中、高温室气体排放情景下2069~2098年中国冬小麦气候适宜种植分区对比北大核心CSCD

基于温度、降水、光照等指标,通过利用区域气候模式所预估的分辨率为1°(纬度)×1°(经度)的未来气候预估数据,对1981~2005年的基准期和RCP4.5、RCP8.5两排放情景下2069~2098年中国热量资源以及冬小麦种植界限、理论生育期和气候适宜种植分区的空间分布特征进行了对比分析。研究主要结论为:与基准期相比,两未来气候变化情景下我国热量资源、冬小麦种植条件与气候适宜性差异显著。且相比于RCP4.5情景,在RCP8.5情景下中国2069~2098年多数地区热量资源增加、冬小麦种植北界和南界北移东扩、可种植面积扩大,多数区域理论适宜播种期推迟、理论成熟期提前、潜在生长季缩短,且潜在生长季内的光—温—水配置使得冬小麦气候适宜性有所提高。但由于冬小麦为喜凉作物,对高温胁迫非常敏感,RCP8.5情景下更多的极端高温天气和不对称增温等因素带来的负面影响很可能抵消前述光—温—水配置所带来的有利影响,从而降低冬小麦的种植适宜性。因此,未来研究工作仍应致力于减缓气候变化,以保障我国粮食生产的安全。     

东北地区玉米气候生产潜力时空分布特征

利用旋转经验正交函数和功率谱等方法分析了1961～2007年东北地区玉米光温生产潜力和气候生产潜力的时间变化趋势及区域特征。结果表明,东北地区玉米光温生产潜力呈显著的上升趋势;气候生产潜力呈下降趋势,但变化趋势不显著。玉米光温生产潜力和气候生产潜力均存在7～9年的显著周期变化。玉米气候生产潜力还存在5年和3年左右的显著周期;东北玉米光温生产潜力呈西南区域与东北区域相反的空间趋势分布,生产潜力的高值区位于辽宁大部、吉林西部和黑龙江西南部,低值区位于东北的东部地区;东北玉米气候生产潜力的高值区位于东北的东南部,低值区位于东北的西部。     

大气环流模式与春玉米生长模拟模式联接的影响评估模拟试验

根据春玉米田间试验资料和历史气候资料,对春玉米生长模拟模式进行了验证与灵敏性分析,在此基础上,运用逐步订正法将当前气候前景和大气环流模式输出资料结合历史气候资料生成的未来气候情景订正到１ｏ×１ｏ网格点上,与春玉米生长模拟模式相联接,就未来气候变化对我国东北地区春玉米生长、发育和最终产量的可能影响进行了网格化定量模拟,并对一些适应性对策的效果进行了定性或定量的分析。结果表明,在ＤＫＲＺＯＰＹＣ模拟的未来情景下,若保持当前作物品种和生产技术措施不变,研究区域除北部将平均增产７０％外,其余地区都将有不同程度的减产,幅度在－１０％～－５０％之间,而在ＮＣＡＲ模拟的情景下,中西部地区将增产,其它地区可维持当前产量水平。适应性对策将对开发利用未来可能的气候资源,减缓未来气候变化的负效应,充分发挥其正效应起到积极作用,进而绝大部分区域将受益于未来水热条件的改变。     

新书架

正《中国农业应对气候变化》周广胜主编该书采用要素—过程结果评估的逻辑思路,从全国、主要农区及主要粮食作物(水稻、玉米、小麦)三个层次,系统分析了我国农业气候资源变化、农业气象灾害变化、农业病虫害变化、农业种植制度变化和作物生长发育与产量变化,探讨了当前及未来气候变化情景下我国主要粮食作物的气候生产潜力以及我国主要粮食作物产量的提升潜力。同时,针对当前农业气候资源下我国主要粮食作物增产面临的问题,从主要粮食作物的种植面积、复种指数、品种布局和生产管理方式等方面探讨了我国适应气候变化的对策措施。     

近36年东北地区春玉米气候资源利用率评估

应用1981—2016年中国东北三省170个气象台站的逐日气象资料和50个农业气象观测站的春玉米发育期资料,在前人研究的基础上,采用基于层次分析法和熵权法的组合权重赋权法,对农业气候资源适宜指数模型进行了改进,分析了东北地区春玉米气候资源利用率的时空分布特征。结果表明:东北地区春玉米不同发育阶段的气候资源利用率从大到小排序是,抽雄-成熟期的出苗-拔节期的拔节-抽雄期的播种-出苗期的。从空间分布看,气候资源利用率在播种-出苗期吉林东部的长白山区的最低,热量不足是主要影响因素;出苗-拔节期大兴安岭东部、黑龙江北部和吉林东部长白山区利用率较低,其余大部利用率较高,水分是主要限制因子;拔节-抽雄期吉林和辽宁东部的长白山区的最低;抽雄-成熟期大部分地区利用率较高,且从北到南呈明显递增趋势,黑龙江后期热量不足可能对玉米成熟不利。从时间演变看,播种-出苗期各省利用率在2010年之前增高,之后开始下降,其他发育阶段黑龙江的年代际波动较大,吉林和辽宁的年波动较小。     

基于NorESM1-M模式的中国东北地区2050s玉米气候生产潜力预估

利用NorESM1-M模式资料驱动AEZ模型模拟了21世纪中叶东北地区春玉米在雨养条件下的气候生产潜力。结果表明：在RCP2.6情景下,东北区域热量资源较1981-2010年有所改善,年平均气温增加1.72℃,≥ 10℃积温增加359.6℃;降水整体呈现略增加趋势且南部多于北部,全区平均增多56.9 mm,蒸散量增加10.0 mm;具有最大气候生产潜力的区域在辽宁省东部;与基准年相比,辽宁单产平均每公顷增加1100 kg。在RCP8.5情景下,东北区域热量资源进一步改善,黑龙江、辽宁和吉林三省≥ 10℃积温分别增加652.7℃、636.3℃和683.9℃,降水总量较RCP2.6情景增加但空间分布差异较大,全区维持增产趋势,辽宁、吉林和黑龙江增产百分比分别为3.3%、8.1%和20.0%。     

基于CMIP5模式的中国气候变化敏感性预估与分析

以CMIP5提供的26个全球气候系统模式的温度和降水数据为基础,采用区域气候变化指数(Regional Climate Change Index,RCCI)分析中国的不同区域对21世纪气候变化响应的敏感性。结果表明,三种排放情景(RCP 2.6、RCP 4.5、RCP 8.5)下,21世纪全期,气候变化最敏感的区域分布在西藏地区,其次为我国西北地区以及东北地区,气候变化敏感性最低的区域分布在我国内蒙古中东部、华北地区以及长江中下游一带,且高排放情景对应更高的气候变化敏感性。对RCCI指数贡献因子分析结果表明,对中国气候变化敏感性贡献的大小依次为Δσ_TΔσ_pΔRRWAF。冬夏两季温度变化的大值区与RCCI指数的大致区分布一致,RCCI大小的分布很大程度上由温度变化的敏感性决定。而夏季降水变化的大值区主要出现在西藏地区、华南地区和东北地区,冬季降水变化的大值区则主要出现在黄河以南长江以北的中原地区以及东北地区。     

未来气候变化对安徽淮河以南一季稻气候生产潜力的影响评估

针对未来气候变化及其对一季稻的可能影响,利用第5次耦合模式比较计划(coupled model intercomparison project phase 5,CMIP5)中5个气候模式(global circulation models,GCMs)和3种RCPs情景输出的逐日气候要素资料以及安徽淮河以南50个气象站1961—2010年逐日平均气温、降水量等观测资料和各县一季稻生育期、单产资料,预估未来21世纪安徽淮河以南一季稻生育期气候变化,并基于潜力衰减法估算近期(2018—2039年)、中期(2040—2069年)和远期(2070—2099年)一季稻气候生产潜力及其对气候变化的响应。结果表明:(1)5个GCMs对安徽淮河以南气温与降水量具有较好的模拟能力,且气温模拟效果更佳。(2)不同RCPs情景下未来一季稻各生育期将提前、全生育期缩短。预估的安徽淮河以南一季稻生育期持续增暖,北部增温幅度高于南部,其中RCP8.5情景下变暖幅度更显著;未来全生育期降水量整体变化趋势不明显,但南部增加较为明显,而太阳总辐射均显著减少。(3)不同RCPs情景预估的一季稻气候生产潜力均呈显著下降趋势,以远期降幅最大。(4)一季稻气候生产潜力与全生育期平均气温和降水量显著相关,且增暖负效应突出。可见,未来气候变化可能对一季稻气候生产潜力的提高不利。     

玉米品种精细化布局气象服务技术

针对兴安盟玉米生产中气候资源利用不合理现状,在建立玉米品种资源数据库和精细化气候资源(80m×80m)推算模型基础上,区分不同耕地类型和有无灌溉条件分类建立了玉米品种布局精细化气候指标,并开发了操作简单的服务系统.结果能够提供任意地区玉米品种优选方案和任意玉米品种的适宜种植地区,为最大限度合理利用气候资源、实现增产增收提供气象服务.     

东北地区农业应对气候变化的策略与措施分析

气候变化的影响与适应已经成为农业生产面临的现实而紧迫的问题。1956-2005年东北地区增温1.5℃,幅度明显高于全国平均水平,给作物生产带来复杂的影响。东北是重要的国家商品粮生产基地,对国家粮食安全起着重要作用。探讨区域层面上适应气候变化的能力建设更具有针对性和现实性。文章分析了近50 a来东北地区气候变化的主要表现及其对农业生产的影响;针对气候变化过程中人类活动对土地利用和温室气体的影响,提出了东北地区适应和减缓气候变化的策略和措施,强调在农业生态、水资源利用、环境保护等多方面综合开展工作,积极采取行动,最终达到维护气候环境、充分利用气候资源的目的,为东北粮食生产安全、农业可持续发展做出贡献。     

气候变化背景下中国小麦需水量的敏感性研究

利用CROPWAT作物模型模拟分析了过去50年（1961-2010年）及IPCC RCPs情景下未来2020年代（2020-2029年）中国小麦需水量的变化情况。在此基础上,以小麦需水量的变化率作为敏感性因子,对RCP4.5和RCP8.5排放情景下中国小麦需水量的敏感性进行了探讨。结果表明：中国小麦多年平均需水量约为1056.4亿m³,最高值位于黄淮海地区。小麦需水量对气候变化的敏感性存在空间差异,华北和西北地区是小麦需水量的重度和极度敏感区,东北地区以及云贵高原地带是小麦需水量的轻度敏感区,而中国中部及南方部分地区的小麦需水量对气候变化不敏感。不同RCP排放情景下小麦需水量的敏感性分布不同,RCP8.5高排放情景下的小麦需水量敏感性区域比RCP4.5中排放情景下明显扩大,轻度和中度敏感区域扩大尤为明显。     

Evaluation of Agricultural Climatic Resource Utilization During Spring Maize Cultivation in Northeast China Under Climate Change

Agricultural climatic resources （such as light,temperature,and water） are environmental factors that affect crop productivity.Predicting the effects of climate change on agricultural climatic resource utilization can provide a theoretical basis for adapting agricultural practices and distributions of agricultural production.This study investigates these effects under the IPCC （Intergovernmental Panel on Climate Change） scenario A1B using daily data from the high-resolution RegCM3 （0.25° ×0.25°） during 1951-2100.Model outputs are adjusted using corrections derived from daily observational data taken at 101 meteorological stations in Northeast China between 1971 and 2000.Agricultural climatic suitability theory is used to assess demand for agricultural climatic resources in Northeast China during the cultivation of spring maize.Three indices,i.e.,an average resource suitability index （Isr）,an average efficacy suitability index （Ise）,and an average resource utilization index （K）,are defined to quantitatively evaluate the effects of climate change on climatic resource utilization between 1951 and 2100.These indices change significantly in both temporal and spatial dimensions in Northeast China under global warming.All three indices are projected to decrease in Liaoning Province from 1951 to 2100,with particularly sharp declines in Isr,Ise,and K after 2030,2021,and 2011,respectively.In Jilin and Heilongjiang provinces,Isr is projected to increase slightly after 2011,while Ise increases slightly and K decreases slightly after 2030.The spatial maxima of all three indices are projected to shift northeastward.Overall,warming of the climate in Northeast China is expected to negatively impact spring maize production,especially in Liaoning Province.Spring maize cultivation will likely need to shift northward and expand eastward to make efficient use of future agricultural climatic resources.     

Scenario Analysis on the Adaptation of Different Maize Varieties to Future Climate Change in Northeast China

Based on gridded meteorological data for the period 1981–2100 from the RegCM3 regional model, the changing trends of climatic resources in Northeast China are analyzed, and the distributions of maize varieties are accordingly adjusted. In order to explore the effects of different adaptation countermeasures on climatic productivity and meteorological suitability in the future, maize cultivars with resistance to high temperatures and/or drought are selected. The results show that, in the future, there is likely to be a significant increase in thermal resources, and potential atmospheric evaporation will increase correspondingly.Meanwhile, radiation is predicted to increase significantly during 2041–2070 in the growing season. However, changes in precipitation are unlikely to be sufficient enough to offset the intensification in atmospheric evaporation caused by the temperature increase. Water resources and high temperatures are found to be the two major factors constraining grain yield. The results also show that the warming climate will be favorable for maize production where thermal resources are already limited, such as in central and northern Heilongjiang Province and eastern Jilin Province; while in areas that are already relatively warm, such as Liaoning Province, climatic productivity will be reduced. The climatic productivity and the meteorological suitability of maize are found to improve when the planting of resistant varieties is modeled. The utilization of agricultural climatic resources through the adaptation countermeasures of maize varieties is to increase obviously with time. Specifically, maize with drought-resistant properties will have a marked influence on meteorological suitability during 2011–2070, with suitable areas expanding. During 2071–2100, those maize varieties with their upper limit of optimum temperature and maximum temperature increased by 2℃, or water requirement reduced to 94%, or upper limit of optimum temperature and maximum temperature increased by 1℃ and water requirement reduced to 98%, all exhibit significant differences in climatic potential productivity, compared to the present-day varieties. The meteorological suitability of maize is predicted to increase in some parts of Heilongjiang Provine, with the eastern boundary of the "unavailable" area shifting westward.     

Attribution of Maize Yield Increase in China to Climate Change and Technological Advancement Between 1980 and 2010

Crop yields are affected by climate change and technological advancement. Objectively and quantitatively evaluating the attribution of crop yield change to climate change and technological advancement will ensure sustainable development of agriculture under climate change. In this study, daily climate variables obtained from 553 meteorological stations in China for the period 1961-2010, detailed observations of maize from 653 agricultural meteorological stations for the period 1981-2010, and results using an Agro-Ecological Zones (AEZ) model, are used to explore the attribution of maize (Zea mays L.) yield change to climate change and technological advancement. In the AEZ model, the climatic potential productivity is examined through three step-by-step levels: photosynthetic potential productivity, photosynthetic thermal potential productivity, and climatic potential productivity. The relative impacts of different climate variables on climatic potential productivity of maize from 1961 to 2010 in China are then evaluated. Combined with the observations of maize, the contributions of climate change and technological advancement to maize yield from 1981 to 2010 in China are separated. The results show that, from 1961 to 2010, climate change had a significant adverse impact on the climatic potential productivity of maize in China. Decreased radiation and increased temperature were the main factors leading to the decrease of climatic potential productivity. However, changes in precipitation had only a small effect. The maize yields of the 14 main planting provinces in China increased obviously over the past 30 years, which was opposite to the decreasing trends of climatic potential productivity. This suggests that technological advancement has offset the negative effects of climate change on maize yield. Technological advancement contributed to maize yield increases by 99.6%-141.6%, while climate change contribution was from-41.4% to 0.4%. In particular, the actual maize yields in Shandong, Henan, Jilin, and Inner Mongolia increased by 98.4, 90.4, 98.7, and 121.5 kg hm^-2 yr^-1 over the past 30 years, respectively. Correspondingly, the maize yields affected by technological advancement increased by 113.7, 97.9, 111.5, and 124.8 kg hm^-2 yr^-1, respectively. On the contrary, maize yields reduced markedly under climate change, with an average reduction of-9.0 kg hm^-2 yr^-1. Our findings highlight that agronomic technological advancement has contributed dominantly to maize yield increases in China in the past three decades.     

西南地区持续性气候事件的未来变化预估

利用RegCM4.0区域气候模式单向嵌套BCC_CSM1.1模式输出资料进行连续积分获得的模拟预估数据,对西南地区未来2025-2055年在两种温室气体排放情景下持续性干期和持续湿期事件的特征及其相对于历史基准期的变化进行了预估分析。结果表明,最长持续干期和湿期在RCP4.5和RCP8.5两种情景下的变化趋势不一致,RCP8.5情景下的最长湿期和持续湿期事件的发生频次相较RCP4.5并没有大幅增加,而是比RCP4.5情景具有更高的年际变率特征。相对于历史基准期,两种情景下的最长持续性气候事件的日数和发生频次在西南地区的东南部区域显著性增加,而在川西高原地区显著减少。对于持续干期发生的频次FCDD和最长持续湿期而言,四川中部以及四川、云南和贵州三省邻接处在RCP4.5情景下表现为显著增加的区域在RCP8.5情景下转变为显著减少。未来几十年西南地区持续性湿期和干期的分布特征可能更加趋于不均匀。     

Assessing the impact of climate changes on the potential yields of maize and paddy rice in Northeast China by 2050

Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed.     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

Historical change and future scenarios of sea level rise in Macau and adjacent waters

Against a background of climate change, Macau is very exposed to sea level rise(SLR) because of its low elevation,small size, and ongoing land reclamation. Therefore, we evaluate sea level changes in Macau, both historical and, especially,possible future scenarios, aiming to provide knowledge and a framework to help accommodate and protect against future SLR. Sea level in Macau is now rising at an accelerated rate: 1.35 mm yr-1over 1925–2010 and jumping to 4.2 mm yr-1over 1970–2010, which outpaces the rise in global mean sea level. In addition, vertical land movement in Macau contributes little to local sea level change. In the future, the rate of SLR in Macau will be about 20% higher than the global average, as a consequence of a greater local warming tendency and strengthened northward winds. Specifically, the sea level is projected to rise 8–12, 22–51 and 35–118 cm by 2020, 2060 and 2100, respectively, depending on the emissions scenario and climate sensitivity. Under the +8.5 W m-2Representative Concentration Pathway(RCP8.5) scenario the increase in sea level by2100 will reach 65–118 cm—double that under RCP2.6. Moreover, the SLR will accelerate under RCP6.0 and RCP8.5, while remaining at a moderate and steady rate under RCP4.5 and RCP2.6. The key source of uncertainty stems from the emissions scenario and climate sensitivity, among which the discrepancies in SLR are small during the first half of the 21 st century but begin to diverge thereafter.     

RegCM4对华北区域21世纪气候变化预估研究

利用国家气候中心完成的RegCM4区域气候模式在RCP4.5和RCP8.5两种排放路径下的气候变化动力降尺度试验结果,在检验模式对基准期(1986—2005年)气温和降水模拟能力基础上,进行华北区域21世纪气候变化预估分析。结果表明:RegCM4对华北区域基准期气温和降水的模拟能力较好。未来21世纪,两种情景下华北区域气温、降水、持续干期(consecutive dry days, CDD)和强降水量(R95p)变化逐渐增大,但变化幅度在高排放的RCP8.5情景下更为显著,其中近期(2021—2035年)、中期(2046—2065年)、远期(2080—2098年)RCP8.5情景下年平均气温分别升高1.77、3.44、5.82℃,年平均降水分别增加8.1%、14%、19.3%,CDD分别减少3、3、12 d, R95p分别增加30.8%、41.9%、69.8%。空间上,未来21世纪华北区域内年、冬季、夏季平均气温将一致升高,夏季升温幅度最大;年、冬季、夏季平均降水整体以增加为主,冬季降水增加幅度最大;CDD以减少为主,但近期和中期在山西和京津冀有所增加,而R95p以增加为主,表明21世纪华北区域干旱事件逐渐减少、极端降水事件不断增加。