云中可溶性物质对冰核化影响的实验研究

用冷台冻滴和２ｍ３云室试验相结合的方法，研究了云中可溶性物质对冰核化的影响。实验结果表明，一般云中观测到的可溶性盐类气溶胶（如ＮａＣｌ、（ＮＨ４）２ＳＯ４等）在温度高于－１８℃时不易成为冰核。而高浓度的可溶性铵盐（如（ＮＨ４）２ＳＯ４，ＮＨＣｌ等）则能显著提高ＡｇＩ的成冰温度。（ＮＨ４）２ＳＯ４能使ＡｇＩ成冰晶数在－１０℃提高２个量级，－６℃提高约１个量级。该结果对人工催化技术有一定指导意义。     

南京市夏季城市不同功能区气溶胶污染特征

利用ＷＰＳ（宽范围颗粒粒径谱仪）、Ａｎｄｅｒｓｏｎ Ⅱ型９级撞击采样器测量了２００８年夏季典型日南京钟山风景区、鼓楼商业区与江北工业区大气气溶胶数浓度谱分布和质量浓度,分析了城市不同功能区气溶胶粒子的分布特征．结果表明：各功能区大气颗粒物浓度均比较高,达到１０４ｃｍ－３,数浓度谱均为单峰型,峰值集中在００１～００４μｍ;其中气溶胶粒子数浓度主要集中在００１～０２μｍ粒径范围内,其日变化受汽车尾气排放、混合层高度变化的影响较大,且呈现明显的双峰型;粒径为００１～０１μｍ的超细粒子对总数粒子贡献较大,鼓楼为９３２８％,江北为８１６６％,钟山为６６５２％;细粒子（粒径＜１１μｍ）与ＴＳＰ质量浓度的比值钟山为９２％,鼓楼３３７７％, 江北２４９８％;质量浓度主要为粗粒子（粒径≥１１μｍ）贡献,但是鼓楼与江北的细粒子的贡献也非常大,说明这两个功能区的细粒子的污染值得关注;数浓度和相对湿度（ＲＨ）有密切联系,当ＲＨ＜７５％时其峰值随着相对湿度的增大而增大,当ＲＨ＞７５％时其峰值随着相对湿度的增大而减少,并且相对湿度对细粒子的影响要大于对大粒子的影响．     

东亚地区气象参数卫星遥感反演理论和方法研究Ⅱ:ISPRM和VSPRM2

在改进的同步物理模式（ＩＳＰＲＭ）实践基础上,根据泛函数变分原理,按ＴＯＶＳ遥感方程,提出了较普遍的变分同步物理反演模式（ＶＳＰＲＭ２）,其一级功能（ＶＳＰＲＭ１）和ＩＳＰＲＭ完全相同。ＶＳＰＲＭ从协合（ｓｙｎｅｒｇｙ）遥感反演机理,进一步拓宽和发展了ＩＳＰＲＭ模式。分析了ＶＳＰＲＭ２模式性能,指出这类模式的反演潜力。特别着重分析了模式的水汽核函数参数化和水汽遥感反演问题。针对这类非适定反问题的强欠定性质,为妥善使用先验信息,以获得精确的正演辐射率Ｒ。,还对透射率精确计算,低层温、湿廓线反演通道最佳选择和云层影响修正的改进作了进一步分析。经过长期业务运行条件反演比较实验,结果表明改进的物理反演方法（ＩＳＰＲＭ）是适于中国大陆包括青藏高原温、湿参数分布的反演方法,特别在有云条件下能反演出温、湿廓线。     

工业SO2排放对东亚和我国温度变化的影响

根据东亚地区工业ＳＯ２排放资料和硫化物输送模式模拟得到的ＳＯ２－４气溶胶的区域分布状况,计算了ＳＯ２－４对地气系统的直接辐射强迫作用,并用能量平衡模式模拟了其对东亚和我国温度变化的影响。模拟结果和资料分析表明,８０年代以来在全球变暖的背景下,我国南方大部分地区平均气温（特别是日最高温度和白天温度）普遍下降。工业ＳＯ２排放引起的大气中ＳＯ２－４含量的增加可能是引起降温的主要原因之一     

给定参数条件下海温脉动随机模式的混沌行为

从Ｓａｌｔｚｍａｎ海气随机气候模式出发，得到了海温脉动θ＇的Ｌａｎｇｅｖｉｎ方程以及对应的Ｆｏｋｋｅｒ－ｐｌａｎｋ方程。在给定参数条件下求数值解，得到的概率密度曲线ｐ（ｘ，ｔ）具有多个极大值，并在ｐ（ｘ，ｔ）－ｐ（ｘ，ｔ＋τ）相空间中呈现Ｃａｎｔｏｒ集合图象，表明该随机系统在上述参数条件下出现了混沌行为。     

IAP PSSCA 两组预测试验的评估及比较Ⅰ.降水部分

利用中国科学院大气物理研究所研制的短期气候距平数值预测系统（ＩＡＰ ＰＳＳＣＡ）,采用两种版本的大气环流模式：ＡＧＣＭ１．１和ＡＧＣＭ１．２,分别以２月１１～１９日的９天大气观测值为初始场,以给定海温边界场,对１９８０～１９９４年的１５年的降水异常进行了两组集合后报试验。对试验结果进行定量评估表明：ＩＡＰ ＰＳＳＣＡ对降水异常具有一定的预测能力,特别是在中国东部受东亚季风及海温异常影响的地区,ＩＡ     

用STEM—Ⅱ模式研究东亚地区春季沙尘气溶胶对硫化物输送和沉降的影响

利用ＳＴＥＭ－ＩＩ三维区域尺度大气化学模式,研究了１９９４年３月１日至１４日东亚地区春季沙尘气溶胶对硫化物输送和沉降的影响。结果表明,ＳＯ２和ＳＯ２４的大值区主要出现在我国东部地区。在模拟时段,日本地区火山源的排放对该地区大气中Ｓ分布的贡献达１０％～３０％。并与当时飞机的观测结果相吻合。模拟区域内ＳＯ２和ＳＯ２４的收支的分析研究表明,在硫的总排放量中,从东边界面流出去的输送通量最大,并出现在３０～４００Ｎ带的２～６ｋｍ高度上,这是与该地区最大的人为排放源所在地相一致的。最后,给出了模拟时段整个对流层大气ＳＯ２－４气溶胶含量的分布,还仨算了ＳＯ２－４气溶胶对地气系统的直接辐射强迫和温度变化的影响。     

赤道东太平洋不同持续时间的海温正常异常对东亚夏季气候影响的数值 …

利用ＩＡＰ两层大气环流模式及９层大气环流谱模式,模拟研究了大气对不同持续时间的赤道太平洋正ＳＳＴＡ的响应,对积分结果进行分析发现,尽管ＳＳＴＡ的持续时间不同（分别为１月;１～２月及１～４月）,但其引起东亚夏季大气环流和气候异常的分布都十分相似,而且有十分相近的时间演变形式,因此,虽然赤道东太平洋ＳＳＴＡ作为一中外源强迫对东亚夏季大气环流和气候有羊明显的影响,但是这种影响对于ＳＳＴＡ的持续时间（１个     

斜压罗斯贝波非线性问题的研究

本文利用两层斜压准地转模式，讨论了波－流相互作用问题，得到以下结论：（１）当大气中基本流切变较大时，波流间能量交换明显。切变较小时，波幅变化较小；（２）在较小的基本流切变下，波动可出现稳定的平衡态，此平衡态多为相当正压状态；（３）斜压波在发展过程中，温度场和流场之间具有制约关系     

用IAP/LASG GOALS模式模拟CO_2增加引起的东亚地区气候变化(英文)

用一个全球耦合的海洋──大气──陆地系统模式（ＩＡＰ／ ＬＡＳＧ ＧＯＡＬＳ）研究因 ＣＯ２增加引起的全球增暖,重点是讨论东亚地区气候变化。完成了两个试验,一个是ＣＯ２含量保持不变的对照试验,一个是ＣＯ２浓度按每年１０％增加的扰动试验。结果表明,在对照试验中没有出现气候漂移,在ＣＯ２含量加倍时全球平均地面气温将增加１．６５℃。ＧＯＡＬＳ模式能较好模拟观测的东亚温度和降水的空间分体和年循环,但模拟的年平均温度略偏低、年降水稍偏大。在ＣＯ２含量加倍时,东亚地区温度和降水将分别增加２．１℃和５％,最大增温出现在中纬度大陆上,最大的降水增加出现在２５°Ｎ附近。     

CAMS-CSM模式及其参与CMIP6的方案

世界气候研究计划(WCRP)组织开展的耦合模式比较计划已实施到第六阶段（CMIP6),中国气象科学研究院发展的气候系统模式CAMS-CSM是注册参加CMIP6的模式之一。除CMIP6要求的气候诊断、评估和描述试验（DECK）以及历史气候模拟试验（Historical）外,CAMS-CSM还计划参加情景模式比较计划（ScenarioMIP)、云反馈模式比较计划（CFMIP)、全球季风模式比较计划（GMMIP）和高分辨率模式比较计划（HighResMIP)这4个模式比较子计划（MIPs)。文中通过介绍CAMS-CSM的基本情况和模拟性能,以及计划参加的CMIP6试验及MIPs,为模式试验数据使用者提供参考。     

西北干旱和半干旱地区地表蒸发计算方法评估应用

针对我国西北地区干旱和半干旱的气候特征,以及相对简单的地表覆盖特点,论证了互补相关模型计算西北地区蒸发量的可行性。通过中国科学院山东禹城试验站农田观测资料,分析了植被多样性分布对互补相关模型的影响。得出植被的多样性以及植被物候变化的非同步变化是造成互补相关模型中关键参数——大尺度平流参数季节变化的重要原因。并利用遥感反演参数和气象台站观测数据计算了覆盖类型相对单一的西北地区蒸发。结果表明,蒸发与地表覆盖类型的空间分布一致,与气象台站20 cm蒸发皿观测数据呈现空间互补特征,其季节变化与区域降水、温度和植被物候变化相吻合。       

LASG全球海洋-大气-陆面系统模式(GOALS/LASG)及其模拟研究

该文扼要介绍了ＬＡＳＧ第一版本全球海洋－大气－陆面系统模式（ＧＯＡＬＳ／ＬＡＳＧ）的发展和结构，及其对气候平均态、季节变化和年际变化的模拟，以及近期发展计划．     

LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in this paper.The experiment forced by CORE-II(Co-ordinated Ocean–Ice Reference Experiments,Phase II)data(1948–2009)is called OMIP1,and that forced by JRA55-do(surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis)data(1958–2018)is called OMIP2.First,the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described.Second,the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation.We find that the mean states,interannual variabilities,and long-term linear trends can be reproduced well by the two experiments.The differences between the two datasets are also discussed.Finally,the usage of these data is described.These datasets are helpful toward understanding the origin system bias of the fully coupled model.     

Uncertainty in resilience to climate change in India and Indian states

This study builds on an earlier analysis of resilience of India and Indian states to climate change. The previous study (Brenkert and Malone, Clim Change 72:57–102, 2005) assessed current resilience; this research uses the Vulnerability–Resilience Indicators Model (VRIM) to project resilience to 2095 and to perform an uncertainty analysis on the deterministic results. Projections utilized two SRES-based scenarios, one with fast-and-high growth, one with delayed growth. A detailed comparison of two states, the Punjab and Orissa, points to the kinds of insights that can be obtained using the VRIM. The scenarios differ most significantly in the timing of the uncertainty in economic prosperity (represented by GDP per capita) as a major factor in explaining the uncertainty in the resilience index. In the fast-and-high growth scenario the states differ most markedly regarding the role of ecosystem sensitivity, land use and water availability. The uncertainty analysis shows, for example, that resilience in the Punjab might be enhanced, especially in the delayed growth scenario, if early attention is paid to the impact of ecosystems sensitivity on environmental well-being of the state. By the same token, later in the century land-use pressures might be avoided if land is managed through intensification rather than extensification of agricultural land. Thus, this methodology illustrates how a policy maker can be informed about where to focus attention on specific issues, by understanding the potential changes at a specific location and time—and, thus, what might yield desired outcomes. Model results can point to further analyses of the potential for resilience-building.     

Extended application of the conditional nonlinear optimal parameter perturbation method in the common land model

An extension of the conditional nonlinear optimal parameter perturbation (CNOP-P) method is applied to the parameter optimization of the Common Land Model (CoLM) for the North China Plain with the differential evolution (DE) method. Using National Meteorological Center (NMC) Reanalysis 6-hourly surface flux data and National Center for Environmental Prediction/Department of Energy (NCEP/DOE) Atmospheric Model Intercomparison Project II (AMIP-II) 6-hourly Reanalysis Gaussian Grid data, two experiments (I and II) were designed to investigate the impact of the percentages of sand and clay in the shallow soil in CoLM on its ability to simulate shallow soil moisture. A third experiment (III) was designed to study the shallow soil moisture and latent heat flux simultaneously. In all the three experiments, after the optimization stage, the percentages of sand and clay of the shallow soil were used to predict the shallow soil moisture in the following month. The results show that the optimal parameters can enable CoLM to better simulate shallow soil moisture, with the simulation results of CoLM after the double-parameter optimal experiment being better than the single-parameter optimal experiment in the optimization slot. Furthermore, the optimal parameters were able to significantly improve the prediction results of CoLM at the prediction stage. In addition, whether or not the atmospheric forcing and observational data are accurate can seriously affect the results of optimization, and the more accurate the data are, the more significant the results of optimization may be.     

The flexible global ocean-atmosphere-land system model, Grid-point Version 2: FGOALS-g2

This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOALS-g2) and the preliminary evaluations of its performances based on results from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiment design. The results suggest that many obvious improvements have been achieved by the FGOALS-g2 compared with the previous version,FGOALS-g1, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example,FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.     

The Impacts of the Interannual Variability of Vegetation on the Interannual Variability of Global Evapotranspiration: A Modeling Study

The impact of the interannual variability (IAV) of vegetation on the IAV of evapotranspiration is investigated with the Community Land Model (CLM3.0) and modified Dynamic Global Vegetation Model (DGVM). Two sets of 50-year off-line simulations are used in this study. The simulations begin with the same initial surface-water and heat states and are driven by the same atmospheric forcing data. The vegetation exhibits interannual variability in one simulation but not in the other simulation. However, the climatological means for the vegetation are the same. The IAV of the 50-year annual total evapotranspiration and its three partitions (ground evaporation, canopy evaporation, and transpiration) are analyzed. The global distribution of the evapotranspiration IAV and the statistics of evapotranspiration and its components in different ecosystems show that the IAV of ground evaporation is generally large in areas dominated by grass and deciduous trees, whereas the IAV of canopy evaporation and transpiration is large in areas dominated by bare soil and shrubs. For ground evaporation, canopy evaporation, and transpiration, the changes in IAV are larger than the mean state over most grasslands and shrublands. The study of two sites with the same IAV in the leaf area index (LAI) shows that the component with the smaller contribution to the total evapotranspiration is more sensitive to the IAV of vegetation. The IAV of the three components of evapotranspiration increases with the IAV of the fractional coverage (FC) and the LAI. The ground evaporation IAV shows the greatest increase, whereas the canopy evaporation shows the smallest increase.     

A Nine-layer Atmospheric General Circulation Model and Its Performance

ＡＮｉｎｅ－ｌａｙｅｒＡｔｍｏｓｐｈｅｒｉｃＧｅｎｅｒａｌＣｉｒｃｕｌａｔｉｏｎＭｏｄｅｌａｎｄＩｔｓＰｅｒｆｏｒｍａｎｃｅＷｕＧｕｏｘｉｏｎｇ（吴国雄），ＬｉｕＨｕｉ（刘辉），ＺｈａｏＹｕｃｈｅｎｇ（赵宇澄），ａｎｄＬｉＷｅｉｐｉｎｇ（李伟平），（...