Probabilistic Quantitative Precipitation Forecasts for River Basins

Roman Krzysztofowicz Department of Systems Engineering, University of Virginia, Charlottesville, Virginia

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William J. Drzal National Weather Service, Forecast Office, Pittsburgh, Pennsylvania

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Theresa Rossi Drake National Weather Service, Forecast Office, Pittsburgh, Pennsylvania

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James C. Weyman National Weather Service, Forecast Office, Pittsburgh, Pennsylvania

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Louis A. Giordano National Weather Service, Forecast Office, Pittsburgh, Pennsylvania

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Abstract

A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with the forecaster's judgmental process, which involves meteorologic inference and probabilistic reasoning; (ii) it can be input directly into a hydrologic model that produces river stage forecasts (at present); and (iii) it provides information sufficient for producing probabilistic river stage forecasts (in the future).

The methodology, implemented as a human–computer system, has been tested operationally on two river basins by the Weather Service Forecast Office in Pittsburgh, Pennsylvania, since August 1990. The article elaborates on the rationale behind methods being proposed, details system components, recommends an information processing scheme for judgmental probabilistic forecasting, and outlines training, testing, and verification programs.

Abstract

A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with the forecaster's judgmental process, which involves meteorologic inference and probabilistic reasoning; (ii) it can be input directly into a hydrologic model that produces river stage forecasts (at present); and (iii) it provides information sufficient for producing probabilistic river stage forecasts (in the future).

The methodology, implemented as a human–computer system, has been tested operationally on two river basins by the Weather Service Forecast Office in Pittsburgh, Pennsylvania, since August 1990. The article elaborates on the rationale behind methods being proposed, details system components, recommends an information processing scheme for judgmental probabilistic forecasting, and outlines training, testing, and verification programs.

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