Probabilistic flood forecasting with a limited-area ensemble prediction system:: Selected case studies

被引:71
作者
Verbunt, M.
Walser, A.
Gurtz, J.
Montani, A.
Schaer, C.
机构
[1] Swiss Fed Off Meteorol & Climatol, Zurich, Switzerland
[2] Serv IdroMeterol, Agenzia Reg Prevenz & Ambiente Emilia Romagna, Bologna, Italy
关键词
D O I
10.1175/JHM594.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A high-resolution atmospheric ensemble forecasting system is coupled to a hydrologic model to investigate probabilistic runoff forecasts for the alpine tributaries of the Rhine River basin (34 550 km(2)). Five-day ensemble forecasts consisting of 51 members, generated with the global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), are downscaled with the limited-area model Lokal Modell (LM). The resulting limited-area ensemble prediction system (LEPS) uses a horizontal grid spacing of 10 km and provides one-hourly output for driving the distributed hydrologic model Precipitation-Runoff-Evapotranspiration-Hydrotope (PREVAH) hydrologic response unit (HRU) with a resolution of 500 x 500 m(2) and a time step of 1 h. The hydrologic model component is calibrated for the river catchments considered, which are characterized by highly complex topography, for the period 1997-98 using surface observations, and validated for 1999-2002. This study explores the feasibility of atmospheric ensemble predictions for runoff forecasting, in comparison with deterministic atmospheric forcing. Detailed analysis is presented for two case studies: the spring 1999 flood event affecting central Europe due to a combination of snowmelt and heavy precipitation, and the November 2002 flood in the Alpine Rhine catchment. For both cases, the deterministic simulations yield forecast failures, while the coupled atmospheric-hydrologic EPS provides appropriate probabilistic forecast guidance with early indications for extreme floods. It is further shown that probabilistic runoff forecasts using a subsample of EPS members, selected by a cluster analysis, properly represent the forecasts using all 51 EPS members, while forecasts from randomly chosen subsamples reveal a reduced spread compared to the representative members. Additional analyses show that the representation of horizontal advection of precipitation in the atmospheric model may be crucial for flood forecasts in alpine catchments.
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收藏
页码:897 / 909
页数:13
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