Projected Regional 1.50℃and 2.00℃Warming Threshold-crossing Time Worldwide Using the CMIP6 Models

The Paris Agreement aims to limit global warming to well below 2.00℃and pursue efforts to limit the temperature increase to 1.50℃.However,the response of climate change to unbalanced global warming is affected by spatial and temporal sensitivities.To better understand the regional warming response to global warming at 1.50℃and 2.00℃,we detected the 1.50℃and 2.00℃warming threshold-crossing time(WTT)above pre-industrial levels globally using the Coupled Model Intercomparison Project phase 6(CMIP6)models.Our findings indicate that the 1.50℃or 2.00℃WTT differs substantially worldwide.The warming rate of land would be approximately 1.35–1.46 times that of the ocean between 60°N–60°S in 2015–2100.Consequently,the land would experience a 1.50℃(2.00℃)warming at least 10–20 yr earlier than the time when the global mean near-surface air temperature reaches 1.50℃(2.00℃)WTT.Meanwhile,the Southern Ocean between 0°and 60°S considerably slows down the global 1.50℃and 2.00℃WTT.In 2040–2060,over 98.70%(77.50%),99.70%(89.30%),99.80%(93.40%),and 100.00%(98.00%)of the land will have warmed by over 1.50℃(2.00℃)under SSP(Shared Socioeconomic Pathway)1–2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5,respectively.We conclude that regional 1.50℃(2.00℃)WTT should be fully considered,especially in vulnerable high-latitude and high-altitude regions.

Changes in temperature extremes over China under 1.5 ℃ and 2 ℃ global warming targets

The long-term goal of the 2015 Paris Agreement is to limit global warming to well below 2 ℃above pre-industrial levels and to pursue efforts to limit it to 1.5 ℃. However, for climate mitigation and adaption efforts, further studies are still needed to understand the regional consequences between the two global warming limits. Here we provide an assessment of changes in temperature extremes over China （relative to 1986-2005） at 1.5 ℃ and 2 ℃ warming levels （relative to 1861-1900） by using the 5th phase of the Coupled Model Intercomparison Project （CMIP5） models under three RCP scenarios （RCP2.6, RCP4.5, RCP8.5）. Results show that the increases in mean temperature and temperature extremes over China are greater than that in global mean temperature. With respect to 1986-2005, the temperature of hottest day （TXx） and coldest night （TNn） are projected to increase about 1/1.6 ℃ and 1.1/1.8 ℃, whereas warm days （TX90p） and warm spell duration （WSDI） will increase about 7.5/13.8% and 15/30 d for the 1.5/2 ℃ global warming target, respectively. Under an additional 0.5 ℃ global warming, the projected increases of temperature in warmest day/night and coldest day/night are both more than 0.5 ℃ across almost the whole China. In Northwest China, Northeast China and the Tibetan Plateau, the projected changes are particularly sensitive to the additional 0.5 ℃ global warming, for example, multi-model mean increase in coldest day （TXn） and coldest night （TNn） will be about 2 times higher than a change of 0.5 ℃ global warming. Although the area-averaged changes in temperature extremes are very similar for different scenarios, spatial hotspot still exists, such as in Northwest China and North China, the increases in temperatures are apparently larger in RCP8.5 than that in RCP4.5.

Changes of heating and cooling degree days over China in response toglobal warming of 1.5℃, 2℃, 3℃ and 4℃

Future changes of heating degree days （HDD） and cooling degree days （CDD） in the 21st century with and without considering populationfactor are investigated based on four sets of climate change simulations over East Asia using the regional climate model version 4.4 （RegCM4.4）driven by the global models of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES, and MPI-ESM-MR. Under global warming of 1.5℃, 2℃, 3℃,and 4℃, significant decrease of HDD can be found over China without considering population factor, with greater decrease over high elevationand high latitude regions, including the Tibetan Plateau, the northern part of Northeast China, and Northwest China; while population-weightedHDD increased in areas where population will increase in the future, such as Beijing, Tianjin, parts of southern Hebei, northern Shandong andHenan provinces. Similarly, the CDD projections with and without considering population factor are largely different. Specifically, withoutconsidering population, increase of CDD were observed over most parts of China except the Tibetan Plateau where the CDD remained zerobecause of the cold climate even under global warming; while considering population factor, the future CDD decreases in South China andincreases in North China, the Sichuan Basin, and the southeastern coastal areas, which is directly related to the population changes. The differentfuture changes of HDD and CDD when considering and disregarding the effects of population show that population distribution plays animportant role in energy consumption, which should be considered in future research.

Future Changes in Extreme High Temperature over China at 1.5℃-5℃ Global Warming Based on CMIP6 Simulations

Extreme high temperature(EHT)events are among the most impact-related consequences related to climate change,especially for China,a nation with a large population that is vulnerable to the climate warming.Based on the latest Coupled Model Intercomparison Project Phase 6(CMIP6),this study assesses future EHT changes across China at five specific global warming thresholds(1.5℃-5℃).The results indicate that global mean temperature will increase by 1.5℃/2℃ before 2030/2050 relative to pre-industrial levels(1861-1900)under three future scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5),and warming will occur faster under SSP5-8.5 compared to SSP1-2.6 and SSP2-4.5.Under SSP5-8.5,global warming will eventually exceed 5℃ by 2100,while under SSP1-2.6,it will stabilize around 2℃ after 2050.In China,most of the areas where warming exceeds global average levels will be located in Tibet and northern China(Northwest China,North China and Northeast China),covering 50%-70%of the country.Furthermore,about 0.19-0.44 billion people(accounting for 16%-41%of the national population)will experience warming above the global average.Compared to present-day(1995-2014),the warmest day(TXx)will increase most notably in northern China,while the number of warm days(TX90p)and warm spell duration indicator(WSDI)will increase most profoundly in southern China.For example,relative to the present-day,TXx will increase by 1℃-5℃ in northern China,and TX90p(WSDI)will increase by 25-150(10-80)days in southern China at 1.5℃-5℃ global warming.Compared to 2℃-5℃,limiting global warming to 1.5℃ will help avoid about 36%-87%of the EHT increases in China.

Changes in surface air temperature over China under the 1.5 and 2.0 ℃ global warming targets

This study investigated the projected changes in the annual mean surface air temperature （SAT） over China under the 1.5 and 2.0 ℃ targets, by analyzing the outputs from 22 models of the Coupled Model Intercomparison Project Phase 5. Under the 1.5 ℃ target, the scope of changes in the average SAT over China is quite narrow and has the largest probability to increase by 1.7-2.0 ℃ under the various RCP pathways, although the time of occurrence of the 1.5 ℃ target has a large spread of 40-60 years. Similarly, the models consistently show that the average SAT over China would most likely increase by 2.4-2.7 ℃ under the 2.0 ℃ target. Furthermore, the warming shows a clear spatial distinction over China： being stronger in the northwest part and weaker in the southeast part. Under all RCP pathways, the SAT over the northwest part would increase by 1.9-2.1 ℃ for the 1.5℃ target, which is much stronger than the SAT increase over the southeast part （1.3-1.5 ℃）. A similar spatial pattern appears for the 2.0 ℃ target.

Intensified East Asian summer monsoon and associated precipitation mode shift under the 1.5 ℃ global warming target

In this study, the East Asian summer climate changes under the 1.5 ℃ global warming （1.5 GW） target in 30 simulations derived from 15 coupled models within the Coupled Model Intercomparison Program phase 5 （CMIP5） are examined. Compared with the current summer climate （1975-2005）, both surface air temperature and precipitation increase significantly over the East Asian continent during the 1.5 GW period （average period 2021-2051）. In northeastern China this is particularly pronounced with regional averaged precipitation increases of more than 7.2%, which is greater than that for the whole East Asian continent （approximately 4.2%）. Due to stronger enhancement of precipitation north of 40°N, the leading empirical orthogonal function （EOF） mode of summer precipitation over the East Asian continent changes from tripolar-like mode to dipole mode. As there is stronger surface warming over the East Asian continent than that over surrounding ocean, the land-sea thermal contrast is enhanced during the 1.5 GW period. As a result, the monsoon circulation in the lower troposphere is significantly strengthened, which causes the increased summer precipitation over the East Asian continent. In addition, larger interannual variabilities of East Asian summer monsoon circulation and associated precipitation are also suggested for the 1.5 GW period.

结合模式性能和独立性加权的全球增暖1.5/2℃下中国区域气候的未来预估

基于耦合模式比较计划第6阶段(CMIP6)中的全球气候模式的模拟结果,采用考虑模式性能和独立性结合(Climate model Weighting by Independence and Performance,ClimWIP)的加权方案进行中国区域气候的多模式集合预估及不确定性研究。结果表明,ClimWIP方案在历史阶段的模拟优于等权重方案,降低了多模式模拟的气候态偏差。温度指数的未来预估不确定性较大的区域主要集中在中国北方和青藏高原,而降水指数主要集中在华北和西北地区。ClimWIP方案的预估不确定性与等权重方案相比有所降低。ClimWIP方案预估的温度指数的增温大值区主要集中在中国北方和青藏高原;降水指数在西北和青藏高原增加最为显著。全球额外0.5℃增暖时,中国区域平均的温度指数变化更强,平均高于全球0.2℃,最低温在东北部分地区的额外增温甚至是全球平均的3倍;总降水额外增加5.2%;强降水额外增加10.5%。全球增暖2℃下,中国大部分区域温度指数较当前气候态增加可能超过1.5℃(概率>50%),在中国北方和青藏高原的部分地区增温超过1.5℃的可能性更大(概率>90%);总降水,强降水和连续干日在西北和华北增加幅度有可能超过10%、25%和-5 d(概率>50%)。

全球温升1.5~4.0℃水平下西江流域径流变化趋势

西江是华南地区最大水系珠江流域的主干,其径流变化对华南地区水资源供给至关重要。基于逐日气象观测数据,对耦合模式国际比较计划第六阶段(CMIP6)中包含7个情景(SSP1-1.9、SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP4-3.4、SSP4-6.0、SSP5-8.5)的5个气候模式进行降尺度和偏差订正,结合水文观测数据对SWAT水文模型进行率定和验证,预估分析了全球温升1.5、2.0、3.0和4.0℃水平下西江流域径流变化特征。结果表明:①1961-2020年,西江流域年平均气温以0.15℃/10 a的速率呈显著上升趋势;年降水量以-0.9 mm/10a的速率呈微弱下降趋势。全球温升1.5~4.0℃水平下,西江流域年平均气温较工业革命前将升高1.7℃(模式范围:1.2~2.2℃)~4.0℃(3.7~4.3℃);流域年降水量较基准期有所增加,且在全球温升3.0℃和4.0℃时增幅较明显。②1961-2020年,西江流域年径流为6923.5 m^(3)/s,以-19.0(m^(3)·s)/10 a的速率呈减少趋势。相比基准期(1995-2014年),全球温升1.5~4.0℃水平下,西江流域年径流将增加3.5%(-20.4%~28.4%)~10.5%(-18.7%~43.2%);7-11月径流较基准期呈增加趋势,4-6月径流呈减少趋势,12月到次年三月径流均在温升3.0℃时出现较基准期有所减少,其他温升水平下呈微弱增加。③与基准期相比,4种温升水平下流域发生洪水和枯水的风险均呈增加趋势,且温升水平越高,流域发生洪水和枯水的风险越大,历史时期百年一遇的洪水在全球温升1.5~4.0℃水平下将分别变为45~50、15~28、10~18、5~8 a一遇;百年一遇枯水事件发生的时长在不同温升水平下将变为不足40~46、22~25、12~13和8~10 a一遇。随着全球气温升高,流域发生丰、枯水事件的风险将有所增加,可能对西江流域水资源管理和防洪抗旱工程造成威胁。

Responses and changes in the permafrost and snow water equivalent in the Northern Hemisphere under a scenario of 1.5℃ warming

In this study, the period that corresponds to the threshold of a 1.5℃ rise (relative to 1861e1880) in surface temperature is validated using a multi-model ensemble mean from 17 global climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). On this basis, the changes in permafrost and snow cover in the Northern Hemisphere are investigated under a scenario in which the global surface temperature has risen by 1.5℃, and the uncertainties of the results are further discussed. The results show that the threshold of 1.5℃ warming will be reached in 2027, 2026, and 2023 under RCP2.6, RCP4.5, RCP8.5, respectively. When the global average surface temperature rises by 1.5℃, the southern boundary of the permafrost will move 1e3.5
northward (relative to 1986e2005), particularly in the southern Central Siberian Plateau. The permafrost area will be reduced by 3.43x106 km2 (21.12%), 3.91x106 km2 (24.1%) and 4.15x106 km2 (25.55%) relative to 1986e2005 in RCP2.6, RCP4.5 and RCP8.5, respectively. The snow water equivalent will decrease in over half of the regions in the Northern Hemisphere but increase only slightly in the Central Siberian Plateau. The snow water equivalent will decrease significantly (more than 40% relative to 1986e2005) in central North America, western Europe, and northwestern Russia. The permafrost area in the QinghaieTibet Plateau will decrease by 0.15x106 km2 (7.28%), 0.18x 106 km2 (8.74%), and 0.17x106 km2 (8.25%), respectively, in RCP2.6, RCP4.5, RCP8.5. The snow water equivalent in winter (DJF) and spring (MAM) over the QinghaieTibet Plateau will decrease by 14.9% and 13.8%, respectively.

Climate Change of 4℃ Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4？C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4？C global warming will occur is 2084.Based on the median results of models that project a 4？C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5？C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.

Projected changes in summer water vapor transport over East Asia under the 1.5°C and 2.0°C global warming targets

This study investigates changes in summer water vapor transport(WVT) over East Asia under 1.5°C and 2.0°C global warming(GW) for the +4.5 and +8.5 W m-2 Representative Concentration Pathway(RCP) scenarios(RCP4.5 and RCP8.5, respectively). Of the 27 models used, 18 show better skill in simulating the climatological summer WVT over East Asia of the present day. Of those 18, 13 reach 1.5°C and 2.0°C GW for the two RCPs. Based on these 13 models, results show that — relative to the present day-th e summer WVT is enhanced over East Asia under 1.5°C and 2.0°C GW for RCP4.5 and RCP8.5. The inte r-model consistency is higher under 2.0°C GW. Increased water vapor content favors the enhanced WVT over both southern and northern East Asia, while lower-level circulation contributes to the enhanced WVT over southern East Asia. Compared to 1.5°C GW, th e summer WVT under 2.0°C GW is further enhanced over most of East Asia for RCP4.5. For RCP8.5, the summer WVT is also further enhanced over southern East Asia, while this is not the case over northern East Asia. Under the additional 0.5°C GW, the changes in summer WVT, with low in ter-model consistency, are closely related to anomalous lower-level circulation. Precipitation increases over the East China Sea to southern Japan, the Korean Peninsula, and North China, for both RCP4.5 and RCP8.5. However, the changes in precipitation over the South China Sea and Northeast China are different for the two RCPs. This is connected to the difference in the changes of WVT divergence.

全球稳定增温1.5℃下北非夏季风降水的响应及其机理

利用第六次国际耦合模式比较计划(CMIP6)模式模拟结果,研究了21世纪末全球稳定增温1.5℃下北非夏季风降水的变化及机理。结果表明,全球稳定增温1.5℃较1985—2014年北非夏季风降水将增加0.26 mm/d,区域降水敏感度为4.8%/℃,且季风区北部降水增幅大于南部。基于水汽收支诊断发现热力项对季风区总降水增加作用明显,动力项对降水空间变化起重要作用。进一步分析当地水汽条件及相应环流场发现:在热力上,相对于1985—2014年,稳定增温1.5℃加强了北非地区表面温度及低层水汽输送,有利于当地维持更高的大气可降水量。在动力上,稳定增温1.5℃下显著的撒哈拉沙漠增温加大了海陆温度梯度,增强了对流层低层季风环流,同时非洲东风急流北移,使得季风区北部低层气流辐合加强,而高层热带东风急流减弱会导致季风区高层辐散运动减弱。总的来说,热力项增加了整个季风区降水,而动力项增强了季风区北部降水,减弱南部降水,主导了降水变化的空间格局。

预估全球升温1.5℃与2.0℃下淮河流域极端降雨的变化特征

淮河流域暴雨洪水灾害严重,科学预估未来全球升温1.5℃和2.0℃下淮河流域极端降雨的变化特征对流域防洪减灾及应对气候变化具有重要意义。基于最新的第六次国际耦合模式比较计划(CMIP6)中22个全球气候模式数据,利用改进的可靠性集合方案与概率比法,采用6个极端降雨指标预估了全球升温1.5℃和2.0℃下淮河流域未来极端降雨的时空变化与风险变化特征。结果表明:改进可靠性集合方案对淮河流域极端降雨的模拟性能要优于单一气候模式与算术平均集合方案;全球升温达到1.5℃与2.0℃阈值的平均时间段分别约为2017—2046年和2026—2055年;全球升温2.0℃下极端降雨指标增幅约为升温1.5℃下的1.4~2.6倍,其中流域北部地区为极端降雨增幅大值区;2种升温条件下极端降雨发生风险呈增加趋势,且额外增暖0.5℃将导致淮河流域极端降雨风险更高,如100 a重现期的极端降雨在升温1.5℃和2.0℃下将分别变为32年一遇和22年一遇,未来淮河流域极端降雨将会更加频繁。

Intraseasonal oscillation intensity over the western North Pacific:Projected changes under global warming

The 30-60-day intraseasonal oscillation(ISO) and 10-20-day ISO are two dominant oscillation modes over the western North Pacific during boreal summer.With daily data derived from eight CMIP5 models,changes of the ISO intensities are projected under the 1.5 and 2.0℃ global warming levels under the Representative Concentration Pathway(RCP) 4.5 and RCP8.5 scenarios.Most of the models agree that the ISO intensities increase along a belt region from the south Indochina Peninsula(ICP) to the east to the Philippines.The variation pattern shows little difference between different warming levels or scenarios.Results indicate that the spatial distribution of ISO anomalies is related with the variation of background fields.Enriched lower-level humidity and moist static energy favor the intensity increases of ISOs,which are projected to be larger over the whole western North Pacific,with the most conspicuous changes located over the east to the Philippines for humidity but over the south of the ICP for moist static energy.In contrast,the ISOs over the west to Indonesia and northeast to the Philippines decrease,which is consistent with the local descending motions.

未来升温1.5℃与2.0℃背景下中国玉米产量变化趋势评估

基于ISI-MIP推荐的5个气候模式在4个RCP情景下的模拟结果,筛选21世纪末全球升温最接近1.5℃和2.0℃的气候数据,运用作物模型DSSAT,模拟升温1.5℃和2.0℃背景下中国玉米产量相对于基准时段1985-2006年的变化,揭示了1.5℃与2.0℃升温背景下中国玉米产量变化的空间分布。结果表明:升温2.0℃背景下玉米减产风险明显高于升温1.5℃,未来升温2.0℃背景下中国玉米减产面积比升温1.5℃背景下多6.2%,升温1.5℃和2.0℃背景下中国玉米平均减产幅度分别为3.7%和11.5%;从空间分布来看,升温1.5℃与2.0℃背景下未来中国玉米产量变化在区域分布上大致相似,但未来玉米增产和减产的面积和幅度不尽相同,在北方与西南玉米种植区都有一定的增产区域,其它区域大多以减产为主,其中西北部玉米种植区减幅最大;1.5℃升温背景下北方大部分地区气候条件对玉米生长有利,2.0℃升温背景下北方地区玉米减产也不明显,说明从近期到未来一段时间内,将全球升温控制在1.5℃以内,北方地区玉米仍具有一定增产潜力。

1.5 ℃增暖对全球和区域影响的研究进展

《巴黎协定》明确提出将全球平均升温控制在相对于工业化前水平2 ℃以内,并努力将其控制在1.5 ℃以内,以降低气候变化的风险与影响。随后,《联合国气候变化框架公约》(UNFCCC)邀请IPCC筹备关于1.5 ℃增暖影响及温室气体排放途径的特别报告,为UNFCCC谈判提供科学依据。通过回顾近期发表的一些成果发现,在1.5 ℃到2 ℃的不同升温条件下,很多极端天气事件发生的概率将增加。2 ℃条件下一些易受威胁的系统,如生态系统和农业系统,将承受全球变暖带来的严重后果;海平面明显上升,珊瑚礁锐减,季风降水减弱等影响将进一步加强。同时,不同地区对全球不同程度增暖的响应也存在很大差异。总的说来,相较于2 ℃增暖而言,将增暖控制在1.5 ℃以内能进一步减小气候变化影响的风险。然而,要把全球增暖控制在1.5 ℃内具有极大的挑战性,并且目前对1.5 ℃增暖的影响认识仍然十分不足。定量分析2 ℃和1.5 ℃增暖对不同区域自然和人类系统造成的影响差异,需要更高分辨率的模式以及更多针对2 ℃和1.5 ℃增暖影响而设计的专门试验支持。

全球升温1.5℃与2.0℃情景下中国极端低温事件变化与耕地暴露度研究

基于区域气候模式COSMO-CLM(CCLM)模拟的1960—2100年逐日最低气温数据及2000年中国土地利用数据,采用强度-面积-持续时间(Intensity-Area-Duration,IAD)方法,以全球升温1.5℃(RCP 2.6情景)和2.0℃(RCP 4.5情景)为目标,研究不同持续时间中国极端低温事件变化特征、最强极端低温事件强度与面积关系和最强中心空间分布,分析极端低温事件下耕地面积暴露度的变化规律。研究发现:(1)全球升温1.5℃情景下,持续1至9 d的极端低温事件频次相对于基准期(1986—2005年)下降30%—54%,强度变化-1%—8.8%,影响面积下降7%—21%;升温2.0℃,频次下降48%—80%,强度上升6%—11.5%,影响面积则在-14%—19%变化。(2)全球不同升温情景有可能发生强度和面积超过基准期最强事件的极端低温。全球升温1.5—2.0℃时,同等面积上的最强极端低温事件强度明显下降,但最强极端低温事件中心由西北和西南转移到华中和华南等地。(3)不同升温情景下,暴露于极端低温事件的中国耕地面积明显少于基准期,且升温幅度越高下降程度越大。最强极端低温事件的耕地暴露度则随温度的升高而增大。升温1.5℃时,华东、华北与华中等地暴露在最强极端低温事件的耕地面积相对于基准期有所增大,升温2.0℃时,华东与华北等地有大幅度上升。全球不同升温情景下,极端低温事件频次与影响面积持续下降,但强度上升;随着升温幅度的增大,这种差异变化特征越来越明显;特别应注意的是,随着温度上升,发生强度和面积超过当前记录到的最强极端低温事件的可能性增大;应加强极端事件的预警、预报和监测,减缓经济社会的损失。

全球1.5℃和2.0℃升温对中国小麦产量的影响研究

采用部门间影响模式比较计划(ISI-MIP)的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统(DSSAT)模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明:(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。

全球升温1.5℃与2.0℃目标下长江流域极端降水的变化特征

基于区域气候模式COSMO-CLM及5个全球气候模式(GFDL-ESM2M,HadGEM2-ES,IPSL-CM5A-LR,MIROC-ESM-CHEM,NorESM1-M)1961-2100年逐日降水数据,采用重现期法计算20 a与50 a一遇极端降水量,研究全球升温1.5℃和2.0℃目标下长江流域极端降水的变化特征。研究发现:全球升温1.5℃目标下,长江流域20 a与50 a一遇极端降水量分别为78和93 mm,相比1986-2005年将增加10%和9%;空间上表现为中下游普遍增加,最大增幅145%,上游地区则主要表现为减少趋势;全球升温2.0℃目标下,20 a与50 a一遇极端降水量分别为81和98 mm,将较基准期上升14%和15%;中下游极端降水量显著上升,最大增幅约188%,上游成都平原以西以北明显下降;随全球升温由1.5℃至2.0℃时,20 a与50 a一遇极端降水量分别增加4%和6%,中下游较上游增幅更明显,最大增幅136%。因此,将温室气体减排目标控制在1.5℃水平对减缓长江流域尤其是中下游地区极端降水事件影响具有重要的意义。

全球升温1.5℃和2.0℃情景下贵州省极端降水的变化特征

利用CCSM4和IPSL-CM5A-MR模式1961-2005年历史模拟和2006−2098年RCP2.6和RCP4.5排放情景下的逐日降水以及1961−2005年贵州省84个气象台站逐日降水资料,使用偏差校正改善模式模拟能力,通过降水强度、日最大降水量和强降水量等9个指标探究全球升温1.5℃和2.0℃条件下贵州省极端降水变化特征。结果表明:贵州省RCP2.6和RCP4.5情景下各极端降水指数虽然波动幅度较大,但总体上均呈现增加的趋势,且相对于基准期(1986−2005年)而言全球升温2.0℃时各极端降水指数增幅约为升温1.5℃时的两倍。在升温2.0℃下9个极端降水指数概率密度曲线尾端均向右延伸,表明在升温2.0℃情景下各极端降水指数中高值出现的概率增大。因此,将全球升温控制在1.5℃而不是2.0℃意义重大。