Projection of Future Changes in Elephant Population in Amboseli under Representative Concentration Pathways

Within savanna environments, movements of elephant are influenced by changes in climate especially seasonal rainfall. In this study, we investigated the possible changes in elephant population based on projected rainfall changes using regional climate models (RCM) and Representative Concentration Pathways (RCPs). The relationship between elephant and rainfall was modelled against annual, wet season, dry season rainfall based on various time lags. Future relation between elephant and rainfall was projected based on three RCPs;2.6, 4.5 and 8.5. There was a strong linear relationship between elephant and October-November-December (OND) rains with time lag of 13 years (Y = −4016.43 + 19.11x, r2 = 0.459, P = 0.006). The rainfall trends for RCP 2.6 and 4.5 showed a slight increase in annual rainfall for the period 2006-2100 but driven by OND increases. Rainfall increase for RCP 8.5 was significant and was driven by increase in both March-April-May (MAM) and OND. These rainfall dynamics had influence on the projected elephant population in the Amboseli ecosystem. For RCP 2.6 and 4.5 the elephant population increase was 2455 and 2814 respectively. RCP 8.5 elephant population doubled to an average of 3348 elephants. In all the RCPs there are seasonal and yearly variations and absolute number varies from the average. The range of variation is small in RCPs 2.6 and 4.5 compared to RCP 8.5. Evidently, elephant population will increase based on projected rainfall projections surpassing park capacity. It therefore, requires that the Park authority put in place measures that could contain these numbers including opening of blocked wildlife corridors, maintain the cross border movement of Amboseli elephant with Tanzania in that case ensure there is no poaching. Lastly, work with local communities so that they can benefit from tourism through setting up conservancies through which they could minimize the human elephant conflicts based on the projected elephant population.

Assessing the impact of climate change on agricultural production in central Afghanistan

Afghanistan has faced extreme climatic crises such as drought,rising temperature,and scarce precipitation,and these crises will likely worsen in the future.Reduction in crop yield can affect food security in Afghanistan,where the majority of population and economy are completely dependent on agriculture.This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference(1990–2020)and future(2025–2100)periods.Climate data(1990–2020)were collected from four meteorological stations and three local organizations,and wheat yield data(1990–2020)were acquired from the United States Agriculture Department.Data during the reference period(1990–2020)were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model(SDSM)and Long Ashton Research Station Weather Generator(LARS-WG).Furthermore,the auto-regression model was used for trend analysis.The results showed that an increase in the average annual temperature of 2.15℃,2.89℃,and 4.13℃will lead to a reduction in the wheat yield of 9.14%,10.20%,and 12.00%under Representative Concentration Pathway(RCP)2.6,RCP4.5,and RCP8.5 during the future period(2025–2100),respectively.Moreover,an increase in the annual maximum temperature of 1.79℃,2.48℃,and 3.74℃also causes a significant reduction in the wheat yield of 2.60%,3.60%,and 10.50%under RCP2.6,RCP4.5,and RCP8.5,respectively.Furthermore,an increase in the annual minimum temperature of 2.98℃,2.23℃,and 4.30℃can result in an increase in the wheat yield of 6.50%,4.80%,and 9.30%under RCP2.6,RCP4.5,and RCP8.5,respectively.According to the SDSM,the decrease of the average monthly precipitation of 4.34%,4.10%,and 5.13%results in a decrease in the wheat yield of 2.60%,2.36%,and 3.18%under RCP2.6,RCP4.5,and RCP8.5,respectively.This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.

Potential impacts of climate change on dengue fever distribution using RCP scenarios in China

This study projected dengue distribution risk map using representative concentration pathways(RCP2.6,RCP4.5,RCP6.0,RCP8.5)in China in 2020s,2030s,2050s and 2100s.Based on the biological characteristics of Aedes albopictus and the dengue epidemic process,dengue transmission biological model was developed to project the risk epidemic areas.Observational temperature data in 1981-2016 at 740 stations and grid data of 0.5°×0.5°(15°-55.5°N,70°-140.5E)under selected RCPs in 2020s,2030s,2050s and 2100s were used.Relative to 142 counties and 168 million people living in the projected high risk area of dengue in the climate condition of 1981-2016,dengue high risk areas in China would expand under same RCP scenarios in the 21st century with time past except RCP2.6 with a turning down point in 2050s.Especially under RCP8.5 which global mean temperature would increase by 4.9 C till 2100s,the high risk area and population for dengue transmission would expand additional 34 counties(20 million)in 2020s,114 counties(60 million)in 2030s,208 counties(160 million)in 2050 and 456 counties(490 million)in 2100s respectively than those of 1981-2016.For RCP8.5 in 2100s,the population and expanded high risk areas would increase 4.2-fold and 2.9-fold than the 1981-2016 mean.The newly added high risk areas should prepare for controlling and preventing dengue in different period according to projected dengue risk map.

Prioritizing the Best Areas for Treated Wastewater Use Using RCP 8.5

The goal of this study is to develop a new framework that prioritizes the best sites for treated wastewater (TWW) use considering climate change impacts. Fuzzy TOPSIS which is a kind of multi-criteria decision making techniques was introduced to reflect the uncertainty of input data and criteria weighting values. Representative concentration pathway 8.5 scenario was included into the hydrologic simulations for the climate change impact to hydrologic regimes using hydrological simulation program-Fortran (HSPF). Furthermore, all year scenarios were considered to determine the rankings, respectively. It can take into consideration the uncertainty of time periods which always exists in all climate change scenarios. This study can be a baseline to start to combine the fuzzy multi-criteria decision making techniques with robust prioritization for climate change adaptation strategies.

Future meteorological drought conditions in southwestern Iran based on the NEX-GDDP climate dataset

Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts.Therefore,studying the future meteorological drought conditions at a local scale is vital.In this study,we assessed the efficiency of seven downscaled Global Climate Models(GCMs)provided by the NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP),and investigated the impacts of climate change on future meteorological drought using Standard Precipitation Index(SPI)in the Karoun River Basin(KRB)of southwestern Iran under two Representative Concentration Pathway(RCP)emission scenarios,i.e.,RCP4.5 and RCP8.5.The results demonstrated that SPI estimated based on the Meteorological Research Institute Coupled Global Climate Model version 3(MRI-CGCM3)is consistent with the one estimated by synoptic stations during the historical period(1990-2005).The root mean square error(RMSE)value is less than 0.75 in 77%of the synoptic stations.GCMs have high uncertainty in most synoptic stations except those located in the plain.Using the average of a few GCMs to improve performance and reduce uncertainty is suggested by the results.The results revealed that with the areas affected by wetness decreasing in the KRB,drought frequency in the North KRB is likely to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios.At the seasonal scale,the decreasing trend for SPI in spring,summer,and winter shows a drought tendency in this region.The climate-induced drought hazard can have vast consequences,especially in agriculture and rural livelihoods.Accordingly,an increasing trend in drought during the growing seasons under RCP scenarios is vital for water managers and farmers to adopt strategies to reduce the damages.The results of this study are of great value for formulating sustainable water resources management plans affected by climate change.

未来主要气候情景下黄淮海地区参考作物蒸散量时空分布

探索未来主要气候情景下参考作物蒸散量（reference evapotranspiration,ET0）的时空分布可为农业水资源科学配置,科学应对气候变化对农业生产的影响提供基础数据支撑。该文利用黄淮海及周围88个站点1961-2010年逐日气象数据,Penman-Monteith公式估算的ET0为因变量,采用非线性回归分析方法对Hargreaves公式进行参数属地化订正,基于1961-2005年温度日序列,利用统计降尺度模型（statistical downscaling model,SDSM）以及大气环流模型（general circulation models,GCMs）中加拿大地球系统模式（the second generation of Canadian Earth System Model,Can ESM2）得到代表性浓度（representative concentration pathways,RCPs）4.5和8.5两种排放情景下2010-2100年温度日序列,通过率定的Hargreaves公式预测黄淮海地区ET0,并采用普通克里格（ordinary Kriging）方法进行空间化处理。结果表明：率定后的Hargreaves公式与Penman-Monteith公式的相关指数波动范围为0.65-0.85,平均值为0.80,SDSM模拟的最低温度、最高温度率定期和验证期的确定性系数都在0.95以上;未来两种气候情景下,黄淮海地区ET0整体上均呈增加趋势;RCP4.5情景下ET0从河北与山东、河南交界处形成的＂勺＂状向周围逐渐减小,在河北唐山与乐亭、江苏东台、河南驻马店附近达到最小值;RCP8.5情景下黄淮海地区2020 s（2011-2040年）、2050 s（2041-2070年）ET0的空间分布和RCP4.5非常相似,但2080 s（2071-2100年）ET0的空间分布差异较大,最高值主要分布在山东惠民县附近、河南新乡附近、安徽蚌阜和江苏盱眙附近。如不采取科学的应对措施,未来ET0的增加,可能会进一步加剧该区水资源短缺程度,该研究可为黄淮海地区水资源的优化管理和灌溉制度制定提供科学参考。

代表性浓度路径情景下的全球温室气体减排和对中国的挑战

介绍了政府间气候变化专门委员会(IPCC)为第五次评估报告开发的新情景——代表性浓度路径(RCPs),分析了RCPs情景的内在优势,并描述了4类代表性RCPs(RCP8.5、RCP6、RCP4.5和RCP3-PD)的特征。利用IPCC最新发布的RCPs数据,分析了高端、中端稳定和低端浓度路径下,全球温室气体的排放空间、区域分担和减排成本,并着重探讨了低端路径与全球温度升幅限制在2℃以下目标之间的关系及其给中国带来的主要挑战和应对途径。

西部调水下长期气候效应研究

调水工程是优化配置水资源的战略措施,我国从1950年代就开始研究西部调水工程。然而,区域外调水的引入必将打破受水区原有的水热平衡,改变当地大气-陆面间的水分、能量交换过程,进而影响局地气候。因此有必要开展有关调水的区域气候效应研究。利用CMIP5中的全球气候模式MPI-ESM-MR输出结果作为区域气候模式RegCM4的初始场和边界场,研究在2021—2050年两种典型浓度路径情景下西北地区调水灌溉对区域气温、降水以及能量收支的影响。结果表明,大面积调水灌溉对全年的气温和降水均产生了影响,其影响在夏季尤为明显。具体来说,蒸散发在夏季明显增加(潜热通量增加35~45 W·m^(-2)),显热通量降低,导致夏季地温降低了近2℃。夏季降水增加主要在受水区及周边天山、祁连山和昆仑山等山脉附近,低空环流异常变化和对流上升运动增强为夏季降水的变化(增加0.5~1 mm·d^(-1))提供了动力条件,增加了受水区及周边高山地区的对流性降水潜力。此外,大面积调水灌溉使得该地区产生了复杂的大气环流变化,气象要素在600~925 hPa的垂直梯度发生了明显改变。

2006-2013年CMIP5模式中国降水预估误差分析

用第五次耦合模式比较计划（CMIP5）的10个模式模拟结果与英国东安格利亚大学（UEA）气候研究机构（CRU）的最新降水格点分析资料比较,评估了三种典型浓度路径（RCPs）排放情景下模式集合对2006-2013年中国降水预估误差,结果发现模式间年降水预估在西北和东部沿海地区差异较明显,在沿海地区模式降水估计偏少,在西部和北方大部分地区偏多;冬半年大部分地区模式降水明显偏多,部分地区甚至偏多一倍以上;夏半年东部季风区降水估计偏少,但西部仍然偏多。模式降水误差随时间变化,夏半年误差变化明显的区域主要集中在北方和东部地区,冬半年在东北南部、华东及华南等地。此外,提高排放情景对年降水量估计影响明显的地区主要集中在我国西部的部分地区,加剧了西北模式降水估计偏多程度,但对东部地区影响不大。El Ni？o与La Ni？a年的模式降水误差分布相似,仅在沿海部分地区和华北北部差异较明显,逐年误差分布特征也与此相似。各种误差的对比分析表明,模式降水误差可能多来自模式本身存在的问题,如积云对流参数化、固体降水物理过程、地形处理及分辨率等。这些误差特征说明,直接使用CMIP5模式集合情景输出资料估计未来降水的方法存在较大的不确定性,必须对其进行评估,以降低潜在用户或决策者们制定未来规划的风险。

CMIP5多模式集合对江苏省气候变化模拟评估及情景预估

利用中国气象局所属的2400余个台站观测资料制作的分辨率为0.25°×0.25°数据集中的气温、降水量资料评估了CMIP5中17个模式对于1961—2004年江苏省气温和降水量空间分布特征的模拟能力,筛选出了5个对江苏省气候特征模拟较好的模式。之后基于5个优选模式集合平均的结果预估了3种典型浓度路径(Representative Concentration Pathways,RCPs)下江苏省2006—2100年的气温和降水量变化趋势。结果表明:(1)全球耦合气候模式对江苏省的气温和降水量空间分布特征具有一定的模拟能力,并且模式集合平均的气温和降水量与观测资料的空间相关系数分别为0.85和0.93;(2)在低浓度路径(RCP2.6)、中浓度路径(RCP4.5)和高浓度路径(RCP8.5)3种温室气体排放情景下,江苏省2006—2100年的地表温度均呈现明显的增温趋势,并且苏北的增温幅度要高于苏南;(3)3种温室气体排放情景下,江苏省未来百年降水量均呈现出北方增多南方减少的趋势;(4)未来百年江苏省降水量随气温变化的趋势并不稳定,RCP2.6和RCP4.5情景下降水量随气温的升高而增加,而RCP8.5情景下降水量随气温的增加而减少。

基于DSSAT模型的长江中下游冬小麦潜在产量模拟研究

为了探明气候变化对长江中下游地区冬小麦潜在产量的影响,基于政府间气候变化专门委员会(IPCC)AR5提出的BCCCSM1-1(Beijing Climate Center Climate System Model version1-1)气候系统模式输出的基于典型浓度RCP各情景(基准时段baseline、RCP 2.6、RCP 4.5和RCP 8.5)主要气象要素的逐日模拟数据和历史观测数据。通过DSSAT模型模拟历史时期(2001—2009年)冬小麦的物候期和产量,并计算模拟数据与实测数据二者的均方根误差和一致性指数(开花、成熟期和产量模拟结果的相对均方差根误差分别在0.83%—2.98%之间和7%以下,符合度D均接近于1)明确最优遗传参数,应用最优参数模拟加以验证,完成模型参数区域化。结合历史阶段(1961—1990年)和未来时期(2021—2050年)主要气象要素变化趋势,利用DSSAT模型模拟分析未来30年长江中下游地区气候变化对小麦产量的影响及变化趋势,以期为未来作物生产提供理论依据。结果表明,DSSAT-CERES-Wheat品种遗传参数本地化后能准确模拟冬小麦的生长发育过程及产量潜力。较基准年相比,2021—2050年RCP情景下,冬小麦生育期内≥10℃积温除RCP 2.6情景外呈现逐渐增加趋势,增加幅度为RCP 8.5>RCP 2.6>RCP 4.5;降水量年际波动都比较大,区域性差异明显;太阳总辐射量较基准年均有所降低,但降低的幅度随着年份的增加逐渐减小,变化率均呈现显著或极显著的增加趋势。除昆山外冬小麦开花期、成熟期较基准年均有所提前,开花期到成熟期天数则随之缩短。仅考虑气候条件时,长江中下游地区冬小麦产量潜力与基准年减少,昆山、英山下降幅度较滁州、钟祥大(3%—59%),且区域差异明显。分析可得,一定范围内冬小麦产量随积温的增加逐渐增加,超过一定阈值时则逐渐减少,其他气候因子增加或减少并不能弥补积温过低产生的负效应。

未来50a长江三角洲地区干旱和洪涝灾害风险预估

中国长江三角洲地区人口稠密,经济发达,在全球气候变暖的背景下未来长江三角洲地区干旱和洪涝灾害风险也将发生变化。本文利用耦合模式比较计划第五阶段(Coupled Model Inter-comparison Project Phase 5,CMIP 5)中26个全球气候模式的模拟结果,对不同预估情景下长江三角洲地区未来50 a(2021—2040年和2046—2065年)两个时期干旱和洪涝灾害风险的变化进行定量预估。结果表明:未来50 a长江三角洲地区干旱和洪涝灾害呈由北向南风险强度降低的空间分布特征。由RCP(Representative Concentration Pathways) 2.6情景至RCP 8.5情景,长江北部地区洪涝灾害风险逐渐增加,而干旱灾害风险变化略有差异。在RCP 8.5情景下,未来50 a第二个时期(2046—2065年)长江三角洲地区干旱和洪涝灾害风险为所有情景中最大,高于IV级(包括IV级)的面积增加,江苏北部和安徽北部地区为V级干旱灾害风险与IV级洪涝灾害风险叠加区域,而江苏南部和上海地区为干旱与洪涝灾害最高等级风险(V级)叠加区域。

未来气候变化情景下湖北省极端降水的人口暴露分析

基于湖北省历史灾情数据构建受灾率与雨强、人均GDP的回归模型,选取RCP4.5和RCP8.5情景下的日降水数据及对应SSPs路径下的人口和GDP资料,分析了湖北省不同时期极端降水事件、人口及人口暴露度的时空分布特征及变化情况.结果表明:受灾率与雨强、人均GDP都存在着显著的相关性(P<0.01).通过构建受灾率模型,使之能够更加准确地刻画人口暴露情况.湖北省的极端降水事件在空间上自东南向西北递减,且整体强度随时间变化而增加;湖北省人口总数整体东密西疏,SSP3路径始终高于SSP2;人均GDP分布由武汉向四周递减,随时间快速增长,SSP2路径下的值始终大于SSP3;湖北省极端降水人口暴露度的高值中心,随时间变化向南向东发展,同时由于人均GDP的快速增长,设防水平大幅提升,人口总量减少,暴露总量不断减少,RCP8.5情景下,极端降水人口暴露度和暴露总量始终高于RCP4.5情景,并在未来中期时差距加大.

基于SPEI和MI分析陕西省干旱特征及趋势变化

【目的】目前干旱研究多为基于历史干旱事件分析成因与变化趋势,而结合过去与未来长时间序列数据更能揭示干旱变化特点。寻找在基于CMIP5模型输出未来气象数据时模拟干旱指数方法并探究陕西省过去与未来干旱变化特点,为陕西省未来农业水资源管理提供依据。【方法】根据陕西省18个气象站历史数据以及CMIP5模式输出未来气象数据,比较了3种模型模拟参考作物蒸发蒸腾量(ET0),并基于参考作物蒸发蒸腾量(ET0)和降水数据计算标准降水蒸发指数(SPEI)和相对湿润指数(MI)反映干旱程度,比较过去(1958-2018年)与未来(2019-2100年)干旱的时空变化特点。【结果】多元线性回归模型(Multiple Linear Regression, MLR)能较准确的模拟参考作物蒸发蒸腾量(ET0)(RMSE=0.457 mm·d^-1);在RCP2.6和RCP8.5情景下未来干旱指数呈现上升趋势,在RCP8.5情景下,21世纪40年代存在干旱指数的突变年份;陕西省未来干旱程度降低,年内干旱分布更加不均匀;未来时期夏玉米生长季干旱程度减小,冬小麦生长季干旱程度增加。【结论】在不同RCP情景下,未来干旱变化特征存在差异,相同RCP情景下,SPEI和MI反映的干旱特征变化基本一致,但部分时段存在变化差异。为有效应对气候变化对旱作作物产量造成的负面影响,应当增强土壤蓄水保墒能力,尤其加强冬小麦生长季的抗旱工作。

An Analysis of Historical and Future Temperature Fluctuations over China Based on CMIP5 Simulations

The trends and fluctuations of observed and CMIP5-simulated yearly mean surface air temperature over China were analyzed.In general,the historical simulations replicate the observed increase of temperature,but the multi-model ensemble （MME） mean does not accurately reproduce the drastic interannual fluctuations.The correlation coefficient of the MME mean with the observations over all runs and all models was 0.77,which was larger than the largest value （0.65） from any single model ensemble.The results showed that winter temperatures are increasing at a higher rate than summer temperatures,and that winter temperatures exhibit stronger interannual variations.It was also found that the models underestimate the differences between winter and summer rates.The ensemble empirical mode decomposition technique was used to obtain six intrinsic mode functions （IMFs） for the modeled temperature and observations.The periods of the first two IMFs of the MME mean were 3.2 and 7.2,which represented the cycle of 2-7-yr oscillations.The periods of the third and fourth IMFs were 14.7 and 35.2,which reflected a multi-decadal oscillation of climate change.The corresponding periods of the first four IMFs were 2.69,7.24,16.15 and 52.5 in the observed data.The models overestimate the period of low frequency oscillation of temperature,but underestimate the period of high frequency variation.The warming rates from different representative concentration pathways （RCPs） were calculated,and the results showed that the temperature will increase by approximately 0.9℃,2.4℃,3.2℃ and 6.1℃ in the next century under the RCP2.6,RCP4.5,RCP6.0 and RCP8.5 scenarios,respectively.

不同辐射背景下大西洋热盐环流下沉区混合层深度变化

基于政府间气候变化专门委员会(Intergovernmental Panel on Climate Change,IPCC)4种最新辐射强迫情景,利用ECHAM5/MPI-OM(European Centre Hamburg Model 5/Max Planck Institute Ocean Model)气候模式输出的1850—2300年逐月混合层深度、海表面温度、海表面盐度数据,分析大西洋热盐环流下沉区混合层深度的变化情况。结果表明:随辐射强迫增加,热盐环流下沉区混合层深度下降,混合层深度振荡周期在格陵兰-冰岛-挪威海(Greenland Sea–Iceland Sea–Norwegian Sea,GIN)海域减小,在拉布拉多海(Labrador Sea,LAB)海域变化不大;与GIN海域相比,LAB海域混合层深度对辐射强迫变化更敏感;两海区温度对混合层深度的影响时间较长,混合层深度对盐度的变化反应迅速;混合层深度变化的主导因素在LAB海域中为盐度,而在GIN海域,低辐射强迫下温度主导混合层深度变化,中高辐射强迫下温度与盐度共同起主导作用。

Projection of the Zhujiang(Pearl) River Delta's potential submerged area due to sea level rise during the 21st century based on CMIP5 simulations

Projections of potential submerged area due to sea level rise are helpful for improving understanding of the influence of ongoing global warming on coastal areas. The Ensemble Empirical Mode Decomposition method is used to adaptively decompose the sea level time series in order to extract the secular trend component. Then the linear relationship between the global mean sea level （GMSL） change and the Zhujiang （Pearl） River Delta （PRD） sea level change is calculated： an increase of 1.0 m in the GMSL corresponds to a 1.3 m （uncertainty interval from 1.25 to 1.46 m） increase in the PRD. Based on this relationship and the GMSL rise projected by the Coupled Model Intercomparison Project Phase 5 under three greenhouse gas emission scenarios （representative concentration pathways, or RCPs, from low to high emission scenarios RCP2.6, RCP4.5, and RCP8.5）, the PRD sea level is calculated and projected for the period 2006-2100. By around the year 2050, the PRD sea level will rise 0.29 （0.21 to 0.40） m under RCP2.6, 0.31 （0.22 to 0.42） m under RCP4.5, and 0.34 （0.25 to 0.46） m under RCP8.5, respectively. By 2100, it will rise 0.59 （0.36 to 0.88） m, 0.71 （0.47 to 1.02） m, and 1.0 （0.68 to 1.41） m, respectively. In addition, considering the extreme value of relative sea level due to land subsidence （i.e., 0.20 m） and that obtained from intermonthly variability （i.e., 0.33 m）, the PRD sea level will rise 1.94 m by the year 2100 under the RCP8.5 scenario with the upper uncertainty level （i.e., 1.41 m）. Accordingly, the potential submerged area is 8.57x103 km2 for the PRD, about 1.3 times its present area.

Characteristics and future projections of summer extreme precipitation in Sichuan Province, China

Based on the precipitation data observed by stations and data simulated by 23 CMIP5 models,the features and future changes of summer(Jun-JulAug)extreme precipitation events in Sichuan Province of China were analysed.We found that the total precipitation(RSum),extreme precipitation threshold(Threshold90),extreme precipitation(TR90),extreme precipitation percentage(TR90 pct)and extreme precipitation intensity(TR90 str)decreased from the southeast to the northwest in Sichuan Province,reflecting the differences between eastern Sichuan(ESC,basins)and western Sichuan(WSC,mountains).Compared with the observations,most of the CMIP5 models showed that there were wet biases in WSC and an unclear bias pattern in ESC for the RSum,Threshold90,TR90,and TR90 str.However,the extreme precipitation days(ND90)and TR90 pct values simulated by the models were generally overestimated and underestimated,respectively.Compared with the historical period,most models showed obvious increases in the TR90 and TR90 pct in the 21 century,while the characteristics of Rsum,ND90,and TR90 str were inconspicuous.Compared with the mid-21 st century,the extreme precipitation in the late-21 st century exhibited a certain degree of increase.Even during the same period,the results of RCP8.5 were higher than those of RCP4.5,especially for the ND90,TR90,and TR90 pct.

Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau, China

Comprehensive assessments of ecosystem services in environments under the influences of human activities and climate change are critical for sustainable regional ecosystem management. Therefore,integrated interdisciplinary modelling has become a major focus of ecosystem service assessment. In this study, we established a model that integrates land use/cover change(LUCC), climate change, and water retention services to evaluate the spatial and temporal variations of water retention services in the Loess Plateau of China in the historical period(2000–2015) and in the future(2020–2050). An improved Markov-Cellular Automata(Markov-CA) model was used to simulate land use/land cover patterns, and ArcGIS 10.2 software was used to simulate and assess water retention services from 2000 to 2050 under six combined scenarios, including three land use/land cover scenarios(historical scenario(HS), ecological protection scenario(EPS), and urban expansion scenario(UES)) and two climate change scenarios(RCP4.5 and RCP8.5, where RCP is the representative concentration pathway). LUCCs in the historical period(2000–2015) and in the future(2020–2050) are dominated by transformations among agricultural land, urban land and grassland. Urban land under UES increased significantly by 0.63×10^(3) km^(2)/a, which was higher than the increase of urban land under HS and EPS. In the Loess Plateau, water yield decreased by 17.20×10^(6) mm and water retention increased by 0.09×10^(6) mm in the historical period(2000–2015),especially in the Interior drainage zone and its surrounding areas. In the future(2020–2050), the pixel means of water yield is higher under RCP4.5 scenario(96.63 mm) than under RCP8.5 scenario(95.46mm), and the pixel means of water retention is higher under RCP4.5 scenario(1.95 mm) than under RCP8.5 scenario(1.38 mm). RCP4.5-EPS shows the highest total water retention capacity on the plateau scale among the six combined scenarios, with the value of 1.27×10^(6) mm. Ecological restoration projects in the Loess Plateau have enhanced soil and water retention. However, more attention needs to be paid not only to the simultaneous increase in water retention services and evapotranspiration but also to the type and layout of restored vegetation. Furthermore, urbanization needs to be controlled to prevent uncontrollable LUCCs and climate change. Our findings provide reference data for the regional water and land resources management and the sustainable development of socio-ecological systems in the Loess Plateau under LUCC and climate change scenarios.

Projections of the Advance in the Start of the Growing Season during the 21st Century Based on CMIP5 Simulations

It is well-known that global warming due to anthropogenic atmospheric greenhouse effects advanced the start of the vegetation growing season （SOS） across the globe during the 20th century. Projections of further changes in the SOS for the 21st century under certain emissions scenarios （Representative Concentration Pathways, RCPs） are useful for improving understanding of the consequences of global warming. In this study, we first evaluate a linear relationship between the SOS （defined using the normalized difference vegetation index） and the April temperature for most land areas of the Northern Hemisphere for 1982-2008. Based on this relationship and the ensemble projection of April temperature under RCPs from the latest state-of-the-art global coupled climate models, we show the possible changes in the SOS for most of the land areas of the Northern Hemisphere during the 21st century. By around 2040-59, the SOS will have advanced by -4.7 days under RCP2.6, -8.4 days under RCP4.5, and -10.1 days under RCPS.5, relative to 1985-2004. By 2080-99, it will have advanced by -4.3 days under RCP2.6, -11.3 days under RCP4.5, and -21.6 days under RCP8.5. The geographic pattern of SOS advance is considerably dependent on that of the temperature sensitivity of the SOS. The larger the temperature sensitivity, the larger the date-shift-rate of the SOS.