Reduction of systematic biases in regional climate downscaling through ensemble forcing
Reduction of systematic biases in regional climate downscaling through ensemble forcing
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DOI：
10.1007/s00382-011-1006-4
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发表时间：
2012-02
期刊：
影响因子：
4.6
通讯作者：
Hongwei Yang;Bin Wang
中科院分区：
文献类型：
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作者：
Hongwei Yang;Bin Wang
利用3个再分析资料集(NCEP-R2、ERA-40和JRA-25)强迫的天气研究和预报(WRF)模式，对1979-2001年东亚夏季风进行了模拟。由不同的再分析资料强迫的实验显示出显著的差异，主要是由于孟加拉湾和菲律宾海的侧边界水汽通量的不确定性造成的。由ERA-40计算的进入模式区域的气候学平均水汽辐合比NCEP-R2再分析高出约24%。我们证明，使用NCEP-R2、ERA-40和JRA-25的集合平均作为LB强迫显著地减少了模式模拟中的偏差。集合强迫的使用改善了模拟的平均环流和降水、季节降水的年际变化和日降水量的表现。模式模拟的降水在气候学和年际变化上均优于再分析模式，说明了动态降尺度的附加值。结果表明，当使用另一组再分析数据作为LB强迫时，在一组LB强迫下具有较好性能的模型可能会恶化。建议使用集合平均LB强迫来评估区域气候模式的性能。
Simulations of the East Asian summer monsoon for the period of 1979–2001 were carried out using the Weather Research and Forecast (WRF) model forced by three reanalysis datasets (NCEP-R2, ERA-40, and JRA-25). The experiments forced by different reanalysis data exhibited remarkable differences, primarily caused by uncertainties in the lateral boundary (LB) moisture fluxes over the Bay of Bengal and the Philippine Sea. The climatological mean water vapor convergence into the model domain computed from ERA-40 was about 24% higher than that from the NCEP-R2 reanalysis. We demonstrate that using the ensemble mean of NCEP-R2, ERA-40, and JRA-25 as LB forcing considerably reduced the biases in the model simulation. The use of ensemble forcing improved the performance in simulated mean circulation and precipitation, inter-annual variation in seasonal precipitation, and daily precipitation. The model simulated precipitation was superior to that in the reanalysis in both climatology and year-to-year variations, indicating the added value of dynamic downscaling. The results suggest that models having better performance under one set of LB forcing might worsen when another set of reanalysis data is used as LB forcing. Use of ensemble mean LB forcing for assessing regional climate model performance is recommended.