中国东北地区气温变化的模拟评估与未来情景预估

doi:10.3969/j.issn.1673-503X.2021.01.005

摘要/Abstract

摘要：

基于RegCM4区域气候模式、CMIP5全球气候模式数据集和中国东北地区162个气象站气温观测资料，采用偏差分析和相关分析评估了RegCM4和CMIP5对东北地区气温的模拟能力，预估了RCP2.6、RCP4.5和RCP8.5排放情景下东北地区未来气温的变化。结果表明：区域模式和全球模式均能较好地再现气温时空变化特征，模式对冬季和夏季的模拟效果优于秋季和春季；在区域尺度信息上，区域模式和全球模式的模拟值均较观测值偏小，RegCM4模式的模拟结果明显优于CMIP5模式，且对模拟的冷偏差有改善。未来东北地区年及四季气温均呈升高趋势，RCP2.6情景下增温相对较小，RCP4.5次之，RCP8.5情景下增温最显著；冬季和秋季气温增幅较大，夏季气温增幅最小；与CMIP5模式相比，RegCM4模式的增温幅度更大，且年际振荡特征更加明显。空间上，区域模式和全球模式预估的近期、中期、末期增温分布格局比较一致，均呈自北向南逐渐减小的纬向分布特征，辽宁地区增温幅度最小，增幅高值区位于黑龙江省大兴安岭地区，虽然北部升温幅度较南部明显，但是升温后未来东北地区的气温分布特征仍是南部气温高于北部。

关键词: RegCM4, CMIP5, 气温, 模拟能力, 情景预估

Abstract:

Based on the RegCM4 (Regional Climate Model 4) regional climate model, CMIP5 (Coupled Model Intercomparison Project Phase 5) global climate model dataset and temperature observation data from 162 meteorological stations in Northeast China, the abilities of RegCM4 and CMIP5 to simulate temperature in Northeast China were evaluated using the deviation and correlation analyses.The future temperature changes under three emission scenarios of RCP2.6, RCP4.5, and RCP8.5 in Northeast China were estimated as well.The results show that both the regional and global models can better represent the spatiotemporal changes in air temperature.The simulation effects in winter and summer are better than those in autumn and spring.In terms of regional-scale information, the simulated values are smaller than the observed ones.The simulation results of the RegCM4 are significantly better than those of the CMIP5, and the simulated deviation cold is improved.In the future, the annual and seasonal temperatures in Northeast China will increase.The warming magnitude in the RCP8.5 scenario is most significant, followed by the RCP4.5, and RCP2.6 is the smallest.The warming effects in winter and autumn are larger than those in summer.Compared with the CMIP5 model, the RegCM4 model has a larger temperature increasing amplitude and more obvious interannual oscillation characteristics.In terms of space, the distribution patterns of short-, medium-, and late-of-term warming predicted by the regional and global models are consistent, showing a zonal distribution reducing from the north to the south, with the minimum amplitude of warming in Liaoning province, the high-value area locating in the Greater Khingan Mountains area of Heilongjiang province.Although the warming effect in the north is more obvious than that in the south, the temperature distribution in the northeast region will continue to be higher in the south than that in the north after warming.

Key words: RegCM4, CMIP5, Temperature, Simulation capability, Scenario projection

中图分类号:

P467

敖雪,赵春雨,崔妍,周晓宇,翟晴飞,沈历都,王涛. 中国东北地区气温变化的模拟评估与未来情景预估[J]. 气象与环境学报, 2021, 37(1): 33-42.

Xue AO,Chun-yu ZHAO,Yan CUI,Xiao-yu ZHOU,Qing-fei ZHAI,Li-du SHEN,Tao WANG. Evaluation and projection of temperature change in Northeast China[J]. Journal of Meteorology and Environment, 2021, 37(1): 33-42.

图/表 7

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模式和观测	年	春季	夏季	秋季	冬季
RegCM4	5.08(-0.69)	5.96(-1.05)	20.97(-0.6)	5.82(-0.74)	-11.76(0.61)
CMIP5	4.35(-1.42)	5.03(-1.98)	20.49(-1.08)	5.16(-1.4)	-13.24(-0.87)
OBS	5.77	7.01	21.57	6.56	-12.37

模式	2020—2035年					2046—2065年					2080—2098年
模式	年	春	夏	秋	冬	年	春	夏	秋	冬	年	春	夏	秋	冬
RegCM4 RCP2.6	1.3	1.31	1.1	1.32	1.48	1.37	1.36	1.19	1.44	1.56	1.51	1.38	1.38	1.6	1.67
RegCM4 RCP4.5	1.34	1.42	1.13	1.34	1.50	2.65	2.31	2.49	2.82	2.84	3.46	2.85	3.05	3.86	3.95
RegCM4 RCP8.5	1.43	1.45	1.24	1.47	1.56	3.32	3.1	3.06	3.53	3.62	5.5	4.91	5.12	5.76	6.31
CMIP5 RCP2.6	1.11	0.89	1.06	1.21	1.27	1.47	1.15	1.51	1.65	1.55	1.58	1.29	1.47	1.71	1.57
CMIP5 RCP4.5	1.13	0.93	1.09	1.22	1.29	2.05	1.75	2.01	2.23	2.21	2.54	2.08	2.44	2.76	2.84
CMIP5 RCP8.5	1.27	1.02	1.16	1.38	1.47	2.93	2.49	2.87	3.17	3.23	5.39	4.63	5.05	5.61	6.28

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