Title: Evaluation of a New Precipitation-Based Index for Global Seasonal Forecasting of Unusually Wet and Dry Periods
Citation: WEATHER AND FORECASTING vol. 35 no. 4 p. 1189-1202
Publication Year: 2020
JRC N°: JRC117954
ISSN: 0882-8156 (online)
URI: https://journals.ametsoc.org/waf/article/35/4/1189/346029/Evaluation-of-a-New-Precipitation-Based-Index-for
DOI: 10.1175/WAF-D-19-0196.1
Type: Articles in periodicals and books
Abstract: This paper describes the assessment of the performance of a method for providing early warnings of unusually wet and dry precipitation conditions globally. The indicator that is used for forecasting these conditions is computed from forecasted standardized precipitation index (SPI) values for accumulation periods of 1, 3, and 6 months. The SPI forecasts are derived from forecasted precipitation produced by the latest probabilistic seasonal forecast of ECMWF. Early warnings of unusual precipitation periods are shown only when and where the forecast is considered robust (i.e., with at least 40% of ensemble members associated with intense forecasts), and corresponding with significant SPI values (i.e., below 21 for dry, or above 11 for wet conditions). The intensity of the forecasted events is derived based on the extreme forecast index and associated shift of tails products developed by ECMWF. Different warning levels are then assessed, depending on the return period of the forecast intensity, and the coherence of the ensemble forecast members. The assessment of the indicator's performance is based on the 25-member ensemble forecast system that is carried out every month during the 36 years of the hindcast period (1981–2016). The results show that significant information is provided even for the longest lead time, albeit with a large variability across the globe with the highest scores over central Russia, Southeast Asia, and the northern part of South America or Australia. Because of the loss of predictability, each SPI is based on the first lead time. A sensitivity test highlights the influence on the robustness of the forecasts of the warning levels used, as well as the effects of prior conditions and of seasonality.
JRC Directorate:Space, Security and Migration

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