Regional climate model simulation of precipitation in central Asia: Mean and interannual variability
Regional climate model simulation of precipitation in central Asia: Mean and interannual variability
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DOI：
10.1029/98jd02501
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发表时间：
1999-03-27
影响因子：
4.4
通讯作者：
Sloan, LC
中科院分区：
文献类型：
--
作者：
Small, EE;Giorgi, F;Sloan, LC
我们研究了美国国家大气研究中心（NCAR）区域气候模式（RegCM2）模拟半干旱地区降水的平均和年际变化的能力，以更充分地建立该模型作为研究区域尺度气候过程的工具的优势和劣势。我们将降水观测结果与RegCM2对中亚气候长达5.5年的模拟结果进行了比较。由欧洲中期天气预报中心分析推动。RegCM2很好地模拟了不同气候分区降水的空间格局和年周期。模拟降水量的大小与观测结果相似，除了中亚最干旱的地区，那里的模拟降水量过高。我们根据观测结果和RegCM2输出结果计算每个月的降水异常，作为该月的月总量和5年平均值之间的差值。模拟的年际变化幅度与观测结果相似，但也存在差异。RegCM2倾向于低估（高估）的变化幅度在同一组合的分区和季节，它低估（高估）平均降水。RegCM2密切再现降水异常观察到的特定月份，除了在夏季和冬季在山区。平均降水量的模式偏差与模式重现一系列降水异常的能力之间没有相关性，这表明控制降水量的平均值和变率的过程是不同的。因此，评估区域气候模式模拟这两个量的能力是对模式性能的一个苛刻的测试。
We examine how well the National Center for Atmospheric Research (NCAR) regional climate model (RegCM2) simulates the mean and interannual variability of precipitation in a semiarid region to more fully establish the strengths and weaknesses of the model as a tool for studying regional scale climate processes, We compare precipitation observations with RegCM2 output from a 5.5 year long simulation of the climate of central Asia, driven by the European Centre for Medium-Range Weather Forecasts analyses. RegCM2 simulates well the spatial patterns and annual cycles of precipitation observed in climatically different subregions. The magnitude of simulated precipitation is similar to observations except over the driest part of Central Asia where the simulated precipitation is too high. We calculate precipitation anomalies for each month as the difference between the monthly total and the 5 year average for that month, from both observations and RegCM2 output. The magnitude of simulated interannual variability is similar to observations, although there are differences. RegCM2 tends to underpredict (overpredict) the magnitude of variability in the same combinations of subregion and season for which it underpredicts (overpredicts) mean precipitation. RegCM2 closely reproduces precipitation anomalies observed in specific months, except during summer and during winter in the mountains. There is no correlation between model biases in mean precipitation and how well the model reproduces a series of precipitation anomalies, This suggests that the processes controlling the mean and the variability of precipitation differ. Therefore evaluating the ability of a regional climate model to simulate both quantities is a demanding test of model performance.