Estimation of climate change in the 21st century in North China by RegCM4

doi:10.11755/j.issn.1006-7639(2022)-01-0001

Abstract

Abstract:

Based on dynamic downscaling simulation data of temperature and precipitation by the regional climate model version 4 (RegCM4) from National Climate Center under the representative concentration pathways 4.5 (RCP4.5) and RCP8.5 scenarios, the simulation ability of RegCM4 was tested in baseline period (1986-2005). And on this basis, the climate change was analyzed in North China in future of the 21st century. The results show that RegCM4 had a better performance in simulating air temperature and precipitation in North China in baseline period. The change of surface air temperature, precipitation, consecutive dry days (CDD) and strong precipitation (R95p) under RCP4.5 and RCP8.5 scenarios will increase gradually in North China in future of the 21st century, but their changes under RCP4.5 scenario will be obviously less than those under RCP8.5 scenario. Under the higher emission scenario of RCP8.5, the annual mean air temperature will rise 1.77, 3.44 and 5.82 ℃ in near term (2021-2035), medium term (2046-2065) and long term (2080-2098) of the 21st century, the annual mean precipitation will increase 8.1%, 14% and 19.3%, CDD will reduce 3, 3 and 12 d, and R95p will increase 30.8%, 41.9% and 69.8%, respectively. In space, the mean air temperature in the whole year, winter and summer in North China will rise consistently in future of the 21st century, and the warming in summer will be the most, while the mean precipitation in the whole year, winter and summer will increase in most regions, and the increase of precipitation in winter will be the most. Meanwhile, CDD will decrease except in Shanxi and Beijing-Tianjin-Hebei areas in near term and medium term, while R95p will increase, which indicated that the drought events will reduce and the extreme precipitation will increase in the 21st century.

Key words: RegCM4, North China, air temperature, precipitation, extreme indexes

摘要：

利用国家气候中心完成的RegCM4区域气候模式在RCP4.5和RCP8.5两种排放路径下的气候变化动力降尺度试验结果,在检验模式对基准期(1986—2005年)气温和降水模拟能力基础上,进行华北区域21世纪气候变化预估分析。结果表明:RegCM4对华北区域基准期气温和降水的模拟能力较好。未来21世纪,两种情景下华北区域气温、降水、持续干期(consecutive dry days, CDD)和强降水量(R95p)变化逐渐增大,但变化幅度在高排放的RCP8.5情景下更为显著,其中近期(2021—2035年)、中期(2046—2065年)、远期(2080—2098年)RCP8.5情景下年平均气温分别升高1.77、3.44、5.82 ℃,年平均降水分别增加8.1%、14%、19.3%,CDD分别减少3、3、12 d,R95p分别增加30.8%、41.9%、69.8%。空间上,未来21世纪华北区域内年、冬季、夏季平均气温将一致升高,夏季升温幅度最大;年、冬季、夏季平均降水整体以增加为主,冬季降水增加幅度最大;CDD以减少为主,但近期和中期在山西和京津冀有所增加,而R95p以增加为主,表明21世纪华北区域干旱事件逐渐减少、极端降水事件不断增加。

关键词: RegCM4, 华北区域, 气温, 降水, 极端指数

CLC Number:

P467

CHEN Ying, ZHANG Dongfeng, WANG Lin, LIU Yueli, WANG Dayong. Estimation of climate change in the 21st century in North China by RegCM4[J]. Journal of Arid Meteorology, 2022, 40(1): 1-10.

陈颖, 张冬峰, 王林, 刘月丽, 王大勇. RegCM4对华北区域21世纪气候变化预估研究[J]. 干旱气象, 2022, 40(1): 1-10.

Figures/Tables 7

Fig.1 The observation (a, c, e) of mean temperature and the difference between simulation and observation (b, d, f) in the whole year (a, b), winter (c, d) and summer (e, f) in North China during the baseline period (Unit: ℃)

Fig.2 The observation (a, c, e) and simulation (b, d, f) of mean precipitation in the whole year (a, b), winter (c, d) and summer (e, f) in North China during the baseline period (Unit: mm·d-1)

Fig.3 The temperature anomaly (a, b) and precipitation anomaly percentage (c, d) simulated by RegCM4 under RCP4.5 (a, c) and RCP8.5 (b, d) scenarios in North China from 2021 to 2098

Tab.1 The change of temperature, precipitation and extreme precipitation indexes simulated by RegCM4 under different scenarios in North China in each period of the 21st century

时期	情景	气温距平/℃			降水距平百分率/%			CDD 距平/d	R95p距平百分率/%
时期	情景	年	冬季	夏季	年	冬季	夏季	CDD 距平/d	R95p距平百分率/%
近期	RCP4.5	1.23	0.82	1.56	5.1	5.8	3.8	-1	19.2
	RCP8.5	1.77	0.83	2.31	8.1	20.6	6.0	-3	30.8
中期	RCP4.5	2.58	2.50	2.80	8.9	22.1	7.7	-3	28.3
	RCP8.5	3.44	2.53	3.79	14.0	32.9	13.1	-3	41.9
远期	RCP4.5	3.49	3.50	3.69	9.2	37.7	6.8	-7	27.2
	RCP8.5	5.82	4.68	6.40	19.3	70.4	11.2	-12	69.8

Fig.4 The anomaly of mean temperature in the whole year (a, b), winter (c, d) and summer (e, f ) simulated by RegCM4 under RCP4.5 (a, c, e) and RCP8.5 (b, d, f) scenarios in North China in the mid-21st century (Unit: ℃)

Fig.5 The anomaly percentage of mean precipitation in the whole year (a, b), winter (c, d) and summer (e, f) simulated by RegCM4 under RCP4.5 (a, c, e) and RCP8.5 (b, d, f) scenarios in North China in the mid-21st century (Unit: %)

Fig.6 The anomaly of CCD (a, b, Unit: d) and anomaly percentage of R95p (c, d, Unit: %) simulated by RegCM4 under RCP4.5 (a, c) and RCP8.5 (b, d) scenarios in North China in the mid-21st century

References 31

[1]	MEINSHAUSEN M, SMITH S J, CALVIN K, et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300[J]. Climatic Change, 2011, 109(1):213-241. DOI URL
[2]	IPCC. Climate change 2013: The physical science basis[M]. Cambridge: Cambridge University Press, 2013:743-866.
[3]	IPCC. Climate change 2021: The physical science basis[M]. Cambridge: Cambridge University Press, 2021.
[4]	王素仙, 张永领, 郭灵辉, 等. 1981—2010年内蒙古气温变化特征及未来趋势预估[J]. 气象与环境科学, 2017, 40(4):114-120.
[5]	GAO X J, SHI Y, ZHANG D F, 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(10):1188-1195. DOI URL
[6]	GAO X J, WANG M L, GIORGI F. Climate change over China in the 21st century as simulated by BCC_CSM1.1-RegCM4.0[J]. Atmospheric and Oceanic Science Letters, 2013, 6(5):381-386. DOI URL
[7]	张冬峰, 高学杰, 罗勇, 等. RegCM4.0对一个全球模式20世纪气候变化试验的中国区域降尺度:温室气体和自然变率的贡献[J]. 科学通报, 2015, 60(17):1631-1642.
[8]	GIORGI F, BATES G T. The climatological skill of a regional model over complex terrain[J]. Monthly Weather Review, 1989, 117(11):2325-2347. DOI URL
[9]	石英. RegCM3对21世纪中国区域气候变化的高分辨率数值模拟[D]. 北京:中国科学院大气物理研究所, 2010.
[10]	吉振明. 新排放情景下中国气候变化的高分辨率数值模拟研究[D]. 北京:中国科学院研究生院, 2012.
[11]	ZHANG D F, HAN Z Y, SHI Y. Comparison of climate projections between driving CSIRO-Mk3.6.0 and downscaling simulation of RegCM4.4 over China[J]. Advances in Climate Change Research, 2017, 8(4):245-255. DOI URL
[12]	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]	GAO X J, SHI Y, ZHANG D F, et al. Uncertainties in monsoon precipitation projections over China: Results from two high-resolution RCM simulations[J]. Climate Research, 2012, 52:213-226. DOI URL
[14]	SHI Y, GAO X J, WU J, et al. Changes in snow cover over China in the 21st century as simulated by a high resolution regional climate model[J]. Environmental Research Letters, 2011, 6(4):045401. DOI URL
[15]	张冬峰, 石英. 区域气候模式RegCM3对华北地区未来气候变化的数值模拟[J]. 地球物理学报, 2012, 55(9):2854-2866.
[16]	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, 54:1113-1130. DOI URL
[17]	ZHOU B T, WU J, XU Y, et al. Projected changes in autumn rainfall over West China: Results from an ensemble of dynamical downscaling simulations[J]. International Journal of Climatology, 2019, 39:4869-4882. DOI URL
[18]	GIORGI F, COPPOLA E, SOLMON F, et al. RegCM4: Model description and preliminary tests over multiple CORDEX domains[J]. Climate Research, 2012, 52:7-29. DOI URL
[19]	COLLINS W J, BELLOUIN N, DOUTRIAUX-BOUCHER M, et al. Development and evaluation of an Earth-system model-HadGEM2[J]. Geoscientific Model Development Discussions, 2011, 4:997-1062.
[20]	MARTIN G M, BELLOUIN N, COLLINS W J, et al. The HadGEM2 family of Met Office Unified Model climate configurations[J]. Geoscientific Model Development, 2011, 4(3):723-757. DOI URL
[21]	GIORGI F, JONES C, ASRAR G R, et al. Addressing climate information needs at the regional level: The CORDEX framework[J]. WMO Bulletin, 2009, 58(3):175-183.
[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 Ocean Science Letters, 2016, 9(4):246-254.
[23]	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 URL
[24]	KIEHL J T, HACK J J, BONAN G B, et al. Description of the NCAR community climate model (CCM3)[J]. NCAR Technical Note, 1996, 108(2):55-60.
[25]	HOLTSLAG A A M, DE BRUIJN E I F, PAN H L. A high resolution air mass transformation model for short-range weather forecasting[J]. Monthly Weather Review, 1990, 118:1561-1575. DOI URL
[26]	PAL J S, SMALL E E, ELTAHIR E A B. Simulation of regional-scale water and energy budgets: Representation of subgrid cloud and precipitation processes within RegCM[J]. Journal of Geophysical Research: Atmospheres, 2000, 105(D24):29579-29594. DOI URL
[27]	EMANUEL K A. A scheme for representing cumulus convection in large-scale models[J]. Journal of the Atmospheric Sciences, 1991, 48(21):2313-2329. DOI URL
[28]	OLESON K W, NIU G Y, YANG Z L, et al. Improvements to the community land model and their impact on the hydrological cycle[J]. Journal of Geophysical Research: Biogeosciences, 2008, 113:G01021.
[29]	韩振宇, 高学杰, 石英, 等. 中国高精度土地覆盖数据在RegCM4/CLM模式中的引入及其对区域气候模拟影响的分析[J]. 冰川冻土, 2015, 37(4):857-866.
[30]	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.
[31]	ZHANG X B, ALEXANDER L, HEGERL G C, et al. Indices for monitoring changes in extremes based on daily temperature and precipitation data[J]. Wiley Interdisciplinary Reviews: Climate Change, 2011, 2(6):851-870. DOI URL