The WGNE Assessment of Short-term Quantitative Precipitation Forecasts

The WGNE Assessment of Short-term Quantitative Precipitation Forecasts Twenty-four-hour and 48-h quantitative precipitation forecasts (QPFs) from 11 operational numerical weather prediction models have been verified for a 4-yr period against rain gauge observations over the United States, Germany, and Australia to assess their skill in predicting the occurrence and amount of daily precipitation.Model QPFs had greater skill in winter than in summer, and greater skill in midlatitudes than in Tropics, where they performed only marginally better than persistence. The best agreement among models, as well as the best ability to discriminate raining areas, occurred for a low rain threshold of 12 mm d1. In contrast, the skill for forecasts of rain greater than 20 mm d1 was generally quite low, reflecting the difficulty in predicting precisely when and where heavy rain will fall. The location errors for rain systems, determined using pattern matching with the observations, were typically about 100 km for 24-h forecasts, with smaller errors occurring for the heaviest rain systems.It does not appear that model QPFs improved significantly during the four years examined. As new model versions were introduced their performance changed, not always for the better. The process of improving model numerics and physics is a complicated juggling act, and unless the accurate prediction of rainfall is made a top priority then improvements in model QPF will continue to come only slowly. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

The WGNE Assessment of Short-term Quantitative Precipitation Forecasts

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/BAMS-84-4-481
Publisher site
See Article on Publisher Site

Abstract

Twenty-four-hour and 48-h quantitative precipitation forecasts (QPFs) from 11 operational numerical weather prediction models have been verified for a 4-yr period against rain gauge observations over the United States, Germany, and Australia to assess their skill in predicting the occurrence and amount of daily precipitation.Model QPFs had greater skill in winter than in summer, and greater skill in midlatitudes than in Tropics, where they performed only marginally better than persistence. The best agreement among models, as well as the best ability to discriminate raining areas, occurred for a low rain threshold of 12 mm d1. In contrast, the skill for forecasts of rain greater than 20 mm d1 was generally quite low, reflecting the difficulty in predicting precisely when and where heavy rain will fall. The location errors for rain systems, determined using pattern matching with the observations, were typically about 100 km for 24-h forecasts, with smaller errors occurring for the heaviest rain systems.It does not appear that model QPFs improved significantly during the four years examined. As new model versions were introduced their performance changed, not always for the better. The process of improving model numerics and physics is a complicated juggling act, and unless the accurate prediction of rainfall is made a top priority then improvements in model QPF will continue to come only slowly.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Apr 11, 2003

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