Sensitivity of the simulation of extreme precipitation events in China to different cumulus parameterization schemes and the underlying mechanisms
Sensitivity of the simulation of extreme precipitation events in China to different cumulus parameterization schemes and the underlying mechanisms
复制标题
中国极端降水事件模拟对不同积云参数化方案的敏感性及其机制
DOI：
10.1016/j.atmosres.2023.106636
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发表时间：
2023
影响因子：
5.5
通讯作者：
Li, Qingquan
中科院分区：
文献类型：
--
作者：
Zhang, Shiyu;Wang, Minghao;Wang, Lanning;Liang, Xin-Zhong;Sun, Chao;Li, Qingquan
气候模式捕捉极端降水事件的能力至关重要，但大多数现有模式对极端降水的模拟存在明显偏差。为了了解这些偏差的原因，我们在区域气候-天气研究与预报（CWRF）模式中使用了5种不同的积云参数化方案，以研究其在中国极端降水事件模拟中的性能和偏差。总体而言，集合积云参数化（ECP）方案在再现第95百分位日降水量的空间分布（P95）方面是最熟练的，其他四个方案要么高估（Kain-Fritsch Eta和Tiedtke方案）要么低估（Betts-Miller-Janjic和新简化Arakawa-Schubert方案）P95。与实测资料相比，ECP方案对中国极端降水的模拟效果显著提高，在大部分地区和季节具有最高的相关性和最小的均方根误差。为了阐明P95模拟偏差的物理过程，建立了基于ECP方案的极端降水回归模型。结果表明，华北地区P95主要受水汽辐合、边界层高度和抬升凝结水平的影响（相对重要性18-32%）。在华中地区，水汽垂直上升运动、感热通量和边界层高度（相对重要性18-30%）是影响P95的主要因子。在华南地区，水汽垂直上升和水平输送占主导地位（相对重要性26-37%）。此外，地面净能量、地面和大气辐射通量、总可降水量、对流有效位能和云水路径等与P95也有很高的相关性（第二重要因子，相对重要性14-31%）。不同积云参数化方案下各因子对P95的模拟影响不同，各因子间的相互作用决定了CWRF模式对极端降水的模拟能力。这些结果为今后的模型评估和改进提供了重要参考。
The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant biases for the simulation of extreme precipitation. To understand the causes of these biases, we used five different cumulus parameterization schemes in the regional Climate–Weather Research and Forecasting (CWRF) model to investigate its performance and biases in the simulation of extreme precipitation events in China. In general, the ensemble cumulus parameterization (ECP) scheme was the most skillful in reproducing the spatial distribution of the 95th percentile daily precipitation (P95) and the other four schemes either overestimated (the Kain-Fritsch Eta and Tiedtke schemes) or underestimated (the Betts-Miller-Janjic and New Simplified Arakawa-Schubert schemes) P95. Compared with the observational data, ECP scheme significantly improved the simulation of extreme precipitation in China and had the highest correlation and the smallest root-mean-square error in most areas and seasons. To clarify the underlying physical processes of P95 simulation biases, we established a regression model of extreme precipitation based on ECP scheme. This showed that P95 in North China is mainly affected by moisture convergence, planetary boundary layer height and lifting condensation level (relative importance 18–32%). In Central China, the vertical upward motion of water vapor, sensible heat flux and planetary boundary layer height (relative importance 18–30%) are main factors associated with P95. In South China, the vertical upward motion and horizontal transport of water vapor are predominant (relative importance 26–37%). In addition, the net surface energy, surface and atmospheric radiation flux, total precipitable water, convective available potential energy and cloud water path also have a high correlation with P95 (the second most important factor; relative importance 14–31%). The influence of each factor on the simulation of P95 is different when using different cumulus parameterization schemes and the interaction among the different factors determines the ability of CWRF model to simulate extreme precipitation. These results provide important references for future model evaluations and improvements.