CMIP6全球气候模式对中亚极端降水模拟能力的评估

本文基于NOAA再分析逐日降水数据和22个CMIP6模式的降水模拟数据,选取了6个极端降水指数,从气候态和相对变率两个角度对CMIP6模式在中亚地区极端降水方面的模拟能力开展了评估。结果表明,在气候态方面,中亚地区降水的空间分布表现为由西南向东北递增,其东南部山地迎风侧降水偏多；多模式集合对SDII(简单降水强度)和CDD(最大无雨期)模拟的平均误差分别为-5.43%和0.45%,对PRCPTOT(年总降水量)、R1mm(有雨日数)、Rx5day(最大连续五日降水)和CWD(最大雨期)的模拟结果存在明显高估,且在中亚东南部高海拔地区误差偏高。在相对变率方面,多模式集合模拟的中亚极端降水的相对变率偏小,其中对CWD的模拟效果相对较好,平均误差为-4.78%；对R1mm的模拟效果最差,平均误差为-36.16%。模式间进行比较,TaiESM1、EC-Earth3-Veg-LR和GFDL-ESM为22个CMIP6模式中模拟能力最好的前3个模式。

Assessment of CMIP6 in simulating extreme precipitation over Central Asia

Based on NOAA reanalysis of daily precipitation data and precipitation simulation data from 22 CMIP6 (Coupled Model Intercomparison Project Phase 6) models, 6 extreme precipitation indices were selected to evaluate the simulation capability of the CMIP6 models in extreme precipitation over Central Asia from the perspectives of climatological mean and relative variability. The results indicate that in terms of climatological mean, the spatial distribution shows an increasing trend from southwest to northeast, with high values on the windward side of the southeast mountainous areas. The average errors of the CMIP6-MME (Multi-model ensemble) for SDII (Simple precipitation intensity index) and CDD (Consecutive dry days) simulations are -5.43% and 0.45%, while there is a significant overestimation of the simulation results for PRCPTOT (Annual total precipitation), R1mm (Annual count of days when precipitation1mm), Rx5day (Maximum consecutive 5-day precipitation) and CWD (Consecutive wet days) , and the error is large in high altitude areas in the southeast. In terms of relative variability, the relative variability of the CMIP6-MME is relatively low, while the simulation of CWD having a relatively good performance, with an average error of -4.78%; the simulation of R1mm is the worst, with an average error of -36.16%. Compared among 22 CMIP6 modes, TaiESM1, EC-Earth3-Veg-LR, and GFDL-ESM are the top three modes with the best simulation capability.