6.25 km高分辨率降尺度数据对21世纪长江经济带极端气候事件及其风险的集合预估

李柔珂; 韩振宇; 徐影; 石英; 吴佳

doi:10.3878/j.issn.1006-9585.2022.21140

6.25 km高分辨率降尺度数据对21世纪长江经济带极端气候事件及其风险的集合预估

doi: 10.3878/j.issn.1006-9585.2022.21140

李柔珂^{1, 2, 3,},
韩振宇²,
徐影^2, ,,
石英²,
吴佳²

1.
中国科学院地球环境研究所黄土与第四纪地质国家重点实验室，西安 710061
2.
国家气候中心，北京 100081
3.
中国科学院大学，北京 100049

基金项目: 国家重点研发计划2020YFA0608201、2018YFC1509002，国家自然科学基金项目 41991254、4214007，中国长江三峡集团有限公司项目0704181

详细信息

作者简介:
李柔珂，女，1989年出生，博士研究生，助理研究员，主要从事气候变化预估研究。E-mail: lirk@cma.gov.cn

通讯作者:
徐影，E-mail: xuying@cma.cn

中图分类号: P467
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出版历程
- 收稿日期: 2021-08-18
- 网络出版日期: 2022-02-18
- 刊出日期: 2023-01-25

An Ensemble Projection of Extreme Climate Events and Related Risk Exposures in the 21st Century in the Yangtze River Economic Zone Using High-Resolution (6.25 km) Downscaling Datasets

Rouke LI^{1, 2, 3
,},
Zhenyu HAN²,
Ying XU^{2
, ,},
Ying SHI²,
Jia WU²

1.
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061
2.
National Climate Center, China Meteorological Administration, Beijing 100081
3.
University of Chinese Academy of Sciences, Beijing 100049

Funds: National Key Research and Development Program of China (Grants 2020YFA0608201 and 2018YFC1509002), National Natural Science Foundation of China (Grants 41991254 and 4214007), China Three Gorges Corporation (Grant 0704081)

摘要

摘要: 使用基于动力降尺度和统计降尺度方法得到的RCP4.5情景下的6.25 km高分辨率联合降尺度预估数据集，对长江经济带未来极端气候事件及其造成的风险展开评估和预估。结果表明：降尺度预估数据能较好的再现各极端温度指数和大部分极端降水指数的空间分布，但一些极端降水指数的偏差略大。未来长江经济带极端热事件将增加，冷事件减少；长江中游东部和下游的极端降水事件将增加，上游地区东南部发生干旱事件的可能性大。长江经济带以及上游、中游和下游3个分区的高温事件和强降水事件的国内生产总值（GDP）暴露度都将增加；人口暴露度呈先增后降的变化趋势。高温事件的GDP暴露度的分布因子和非线性因子的贡献同样重要，人口暴露度中分布因子的影响更大；强降水事件的暴露度主要取决于GDP或人口分布因子。
- 极端气候事件 /
- 暴露度 /
- 长江经济带
Abstract: The 6.25 km high-resolution downscaling projection datasets under the RCP4.5 scenario based on a combined dynamical and statistical downscaling method are used to evaluate and project the future extreme climatic events and the associated risks in the Yangtze River Economic Zone (YREZ). The results show that the datasets can well reproduce the spatial distribution of all temperature extremes and most precipitation extremes, providing a reliable forecasting capability. However, Slightly larger deviations in some extreme precipitation indices The heat events will increase, while the cold events will decrease substantially in the YREZ. Extreme precipitation is projected to increase in the lower and eastern middle reaches and decrease in the east and south upper reaches. The gross domestic product (GDP) exposure to heat events and heavy rainfall showed an increasing trend in the 21st century in YREZ, most significantly in the lower reaches. Meanwhile, population exposure increased and then decreased in the 21st century. The contribution of the distribution factor and the non-linear factor are equally important for GDP exposure to high events, while the distribution factor having a greater impact in population exposure. The GDP/population exposure to heavy rainfall mainly depends on its distribution factor.
- Extreme climate events /
- Exposures /
- Yangtze River economic zone

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图 1 长江经济带及其上游、中游、下游的地形分布（单位：m）

Figure 1. Elevation (m) of the upper, middle, and lower reaches of the Yangtze River Economic Zone (YREZ)

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图 2 2008～2017年长江经济带（a）极端气温指数和（b）极端降水指数的多变量泰勒图

Figure 2. Multivariable Taylor diagrams of the (a) temperature extremes and (b) precipitation extremes in the YREZ during 2008–2017

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图 3 2008～2017年降尺度结果对极端指数的模拟误差（相对于观测）：（a）HD（单位：d）；（b）FD（单位：d）；（c）TXx（单位：°C）；（d）TNn（单位：°C）；（e）RX5day（单位：mm）；（f）R20mm（单位：d）；（g）SDII（单位：mm/d）；（h）PRCPTOT（单位：mm）。AVE为YREZ偏差的平均值，黑色十字标记表示在95%置信水平下误差是显著的

Figure 3. Biases of the downscaled dataset over the YREZ for extremes indices during 2008–2017 (relative to observation): (a) HD (units: d); (b) FD (units: d); (c) TXx (units:°C); (d) TNn (units:°C); (e) RX5day (units: mm); (f) R20mm (units: d); (g) SDII (units: mm/d); (h) PRCPTOT (units: mm). The biases averaged over the YREZ are listed as AVE in each panel. The black cross indicates the bias that is significant at the 95% confidence level

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图 4 21世纪3个时段2026～2045年（第一列）、2046～2065年（第二列）、2080～2099年（第三列）长江经济带极端温度指数的变化（相对于1986～2005年）：（a–c）HT；（d–f）FD；（g–i）TXx；（j–l）TNn

Figure 4. Projected changes in extreme temperature indices (relative to 1986–2005) during 2026–2045 (the first column), 2046–2065 (the second column), and 2080–2099 (the third column) across the YREZ: (a–c) HT; (d–f) FD; (g–i) TXx; (j–l) TNn

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图 5 21世纪3个时段2026～2045年（第一列）、2046～2065年（第二列）、2080～2099年（第三列）长江经济带极端降水指数的变化（相对于1986～2005年）：（a－c）RX5day（单位：mm）；（d－f）R20mm（单位：d）；（g－i）SDII（单位：mm/d）；（j－l）PRCPTOT（单位：mm）

Figure 5. Projected changes in extreme precipitation indices (relative to 1986–2005) during 2026–2045 (the first column), 2046–2065 (the second column), and 2080–2099 (the third column) across the YREZ: (a–c) RX5day (units: mm); (d–f) R20mm (units: d); (g–i) SDI (units: mm/d); (j–l) PRCPTOT (units: mm)

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图 6 21世纪长江经济带及长江上游、中游和下游9年平滑的（a）GDP（单位：10⁹元）和（b）人口（POP，单位：10³人）时间序列（不同颜色表示不同分区）

Figure 6. Nine-year smoothed time series of changes in (a) GDP (units: 10⁹ CNY) and (b) population (POP, units: 10³ people) over the YREZ and its upper, middle, and lower reaches during the 21st century. The different colored lines indicate different regions

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图 7 参照时段（1986～2005年）和21世纪3个时段的长江经济带高温事件（a–d）GDP暴露度（单位：10⁸元）和（e–h）人口暴露度（单位：100人）的空间分布：（a、e）1986～2005年；（b、f）2026～2045年；（c、g）2046～2065年；（d、h）2080～2099年

Figure 7. Present period (1986–2005) and projected changes during three periods of the 21st century in (a–d) GDP exposures (units: 10⁸ CNY), (e–h) population exposures (units: 100) to heat events across the YREZ: (a, e) 1986–2005; (b, f)2026–2045; (c, g) 2046–2065; (d, h) 2080–2099

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图 8 同图7，但为强降水事件GDP和人口暴露度

Figure 8. Same as in Fig. 7 but for GDP exposure and population exposure to heavy rainfall events

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图 9 长江经济带和长江上游、中游和下游（a、b）高温事件和（c、d）强降水事件暴露度在参照时段（1986～2005）和21世纪的不确定性分析（柱状图表示多模式集合结果，黑色线条表示5个模式的不确定性范围）：（a、c）GDP暴露度（单位：10⁸元）；（b、d）人口暴露度（单位：100人）

Figure 9. Present period (1986–2005) and projected changes during the 21st century in exposures to (a, b) heat events and (c, d) heavy rainfall over the YREZ and the upper, middle, and lower reaches of Yangtze River (the black bars indicate the uncertainty ranges of the five simulations): (a, c) GDP exposure (units: 10⁸ CNY); (b, d) population exposure (units: 100 people)

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表 1 极端事件指数定义

Table 1. Definition of extreme climate indices

指数	定义	单位
日最高气温最高值（TXx）	每年日最高气温的最大值	°C
日最低气温最低值（TNn）	每年日最低气温的最小值	°C
高温日数（HD）	每年日最高气温大于35°C的全部天数	d
霜冻日数（FD）	每年日最低气温小于0°C的全部天数	d
5日最大降水量（RX5day）	每年最大的连续5 d降水量	mm
湿日总降水量（PRCPTOT）	每年所有湿日(日降水量大于1 mm)降水量的总和	mm
大雨日数（R20mm）	每年日降水量大于等于20 mm的天数	d
降水强度（SDII）	年湿日总降水量与湿日日数的比值	mm/d

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表 2 21世纪长江经济带及其上游、中游和下游的极端温度指数的变化（21世纪近期/中期/末期，相对于1986～2005年）

Table 2. Projected changes in the extreme temperature indices averaged over the YREZ and its upper, middle, and lower reaches in the 21st century (near term/ mid-term/long term; relative to 1986－2005)

	21世纪近期/中期/末期极端温度指数的变化
	HT/d	FD/d	TXx/°C	TNn/°C
长江经济带上游	3.2/5.5/8.0	−8.7/−12.2/−15.9	1.2/2.0/2.6	1.3/1.8/2.5
长江经济带中游	11.6/17.6/22.6	−8.1/−11.5/−15.8	1.1/1.8/2.5	1.1/1.4/2.2
长江经济带下游	8.8/14.2/18.3	−8.4/−13.1/−17.1	1.2/1.9/2.5	1.2/1.8/2.5
长江经济带	6.5/10.4/13.9	−8.5/−12.2/−16.1	1.2/2.0/2.6	1.2/1.7/2.4

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表 3 21世纪长江经济带及其上游、中游和下游的极端降水指数的变化（21世纪近期/中期/末期，相对于1986～2005年）

Table 3. Projected changes in the extreme precipitation indices averaged over the YREZ and its upper, middle, and lower reaches and in the 21st century (near term/ mid-term/long term; relative to 1986－2005)

	21世纪近期/中期/末期极端降水指数的变化
	RX5day/mm	R20mm/d	SDII/mm d⁻¹	PRCPTOT/mm
长江上游	6.0/7.1/7.0	0.5/0.4/0.3	0.3/0.2/0.3	24.1/23.2/13.3
长江中游	8.3/9.2/16.0	0.3/0.6/1.0	0.2/0.4/0.6	19.4/35.9/56.9
长江下游	14.0/23.4/30.9	0.6/0.5/1.2	0.4/0.6/0.9	48.4/53.5/92.6
长江经济带	8.0/10.6/13.7	0.5/0.5/0.7	0.3/0.3/0.5	27.1/32.0/39.3

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表 4 21世纪长江经济带及其上游、中游和下游高温事件GDP暴露度影响因子的相对贡献

Table 4. Relative contributions to the change in exposures to heat events over the YREZ and its upper, middle, and lower reaches during the 21st century

	21世纪近期/中期/末期高温事件GDP暴露度相对贡献
	GDP分布因子	GDP数量因子	气候因子	非线性因子
长江经济带上游	59.2%/50.6%/40.0%	8.4%/5.6%/6.3%	3.1%/2.7%/3.5%	29.3%/41.1%/50.1%
长江经济带中游	45.6%/42.2%/33.6%	16.8%/11.4%/14.2%	3.5%/2.8%/3.4%	34.1%/43.6%/48.9%
长江经济带下游	46.8%/41.9%/33.8%	17.7%/12.2%/13.9%	3.3%/2.7%/3.2%	32.3%/43.2%/43.2%
长江经济带	52.0%/46.0%/37.8%	12.2%/8.2%/9.7%	3.3%/2.8%/3.4%	32.5%/43.0%/49.2%
注：黑体表示贡献度占主导地位的影响因子，下同。

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表 5 21世纪长江经济带和长江上游、中游和下游高温事件人口暴露度影响因子的相对贡献

Table 5. Relative contributions to the change in population exposures to heat events over the YREZ and its the upper, middle, and lower reaches during the 21st century

	21世纪近期/中期/末期高温事件人口暴露度相对贡献
	人口分布因子	人口数量因子	气候因子	非线性因子
长江经济带上游	80.6%/68.0%/74.4%	0.5%/−0.6%/−1.5%	−11.7%/−6.8%/−23.6%	30.6%/39.4%/50.8%
长江经济带中游	72.0%/62.3%/74.9%	1.2%/−0.7%/−2.6%	−13.1%/−11.4%/−42.0%	39.9%/49.7%/69.7%
长江经济带下游	63.6%/49.8%/48.6%	1.3%/0.4%/−1.2%	1.5%/8.6%/4.7%	33.6%/41.2%/47.9%
长江经济带	68.6%/55.2%/58.0%	0.8%/-0.2%/−1.3%	−4.4%/2.0%/−10.1%	35.0%/43.1%/53.4%

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表 6 同表4但为强降水事件GDP暴露度影响因子的相对贡献

Table 6. Same as Table 4, but for heavy rainfall events

	21世纪近期/中期/末期强降水事件GDP暴露度相对贡献
	GDP分布因子	GDP数量因子	气候因子	非线性因子
长江经济带上游	73.0%/78.9%/72.2%	21.8%/17.0%/24.9%	0.5%/0.3%/0.2%	4.7%/3.8%/2.8%
长江经济带中游	65.6%/72.0%/59.5%	32.1%/25.8%/33.0%	0.2%/0.2%/0.5%	2.2%/2.0%/7.0%
长江经济带下游	66.0%/67.9%/59.2%	27.8%/21.2%/26.6%	0.6%/0.6%/0.9%	5.6%/10.3%/13.4%
长江经济带	74.6%/76.6%/68.8%	20.3%/15.3%/19.7%	0.5%/0.5%/0.7%	4.60%/7.6%/10.8%

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表 7 同表5，但为强降水事件人口暴露度影响因子的相对贡献

Table 7. Same as Table 5, but for heavy rainfall events

	21世纪近期/中期/末期强降水事件人口暴露度相对贡献
	人口分布因子	人口数量因子	气候因子	非线性因子
长江经济带上游	99.0%/99.5%/96.2%	0.3%/0.1%/4.4%	−3.9%/−2.7%/−2.0%	4.7%/3.1%/1.4%
长江经济带中游	98.5%/98.9%/96.5%	0.5%/−0.0%/4.2%	−1.0%/−0.1%/−7.7%	2.0%/1.3%/6.9%
长江经济带下游	96.7%/94.3%/93.6%	1.1%/0.2%/1.2%	−2.8%/−4.0%/−9.4%	5.0%/9.5%/14.6%
长江经济带	97.8%/95.9%/94.8%	0.4%/−0.0%/2.1%	−2.5%/−3.1%/−8.1%	4.3%/7.2%/11.2%

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