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Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts.

Authors :
Gallus, Jr., William A.
Baldwin, Michael E.
Elmore, Kimberly L.
Source :
Weather & Forecasting; Feb2007, Vol. 22 Issue 1, p207-215, 9p, 7 Charts, 2 Graphs
Publication Year :
2007

Abstract

This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-yr period on a contiguous U.S. domain. Specifically, the quantitative precipitation forecast (QPF)–probability relationship found recently by Gallus and Segal in 10-km grid spacing model runs for 20 warm season mesoscale convective systems is tested over this much larger temporal and spatial dataset. A 1-yr period was used to investigate the QPF–probability relationship, and the predictive capability of this relationship was then tested on an independent 1-yr sample of data. The same relationship of a substantial increase in the likelihood of observed rainfall exceeding a specified threshold in areas where model runs forecasted higher rainfall amounts is found to hold over all seasons. Rainfall is less likely to occur in those areas where the models indicate none than it is elsewhere in the domain; it is more likely to occur in those regions where rainfall is predicted, especially where the predicted rainfall amounts are largest. The probability of rainfall forecasts based on this relationship are found to possess skill as measured by relative operating characteristic curves, reliability diagrams, and Brier skill scores. Skillful forecasts from the technique exist throughout the 48-h periods for which Eta and AVN output were available. The results suggest that this forecasting tool might assist forecasters throughout the year in a wide variety of weather events and not only in areas of difficult-to-forecast convective systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08828156
Volume :
22
Issue :
1
Database :
Complementary Index
Journal :
Weather & Forecasting
Publication Type :
Academic Journal
Accession number :
24111169
Full Text :
https://doi.org/10.1175/WAF976.1