近10年来“国际古气候模拟比较计划(PMIP)”回顾和未来古气候模拟研究热点

国际古气候模拟比较计划(PMIP)是古气候领域里的一项长期开展的大型国际研究计划。该计划的主旨是利用气候数值模式,通过开展一系列针对古气候变化的模拟试验理解全球气候变化的机理,确定气候系统内部的各种影响气候变化的关键反馈因子; 通过比较不同气候模式对不同于现代气候(古气候)的模拟能力评价模式的优劣,进而促进气候模式的发展; 同时也为全球变化背景下利用气候模式预估未来气候变化提供借鉴。PMIP自1991年酝酿开始至今经历了PMIP1(1991～2001年)、PMIP2(2002～2007年)两个阶段,并正在开展第三阶段(PMIP3)(2008～)的研究。本文简要回顾了近10年来PMIP研究进展及概述了未来PMIP将要开展研究的重点领域和方向,主要包括4个主题： 1)基准(benchmark)时段(6kaB.P.和21kaB.P.)模拟; 2)间冰期和温暖期气候模拟; 3)快速气候变化模拟; 4)不确定性研究。     

近10年来"国际古气候模拟比较计划(PMIP)"回顾和未来古气候模拟研究热点

国际古气候模拟比较计划(PMIP)是古气候领域里的一项长期开展的大型国际研究计划.该计划的主旨是利用气候数值模式,通过开展一系列针对古气候变化的模拟试验理解全球气候变化的机理,确定气候系统内部的各种影响气候变化的关键反馈因子;通过比较不同气候模式对不同于现代气候(古气候)的模拟能力评价模式的优劣,进而促进气候模式的发展;同时也为全球变化背景下利用气候模式预估未来气候变化提供借鉴.PMIP白1991年酝酿开始至今经历了PMIP1(1991～2001年)、PMlP2(2002～2007年)两个阶段,并正在开展第三阶段(PMfP3)(2008～)的研究.本文简要回顾了近10年来PMIP研究进展及概述了未来PMIP将要开展研究的重点领域和方向,主要包括4个主题:1)基准(benchmak)时段(6kaB.P.和21kaB.P.)模拟;2)间冰期和温暖期气候模拟;3)快速气候变化模拟;4)不确定性研究.     

全球高分辨率气候系统模式研究进展

气候模式是定量研究气候演变规律、预测或预估未来气候变化的重要工具。提高气候模式空间分辨率并改进相应的物理参数化过程,是改善模式性能的重要途径之一,对于认识气候变化规律、提高气候预测能力具有重要作用。在阐述发展全球高分辨率气候系统模式重要性的基础上,对当今国内外高分辨率气候系统模式的研究进展进行总结,介绍全球高分辨率气候系统模式研发和评估的现状及其存在的问题,并着重讨论了制约当前高分辨率气候系统模式发展的关键科学问题和技术瓶颈,其中包括高分辨率海洋和大气模式动力框架的研制和大规模高性能并行计算、次网格物理参数化过程的改进,以及中尺度海气相互作用等。同时,还介绍了国际耦合模式比较计划第六阶段中的高分辨率模式比较子计划的科学目标及其试验设计方案。最后对未来我国全球高分辨率气候系统模式的发展和评估进行了展望。     

气候模式对长江流域气温和降水的模拟性能评估及未来情景预估

利用政府间气候变化专门委员会第四次评估报告的22个新一代全球气候模式基准期(1961～1990年)模拟结果,从时空尺度分别讨论了与观测过程的差异,评估了模式对长江流域气温和降水的模拟性能。结果表明22个气候模式对长江流域具有一定的模拟能力,地面气温的模拟值都偏低,部分降水的模拟值局部偏高。不同的气候模式的模拟能力差异显著,大部分模式对长江流域的模拟精度有待进一步改进,只有少数几个模式（降水有6个模式,气温有5个模式）的年变化趋势与实况基本一致。综合比较,UKMO_HadCM3和NCAR_PCM两个模式基本能再现长江流域降水和气温的年变化特征。长江流域降水和气温未来情景预估表明各个模式和情景结果虽然存在差异,但对未来90年气候变化的模拟趋势基本一致,将持续增温、降水出现区域性增加,并着重讨论了UKMO_HadCM3模式在2020s（2010～2039年）、2050s（2040～2069年）和2080s（2070～2099年）3个时段的降水和气温时空变化特征,研究结果表明3个时段气温和降水在不同情景下都是逐渐增加的,A2情景下未来降水增幅最显著,B1情景增幅最小。     

气候自然变异在气候变化对水资源影响 评价中的贡献分析——Ⅱ.未来期应用分析

基于模型率定期(基准期)气候自然变异的模拟方法及气候自然变异引起的径流变化的可能情况分析,此部分研究未来期(2021~2051年,2061~2091年)气候变化下径流变化情况及气候自然变异的影响。基于CSIRO、NCAR、MPI三种气候模式及A1B、A2、B1三种排放方式共7种未来气候情景,应用和基准期相同的水文模型和研究流域,引入基准期模型率定出的参数,考虑气候自然变异的影响,对未来气候变化对水资源的影响进行分析。为消除气候模式本身的系统误差,采用δ差值方法得到各模式各排放情景下的未来气候情景。该项研究主要说明如何在气候变化的影响评价中将气候自然变异的贡献分离出来,从而实现更客观的气候变化的影响评价。研究结果表明,气候变异的影响在整个气候变化进程中的贡献随时间的推移将有所不同。未来2021~2051年期间,气候自然变异的影响相对较大;未来2061~2091年期间,由温室气体引起的气候变化的影响占主导。     

应用随机方法研究全球气候变暖对东江流域水资源的影响

介绍了全球气候变暖对流域水资源影响研究中流域随机模型的应用.根据IPCC最新公布的2010～2039年和2040～2069年气候变化情景的GCMs模拟结果,计算并讨论了广东东江流域未来相应期内不同保证率径流量可能发生的变化.     

我国气候变化将比模式预期的小吗？

从当今国际上不同的气候系统模式模拟的全新世大暖期和末次盛冰期我国气候变化量级和复原资料结果的对比,以及从目前气候变化的趋势(包括温室气体、气温、海洋温度、海平面高度、冰川等),来评述我国区域气候未来变化的量级。从以上两个方面的情况看,我国区域的未来气候变化量级可能比现有模式预估的还要大。文章最后讨论了我国的气候变化脆弱区以及关键的气候变化要素问题。     

基于可靠性集合平均方法的全球1.5/2.0℃变暖下中国极端气候的未来预估

全球变暖下我国气候响应的研究对进一步预估我国未来气候变化相关风险及制定适应和减缓政策具有重要意义。利用第六次耦合模式比较计划中25个全球气候模式的模拟结果,评估比较了各种可靠性集合加权方案对中国区域气候的模拟性能,基于表现最好的可靠性集合平均方案预估了SSP2-4.5和SSP5-8.5情景下中国极端气候指数在全球增暖1.5和2.0℃下的未来变化。结果表明,改进的可靠性集合方案模拟中国气候指数表现最好,与观测的偏差最小。未来中国区域温度明显增加,极端温度的增幅强于平均温度,极端降水整体也增加,且SSP5-8.5情景下增幅略强于SSP2-4.5情景。SSP5-8.5情景下,中国区域平均温度、最高温和最低温在全球增暖1.5(2.0℃)下较1995—2014年分别增加了1.11、1.18和1.31℃(1.88、1.98和2.14℃),总降水和强降水分别增加了5.6%和14.4%(10.5%和25.7%)。中国北方和青藏高原部分区域为增温的大值区,中国西部为降水增加的大值区。额外0.5℃增暖对中国地区产生显著影响,几乎整个中国地区温度指数的增幅都将超过全球平均。极端降水也将进一步增加,SSP5-...     

1470年以来中国东部季风区降水变化规律及趋势预估

超长系列的降水资料是分析气候变化和预估未来区域水安全形势的重要支撑,但目前观测资料只有几十年时间尺度,利用相关历史文献资料进行系列重建是延长现有观测资料的主要手段。基于《中国近五百年旱涝分布图集》和1959年以来实测降水资料,重建1470—2019年中国东部季风区的长序列降水数据,分析近550 a以来区域降水变化规律,剖析气候自然变异规律和人为气候变化对历史降水的影响,并通过CMIP6中等分辨率气候系统模式下的4种情景降水数据预估未来降水变化趋势。研究表明：(1)东部季风区降水年际分布不均,有明显的丰枯变化,1470—1691年整体处于枯水期,1692—1924年处于丰水期,1925年至今处于枯水期,存在准181 a周期;(2) 1991年后人为气候变化的影响已经显现,海河、黄河下游和长江流域部分降水倾向率发生显著变化,东部季风区总体降水增加趋势加快;(3)在未来气候变化情景下多年平均降水量较基准期(1961—1990年)显著增加,季节性变化加大,区域旱涝风险加剧。由于未来气候情景的不确定性,未来降水趋势预测的可信度尚未可知,需要进一步增强风险分析。     

使用订正的“空间型标度”法预估1.5℃温升阈值下地表气温变化

近10年(2007—2016年)全球地表气温相对于工业革命前(1861—1890年)已上升约1℃,未来达到1.5℃温升阈值时的气候变化及其影响成为国际社会高度关注的问题。目前对未来温度的预估多依赖气候模式,但模式在区域气候预估方面尚存在较大不确定性。采用国际通用的"空间型标度(Pattern scaling)"方法,尝试基于1951—2005年历史温度观测资料,预估1.5℃温升阈值下全球区域地表气温相对于当前升温1℃的变化。由于未来气温变化的空间型可能与历史时期不完全相同,同时非线性因素亦可能令基于线性假设的空间型标度法出现偏差,故利用参加第五次耦合模式比较计划(CMIP5)的21个气候模式在4种典型浓度路径情景(RCP8.5,RCP6.0,RCP4.5,RCP2.6)下增暖空间型相对于历史时期(1951—2005年)的变化,对观测的空间型进行订正,并考虑非线性因素的影响。结果表明,全球平均温度继续上升0.5℃,达到1.5℃时,4种情景下预估的地表气温变化的空间型和增暖幅度接近。大部分陆地将升温0.6℃以上,北半球比南半球高约0.2℃,陆地比海洋高约0.3℃。预估中国区域升温0.7℃以上。RCP2.6下中国北部和中部升温明显高于其他情景。若不考虑订正方法的影响,在全球和区域尺度上,基于观测资料的空间型标度法预估结果的不确定性均远小于气候模式。     

Climate change impact projections at the catchment scale in Tunisia using the multi-model ensemble mean approach

In this work, we developed a mean projection for climate change and assessed its impact on some hydro-meteorological indicators relevant to climatic condition, precipitation extremes magnitude and frequency for the Siliana catchment in Tunisia based on an ensemble of seven combinations of global circulation models (GCMs) and regional climate models (RCMs) derived from the EU-FP6 ENSEMBLES project. We performed quantile-based mapping (QM) bias correction technique of climate model projection using local observations. Because there is no warranty that the best climate model based on its performances in reproducing historic climate will be superior to other models in simulating future climate, we used the multi-model ensemble (MME) mean approach to derive a mean projection as the best guess for climate change projection for the Siliana catchment. We also quantified the uncertainty of the MME in the projected change in the selected indicators by comparing their values in the reference period (1981–2010) to these in the future period (2041–2070). Results reveal that the Siliana catchment will be prone to drier and warmer climate in the future with less rainy days for each month. The uncertainty associated with the MME projection suggests that no clear general tendency for extreme rainy days in the future is expected. These findings highlight the need to consider an ensemble of multi-climate models with an uncertainty framework if reliable climate change impact study is sought at the catchment scale.     

Episodic recharge and climate change in the Murray-Darling Basin, Australia

In semi-arid areas, episodic recharge can form a significant part of overall recharge, dependant upon infrequent rainfall events. With climate change projections suggesting changes in future rainfall magnitude and intensity, groundwater recharge in semi-arid areas is likely to be affected disproportionately by climate change. This study sought to investigate projected changes in episodic recharge in arid areas of the Murray-Darling Basin, Australia, using three global warming scenarios from 15 different global climate models (GCMs) for a 2030 climate. Two metrics were used to investigate episodic recharge: at the annual scale the coefficient of variation was used, and at the daily scale the proportion of recharge in the highest 1% of daily recharge. The metrics were proportional to each other but were inconclusive as to whether episodic recharge was to increase or decrease in this environment; this is not a surprising result considering the spread in recharge projections from the 45 scenarios. The results showed that the change in the low probability of exceedance rainfall events was a better predictor of the change in total recharge than the change in total rainfall, which has implications for the selection of GCMs used in impact studies and the way GCM results are downscaled.     

Surface Air Temperature Projection Under 1.5 ℃ Warming Threshold Based on Corrected Pattern Scaling Technique

The global mean temperature during the recent decade (2007-2016) has increased above 1 ℃ relative to the pre-industrial period (1861-1890). The climate change and impact under 1.5 ℃ warming in the future have become a great concern in global society. Temperature projections, especially in regional scale, show great uncertainty depending on used climate models. Taking advantage of pattern scaling technique and observed temperature changes during 1951-2005, we tried to project the temperature changes globally under 1.5 ℃ threshold relative to current climate state, i.e. about 1 ℃ warming around 2007-2016. The projections of 21 climate models from the Coupled Model Intercomparison Project - Phase 5 under four Representative Concentration Pathways (RCP2.6, RC4.5, RCP6.0 and RCP8.5) were used to correct the assumptions in pattern scaling. Results showed that the geographical distribution and warming amplitude of surface air temperature changes under 1.5 ℃ threshold are similar in the four scenarios. Warming over most of the land would be above 0.6 ℃, 0.3 ℃ warmer than ocean. The Northern Hemisphere would be 0.2 ℃ warmer than the Southern Hemisphere. The temperature over China region will increase by 0.7 ℃. The warming in the Northern and Central China under RCP2.6 was obviously higher than that in the other scenarios. Ignoring the impact of correction method, uncertainty in temperature projection based on pattern scaling was much smaller than that in climate models, both in global and regional scales.     

Application of Bias Correction and Spatial Disaggregation in Removing Model Biases and Downscaling over China

Global Climate Models (GCM) are the primary tools for studying past climate change and evaluating the projected future response of climate system to changing atmospheric composition. However, the state of art GCMs contain large biases in regional or local scales and are often characterized by low resolution which is too coarse to provide the regional scale information required for regional climate change impact assessment. A popular technique, Bias Correction and Spatial Disaggregation (BCSD), are widespreadly employed to improve the quality of the raw model output and downscaling throughout the world. Unfortunately, this method has not been applied in China. Consequently, the detailed principle and procedure of BCSD are introduced systematically in this study. Furthermore, the applicability of BCSD over China is also examined based on an ensemble of climate models from phase five of the Coupled Model Intercomparison Project (CMIP5), though the excellent performance of it has been validated for other parts of the world in many works. The result shows that BCSD is an effective, model independent approach to removing biases of model and downscaling. Finally, application scope of BCSD is discussed, and a suite of fine resolution multimodel climate projections over China is developed based on 34 climate models and two emissions scenarios (RCP4.5 and RCP8.5) from CMIP5.     

气候变化对京津唐地区水资源及供需平衡的影响

根据大气环流模型(GCMs)输出的未来气候变化情景,结合历史资料的诊断分析,应用建立的流域水文模型及水资源利用综合评价模型,研究了气候变化对京津唐地区水资源数量和时空变化的影响。在地区未来经济发展及部门用水量预测的基础上,分析了气候变化对供水、需水和部门缺水的影响以及经济损失。     

Climate change and groundwater conditions in the Mekong Region–A review

Changes in the climatic system introduce uncertainties in the supply and management of water resources. The Intergovernmental Panel on Climate Change(IPCC) predicts an increase of 2 to 4 °C over the next 100 years. Temperature increases will impact the hydrologic cycle by directly increasing the evaporation of surface water sources. Consequently, changes in precipitation will indirectly impact the flux and storage of water in surface and subsurface reservoirs(i.e., lakes, soil moisture, groundwater, etc.). In addition, increases in temperature contribute to increases in the sea level, which may lead to sea water intrusions, water quality deterioration, potable water shortages, etc. Climate change has direct impacts on the surface water and the control of storage in rivers, lakes and reservoirs, which indirectly controls the groundwater recharge process. The main and direct impact of climate change on groundwater is changes in the volume and distribution of groundwater recharge. The impact of climate change on groundwater resources requires reliable forecasting of changes in the major climatic variables and accurate estimations of groundwater recharge. A number of Global Climate Models(GCMs) are available for understanding climate and projecting climate change.These GCMs can be downscaled to a basin scale, and when they are coupled with relevant hydrological models, the output of these coupled models can be used to quantify the groundwater recharge, which will facilitate the adoption of appropriate adaptation strategies under the impact of climate change.     

Impact of Climate Change on the Regional Hydrology – Scenario-Based Modelling Studies in the German Rhine Catchment

The aim of the study is an impact analysis of global climate change on regional hydrology with special emphasis on discharge conditions and floods. The investigations are focussed on the major part of the German Rhine catchment with a drainage area of approx. 110,000 km². This area is subdivided into 23 subcatchments. In a first step, the hydrological model HBV-D serves to simulate runoff conditions under present climate for the individual subbasins. Simulated, large scale atmospheric fields, provided by two different Global Circulation Models (GCMs) and driven by the emission scenario IS95a (“business as usual”) are then used as input to the method of expanded downscaling (EDS). EDS delivers local time series of scenario climate as input to HBV-D. In a final step, the investigations are focussed on the assessment of possible future runoff conditions under the impact of climate change. The study indicates a potential increase in precipitation, mean runoff and flood discharge for small return intervals. However, the uncertainty range that originates from the application of the whole model chain and two different GCMs is high. This leads to high cumulative uncertainties, which do not allow conclusions to be drawn on the development of future extreme floods.     

末次冰盛期气候反馈特征研究

末次冰盛期(Last Glacial Maximum,简称LGM)被认为是较适合用来估算气候系统响应对辐射强迫变化的古气候区间之一.理解LGM时期气候反馈过程有助于进一步限定气候敏感度的范围.本研究利用辐射核方法和参加第三次古气候模式比较计划(Paleoclimate Modelling Intercomparison Project Phase Ⅲ,简称PMIP3)的8个耦合模式资料,对比研究了LGM时期与abrupt4xCO2(4CO2)情景下的气候反馈特征.结果表明:全球平均而言,不同情景下温度反馈、水汽反馈和反照率反馈的强度存在显著差异,然而这一关系并不存在于云反馈过程中,这可能与情景间/模式间云反馈的不确定性相联系;在不同情景下,不同反馈过程强度也存在明显空间差异.温度反馈过程的差异主要来源于LGM时期大陆冰盖强迫引起的温度变化的高度空间不均一性和海陆分布改变引起的热带对流活动的变化;水汽反馈变化可能与海陆分布变化引起的沃克环流变化以及全球降温相联系;大陆冰盖和海冰存在是导致LGM时期地表反照率反馈增加的主要原因;而云反馈的差异可能与低云云量和模式间不确定性有关.LGM时期单独强迫数值试验将有助于进一步厘清不同气候状态下气候反馈过程差异的原因.     

Climate change impacts in Romania: Vulnerability and adaptation options

Using the output from five climate model experiments (four equilibrium GCMs and one transient GCM) for a double carbon dioxide atmospheric concentration, the climate change scenarios in Romania for a time slice up to 2075 were constructed. These scenarios were used to assess the climate change impacts on different resource sectors: agricultural crops, forests, and water resources. The vulnerability of each sector and specific adaptation options were then analysed. This revised version was published online in July 2006 with corrections to the Cover Date.