Eastern U.S. verification of ensemble precipitation forecasts

Sanjib Sharma, Ridwan Siddique, Nicholas Balderas, Jose D. Fuentes, Seann Reed, Peter Ahnert, Robert Shedd, Brian Astifan, Reggina Cabrera, Arlene Laing, Mark Klein, Alfonso Mejia

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


The quality of ensemble precipitation forecasts across the eastern United States is investigated, specifically, version 2 of the National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System Reforecast (GEFSRv2) and Short Range Ensemble Forecast (SREF) system, as well as NCEP's Weather Prediction Center probabilistic quantitative precipitation forecast (WPC-PQPF) guidance. The forecasts are verified using multisensor precipitation estimates and various metrics conditioned upon seasonality, precipitation threshold, lead time, and spatial aggregation scale. The forecasts are verified, over the geographic domain of each of the four eastern River Forecasts Centers (RFCs) in the United States, by considering first 1) the three systems or guidance, using a common period of analysis (2012-13) for lead times from 1 to 3 days, and then 2) GEFSRv2 alone, using a longer period (2004-13) and lead times from 1 to 16 days. The verification results indicate that, across the eastern United States, precipitation forecast bias decreases and the skill and reliability improve as the spatial aggregation scale increases; however, all the forecasts exhibit some underforecasting bias. The skill of the forecasts is appreciably better in the cool season than in the warm one. The WPC-PQPFs tend to be superior, in terms of the correlation coefficient, relative mean error, reliability, and forecast skill scores, than both GEFSRv2 and SREF, but the performance varies with the RFC and lead time. Based on GEFSRv2, medium-range precipitation forecasts tend to have skill up to approximately day 7 relative to sampled climatology.

Original languageEnglish (US)
Pages (from-to)117-139
Number of pages23
JournalWeather and Forecasting
Issue number1
StatePublished - 2017

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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