Implementation and performance analysis of a high resolution coupled numerical weather and river runoff prediction model system for an Alpine catchment
Implementation and performance analysis of a high resolution coupled numerical weather and river runoff prediction model system for an Alpine catchment
复制标题
高山流域高分辨率数值天气与河流径流耦合预测模型系统的实现和性能分析
DOI:
10.1016/j.envsoft.2012.06.001
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发表时间:
2012
期刊:
影响因子:
--
通讯作者:
J. Werhahn
中科院分区:
文献类型:
--
作者:
G. Smiatek;H. Kunstmann;J. Werhahn
This study describes the implementation of a one way coupled high resolution numerical weather and river runoff forecasting system within the Perl Object Environment (POE) framework and presents its application and performance analysis for the Alpine catchment of the Ammer River located in southern Germany. The simulation system employs the hydrological water balance model WaSiM-ETH run at 100 m × 100 m grid resolution one way coupled with the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution. The state and event driven forecasting system implements the input data download, input data provision via SOAP based WEB service and the run of the hydrology model with observed and with predicted NWP meteorology fields. It applies a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. The simulation system has been setup and designed for flood forecasting in the alpine environment. It is run operationally as well as in extended time slice experiments for all episodes with highest observed runoff in the period 01.10.2005–30.09.2010. The system application demonstrates the great potential of the POE based system in networking, distributed computing as well in the setup of various experiments. The river runoff simulation results show high correlation with observed runoff when driven with precipitation interpolated from station observations. The performance of the forecast shows limitations resulting from deficient timing and amount of the predicted rainfall in the complex mountainous area. Forecast skills were improved after application of a lagged ensemble prediction system.
影响因子:
2.7
作者:
Cloke, Hannah L.;Pappenberger, Florian
通讯作者:
Pappenberger, Florian