RegCM4.6两种积云参数化方案在东亚模拟结果的评估
收稿日期: 2022-05-10
修回日期: 2022-06-28
网络出版日期: 2023-02-21
基金资助
国家自然科学基金项目(42030612);国家自然科学基金项目(41675026);国家自然科学基金项目(41375021)
Evaluation of simulation results from two cumulus parameterization schemes in RegCM4.6 in East Asia
Received date: 2022-05-10
Revised date: 2022-06-28
Online published: 2023-02-21
新一代区域气候模式RegCM4.6引进了Mix积云参数化方案,可以将之前版本中的Emanuel和Grell方案结合在一起,以弥补单个参数化方案的不足。利用2016年MODIS(Moderate-resolution imaging spectroradiometer)数据对RegCM4.6中Mix和Emanuel积云参数化方案模拟的东亚云量(Cloud fraction,CF)、冰水柱含量(Ice water path,IWP)和液水柱含量(Liquid water path,LWP)进行初步评估,计算了相关系数(r)、平均绝对误差(Mean absolute error,MAE)、平均偏差(Mean bias error,MBE)和均方根误差(Root mean square error,RMSE),以便为相关研究选取积云参数化方案提供参考依据。结果表明:(1) 模拟的CF的MBE大致以胡焕庸线为界,西北部为轻微高估,东南部通常为低估。2种方案在夏季的模拟效果最好,冬季最差。Mix方案的MAE、MBE和RMSE的绝对值在四季普遍小于Emanuel方案。(2) 模式明显低估了东亚的IWP,除夏季外,2种方案模拟的IWP与MODIS的都呈显著负相关,表明模式难以准确模拟出云中冰晶相关的物理过程。(3) 2种方案模拟的LWP在青藏高原和东部海域均为低估,在中国南部、中部和北部为高估,但Mix方案的偏差更接近于0。冬季,2种方案的评估参数相近,其他季节Mix方案的MAE、MBE和RMSE的绝对值均小于Emanuel方案,其中MAE相差21~39 g·m-2。因此,Mix方案更适用于在东亚进行云水资源方面的模拟研究。
刘鑫 , 亢燕铭 , 辛渝 , 陈勇航 , 周海江 , 秦汉 , 何清 , 王智敏 . RegCM4.6两种积云参数化方案在东亚模拟结果的评估[J]. 干旱区地理, 2023 , 46(1) : 23 -35 . DOI: 10.12118/j.issn.1000-6060.2022.209
Previous studies have shown that the Emanuel scheme performs relatively well in simulating temperature and precipitation in East Asia. However, the user’s guide of RegCM4.6 points out that the Emanuel scheme tends to produce excessive precipitation over lands, especially in some intense individual precipitation events. In contrast, the Grell scheme tends to produce weak precipitation over tropical oceans. Therefore, the new version of the regional climate model RegCM4.6 has incorporated the Mix cumulus convective parameterization scheme, which means that the Emanuel scheme can be used over oceans and the Grell scheme over land, to compensate for the deficiencies of a single scheme. Previous validation studies have mainly focused on temperature and precipitation, and few studies have been conducted on the Mix scheme. The MODIS product from January 1st, 2016, to December 31st, 2016, was used as a reference to evaluate the simulation results of cloud fraction (CF), ice water path (IWP), and liquid water path (LWP) in East Asia from the Emanuel and Mix schemes in RegCM4.6 at various time scales. Some statistical parameters were calculated, such as the correlation coefficient (r), mean absolute error (MAE), mean bias error (MBE), and root mean square error (RMSE). The results were as follows. (1) The simulated CF were slightly overestimated in the northwest and mainly underestimated in the southeast roughly bounded by the Hu Huanyong line. The performance of the two schemes in simulating CF was the best in summer and the worst in winter. In the four seasons, the absolute values of MAE, MBE, and RMSE of the Mix scheme were generally lower than those of the Emanuel scheme. (2) The systematic deviations of IWP were negative in the whole of East Asia. Except in summer, the IWP from the two simulations and MODIS was significantly negatively correlated in the other three seasons, indicating that it was a challenge to accurately simulate physical processes related to ice particles in the cloud. (3) The LWP was underestimated by the two schemes in the Qinghai Tibet Plateau and Eastern Ocean and was overestimated in southern, central, and northern China, but the annual MBE of the Mix scheme were closer to 0. The performances of the two schemes were similar in winter. In the other three seasons, the absolute values of MAE, MBE, and RMSE of the Mix scheme were less than those of the Emanuel scheme, and the differences in MAE for the two schemes were 21-39 g·m-2. In conclusion, the Mix scheme is more suitable to simulate cloud water resources in East Asia. This study will contribute to the exploitation of cloud water resources in East Asia and provide a reference for the selection and improvement of the cumulus convection parameterization scheme in a regional climate model.
Key words: regional climate model; East Asia; cloud fraction; ice water path; liquid water path
[1] | 陈勇航, 邓军英, 张萍, 等. 中天山附近强降雨过程中云冰水含量随高度变化特征[J]. 资源科学, 2013, 35(3): 655-664. |
[1] | [Chen Yonghang, Deng Junying, Zhang Ping, et al. Vertical distribution of ice water content in clouds during heavy rains around Tianshan Mountain[J]. Resources Science, 2013, 35(3): 655-664.] |
[2] | 张萍, 彭宽军, 陈勇航, 等. 新疆三大山区云的垂直分布特征初探[J]. 资源科学, 2011, 33(11): 2090-2098. |
[2] | [Zhang Ping, Peng Kuanjun, Chen Yonghang, et al. A preliminary study of vertical distribution of clouds over three major mountains in Xinjiang[J]. Resources Science, 2011, 33(11): 2090-2098.] |
[3] | 张华, 彭杰, 荆现文, 等. 东亚地区云的垂直重叠特性及其对云辐射强迫的影响[J]. 中国科学: 地球科学, 2013, 43(4): 523-535. |
[3] | [Zhang Hua, Peng Jie, Jing Xianwen, et al. The features of cloud overlapping in Eastern Asia and their effect on cloud radiative forcing[J]. Science China: Earth Sciences, 2013, 43(4): 523-535.] |
[4] | 王清平, 秦贺, 程海艳, 等. 天山北坡中部一次短时暴雨的卫星反演云参数特征及成因分析[J]. 干旱区地理, 2021, 44(6): 1580-1589. |
[4] | [Wang Qingping, Qin He, Cheng Haiyan, et al. Cloud parameter characteristics of a β-mesoscale short-term rainstorm in the center of the northern slope of Tianshan Mountains[J]. Arid Land Geography, 2021, 44(6): 1580-1589.] |
[5] | 张小娟, 王军, 黄观, 等. 新疆3大山区云中液态水时空分布特征[J]. 干旱区研究, 2018, 35(4): 846-854. |
[5] | [Zhang Xiaojuan, Wang Jun, Huang Guan, et al. Spatiotemporal distribution of cloud liquid water volume over three main mountains in Xinjiang[J]. Arid Zone Research, 2018, 35(4): 846-854.] |
[6] | 王昀, 王旭, 赵笑颜, 等. 新疆层云和层积云冰粒子属性的季节变化[J]. 干旱区地理, 2017, 40(3): 589-597. |
[6] | [Wang Jun, Wang Xu, Zhao Xiaoyan, et al. Seasonal variations of microphysical properties of ice particles for stratus and stratocumulus in Xinjiang[J]. Arid Land Geography, 2017, 40(3): 589-597.] |
[7] | 孙美平, 史继花, 姚晓军, 等. 冰川下垫面对夏季云结构和云水含量的影响——以祁连山区疏勒南山为例[J]. 干旱区地理, 2021, 44(1): 141-148. |
[7] | [Sun Meiping, Shi Jihua, Yao Xiaojun, et al. Effects of glacial surface on cloud structure and cloud water content in summer: A case study of the Shulenan Mountain of Qilian Mountains[J]. Arid Land Geography, 2021, 44(1): 141-148.] |
[8] | 郑倩, 郑有飞, 王立稳, 等. 基于MODIS和CloudSat的京津冀降水冰云季节分布特征[J]. 干旱区地理, 2020, 43(6): 1446-1455. |
[8] | [Zheng Qian, Zheng Youfei, Wang Liwen, et al. Seasonal distribution characteristics of precipitating ice clouds in Beijing-Tianjin-Hebei region based on MODIS and Cloudsat[J]. Arid Land Geography, 2020, 43(6): 1446-1455.] |
[9] | Liu X, Kang Y M, Liu Q, et al. Evaluation of net shortwave radiation over China with a regional climate model[J]. Climate Research, 2020, 80(2): 147-163. |
[10] | 刘鸿波, 张大林, 王斌. 区域气候模拟研究及其应用进展[J]. 气候与环境研究, 2006, 11(5): 649-668. |
[10] | [Liu Hongbo, Zhang Dalin, Wang Bin. Recent advances in regional climate modeling and applications[J]. Climatic and Environmental Research, 2006, 11(5): 649-668.] |
[11] | 吴婕, 高学杰, 徐影. RegCM4模式对雄安及周边区域气候变化的集合预估[J]. 大气科学, 2018, 42(3): 696-705. |
[11] | [Wu Jie, Gao Xuejie, Xu Ying. Climate change projection over Xiong’an District and its adjacent areas: An ensemble of RegCM4 simulations[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(3): 696-705.] |
[12] | 王政琪, 高学杰, 童尧, 等. 新疆地区未来气候变化的区域气候模式集合预估[J]. 大气科学, 2021, 45(2): 407-423. |
[12] | [Wang Zhengqi, Gao Xuejie, Tong Yao, et al. Future climate change projection over Xinjiang based on an ensemble of regional climate model simulations[J]. Chinese Journal of Atmospheric Sciences, 2021, 45(2): 407-423.] |
[13] | 张冬峰, 高学杰. 中国21世纪气候变化的RegCM4多模拟集合预估[J]. 科学通报, 2020, 65(23): 2516-2526. |
[13] | [Zhang Dongfeng, Gao Xuejie. Climate change of the 21st century over China from the ensemble of RegCM4 simulations[J]. Chinese Science Bulletin, 2020, 65(23): 2516-2526.] |
[14] | 高学杰, 石英, 张冬峰, 等. RegCM3对21世纪中国区域气候变化的高分辨率模拟[J]. 科学通报, 2012, 57(5): 374-381. |
[14] | [Gao Xuejie, Shi Ying, Zhang Dongfeng, et al. Climate change in China in the 21st century as simulated by a high resolution regional climate model[J]. Chinese Science Bulletin, 2012, 57(5): 374-381.] |
[15] | 赵勇, 房永杰, 黄有志. RegCM3模式对新疆1996年降水和气温的数值模拟分析[J]. 沙漠与绿洲气象, 2012, 6(4): 38-43. |
[15] | [Zhao Yong, Fang Yongjie, Huang Youzhi. The numerical simulation analysis of precipitation and air temperature in Xinjiang in 1996 by regional climate model[J]. Desert and Oasis Meteorology, 2012, 6(4): 38-43.] |
[16] | Martínez C D, Vichot L A, Bezanilla M A, et al. The performance of RegCM4 over the central America and Caribbean region using different cumulus parameterizations[J]. Climate Dynamics, 2018, 50: 4103-4126. |
[17] | Gao X J, Shi Y, Han Z Y, et al. Performance of RegCM4 over major river basins in China[J]. Advances in Atmospheric Sciences, 2017, 34(4): 441-55. |
[18] | Chow K C, Chan J C L, Pal J S, et al. Convection suppression criteria applied to the MIT cumulus parameterization scheme for simulating the Asian summer monsoon[J]. Geophysical Research Letters, 2006, 33(24): L24709, doi: 10.1029/2006GL028026. |
[19] | Elguindi N, Bi X Q, Giorgi F, et al. Regional climate model RegCM reference manual version 4.6[M]. Trieste, Italy: The Abdus Salam International Centre for Theoretical Physics, 2014: 25-27. |
[20] | Grell G A, Dudhia J, Stauffer D R. A description of the fifth generation Penn State/MCAR mesoscale model (MM5)[R]. Boulder: National Center for Atmospheric Research, 1994. |
[21] | 赵济. 中国自然地理[M]. 北京: 高等教育出版社, 1995. |
[21] | [Zhao Ji. Physical geography of China[M]. Beijing: Higher Education Press, 1995.] |
[22] | Li Z, Cribb M C, Chang F L, et al. Validation of MODIS-retrieved cloud fractions using whole sky imager measurements at the three ARM sites[C]// Fourteenth ARM Science Team Meeting Proceedings. Albuquerque, New Mexico, 2004. |
[23] | King M D, Platnick S, Menzel W P, et al. Spatial and temporal distribution of clouds observed by MODIS onboard the Terra and Aqua satellites[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(7): 3826-3852. |
[24] | Fritsch J M, Chappell C F. Numerical prediction of convectively driven mesoscale pressure systems. Part I: Convective parameterization[J]. Journal of the Atmospheric Sciences, 1980, 37: 1722-1733. |
[25] | Emanuel K A, Zivkovic-Rothman M. Development and evaluation of a convection scheme for use in climate models[J]. Journal of the Atmospheric Sciences, 1999, 56: 1766-1782. |
[26] | 韩振宇, 王宇星, 聂羽. RegCM4对中国东部区域气候模拟的辐射收支分析[J]. 大气科学学报, 2016, 39(5): 683-691. |
[26] | [Han Zhenyu, Wang Yuxing, Nie Yu. The radiation budget in a regional climate simulation by RegCM4 for eastern China[J]. Transactions of Atmospheric Sciences, 2016, 39(5): 683-691.] |
[27] | 王澄海, 余莲. 区域气候模式对不同的积云参数化方案在青藏高原地区气候模拟中的敏感性研究[J]. 大气科学, 2011, 35(6): 1132-1144. |
[27] | [Wang Chenghai, Yu Lian. Sensitivity of regional climate model to different cumulus parameterization schemes in simulation of Tibetan Plateau climate[J]. Chinese Journal of Atmospheric Sciences, 2011, 35(6): 1132-1144.] |
[28] | Bauer P, Thorpe A, Brunet G. The quiet revolution of numerical weather prediction[J]. Nature, 2015, 525(7567): 47-55. |
[29] | 贾海灵, 马晓燕, 熊飞麟. 中国东部大陆和邻近海域暖云特性时空分布及其与气象条件的关系[J]. 气候与环境研究, 2018, 23(6): 737-748. |
[29] | [Jia Hailing, Ma Xiaoyan, Xiong Feilin. Spatial and temporal distributions of warm cloud properties in eastern China and its adjacent ocean and their relationships with meteorological conditions[J]. Climatic and Environmental Research, 2018, 23(6): 737-748.] |
[30] | 汪会, 罗亚丽, 张人禾. 用CloudSat/CALIPSO资料分析亚洲季风区和青藏高原地区云的季节变化特征[J]. 大气科学, 2011, 35(6): 1117-1131. |
[30] | [Wang Hui, Luo Yali, Zhang Renhe. Analyzing seasonal variation of clouds over the Asian monsoon regions and the Tibetan Plateau region using CloudSat/CALIPSO data[J]. Chinese Journal of Atmospheric Sciences, 2011, 35(6): 1117-1131.] |
[31] | 司钰文, 郑宁, 杨洪海, 等. 东亚单层低云特性及其短波辐射强迫的季节变化[J]. 干旱区研究, 2020, 37(1): 37-45. |
[31] | [Si Yuwen, Zheng Ning, Yang Honghai, et al. Seasonal variation of single-layer low cloud physical properties and radiative forcing in East Asia[J]. Arid Zone Research, 2020, 37(1): 37-45.] |
[32] | 李荔珊, 胡轶佳, 钟中, 等. 积云参数化方案对夏季东亚季风区海气系统位相关系模拟的影响[J]. 气象科学, 2016, 36(3): 329-339. |
[32] | [Li Lishan, Hu Yijia, et al. Influence of cumulus parameterization scheme on the simulation of the air-sea system phase relation in East Asia summer monsoon region[J]. Journal of the Meteorological Sciences, 2016, 36(3): 329-339.] |
[33] | 鞠丽霞, 王会军. 用全球大气环流模式嵌套区域气候模式模拟东亚现代气候[J]. 地球物理学报, 2006, 49(1): 52-60. |
[33] | [Ju Lixia, Wang Huijun. Modern climate over East Asia simulated by a regional climate model nested in a global gridpoint general circulation model[J]. Chinese Journal of Geophysics, 2006, 49(1): 52-60.] |
[34] | Zou L W, Qian Y, Zhou T J, et al. Parameter tuning and calibration of RegCM3 with MIT-Emanuel cumulus parameterization scheme over CORDEX East Asia domain[J]. Journal of Climate, 2014, 27(20): 7687-7701. |
/
〈 |
|
〉 |