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- Author or Editor: John J. Cahir x
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Abstract
Experiments were made in prediction of the elevation of warm season shower-tops, both prevailing and highest, using a one-dimensional cloud model run on a real-time minicomputer system. A forecaster inter-actively altered the initial temperatures and/or mixing ratios taken from 1200 GMT radiosondes over the eastern two-thirds of the United States. Subjective methods and numerical guidance were used to estimate upper air changes from morning to afternoon, but observed afternoon surface dewpoints were employed in the developmental work. A forecast based on the unaltered initial sounding was run as a control. Observed tops were taken from radar reports within 2° latitude boxes, fine-tuned somewhat by enhanced infrared satellite imagery.
Development results show root-mean-square errors (RMSE) of less than 2.0 km can be achieved for both prevailing and highest tops if the surface dewpoint is specified accurately. Independent tests were consistent only for highest tops, and the RMSE increased to 2.54 km when forecasters had to predict the dewpoint. “Prevailing tops” are apparently difficult to distinguish from “highest tops” reliably in real-time conditions.
Abstract
Experiments were made in prediction of the elevation of warm season shower-tops, both prevailing and highest, using a one-dimensional cloud model run on a real-time minicomputer system. A forecaster inter-actively altered the initial temperatures and/or mixing ratios taken from 1200 GMT radiosondes over the eastern two-thirds of the United States. Subjective methods and numerical guidance were used to estimate upper air changes from morning to afternoon, but observed afternoon surface dewpoints were employed in the developmental work. A forecast based on the unaltered initial sounding was run as a control. Observed tops were taken from radar reports within 2° latitude boxes, fine-tuned somewhat by enhanced infrared satellite imagery.
Development results show root-mean-square errors (RMSE) of less than 2.0 km can be achieved for both prevailing and highest tops if the surface dewpoint is specified accurately. Independent tests were consistent only for highest tops, and the RMSE increased to 2.54 km when forecasters had to predict the dewpoint. “Prevailing tops” are apparently difficult to distinguish from “highest tops” reliably in real-time conditions.
Abstract
Real-time computer graphics systems are being introduced into weather stations throughout the United States. A sample of student forecasters used such a system to solve specific specialized forecasting problems. Results suggest that for some types of problems, involving timing, their forecasts were better than those made by forecasters who did not have access to the system.
Examples are given of the diagnostic use of some of the available analyses.
Abstract
Real-time computer graphics systems are being introduced into weather stations throughout the United States. A sample of student forecasters used such a system to solve specific specialized forecasting problems. Results suggest that for some types of problems, involving timing, their forecasts were better than those made by forecasters who did not have access to the system.
Examples are given of the diagnostic use of some of the available analyses.
Abstract
A method of introducing subsynoptic-scale initial data into a six-level primitive equation model is presented. Vorticity perturbations on the scale of subsynoptic disturbances are added to the initial winds; the amplitudes and slopes of the perturbations are subjectively determined from physical, climatological and observational considerations. Balanced winds, heights and temperatures are then derived from the enhanced vorticity fields.
Two 12 h forecasts are made from two different initial analyses. The first
Abstract
A method of introducing subsynoptic-scale initial data into a six-level primitive equation model is presented. Vorticity perturbations on the scale of subsynoptic disturbances are added to the initial winds; the amplitudes and slopes of the perturbations are subjectively determined from physical, climatological and observational considerations. Balanced winds, heights and temperatures are then derived from the enhanced vorticity fields.
Two 12 h forecasts are made from two different initial analyses. The first
Objective analyses on vertical cross sections are presented as examples of the type of real-time product available on the Penn State, Department of Meteorology, on-line minicomputer. The analyses are not new, but their real-time availability is. Our experience has been that such products improve forecaster diagnosis and understanding and suggest that the “man-machine mix” concept, extended to other types of analyses and diagnoses, may be as appropriate to small machines as to large ones.
Objective analyses on vertical cross sections are presented as examples of the type of real-time product available on the Penn State, Department of Meteorology, on-line minicomputer. The analyses are not new, but their real-time availability is. Our experience has been that such products improve forecaster diagnosis and understanding and suggest that the “man-machine mix” concept, extended to other types of analyses and diagnoses, may be as appropriate to small machines as to large ones.
Abstract
Multiple linear regression is used to relate monthly means and year-to-year changes of the monthly mean planetary albedo and infrared flux leaving the atmosphere, as measured by NOAA satellites, to certain meteorological quantities. Physical predictors are selected which are likely to influence cloudiness, such as temperature, relative humidity and wind. Such predictors can be readily obtained from numerical models.
Forty-two months of polar orbiter measurements of radiation fluxes and objective analyses from NMC's operational model were related. Continental and oceanic samples were evaluated separately. Checks on the model consisted of independent tests and comparison with estimation of radiation fluxes in which predictors were functions of latitude, longitude and time of year only. Physical predictors are consistently superior, with the single exception of oceanic albedo, where there was little difference.
In the case of the infrared flux, 93 and 84% of the variance in the monthly means is explained over land and ocean, respectively. The Planck function computed from a humidity (cloud) sensitive radiating temperature is the dominant predictor, with other humidity predictors also useful. Between 60 and 72% of the variance of the albedo is explained; results over land again are superior. Relative humidity and midtropospheric wind speed variables dominate in this case. Greater success with infrared is probably attributable to a failure to adequately estimate the effect of low-topped clouds, which impact the albedo differentially. Over land, patterns of year-to-year changes of visible and infrared fluxes (surrogates for anomalies) are predicted well and are consistent with observed changes in rainfall and cloudiness. Over the means the skill for year-to-year changes is low, possibly because low-topped clouds are more common, but also because analyses are poorer there.
Abstract
Multiple linear regression is used to relate monthly means and year-to-year changes of the monthly mean planetary albedo and infrared flux leaving the atmosphere, as measured by NOAA satellites, to certain meteorological quantities. Physical predictors are selected which are likely to influence cloudiness, such as temperature, relative humidity and wind. Such predictors can be readily obtained from numerical models.
Forty-two months of polar orbiter measurements of radiation fluxes and objective analyses from NMC's operational model were related. Continental and oceanic samples were evaluated separately. Checks on the model consisted of independent tests and comparison with estimation of radiation fluxes in which predictors were functions of latitude, longitude and time of year only. Physical predictors are consistently superior, with the single exception of oceanic albedo, where there was little difference.
In the case of the infrared flux, 93 and 84% of the variance in the monthly means is explained over land and ocean, respectively. The Planck function computed from a humidity (cloud) sensitive radiating temperature is the dominant predictor, with other humidity predictors also useful. Between 60 and 72% of the variance of the albedo is explained; results over land again are superior. Relative humidity and midtropospheric wind speed variables dominate in this case. Greater success with infrared is probably attributable to a failure to adequately estimate the effect of low-topped clouds, which impact the albedo differentially. Over land, patterns of year-to-year changes of visible and infrared fluxes (surrogates for anomalies) are predicted well and are consistent with observed changes in rainfall and cloudiness. Over the means the skill for year-to-year changes is low, possibly because low-topped clouds are more common, but also because analyses are poorer there.
