基于CMIP6多模式集合的华中地区气候变化模拟与预估

doi:10.3969/j.issn.1673-503X.2023.06.007

Abstract

Abstract:

Utilizing daily meteorological observation data from Central China from 1961-2014, along with downscaled and bias-corrected data from 12 CMIP6 models from 1961-2100, this study assesses the spatial and temporal distributions of temperature and precipitation simulations of the CMIP6 models for the region, using the selected temperatures from six models and the precipitation data from four models. Based on the ensemble mean of the selected model results, the change trends in temperature and precipitation for Central China during different periods from 2021 to 2100 under three future scenarios i.e. SSP1-2.6, SSP2-4.5, and SSP5-8.5 were analyzed. The results indicate that the ensemble mean provides better interannual variability in temperature simulations than those of precipitation, while the spatial simulation of precipitation is better than that of temperature. Under all three scenarios, both regional temperature and precipitation show increasing trends, with temperature rise rates of 0.13 ℃/decade, 0.30 ℃/decade, and 0.62 ℃/decade, and precipitation rise rates of 16.2 mm/decade, 12.3 mm/decade, and 19.3 mm/decade, respectively. For the future period from 2021 to 2100 under the three scenarios, precipitation in Central China is projected to decrease in the south and to increase in the north. Near-term and mid-term temperatures are expected to decrease in the west and to increase in the central and eastern parts, while the long-term trend indicates that temperature increases across the region and only decreases in the western mountainous area of Hubei.

Key words: Precipitation, Temperature, CMIP6, Model Ensemble

CLC Number:

P467

Miao WANG,Pengcheng QIN,Chenxu SHE,Xiaofang ZHAO,Mingwei YANG. Simulation and projection of climate change in Central China based on CMIP6 multi-model ensemble[J]. Journal of Meteorology and Environment, 2023, 39(6): 51-60.

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序号	模式	国家	分辨率/(纬度°×经度°)	情景	历史时间/预估时间
1	ACCESS-CM2	澳大利亚	1.2°×1.8°	HIS/126/245/370/585	1901—2014年/2015—2100年
2	ACCES-ESM1-5	澳大利亚	1.2°×1.8°	HIS/126/245/370/585	1901—2014年/2015—2100年
3	BCC-CSM2-MR	中国	1.1°×1.1°	HIS/126/245/370/585	1961—2014年/2005—2100年
4	CCCma-CanESM5	加拿大	2.8°×2.8°	HIS/126/245/370/585	1961—2014年/2005—2100年
5	CNRM-CM6-1	法国	1.4°×1.4°	HIS/126/245/370/585	1850—2014年/2005—2100年
6	Hadgem3-gc31-LL	英国	1.3°×1.9°	HIS/126/245/585	1901—2014年/2015—2100年
7	INM-CM4-8	俄罗斯	1.5°×2.0°	HIS/126/245/585	1901—2014年/2015—2100年
8	INM-CM5-0	俄罗斯	1.5°×1.5°	HIS/126/245/585	1901—2014年/2015—2100年
9	IPSL-CM6A-LR	法国	1.3°×2.5°	HIS/126/245/585	1901—2014年/2015—2100年
10	MIROC6	日本	1.4°×1.4°	HIS/126/245/585	1901—2014年/2015—2100年
11	MPI-ESM1-2-HR	德国	0.9°×0.9°	HIS/126/245/585	1901—2014年/2015—2100年
12	MRI-ESM2-0	德国	1.1°×1.1°	HIS/126/245/585	1901—2014年/2015—2100年

序号	模式	气温			降水
序号	模式	空间相关系数	标准差比	均方根误差/℃	空间相关系数	标准差比	均方根误差/mm
1	ACCESS-CM2	0.84^*	1.27^*	0.04^*	0.98	0.96	3.51
2	ACCES-ESM1-5	0.82	1.26	0.04	0.99	1.02	1.93
3	BCC-CSM2-MR	0.83^*	1.25^*	0.05^*	0.98	1.16	7.62
4	CCCma-CanESM5	0.83	1.29	0.04	0.98	0.93	3.34
5	CNRM-CM6-1	0.84^*	1.29^*	0.05^*	0.98^*	1.01^*	2.61^*
6	Hadgem3-gc31-Ⅱ	0.84^*	1.26^*	0.05^*	0.98	0.97	3.83
7	INM-CM4-8	0.84	1.28	0.05	0.98^*	0.97^*	2.24^*
8	INM-CM5-0	0.83^*	1.28^*	0.05^*	0.98	1.04	2.15
9	IPSL-CM6A-LR	0.83	1.28	0.04	0.97^*	0.93^*	2.70^*
10	MIROC6	0.82^*	1.26^*	0.05^*	0.98^*	1.02^*	2.89^*
11	MPI-ESM1-2-HR	0.85	1.32	0.05	0.98	0.89	2.46
12	MRI-ESM2-0	0.84	1.28	0.55	0.97	1.01	4.64
优选模式集合平均		0.84	1.26	0.04	0.98	0.98	2.22

气象要素	情景	2021—2100年	近期	中期	远期
气温/(℃/10 a)	SSP1-2.6	0.13	0.35	0.28	-0.06
	SSP2-4.5	0.30	0.39	0.33	0.15
	SSP5-8.5	0.62	0.50	0.53	0.75
降水/(mm/10 a)	SSP1-2.6	16.2	-18.3	-3.9	39.5
	SSP2-4.5	12.3	10.8	40.6	-0.6
	SSP5-8.5	19.3	6.2	4.3	-14.1

统计量	情景	未来	近期	中期	远期
气温变幅/℃	SSP2-4.5	1.29	0.34	1.01	2.14
气温变幅/℃	RCP4.5	2.08	1.13	2.07	2.88
气温变化趋势/(℃/10 a)	SSP2-4.5	0.30	0.39	0.33	0.15
气温变化趋势/(℃/10 a)	RCP4.5	0.30	0.27	0.46	-0.11
降水变率/(%)	SSP2-4.5	6.85	3.24	8.62	8.67
降水变率/(%)	RCP4.5	2.79	2.73	-1.86	7.58
降水变化趋势/(mm/10 a)	SSP2-4.5	12.3	10.8	40.6	-0.6
降水变化趋势/(mm/10 a)	RCP4.5	7.71	-21.13	18.19	35.00

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Simulation and projection of climate change in Central China based on CMIP6 multi-model ensemble

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