Evaluation of RegCM4 downscaling simulations on regional rainstorm events in China

doi:10.12006/j.issn.1673-1719.2020.197

Abstract

Abstract:

Based on the Regional Climate Model Version 4 (RegCM4) simulations (named CdR, EdR, HdR, and MdR, respectively) dynamically downscaling from four global climate models (GCMs) as well as the observed high-resolution grid dataset CN05.1, the regional rainstorm events that occurred in China during 1981-2005 were identified by using a “tracing” objective method. On this basis, the fidelity of the RegCM4 downscaling in simulating the climate features of regional rainstorm events in China was evaluated. The results show that the four RegCM4 simulations and their ensemble can reasonably capture the observed annual cycles and climate mean values of the frequency, duration, rainfall amount, extent, and comprehensive intensity of regional rainstorm events averaged in China. They can also well reproduce the probability of duration, rainfall amount, extent and comprehensive intensity of regional rainstorm events in different bands and the climatologically spatial distribution of accumulative frequency, duration and rainfall amount of regional rainstorm events in the observation. The spatial correlations of the simulations with the observation are all above 0.9 and the root-mean-square errors are generally below 0.4. However, the simulations slightly underestimate the frequency of regional rainstorm events, mainly due to the underestimation of moderate regional rainstorm events. The average duration and average rainfall amount are slightly overestimated, while the average extent is slightly underestimated. The comprehensive intensity is overestimated by the simulations (especially by MdR) with the exception of HdR. For spatial distribution, the performance of CdR is relatively lower than that of other simulations. The relative errors of the ensemble simulation with reference to the observation are 13%, 2%, -11%, and 3% for the average duration, rainfall amount, extent, and comprehensive intensity of regional rainstorm events, respectively.

Key words: Regional rainstorm event, Dynamical downscaling, Model evaluation, Climate feature

CAI Yi-Heng, HAN Zhen-Yu, ZHOU Bo-Tao. Evaluation of RegCM4 downscaling simulations on regional rainstorm events in China[J]. Climate Change Research, 2021, 17(4): 420-429.

Figures/Tables 9

Table 1 Frequency of regional rainstorm events in China averaged from 1981 to 2005 and the percentages of different category of regional rainstorm events to total events

Table 2 Climate mean of the metrics for regional rainstorm events in China averaged from 1981 to 2005

Fig. 1 Monthly distribution of the percentage of frequency (a), duration (b), average rainfall amount (c), average extent (d), and average comprehensive intensity (e) of regional rainstorm events during 1981-2005

Fig. 2 Frequency percentage distributions for duration (a), average rainfall amount (b), average extent (c), and average comprehensive intensity (d) of regional rainstorm events during 1981-2005

Table 3 S score of the frequency percentage distribution for each metric of regional rainstorm events in China during 1981-2005

Fig. 3 Observed (a) and MME simulated (b) climatological distribution of the accumulative frequency of regional rainstorm events during 1981-2005 and the relative errors of the MME simulation (c) with reference to the observation (the number in the Fig. (c) indicates the proportion of areas where the absolute relative error is less than 0.4)

Fig. 4 Same as Fig. 3, but for the accumulative duration of regional rainstorm events

Fig. 5 Same as Fig. 3, but for the accumulative rainfall amount of regional rainstorm events

Fig. 6 Taylor diagram for accumulative frequency, duration and rainfall amount of regional rainstorm events in China during 1981-2005 with reference to the observation

References 37

[1]	IPCC. Climate change 2013: the physical science basis [M]. Cambridge: Cambridge University Press, 2013
[2]	Wang Y Q, Zhou L. Observed trends in extreme precipitation events in China during 1961-2001 and the associated changes in large-scale circulation[J]. Geophysical Research Letters, 2005, 32(9), L09707
[3]	Zhai P M, Zhang X B, Wan H, et al. Trends in total precipitation and frequency of daily precipitation extremes over China[J]. Journal of Climate, 2005, 18(7):1096-1108 doi: 10.1175/JCLI-3318.1 URL
[4]	Zhang D Q, Feng G L, Hu J G. Trend of extreme precipitation events over China in last 40 years[J]. Chinese Physics B, 2008, 17(2):736-742 doi: 10.1088/1674-1056/17/2/062 URL
[5]	Zhou B T, Xu Y, Wu J, et al. Changes in temperature and precipitation extreme indices over China: analysis of a high-resolution grid dataset[J]. International Journal of Climatology, 2016, 36(3):1051-1066 doi: 10.1002/joc.4400 URL
[6]	Chen H P. Projected change in extreme rainfall events in China by the end of the 21st century using CMIP5 models[J]. Chinese Science Bulletin, 2013, 58(12):1462-1472 doi: 10.1007/s11434-012-5612-2 URL
[7]	Zhou B T, Wen H Q, Xu Y, et al. Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles[J]. Journal of Climate, 2014, 27(17):6591-6611 doi: 10.1175/JCLI-D-13-00761.1 URL
[8]	Chen H P, Sun J Q, Lin W Q, et al. Comparison of CMIP6 and CMIP5 models in simulating climate extremes[J]. Science Bulletin, 2020, 65:1415-1418 doi: 10.1016/j.scib.2020.05.015 URL
[9]	Xu Y, Zhang B, Zhou B T, et al. Projected risk of flooding disaster in China based on CMIP5 models[J]. Advances in Climate Change Research, 2014, 5(2):57-65 doi: 10.3724/SP.J.1248.2014.057 URL
[10]	Klein Tank A M G, Zwiers F W, Zhang X B. Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation[C]. World Meteorological Organization: Climate Data and Monitoring, 2009, 1-56
[11]	钱维宏. 气候变化与中国极端气候事件图集 [M]. 气象出版社, 2011: 146-156.
	Qian W H. Atlas of climate change and China extreme climate events [M]. Beijing: China Meteorological Press, 2011: 146-156(in Chinese)
[12]	Ren F M, Cui D L, Gong Z Q, et al. An objective identification technique for regional extreme events[J]. Journal of Climate, 2012, 25(20):7015-7027 doi: 10.1175/JCLI-D-11-00489.1 URL
[13]	Zou X K, Ren F M. Changes in regional heavy rainfall events in China during 1961-2012[J]. Advances in Atmospheric Sciences, 2015, 32(5):704-714 doi: 10.1007/s00376-014-4127-y URL
[14]	Wu Y J, Ji H X, Wen J H, et al. The characteristics of regional heavy precipitation events over eastern monsoon China during 1960-2013[J]. Global and Planetary Change, 2019, 172:414-427 doi: 10.1016/j.gloplacha.2018.11.001 URL
[15]	景丞, 姜彤, 王艳君, 等. 中国区域性极端降水事件及人口经济暴露度研究[J]. 气象学报, 2016, 74(4):572-582.
	Jing C, Jiang T, Wang Y J, et al. A study on regional extreme precipitation events and the exposure of population and economy in China[J]. Acta Meteorologica Sinica, 2016, 74(4):572-582 (in Chinese)
[16]	叶殿秀, 王遵娅, 高荣, 等. 1961—2016年我国区域暴雨过程的客观识别及其气候特征[J]. 气候变化研究进展, 2019, 15(6):575-583.
	Ye D X, Wang Z Y, Gao R, et al. Objective identification and climatic characters of the regional rainstorm event in China from 1961 to 2016[J]. Climate Change Research, 2019, 15(6):575-583 (in Chinese)
[17]	Yu E T, Sun J Q, Chen H P, et al. Evaluation of a high-resolution historical simulation over China: climatology and extremes[J]. Climate Dynamics, 2015, 45(7-8):2013-2031 doi: 10.1007/s00382-014-2452-6 URL
[18]	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):441-455 doi: 10.1007/s00376-016-6179-7 URL
[19]	Zou L W, Zhou T J. Near future (2016-40) summer precipitation changes over China as projected by a regional climate model (RCM) under the RCP8.5 emissions scenario: comparison between RCM downscaling and the driving GCM[J]. Advances in Atmospheric Sciences, 2013, 30(3):806-818 doi: 10.1007/s00376-013-2209-x URL
[20]	Yao J C, Zhou T J, Guo Z, et al. Improved performance of high-resolution atmospheric models in simulating the East-Asian summer monsoon rainbelt[J]. Journal of Climate, 2017, 30(21):8825-8840 doi: 10.1175/JCLI-D-16-0372.1 URL
[21]	Giorgi F, Coppola E, Solmon F, et al. RegCM4: model description and preliminary tests over multiple CORDEX domains[J]. Climate Research, 2012, 52(29):7-29 doi: 10.3354/cr01018 URL
[22]	Gao X J, Shi Y, Giorgi F. Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model[J]. Atmospheric and Oceanic Science Letters, 2016, 9(4):246-254 doi: 10.1080/16742834.2016.1172938 URL
[23]	Gao X J, Wu J, Shi Y, et al. Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations[J]. Atmospheric and Oceanic Science Letters, 2018, 11(4):291-299 doi: 10.1080/16742834.2018.1471578 URL
[24]	Han Z Y, Zhou B T, Xu Y, et al. Projected changes in haze pollution potential in China: an ensemble of regional climate model simulations[J]. Atmospheric Chemistry and Physics, 2017, 17(16):10109-10123 doi: 10.5194/acp-17-10109-2017 URL
[25]	吴佳, 高学杰. 一套格点化的中国区域逐日观测资料及与其它资料的对比[J]. 地球物理学报, 2013, 56(4):1102-1111.
	Wu J, Gao X J. A gridded daily observation dataset over China region and comparison with the other datasets[J]. Chinese Journal of Geophysics, 2013, 56(4):1102-1111 (in Chinese)
[26]	Tong Y, Gao X J, Han Z Y, et al. Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods[J]. Climate Dynamics, 2020, DOI: 10.1007/s00382-020-05447-4
[27]	Lu E, Zhao W, Zou X, et al. Temporal-spatial monitoring of extreme precipitation event: determining simultaneously the time period it lasts and the geographic region it affects[J]. Journal of Climate, 2017, 30(16):6123-6132 doi: 10.1175/JCLI-D-17-0105.1 URL
[28]	Perkins S E, Pitman A J, Holbrook N J, et al. Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions[J]. Journal of Climate, 2007, 20(17):4356-4376 doi: 10.1175/JCLI4253.1 URL
[29]	Taylor K E. Summarizing multiple aspects of model performance in a single diagram[J]. Journal of Geophysical Research: Atmospheres, 2001, 106(D7):7183-7192 doi: 10.1029/2000JD900719 URL
[30]	Jiang D B, Tian Z P. East Asian monsoon change for the 21st century: results of CMIP3 and CMIP5 models[J]. Chinese Science Bulletin, 2013, 58(12):1427-1435 doi: 10.1007/s11434-012-5533-0 URL
[31]	Jiang D B, Tian Z P, Lang X M. Reliability of climate models for China through the IPCC Third to Fifth assessment reports[J]. International Journal of Climatology, 2016, 36(3):1114-1133 doi: 10.1002/joc.4406 URL
[32]	Xu Z F, Hou Z L, Han Y, et al. A diagram for evaluating multiple aspects of model performance in simulating vector fields[J]. Geoscientific Model Development, 2016, 9(12):4365-4380 doi: 10.5194/gmd-9-4365-2016 URL
[33]	Wu J, Gao X J. Present day bias and future change signal of temperature over China in a series of multi-GCM driven RCM simulations[J]. Climate Dynamics, 2020, 54(1-2):1113-1130 doi: 10.1007/s00382-019-05047-x URL
[34]	Niu X R, Wang S Y, Tang J P, et al. Multimodel ensemble projection of precipitation in Eastern China under A1B emission scenario[J]. Journal of Geophysical Research: Atmospheres, 2015, 120(19):9965-9980 doi: 10.1002/jgrd.v120.19 URL
[35]	Ou T H, Chen D L, Linderholm H W, et al. Evaluation of global climate models in simulating extreme precipitation in China[J]. Tellus A: Dynamic Meteorology and Oceanography, 2013, 65(1), 19799 doi: 10.3402/tellusa.v65i0.19799 URL
[36]	Yang S L, Feng J M, Dong W J, et al. Analyses of extreme climate events over China based on CMIP5 historical and future simulations[J]. Advances in Atmospheric Sciences, 2014, 31(5):1209-1220 doi: 10.1007/s00376-014-3119-2 URL
[37]	Zhou T J, Chen Z M, Zou L W, et al. Development of climate and Earth System Models in China: past achievements and new CMIP6 results[J]. Journal of Meteorological Research, 2020, 34(1):1-19 doi: 10.1007/s13351-020-9164-0 URL