气候变化研究进展 ›› 2024, Vol. 20 ›› Issue (3): 278-290.doi: 10.12006/j.issn.1673-1719.2023.210
全球升温1.5℃和2℃下中国群发性高温事件与人口暴露度预估
程阳1,2,3(
), 韩振宇4()
- 1 中国气象局·河南省农业气象保障与应用技术重点开放实验室，郑州 450003
2 新乡市气象防灾减灾重点实验室，新乡 453000
3 延津县气象局，新乡 453200
4 中国气象局国家气候中心，北京 100081
-
收稿日期:2023-09-21修回日期:2023-12-16出版日期:2024-05-30发布日期:2024-02-28 -
通讯作者:韩振宇，男，正高级工程师，hanzy@cma.cn -
作者简介:程阳，女，工程师，chengyang199102@163.com -
基金资助:广东省基础与应用基础研究重大项目(2020B0301030004);中国气象局气候变化专题项目(QBZ202404);中国气象局重点创新团队“气候变化检测与应对”(CMA2022ZD03);中国气象局·河南省农业气象保障与应用技术重点实验室应用技术研究基金项目(KM202345);新乡市气象防灾减灾重点实验室技术研究项目(XX202205)
Projection of the cluster high temperature events in China and population exposure under 1.5℃ and 2℃ global warming
CHENG Yang1,2,3(), HAN Zhen-Yu4()
- 1 CMA·Henan Key Laboratory of Agrometeorological Support and Applied Technique, Zhengzhou 450003, China
2 Key Laboratory of Meteorological Disaster Prevention and Mitigation of Xinxiang, Xinxiang 453000, China
3 Yanjin Meteorological Service, Xinxiang 453200, China
4 National Climate Centre, China Meteorological Administration, Beijing 100081, China
-
Received:2023-09-21Revised:2023-12-16Online:2024-05-30Published:2024-02-28
摘要：
基于区域气候模式RegCM4对4个全球气候模式的动力降尺度模拟数据及未来人口预估数据，预估了SSP2-RCP4.5情景下全球升温1.5℃和2℃时，中国群发性高温事件（cluster high temperature events，CHTE）和CHTE人口暴露度的变化。结果表明：1.5℃和2℃升温阈值下，多模式集合（MME）预估CHTE年均频次相对于基准期分别增加31%和44%。不同强度事件中，严重CHTE事件的频次在1.5℃和2℃升温阈值下可分别增加约4.2倍和6.8倍。事件强度、持续时间、频次等指标趋向高值的发生概率更大。相对于2℃，1.5℃温升阈值下CHTE年均频次、持续时间和累计强度在全国大范围呈降低趋势，且表现出明显的区域性差异，年均频次的降幅自北到南递增，新疆和长江以南地区持续时间年均减少6 d以上（全国平均降幅为0.2 d)，我国中东部地区累计强度年均减少20℃以上、新疆东部减少50℃以上（全国平均降幅为0.6℃)。此外，在1.5℃和2℃升温阈值下，MME预估CHTE影响人口的变化均呈现南增北减的空间分布，内蒙古地区略有减少，中东部地区普遍增加，全国总影响人口分别增加1.4倍和1.8倍。高温事件对城市的影响人口增幅更大（分别增加2.9倍和3.8倍)，尤其是京津冀、长三角、珠三角、中原地区增幅最明显。全国的CHTE强度暴露度（分别增加2.2倍和5.2倍）和综合暴露度（分别增加1.2倍和1.8倍）呈明显增加趋势，特别是2℃升温阈值下城市的CHTE强度暴露度和综合暴露度的增幅分别高达10倍和4倍。
引用本文
程阳, 韩振宇. 全球升温1.5℃和2℃下中国群发性高温事件与人口暴露度预估[J]. 气候变化研究进展, 2024, 20(3): 278-290.
CHENG Yang, HAN Zhen-Yu. Projection of the cluster high temperature events in China and population exposure under 1.5℃ and 2℃ global warming[J]. Climate Change Research, 2024, 20(3): 278-290.
表1 RCP4.5情景下模式预估全球温度较工业革命前达到1.5℃和2℃升温阈值的时间
Table 1 The crossing time in response to global warming of 1.5℃ and 2℃ in the future relative to pre-industrial level simulated by the four climate models under the RCP4.5
 |
表1 RCP4.5情景下模式预估全球温度较工业革命前达到1.5℃和2℃升温阈值的时间
Table 1 The crossing time in response to global warming of 1.5℃ and 2℃ in the future relative to pre-industrial level simulated by the four climate models under the RCP4.5
| |
表2 RCP4.5情景下中国群发性高温事件年均频次
Table 2 The annual mean frequency of the simulated cluster high temperature events (CHTE) averaged over China under RCP4.5 scenario
 |
表2 RCP4.5情景下中国群发性高温事件年均频次
Table 2 The annual mean frequency of the simulated cluster high temperature events (CHTE) averaged over China under RCP4.5 scenario
| |
图1 中国群发性高温事件在各月发生的分布比例
Fig. 1 Relative frequency of the cluster high temperature events (CHTE) for each month averaged over China
图1 中国群发性高温事件在各月发生的分布比例
Fig. 1 Relative frequency of the cluster high temperature events (CHTE) for each month averaged over China
图2 全球升温1.5℃和2℃下中国群发性高温事件各特征量年均值较基准期变化的空间分布
Fig. 2 MME projected changes (relative to 1986-2005) of annual mean frequency (a, b), duration (c, d), and cumulative intensity (e, f) of the CHTE during the crossing times of global warming of 1.5℃ and 2℃
图2 全球升温1.5℃和2℃下中国群发性高温事件各特征量年均值较基准期变化的空间分布
Fig. 2 MME projected changes (relative to 1986-2005) of annual mean frequency (a, b), duration (c, d), and cumulative intensity (e, f) of the CHTE during the crossing times of global warming of 1.5℃ and 2℃
图3 模式集合预估两种升温情景下中国群发性高温事件年均空间差值分布（1.5℃减2℃）
Fig. 3 MME projected changes of annual mean frequency (a), duration (b), and cumulative intensity (c) of the CHTEs in 1.5℃ compared with 2℃ warmer future
图3 模式集合预估两种升温情景下中国群发性高温事件年均空间差值分布（1.5℃减2℃）
Fig. 3 MME projected changes of annual mean frequency (a), duration (b), and cumulative intensity (c) of the CHTEs in 1.5℃ compared with 2℃ warmer future
图4 1.5℃和2℃升温阈值下中国群发性高温事件各指标频率占比分布（较基准期的变化）
Fig. 4 MME projected changes of relative frequency distributions of each CHTE metrics in response to global warming of 1.5℃ and 2℃ (relative to 1986-2005)
图4 1.5℃和2℃升温阈值下中国群发性高温事件各指标频率占比分布（较基准期的变化）
Fig. 4 MME projected changes of relative frequency distributions of each CHTE metrics in response to global warming of 1.5℃ and 2℃ (relative to 1986-2005)
表3 中国群发性高温事件各指标在各个时段的平均值及其变化
Table 3 MME simulated mean value for each CHTE metrics
 |
表3 中国群发性高温事件各指标在各个时段的平均值及其变化
Table 3 MME simulated mean value for each CHTE metrics
| |
图5 全国和城市人口及CHTE人口暴露度相对基准期的变化 注：图中两条竖虚线分别代表MME模拟的达到1.5℃和2℃升温阈值的时间。
Fig. 5 The relative changes in total population (a), the population affected by the CHTEs (b), CHTE cumulative intensity population exposure (c), and CHTE comprehensive intensity population exposure (d) averaged over China and urban areas relative to 1986-2005
图5 全国和城市人口及CHTE人口暴露度相对基准期的变化 注：图中两条竖虚线分别代表MME模拟的达到1.5℃和2℃升温阈值的时间。
Fig. 5 The relative changes in total population (a), the population affected by the CHTEs (b), CHTE cumulative intensity population exposure (c), and CHTE comprehensive intensity population exposure (d) averaged over China and urban areas relative to 1986-2005
表4 中国群发性高温事件人口暴露度相对于基准期的变化
Table 4 The changes of population exposure to the CHTEs over China relative to 1986-2005
 |
表4 中国群发性高温事件人口暴露度相对于基准期的变化
Table 4 The changes of population exposure to the CHTEs over China relative to 1986-2005
| |
图6 模式集合预估中国群发性高温事件年均影响人口相对于基准期变化的空间分布 注：图中显示的是每个0.25°×0.25°格点上的影响人口变化。
Fig. 6 MME projected changes of annual mean population affected by the CHTEs relative to reference period at the times of global warming of 1.5℃ and 2.0℃. (Data shown are the changes in affected population at each 0.25° ×0.25° grid point)
图6 模式集合预估中国群发性高温事件年均影响人口相对于基准期变化的空间分布 注：图中显示的是每个0.25°×0.25°格点上的影响人口变化。
Fig. 6 MME projected changes of annual mean population affected by the CHTEs relative to reference period at the times of global warming of 1.5℃ and 2.0℃. (Data shown are the changes in affected population at each 0.25° ×0.25° grid point)
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| [1] | 韩振宇, 徐影, 吴佳, 石英. 多区域气候模式集合对中国径流深的模拟评估和未来变化预估[J]. 气候变化研究进展, 2022, 18(3): 305-318. |
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