4.6 Article

Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins

Journal

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Volume 140, Issue 682, Pages 1615-1628

Publisher

WILEY
DOI: 10.1002/qj.2243

Keywords

ECMWF EPS; Huai; skill score; diurnal cycle

Funding

  1. UK ESRC research project 'Improving the communication and use of ensemble flood predictions' [RES-189-25-0286]
  2. National Natural Science Foundation of China [41130639, 51179045]
  3. China Meteorological Administration Special Public Welfare Research Fund [GYHY201006037]
  4. ESRC [ES/I03031X/1] Funding Source: UKRI
  5. NERC [NE/I005358/1, NE/I005358/2] Funding Source: UKRI
  6. Economic and Social Research Council [ES/I03031X/1] Funding Source: researchfish
  7. Natural Environment Research Council [NE/I005358/2, NE/I005358/1] Funding Source: researchfish

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Providing probabilistic forecasts using Ensemble Prediction Systems has become increasingly popular in both the meteorological and hydrological communities. Compared to conventional deterministic forecasts, probabilistic forecasts may provide more reliable forecasts of a few hours to a number of days ahead, and hence are regarded as better tools for taking uncertainties into consideration and hedging against weather risks. It is essential to evaluate performance of raw ensemble forecasts and their potential values in forecasting extreme hydro-meteorological events. This study evaluates ECMWF's medium-range ensemble forecasts of precipitation over the period 1 January 2008 to 30 September 2012 on a selected midlatitude large-scale river basin, the Huai river basin (ca. 270 000 km(2)) in central-east China. The evaluation unit is sub-basin in order to consider forecast performance in a hydrologically relevant way. The study finds that forecast performance varies with sub-basin properties, between flooding and non-flooding seasons, and with the forecast properties of aggregated time steps and lead times. Although the study does not evaluate any hydrological applications of the ensemble precipitation forecasts, its results have direct implications in hydrological forecasts should these ensemble precipitation forecasts be employed in hydrology.

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