未来情景下中国高温的人口暴露度变化及影响因素研究

doi:10.11821/dlxb201607008

摘要/Abstract

摘要：

基于RCP 8.5气候情景下21个高分辨率全球气候模式的日最高气温数据和A2r社会经济发展情景下的人口数据,以高温日数和人口数量的乘积构建高温的人口暴露度指标,采用多个气候模式集合平均的方法从网格单元尺度分析未来不同时段中国高温和强危害性高温的人口暴露度变化,并从全国和气象地理分区两种空间尺度研究人口暴露度变化的影响因素。研究表明：未来情景下,中国高温的人口暴露度明显增加,2021-2040年、2041-2060年、2061-2080年和2081-2100年相比基准时段1981-2010年分别增加了1.3、2.0、3.6和5.9倍,强危害性高温的人口暴露度增加更为显著,相比基准时段分别增加了2.0、8.3、24.2和82.7倍。高温的人口暴露度在华北、黄淮、华南、江南、江淮、西南和江汉地区增加较为明显,其中华北、黄淮、华南和江南最为显著;强危害性高温的人口暴露度在华北、黄淮、江南、江淮、西南和江汉等区域增加较为明显,其中华北、黄淮、江南和江淮最为显著;未来情景下人口暴露度的变化主要受气候因子的影响,其次受人口和气候因子的共同影响,单独人口因子的影响很小。全国尺度上,气候因子对未来不同时段人口暴露度变化的影响逐渐减弱,贡献率由70.0%左右逐渐减至60.0%左右。人口和气候因子的共同作用逐渐增强,贡献率由20.0%左右逐渐增至40.0%左右。

关键词: 未来情景, 人口暴露度, 高温, 强危害性高温, 影响因子, 中国

Abstract:

Population exposure to high temperature (extremely high temperature) is represented by the multiplication of the population in each grid cell and the projected mean annual number of hot days with daily maximum temperature above 35℃ (40℃) for each corresponding grid cell. Based on daily maximum temperature data from 21 global climate models under the RCP8.5 scenario and population projection data under the A2r socio-economic scenario, population exposures for four future periods (2021-2040, 2041-2060, 2060-2081 and 2081-2100) in China were projected at the grid cell level. The ensemble mean method was used to calculate the annual number of hot days. The relative importance of population and climate as drives of exposures was evaluated at the national level and the meteorological geographical division level. Compared with the population exposure for the 1981-2010 base period, population exposure to high temperature (≥ 35℃) over China for four future periods will increase by 1.3, 2.0, 3.6 and 5.9 times respectively and population exposure to extremely high temperature (≥ 40℃) will increase by 2.0, 8.3, 24.2 and 82.7 times respectively. Population exposure to high temperature will increase significantly in Jianghuai region, Southwest China and Jianghan region, especially in North China, Huanghuai region, South China, Jiangnan region. Population exposure to extremely high temperature will increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai region, Jiangnan region and Jianghuai region. Climate factors are the most important driver of exposures for Huanghuai region, Jianghuai region, Jianghan region, Jiangnan region, South China and Southwest China, followed by the interact effect of population and climate. At the national level, climate factor is also the most important driver, followed by the interact effect of population and climate. The contribution rate of climate to national-level projected change in exposure will decrease gradually from about 70% to about 60% and the contribution rate of concurrent changes in population and climate will increase gradually from about 20% to about 40% over the four future periods.

Key words: future scenario, population exposure, high temperature, extremely high temperature, influencing factors, China

黄大鹏, 张蕾, 高歌. 未来情景下中国高温的人口暴露度变化及影响因素研究[J]. 地理学报, 2016, 71(7): 1189-1200.

Dapeng HUANG, Lei ZHANG, Ge GAO. Changes in population exposure to high temperature under a future scenario in China and its influencing factors[J]. Acta Geographica Sinica, 2016, 71(7): 1189-1200.

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气候模式名称/所属国家
ACCESS1-0 /澳大利亚	CSIRO-MK3-6-0 /澳大利亚	MIROC-ESM /日本
BCC-CSM1-1 /中国	GFDL-CM3 /美国	MIROC-ESM-CHEM /日本
BNU-ESM /中国	GFDL-ESM2G /美国	MIROC5 /日本
CanESM2 /加拿大	GFDL-ESM2M /美国	MPI-ESM-LR /德国
CCSM4 /美国	INMCM4 /俄罗斯	MPI-ESM-MR /德国
CESM1-BGC /美国	IPSL-CM5A-LR /法国	MRI-CGCM3 /日本
CNRM-CM5 /法国	IPSL-CM5A-MR /法国	NorESM1-M /挪威

暴露度变化	高温(≥ 35℃)				强危害性高温(≥ 40℃)
暴露度变化	人口因子(%)		气候因子(%)	人口和气候因子(%)	人口因子(%)	气候因子(%)	人口和气候因子(%)
2021-2040年较1981-2010年	13.1	67.6	19.4		7.7	68.9	23.4
2041-2060年较2021-2040年	2.9	67.6	29.5		0.9	67.1	32.1
2061-2080年较2041-2060年	1.5	66.3	32.2		0.3	65.4	34.4
2081-2100年较2061-2080年	1.8	58.4	39.9		0.1	59.9	40.0

暴露度变化	气象地理分区	高温(≥ 35℃)				强危害性高温(≥ 40℃)
暴露度变化	气象地理分区	人口因子(%)		气候因子 (%)	人口和气候因子(%)	人口因子 (%)	气候因子 (%)	人口和气候因子(%)
2021-2040年较1981-2010年增幅	华北	30.1	40.0	29.9		19.0	45.6	35.5
	黄淮	13.5	63.4	23.1		8.6	66.9	24.5
	江淮	11.1	68.3	20.6		3.4	75.7	20.9
	江汉	9.0	72.1	18.9		2.4	77.8	19.8
	江南	9.7	74.6	15.7		1.9	78.6	19.5
	华南	3.9	78.9	17.2		-12.7	152.6	-39.9
	西南	2.5	92.9	4.6		0.3	96.4	0.3
2041-2060年较2021-2040年增幅	华北	8.7	39.7	51.7		2.6	43.5	53.9
	黄淮	2.8	62.3	34.9		0.5	65.8	33.7
	江淮	2.0	67.9	30.1		0.3	71.7	28.0
	江汉	1.7	73.0	25.3		0.1	74.0	25.9
	江南	1.3	77.7	21.1		0.1	76.0	23.9
	华南	0.3	76.2	23.5		-0.4	125.1	-24.7
	西南	-2.5	106.5	-4.0		-0.4	107.6	-7.1
2061-2080年较2041-2060年增幅	华北	4.7	36.6	58.7		0.7	40.0	59.2
	黄淮	14.6	58.8	39.8		0.1	63.2	36.6
	江淮	1.1	64.3	34.6		0.1	67.6	32.3
	江汉	1.1	71.3	27.6		0.0	71.2	28.8
	江南	1.0	77.2	21.8		0.1	75.4	24.6
	华南	0.2	71.7	28.1		0.0	92.8	7.2
	西南	-0.9	108.0	-7.0		-0.1	106.7	-6.6
2081-2100年较2061-2080年增幅	华北	3.6	31.8	64.6		0.3	35.3	64.4
	黄淮	1.7	48.7	49.6		0.1	56.2	43.7
	江淮	1.5	54.3	44.2		0.1	61.3	38.6
	江汉	2.0	61.2	36.9		0.0	65.5	34.5
	江南	2.1	66.4	31.5		0.1	69.0	30.9
	华南	0.4	62.1	37.6		0.0	80.9	19.1
	西南	0.4	99.9	-0.3		0.0	100.6	-0.6