Climatological Characteristics of Daily Precipitation over Japan in the Kakushin Regional Climate Experiments Using a Non-Hydrostatic 5-km-Mesh Model: Comparison with an Outer Global 20-km-Mesh Atmospheric Climate Model
Climatological Characteristics of Daily Precipitation over Japan in the Kakushin Regional Climate Experiments Using a Non-Hydrostatic 5-km-Mesh Model: Comparison with an Outer Global 20-km-Mesh Atmospheric Climate Model
复制标题
使用非静水力 5 公里网格模型的 Kakushin 区域气候实验中日本日降水量的气候特征：与外部全球 20 公里网格大气气候模型的比较
作者：
S. Kanada;M. Nakano;T. Kato
利用水平分辨率为5 km（NHM 5 km）的非静力模式，对1990 ~ 1999年6 ~ 10月日本Kakushin区域气候变化试验中日降水的气候特征进行了研究。与全球20 km网格大气气候模式（AGCM 20 km）的模拟结果比较表明，NHM 5 km模式可以提高AGCM 20 km模式降水特征的重现性，包括强降水频率和湿日数。AGCM 20 km模式对日本31°N ~ 38°N和129.8°E ~ 142.0°E区域6 ~ 10月最大降水量和湿日数的10年平均值的偏差分别为-30%和+33%，NHM 5 km模式的偏差分别为+9%和+12%。AGCM 20 km中最大的偏差，高估了7月和8月的湿日，在NHM 5 km中成功地减少了。日降水量的概率密度分布在NHM 5 km上级AGCM 20 km的所有分析月，是在强一致的雨量计为基础的日降水数据集6月至8月。这些特征表明NHM 5 km还提供了降水特征的改善的季节变化，这对于可靠的气候变化实验至关重要。
The climatological characteristics of daily precipitation over Japan in the Kakushin regional climate change experiments using a non-hydrostatic model with a horizontal resolution of 5 km (NHM5km) are investigated from June to October between 1990 and 1999. Comparisons with the results of a global 20-km-mesh atmospheric climate model (AGCM20km), which provides the boundary conditions for NHM5km, show that NHM5km can improve the reproducibility of precipitation characteristics, including the frequencies of intense precipitation and wet days, from those in AGCM20km. Compared with observations, AGCM20km shows -30% and +33% biases in terms of the 10-year mean values of regional maximum precipitation and wet days, respectively, in the region 31°N-38°N and 129.8°E-142.0°E over Japan from June to October; these biases are reduced to +9% and +12% in the case of NHM5km. The largest biases in AGCM20km, overestimation of wet days in July and August, are successfully reduced in NHM5km. Probability density distributions of daily precipitation amount are superior in NHM5km than in AGCM20km for all analysis months, being in strong agreement with a raingauge-based daily precipitation dataset for June-August. These features indicate that NHM5km also provides improved seasonal variations in precipitation characteristics, which are crucial for reliable climate change experiments.