mean absolute error, root mean square error, and percentage of errors over 10°F. For precipitation, the indexes were Brier score (accuracy) and reliability.
The accuracy of temperature forecasts was not greatly different for the telecasters and the NWS. Three of 20 pairings show a statistically significant difference according to the sign test; this is not much more than would be expected by chance. For precipitation similar results were obtained: only 1 of 20 Brier score pairings is statistically significant. The NWS has higher reliability scores, although no test exists for determining the statistical significance of this difference.
Abstract
A stochastic model for hourly temperatures for Big Spring, Tex., has been developed. The governing parameters were deduced from an 11-year developmental sample, and give hourly temperatures as a function of harmonics representing annual and diurnal variations, and a first-order Markov chain process. The latter incorporates adjustments for the seasonal variation of the serial (hour-to-hour) correlation coefficient, and for the seasonal and diurnal variations of the variability and non-normality of frequency distributions of hourly temperatures. Each of the characteristics is given explicitly as a function of hour of the year.
Two 10-year samples were generated and compared to the developmental sample. Criteria were established to determine how well the model duplicates nature. The variability of mean monthly temperature and the frequency of occurrence of low diurnal ranges are underestimated. However, the model gives good estimates of the duration of temperatures below 32°F, and above 65° and 90°F, and of the frequency distribution of monthly 3, 6, 12, 24, 72 and 144 h maximum and minimum temperatures.
The general applicability of the model and its utility are discussed. The model could be used to determine the effects of climatic trends, e.g., a gradual cooling, on the average length of the growing season, the mean number of heating/cooling degree days, and other temperature-related parameters.
Abstract
A stochastic model for hourly temperatures for Big Spring, Tex., has been developed. The governing parameters were deduced from an 11-year developmental sample, and give hourly temperatures as a function of harmonics representing annual and diurnal variations, and a first-order Markov chain process. The latter incorporates adjustments for the seasonal variation of the serial (hour-to-hour) correlation coefficient, and for the seasonal and diurnal variations of the variability and non-normality of frequency distributions of hourly temperatures. Each of the characteristics is given explicitly as a function of hour of the year.
Two 10-year samples were generated and compared to the developmental sample. Criteria were established to determine how well the model duplicates nature. The variability of mean monthly temperature and the frequency of occurrence of low diurnal ranges are underestimated. However, the model gives good estimates of the duration of temperatures below 32°F, and above 65° and 90°F, and of the frequency distribution of monthly 3, 6, 12, 24, 72 and 144 h maximum and minimum temperatures.
The general applicability of the model and its utility are discussed. The model could be used to determine the effects of climatic trends, e.g., a gradual cooling, on the average length of the growing season, the mean number of heating/cooling degree days, and other temperature-related parameters.
Abstract
An objective weather typing scheme first proposed by Christensen and Bryson (1966) was applied to surface and upper air variables for the period April–September of 1973–76 at Midland, Texas. Principal components analysis showed that moisture and temperature, which were represented by the first and second components, respectively, are most important in distinguishing day-to-day weather, while synoptic variables such as wind and pressure are relatively unimportant.
The days of the study period were then assigned to weather types after applying multiple regression analysis and an objective grouping method. The principal disadvantages of the latter procedure are the large number of untyped days and the relatively few days assigned to types after the second. Suggestions for improving this grouping method are offered.
Surface and 500 mb charts for the same period were examined and each day was typed according to a method specifying surface and upper air synoptic features. The two methods were then compared. The correspondence is very general because the variables manifest in synoptic representation, pressure and wind, are of only secondary significance in the principal components. Air mass changes are therefore more important in distinguishing day-to-day weather than are synoptic controls; this applies less so at the beginning and end of the convective season than in the middle of it.
In a specific application of both methods to convective activity levels as inferred from the number of initial echoes per day, the greater distinction was made by the objective method, with highest levels occurring in the warmest and most moist types.
Abstract
An objective weather typing scheme first proposed by Christensen and Bryson (1966) was applied to surface and upper air variables for the period April–September of 1973–76 at Midland, Texas. Principal components analysis showed that moisture and temperature, which were represented by the first and second components, respectively, are most important in distinguishing day-to-day weather, while synoptic variables such as wind and pressure are relatively unimportant.
The days of the study period were then assigned to weather types after applying multiple regression analysis and an objective grouping method. The principal disadvantages of the latter procedure are the large number of untyped days and the relatively few days assigned to types after the second. Suggestions for improving this grouping method are offered.
Surface and 500 mb charts for the same period were examined and each day was typed according to a method specifying surface and upper air synoptic features. The two methods were then compared. The correspondence is very general because the variables manifest in synoptic representation, pressure and wind, are of only secondary significance in the principal components. Air mass changes are therefore more important in distinguishing day-to-day weather than are synoptic controls; this applies less so at the beginning and end of the convective season than in the middle of it.
In a specific application of both methods to convective activity levels as inferred from the number of initial echoes per day, the greater distinction was made by the objective method, with highest levels occurring in the warmest and most moist types.
