کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4451055 1311729 2009 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Operational 0–3 h probabilistic quantitative precipitation forecasts: Recent performance and potential enhancements
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
Operational 0–3 h probabilistic quantitative precipitation forecasts: Recent performance and potential enhancements
چکیده انگلیسی

The NOAA National Weather Service has maintained an automated, centralized 0–3 h prediction system for probabilistic quantitative precipitation forecasts since 2001. This advective-statistical system (ADSTAT) produces probabilities that rainfall will exceed multiple threshold values up to 50 mm at some location within a 40-km grid box. Operational characteristics and development methods for the system are described. Although development data were stratified by season and time of day, ADSTAT utilizes only a single set of nation-wide equations that relate predictor variables derived from radar reflectivity, lightning, satellite infrared temperatures, and numerical prediction model output to rainfall occurrence. A verification study documented herein showed that the operational ADSTAT reliably models regional variations in the relative frequency of heavy rain events. This was true even in the western United States, where no regional-scale, gridded hourly precipitation data were available during the development period in the 1990s. An effort was recently launched to improve the quality of ADSTAT forecasts by regionalizing the prediction equations and to adapt the model for application in the Czech Republic. We have experimented with incorporating various levels of regional specificity in the probability equations. The geographic localization study showed that in the warm season, regional climate differences and variations in the diurnal temperature cycle have a marked effect on the predictor–predictand relationships, and thus regionalization would lead to better statistical reliability in the forecasts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Research - Volume 92, Issue 3, May 2009, Pages 318–330
نویسندگان
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