Threshold of climate extremes that impact vegetation productivity over the Tibetan Plateau

Vegetation growth is adversely impacted by multiple climate extremes related to the water and thermal stress over the Tibetan Plateau(TP).However,it remains unknown at which stress level these climate extremes can trigger the abrupt shifts of vegetation response to climate extremes and result in the maximum vegetation response across TP.To fill this knowledge gap,we combined the hydrometeorological data and the satellite-derived vegetation index to detect two critical thresholds that determine the response of vegetation productivity to droughts,high-temperature extremes,and low-temperature extremes,respectively,during 2001-2018.Our results show that the response of vegetation productivity to droughts rapidly increases once crossing -1.41±0.6 standard deviation(σ)below the normal conditions of soil moisture.When crossing-2.98σ±0.9σ,vegetation productivity is maximum damaged by droughts.High-temperature extremes,which have the two thresholds of 1.34σ±0.4σand 2.31σ±0.4σover TP,are suggested to trigger the strong response of vegetation productivity at a milder stress level than low-temperature extremes(two thresholds:-1.44σ±0.5σand-2.53σ±0.8σ).Moreover,we found the compounded effects of soil moisture deficit in reducing the threshold values of both high-and low-temperature extremes.Based on the derived thresholds of climate extremes that impact vegetation productivity,Earth System Models project that southwestern TP and part of the northeastern TP will become the hotspots with a high exposure risk to climate extremes by 2100.This study deciphers the high-impact extreme climates using two important thresholds across TP,which advances the understanding of the vegetation response to different climate extremes and provides a paradigm for assessing the impacts of climate extremes on regional ecosystems.

Uncertainty in Projection of Climate Extremes:A Comparison of CMIP5 and CMIP6

Climate projections by global climate models(GCMs)are subject to considerable and multi-source uncertainties.This study aims to compare the uncertainty in projection of precipitation and temperature extremes between Coupled Model Intercomparison Project(CMIP)phase 5(CMIP5)and phase 6(CMIP6),using 24 GCMs forced by 3 emission scenarios in each phase of CMIP.In this study,the total uncertainty(T)of climate projections is decomposed into the greenhouse gas emission scenario uncertainty(S,mean inter-scenario variance of the signals over all the models),GCM uncertainty(M,mean inter-model variance of signals over all emission scenarios),and internal climate variability uncertainty(V,variance in noises over all models,emission scenarios,and projection lead times);namely,T=S+M+V.The results of analysis demonstrate that the magnitudes of S,M,and T present similarly increasing trends over the 21 st century.The magnitudes of S,M,V,and T in CMIP6 are 0.94-0.96,1.38-2.07,1.04-1.69,and 1.20-1.93 times as high as those in CMIP5.Both CMIP5 and CMIP6 exhibit similar spatial variation patterns of uncertainties and similar ranks of contributions from different sources of uncertainties.The uncertainty for precipitation is lower in midlatitudes and parts of the equatorial region,but higher in low latitudes and the polar region.The uncertainty for temperature is higher over land areas than oceans,and higher in the Northern Hemisphere than the Southern Hemisphere.For precipitation,T is mainly determined by M and V in the early 21 st century,by M and S at the end of the 21 st century;and the turning point will appear in the 2070 s.For temperature,T is dominated by M in the early 21 st century,and by S at the end of the 21 st century,with the turning point occuring in the 2060 s.The relative contributions of S to T in CMIP6(12.5%-14.3%for precipitation and 31.6%-36.2%for temperature)are lower than those in CMIP5(15.1%-17.5%for precipitation and 38.6%-43.8%for temperature).By contrast,the relative contributions of M in CMIP6(50.6%-59.8%for precipitation and 59.4%-60.3%for temperature)are higher than those in CMIP5(47.5%-57.9%for precipitation and 51.7%-53.6%for temperature).The higher magnitude and relative contributions of M in CMIP6 indicate larger difference among projections of various GCMs.Therefore,more GCMs are needed to ensure the robustness of climate projections.

Multi-model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part I: Precipitation

Potential changes in precipitation extremes in July–August over China in response to CO 2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and the 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. Evaluation of the models’ performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50%. The spread among the models over the Tibetan Plateau is ～2–3 times larger than that over the other areas. Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the 1pctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China, which follows the Clausius–Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.

Multi-Model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part II: Temperature

This is the second part of the authors’ analysis on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. The study focuses on the potential changes of July–August temperature extremes over China. The pattern correlation coefficients of the simulated temperature with the observations are 0.6–0.9, which are higher than the results for precipitation. However, most models have cold bias compared to observation, with a larger cold bias over western China （5°C） than over eastern China （2°C）. The multi-model ensemble （MME） exhibits a significant increase of temperature under the 1pctto2x scenario. The amplitude of the MME warming shows a northwest–southeast decreasing gradient. The warming spread among the models （～1°C– 2°C） is less than MME warming （～2°C–4°C）, indicating a relatively robust temperature change under CO 2 doubling. Further analysis of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） simulations suggests that the warming pattern may be related to heat transport by summer monsoons. The contrast of cloud effects also has contributions. The different vertical structures of warming over northwestern China and southeastern China may be attributed to the different natures of vertical circulations. The deep, moist convection over southeastern China is an effective mechanism for ＂transporting＂ the warming upward, leading to more upper-level warming. In northwestern China, the warming is more surface-orientated, possibly due to the shallow, dry convection.

Extreme climate projections over the transboundary Koshi River Basin using a high resolution regional climate model

The high-resolution climate model Providing REgional Climates for Impacts Studies (PRECIS) was used to project the changes in futureextreme precipitation and temperature over the Koshi River Basin for use in impact assessments. Three outputs of the Quantifying Uncertaintiesin Model Prediction (QUMP) simulations using the Hadley Centre Couple Model (HadCM3) based on the IPCC SRES A1B emission scenario were used to project the future climate. The projections were analysed for three time slices, 2011e2040 (near future), 2041e2070 (mid-century), and 2071e2098 (distant future). The results show an increase in the future frequency and intensity of climate extremes events such as dry days, consecutive dry days, and very wet days (95th percentile), with greater increases over the southern plains than in the mountainous area to the north. A significant decrease in moderate rainfall days (75th percentile) is projected over the middle (high) mountain and trans-Himalaya areas. Increases are projected in both the extreme maximum and extreme minimum temperature, with a slightly higher rate in minimum temperature. The number of warm days is projected to increase throughout the basin, with more rapid rates in the trans-Himalayan and middle mountain areas than in the plains. Warm nights are also projected to increase, especially in the southern plains. A decrease is projected in cold days and cold nights indicating overall warming throughout the basin.

Multimodel ensemble projection of photovoltaic power potential in China by the 2060s

为了实现能源转型的目标,中国对太阳能的需求一直在极速增长.然而,太阳能发电潜力受到天气条件的影响并预期在气候变暖背景下发生改变.本文中,作者利用第六次国际耦合模式比较计划(CMIP6)24个气候模式的气象变量以及4个不同形式的光伏模型,预估了在2060年代低排放或高排放情况下中国的光伏发电潜力.多模式集合平均光伏功率在2004-2014年为277.2KWhm-2yr-1,并呈现出从西到东的下降趋势.到2054-2064年,在低排放情景下,全国平均光伏发电潜力将增加2.29%,而在高排放情景下则减少0.43%.低排放情景的排放控制大大增强了地表太阳辐射,促进了东部的光伏发电.相反,在高排放情景下,强烈的变暖对光伏发电产生了抑制作用.极端暖事件使光伏发电潜力在低排放情景下降低0.28%,而高排放情景下降低0.44%,分别相当于当代损失量的两倍和三倍.预估表明排放控制带来的清洁空气和适度变暖对中国未来的太阳能利用是有益的.

Bayesian multi-model projections of extreme hydroclimatic events under RCPs scenarios

一个贝叶斯的多模型推理框架被用来在中国在四主要的河盆在极端 hydroclimatic 事件的出现估计变化(即， Liaohe 河盆，黄河盆，长江盆，和珀尔河盆)在 RCP2.6 下面， RCP4.5 ，并且用多重全球气候的 RCP8.5 情形从 IPCC 为设计建模第五份评价报告。结果在 2006-2099 投射了更多的夏日和更少霜天。整体预言证明珍珠河盆被投射与 16.3， 38.0，和 73.0 的增加的趋势比另外的盆经历更多的夏日 ? d 每为 RCP2.6， RCP4.5 和 RCP8.5 的 100 年分别地。Liaohe 河盆和黄河盆被预报变得与夏日和湿天的增加的同现更湿、更温暖。很重的降水天(R20，每日的降水 20 ? 公里) 被投射在所有盆增加。在长江盆的 R20 被投射让最高的变化在 1.8， 2.5，和 3.8 的 2006-2099 评价 ? d 每为 RCP2.6， RCP4.5 和 RCP8.5 的 100 年分别地。

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

Projected increases in population exposure of daily climate extremes in eastern China by 2050

Climate extremes pose severe threats to human health,economic stability and environmental sustainability,especially in densely populated areas.It is generally believed that global warming drives increase in frequency,intensity and duration of climate extremes,and socioeconomic exposure plays a dominant role in climate impacts.In order to promote climate risk governance at regional level,the historical and projected trends in the population exposure to climate extremes are quantified in eastern China using downscaled climate simulations and population growth scenarios.The frequency of temperature extremes(tx35days)is projected to more than double by 2050 in nearly half of prefecture-level cities in eastern China,leading to an 81.8%increment of total exposure under SSP2-4.5 scenario.The increasing trend is also detectable in the frequency of precipitation extremes(r20mm)in eastern China,and the exposure increment is projected to be 22.9%by 2050,with a near equivalent contributions of both climate change and population growth.Spatially,temperature exposure mainly grows in southern Hebei,western Shandong and inland Guangdong provinces,while precipitation exposure raises principally in southeast coastal areas of China.Based on the historical baseline and projected amplification of population exposure,we identify some hotspot cities such as Guangzhou,Shanghai,Dongguan and Hangzhou that response to climate change dramatically and confront greater potential risk of climate extremes in the coming future.

Assessment of Central Asian heat extremes by statistical downscaling:Validation and future projection for 2015-2100

Increasing heatwaves and extreme temperatures have recently been observed across Central Asia(CA).Accurately assessing and projecting the changing climate extremes at the local(station)scale required for climate risk management are therefore highly important.However,global and regional climate models often fail to represent the statistical distributions of observed daily extreme variables and hence extremes in complex terrain.In this work,we developed a statistical downscaling(SD)model to project summer daily maximum temperature(Tmax)and heatwave indices for 65 meteorological stations in CA toward 2100.The SD model involves first-order autoregression and multiple linear regression using large-scale Tmax and circulation indices(Cis)as predictors,and the model is cross-validated against historical observations.The local Tmax and heatwave indices are then projected for 2015-2100 driven by the output of a global climate model(CNRM-CM6-1)under four Shared Socioeconomic Pathways(SSP126,SSP245,SSP370,and SSP585).The application of the SD model significantly improves forecasting of the probability distribution(10th/90th percentiles)of Tmax at stations,particularly across mountainous regions.The model also captures interannual variability and the long-term trend in Tmax,consistent with synoptic-scale inputs.SD projections demonstrate strong warming trends of summer Tmax in CA toward 2100 with rates between 0.35-0.64℃ per decade based on the SSP245 and SSP370 seenarios.Consequently,heatwave occurrence is projected to rise by 1.0-5.0 and 2.0-7.0 d per decade under the SSP245 and SSP370 scenarios,respectively,by 2100.Duration,intensity,and amplitude of heatwaves rise at greater rates under higher-emission scenarios,particularly in southeastern CA.The proposed SD model serves as a useful tool for assessing local climate extremes,which are needed for regional risk management and policymaking for adaption to climate change.

气候变化与碳中和

工业化以来化石燃料的广泛使用使大气中的二氧化碳浓度急剧升高,造成全球气候变暖、极端天气气候事件频发。为有效应对和减缓气候变化,国际社会通过《巴黎协定》设定了2℃和1.5℃温控目标,由此提出了碳中和的概念。文章介绍了全球变暖的基本事实、人类碳排放对工业化以来全球变暖的作用,归纳了关于未来气候变化的主要结果,阐释了1.5/2℃温升阈值与碳中和的关系,概述了国际社会为有效应对全球变暖而在减少碳排放方面的努力。

关于亚洲中高纬区极端气候的研究——国家自然科学基金重大项目内容及阶段进展简介

近年来极端气候的发生频率和强度有明显增强的趋势,在我国尤为突出(Yin et al., 2023b),造成了越来越大的对经济社会和人民生命安全的威胁。我国科学家也越来越关注我国及东亚区域的极端气候问题。对比而言,亚洲中高纬区虽然也是气候变化的高敏感区,受到的关注却相当少,可能是源于气候资料的相对欠缺,也可能和亚洲高纬度区域(特别是西伯利亚地区)人口少、经济社会发展滞后有关。实际上,随着对于北极放大效应的研究的深入,极其有必要开展对整个亚洲中高纬区开展气候变化影响和极端气候研究,把我国科学家高度关注的研究区域从东亚区向北延伸。其中有很多关键科学问题需要研究,特别是该区域极端气候的形成与变异过程、机制以及可预测性,极端气候对生态系统的影响,极端气候的未来演变趋势,等等。因此,国家自然科学基金委地学部在择优的基础上以重大项目的方式支持了这个方面的研究(项目执行期为2020~2024年)。本文概要介绍了该项目的框架和若干初步研究进展。

Recent Progress in Studies of Climate Change in China

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature （SAT） has increased at a rate ranging from 0.03℃ （10 yr）-1 to 0.12℃ （10 yr）-1. This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period （1000 1300 AD）. Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas （GHG） concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events.

Projected changes in mean and extreme climates over Hindu Kush Himalayan region by 21 CMIP5 models

Based on the outputs from 21 CMIP5 (Coupled Model Intercomparison Project phase 5) models, future changes in the mean temperature, precipitation and four climate extreme indices (annual maximum of daily maximum temperature (TXx), minimum of daily minimum temperature (TNn), annual total precipitation when the daily amount exceeds the 95th percentile of wet-day precipitation (R95p), and maximum consecutive 5-day precipitation (RX5day)) over Hindu Kush Himalayan (HKH) region are investigated under the greenhouse gas concentration pathways of RCP4.5 and RCP8.5. Two periods of the 21st century, 2036e2065 and 2066e2095, are selected, with the reference period is considered as 1976e2005. Results show general increase of the mean temperature, TXx and TNn under both scenarios, with the largest increases found during 2066e2095 under RCP8.5. Future precipitation is projected to increase over most part of HKH, except for the northwestern part. Intensification of the precipitation extremes is projected over the region. The uncertainties of mean temperature, TXx and TNn over the HKH1 subregions are the largest compared to the other three subregions and the overall HKH. Besides RX5day during 2036e2065 over HKH1, the uncertainties of R95p and RX5day tend to be larger following the increase of greenhouse gas concentrations. The multimodel ensemble medians of temperature and four extreme indices under RCP8.5 are projected to be larger than those under RCP4.5 in each of the subregions.

Change in Extreme Climate Events over China Based on CMIP5

The changes in a selection of extreme climate indices(maximum of daily maximum temperature(TXx),minimum of daily minimum temperature(TNn),annual total precipitation when the daily precipitation exceeds the 95th percentile of wet-day precipitation(very wet days,R95p),and the maximum number of consecutive days with less than 1 mm of precipitation(consecutive dry days,CDD))were projected using multi-model results from phase 5 of the Coupled Model Intercomparison Project in the early,middle,and latter parts of the 21st century under different Representative Concentration Pathway(RCP)emissions scenarios.The results suggest that TXx and TNn will increase in the future and,moreover,the increases of TNn under all RCPs are larger than those of TXx.R95p is projected to increase and CDD to decrease significantly.The changes in TXx,TNn,R95p,and CDD in eight sub-regions of China are different in the three periods of the 21st century,and the ranges of change for the four indices under the higher emissions scenario are projected to be larger than those under the lower emissions scenario.The multi-model simulations show remarkable consistency in their projection of the extreme temperature indices,but poor consistency with respect to the extreme precipitation indices.More substantial inconsistency is found in those regions where high and low temperatures are likely to happen for TXx and TNn,respectively.For extreme precipitation events(R95p),greater uncertainty appears in most of the southern regions,while for drought events(CDD)it appears in the basins of Xinjiang.The uncertainty in the future changes of the extreme climate indices increases with the increasing severity of the emissions scenario.

Uncertainty in crossing time of 2 °C warming threshold over China

The 2 °C warming target has been used widely in global and regional climate change research. Previous studies have shown large uncertainties in the time when surface air temperature(SAT) change over China will reach 2 °C relative to the pre-industrial era. To understand the uncertainties,we analyzed the projected SAT in the twenty-first century using 40 state-of-the-art climate models under two Representative Concentration Pathways(RCP4.5 and RCP8.5)from the Coupled Model Intercomparison Project Phase 5.The 2 °C threshold-crossing time(TCT) of SAT averaged across China was around 2033 and 2029 for RCP4.5 and RCP8.5, respectively. Considering a ±1r range of intermodel SAT change, the upper and lower bounds of the 2 °C TCT could differ by about 25 years or even more. Uncertainty in the projected SAT and the warming rate around the TCT are the two main factors responsible for the TCT uncertainty. The former is determined by the climate sensitivity represented by the global mean surface temperature response. About 45 % of the intermodel variance of the projected 2 °C TCT for averaged SAT over China can be explained by climate sensitivity across the models, which is contributed mainly by central and southern China. In a climate more sensitive to CO2 forcing, stronger greenhouse effect, less stratus cloud over the East Asian monsoon region,and less snow cover on the Tibetan Plateau result in increased downward longwave radiation, increased shortwave radiation, and decreased shortwave radiation reflected by the surface, respectively, all of which may advance the TCT.

Future Changes in Temperature and Precipitation Extremes in the State of Rio de Janeiro (Brazil)

In this study, we document the air temperature and precipitation changes between present-day conditions and those projected for the period 2041-2070 in the state of Rio de Janeiro (Brazil) by means of Eta driven by HadCM3 climate model output, considering the variation among its four ensemble members. The main purpose is to support studies of vulnerability and adaptation policy to climate change. In relation to future projections of temperature extremes, the model indicates an increase in average minimum (maximum) temperature of between +1.1°C and +1.4°C (+1.0°C and +1.5°C) in the state by 2070, and it could reach maximum values of between +2.0°C and +3.5°C (+2.5°C and +4.5°C). The model projections also indicate that cold nights and days will be much less frequent in Rio de Janeiro by 2070, while there will be significant increases in warm nights and days. With respect to annual total rainfall, the Northern Region of Rio de Janeiro displays the greatest variation among members, indicating changes ranging from a decrease of -350 mm to an increase of +300 mm during the 21st century. The southern portion of the state has the largest increase in annual total rainfall occurring due to heavy rains, ranging from +50 to +300 mm in the period 2041-2070. Consecutive dry days will increase, which indicates poorly time distributed rainfall, with increased rainfall concentrated over shorter time periods.

基于CMIP6气候模式的中国内地未来极端降水情景预估

【目的】为分析全球变暖背景下中国内地历史和未来不同排放情景下极端降水事件的变化特征,研究我国不同地区极端降水事件频率和强度的变化规律。【方法】选取日尺度历史降水数据(1979-2021年)和CMIP6未来情景模式降水数据(2015-2100年),使用Mann-Kendall检验等方法,分析历史和未来低(SSP1-2.6)、中低(SSP2-4.5)、中高(SSP3-7.0)和高(SSP5-8.5)排放情景下极端降水的时空变化趋势。【结果】结果表明:1979-2021年,我国各区域极端降水指数呈现东高西低的空间格局,连续干旱日数(CDD)、雨日日数(RD)在全国范围内呈下降趋势,其他极端降水量指数(如最大1 d降水量Rx1day)和日数指数(如大雨日数R25)等均为上升趋势,其中华东、华南和西南地区趋势最显著。未来不同时期,极端降水日、量数指数在不同经济路径下变化趋势亦有差异,2045-2075年上升面积占比增幅最大;华东地区在SSP3-7.0路径下极端降水量上升幅度最大,华南地区在SSP2-4.5路径下极端降水日指数上升面积最小,华北、西北和东北地区极端降水量指数随排放升高规律变化,西南地区受排放升高影响极端降水量指数上升面积占比最高。【结论】历史数据表明,我国极端降水事件频率与降水强度有增加趋势。未来情景模式4种经济路径下,全国范围内极端降水强度增加的面积占比有不同程度增加,本世纪后期(2060-2100年)面积占比变化趋于稳定。华中、东北、西北和西南青藏高原及其周边地区随排放升高极端降水事件发生频率与降水强度增加。不同地区极端降水对排放升高的响应有明显的区域差异,华北、东北和西北地区响应程度相近且规律性增加,华中、西南地区响应程度相近但无规律变化,华东和华南地区响应程度接近且强度升高面积占比接近于1。

基于CMIP6集合优化数据集的全球陆地极端气候变化预估

预估极端气候事件趋势能够降低其引起的灾害风险.该文基于CMIP6集合优化数据集EPTGODD-WHU,选取5个极端气候指数,即最高气温极大值(TXx)、最高气温极小值(TXn)、最低气温极大值(TNx)、最低气温极小值(TNn)和最大月降水量(PXx),并结合GIS分析手段,对2021—2100年SSP1-2.6、SSP2-4.5和SSP5-8.5情景下的全球陆地极端气温及降水进行预估.结果表明:1)相较于CMIP单一模式,EPT GODD-WHU数据集模拟性能显著提升,气温及降水的空间相关系数分别达到0.99和0.81.2)SSP5-8.5情景下,年最低气温和最高气温均上升明显,且这种上升趋势年内波动不大,地球陆地极寒地区将面临升温的风险,而赤道等极热地区将处于年内长时间酷热状态.3)六大洲在SSP5-8.5情景下的极端降水整体上升趋势最剧烈,但北美洲密西西比平原和滨海平原的地区在SSP5-8.5情景下在未来面临较高的旱灾风险.4)中国西南部地区的极端降水在三个情景下均呈稳定的增幅,且增幅高达60%,预示面临较高的洪灾风险.

未来的极端天气气候与水文事件预估及其应对

人类活动造成的气候变化已经影响到全球每个地区的极端天气气候和水文事件。全球变暖的任何额外增量都会伴随极端事件更大的变化,如果没有全球性的碳中和行动,极端高温事件的增多增强以及极端冷事件的减少减弱趋势将贯穿整个21世纪,强降水以及一些地区的农业和生态干旱的强度和发生频率也会显著增加。当代的儿童和后代在未来更容易受到气候变化和相关极端事件风险的影响,即使是在相对于工业化以前的1.5℃温升水平下,到21世纪末遭受的极端天气气候和水文事件的数量仍将增加近4倍。针对日益严峻的气候变化与极端事件灾害风险,亟须积极推进“双碳”行动,并大力减少甲烷等其他温室气体的排放。同时,亟须做好防灾减灾相关政策与措施的制定,推进极端事件监测与早期预警系统及恢复力建设,加强对复合极端事件与小概率高影响事件的预防,保障未来几代人的福祉安康和可持续发展。