Projection of extreme temperature in Fujian based on CMIP6 output

doi:10.11755/j.issn.1006-7639（2022）-03-0415

Abstract

Abstract:

Based on Coupled Model Intercomparison Project Phase 6 (CMIP6) simulation data and high resolution daily grid observation data, quantile mapping method and Taylor diagram were used to correct and evaluate the simulation values of extreme temperature index,respectively. It was found that corrected simulation value of each extreme temperature index was closer to the observation during historical reference period (1991-2010).The spatial-temporal variation characteristic of extreme temperature indies in near-term, mid-term and late-term of the 21st century relative to historical reference period in Fujian Province under SSP2-4.5 and SSP5-8.5 scenarios were analyzed. From the perspective of temporal variation, in each period of the 21st century, the extreme temperature indices in Fujian Province showed an increasing trend and the incremental value increased over time.From the perspective of spatial variation, the extreme maximum temperature (TXx) showed a trend of increasing more in northwest inland area and less in southeast coastal area.The spatial distribution of extreme minimum temperature (TNn) was similar to that of TXx, but the warming rate was slightly smaller. The summer days (Su) increased more in the southwest of Fujian, while the warm days (TX90p) increased faster in the southeast area. Based on the generalized extreme value (GEV) distribution, it was found that under SSP2-4.5 scenario, the temperature increase in three periods in the 21st century was relatively uniform and stable, while under SSP5-8.5 scenario, the temperature increase showed an accelerating trend. Under SSP5-8.5 scenario, TXx of 20-year return period in the historical period was likely to occur every year in late-term of the 21st century.

Key words: SSPs scenarios, extreme temperature indices, climate change, GEV distribution

摘要：

基于第六阶段耦合模式比较计划（Coupled Model Intercomparison Project Phase 6, CMIP6）模拟数据和高分辨率逐日格点观测数据,分别采用分位数映射法和泰勒图对福建省极端气温指数模拟值进行订正和评估,发现在历史参照期（1991—2010年）订正后的各极端气温指数模拟值与观测值更加接近。在此基础上,分析了SSP2-4.5和SSP5-8.5情景下福建省21世纪近期（2021—2040年）、中期（2051—2070年）和末期（2081—2100年）订正后的极端气温指数相对于历史参照期的时空变化特征。从时间变化来看,21世纪各时期,全省平均极端气温指数呈现升高趋势,且随着时间推移增幅不断加大。从空间变化来看,极端最高气温TXx呈现西北内陆增幅大、东南沿海增幅小的趋势,极端最低气温TNn空间分布与TXx类似,增幅略小,夏季日数Su增量在福建西南部为大值区,暖昼日数TX90p在福建东南部增幅最大。采用广义极值（generalized extreme value, GEV）分布研究了TXx重现期变化,发现SSP2-4.5情景下,21世纪3个时期增温较为匀速,而SSP5-8.5情景下增温呈加速趋势。在SSP5-8.5情景下,历史参照期20 a一遇的极端最高气温在21世纪末期每年都可能发生。

关键词: SSPs情景, 极端气温指数, 气候变化, GEV分布

CLC Number:

P467

CEHN Xiaochen, TANG Zhenfei, CHEN Xikuan, ZHENG Chaoyu, LI Xinxin, YANG Ting. Projection of extreme temperature in Fujian based on CMIP6 output[J]. Journal of Arid Meteorology, 2022, 40(3): 415-423.

陈笑晨, 唐振飞, 陈锡宽, 郑潮宇, 李欣欣, 杨婷. 基于CMIP6的福建省极端气温预估[J]. 干旱气象, 2022, 40(3): 415-423.

Figures/Tables 9

Tab.1 Basic information of six CMIP6 global climate models

序号	模式	研究机构	空间分辨率
1	BCC-CSM2-MR	中国气象局国家气候中心（BCC）	1.125°×1.125°
2	EC-Earth3-Veg	欧盟地球系统模式联盟	0.7°×0.7°
3	GFDL-ESM4	美国大气与海洋管理局地球物理流体动力实验室（GFDL）	1.0°×1.25°
4	IPSL-CM6A-LR	法国皮埃尔-西蒙拉普斯研究所（IPSL）	1.26°×2.5°
5	MRI-ESM2-0	日本气象研究所（MRI）	1.125°×1.125°
6	NorESM2-MM	挪威气候中心（NCC）	0.94°×1.25°

Tab.1 The definition of extreme temperature indices

名称	缩写	定义	单位
极端最高气温	TXx	每年日最高气温的最大值	℃
极端最低气温	TNn	每年日最低气温的最小值	℃
夏季日数	Su	每年日最高气温大于25 ℃的全部日数	d
暖昼日数	TX90p	每年日最高气温大于90百分位阈值的日数	d

Fig.1 Taylor diagrams of simulated fields of four extreme temperature indices relative to observation fieldsin Fujian Province during historical reference period （a） before bias correction by QM method,（b） after bias correction by QM method（numbers 1 to 6 correspond to the model serial number in Table 1）

Fig.2 The spatial distribution of TXx （a） and TNn （b）（Unit：℃）,Su （c） and TX90p （d）（Unit：d）simulations corrected by QM method during historical reference period

Tab.3 The change of extreme temperature indices during different period in the 21st century relative to historical reference period in Fujian Province under SSP2-4.5 and SSP5-8.5 scenarios

情景	时期	TXx/ºC	TNn/ºC	Su/d	TX90p/d
	21世纪近期	1.11	1.00	15.94	8.04
SSP2-4.5	21世纪中期	2.12	1.88	31.82	19.89
	21世纪末期	2.76	2.38	38.57	27.34
	21世纪近期	1.20	1.22	18.89	9.55
SSP5-8.5	21世纪中期	2.93	2.78	41.18	28.60
	21世纪末期	4.86	4.55	66.12	47.98

Fig.3 Spatial distribution of change values of TXx and TNn （Unit：℃）,Su and TX90p （Unit：d） in near-term （the top）,mid-term （the middle） and late-term （the bottom）of the 21st century relative to historical reference period in Fujian Province under SSP2-4.5 scenario （The dark dots passed the 0.05 significance test. the same as below ）

Fig.4 Spatial distribution of change values of TXx and TNn （Unit：℃）,Su and TX90p （Unit：d） in near-term （the top）,mid-term （the middle） and late-term （the bottom）of the 21st century relative to historical reference period in Fujian Province under SSP5-8.5 scenario

Fig.5 The change of TXx of 20-year,50-year and 100-year return periods during different period in the 21st century relative to historical reference period in Fujian Province under SSP2-4.5 (a) and SSP5-8.5 (b) scenarios

Fig.6 The return period of TXx under 20-year return period in historical reference period in different periods in the 21st century under SSP2-4.5 and SSP5-8.5 scenarios

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