陆面模式CLSM的设计及性能检验Ⅰ.模式设计

在现有陆面模式的基础上,详细考虑了地气系统中的积雪、土壤水热传输、植被及湍流边界层中的各种物理过程,发展了一个既能反映积雪变化、干旱/半干旱区地气交换过程,同时又能描述不同陆面状况物理过程的陆面模式(Comprehensive Land Surface Model,简称CLSM),改善了陆面模式对全球范围内不同下垫面条件下的陆面过程及地-气交换过程的模拟能力.     

Satellite monitoring of global land cover changes and their impact on climate

Land cover is a crucial, spatially and temporally varying component of global carbon and climate systems. Therefore accurate estimation and monitoring of land cover changes is important in global change research. Although, land cover has dramatically changed over the last few centuries, until now there has been no consistent way of quantifying the changes globally.In this study we used long-term climate, soils data along with coarse resolution satellite observations to quantify the magnitude and spatial extent of global land cover changes due to anthropogenic processes. Differences between potential leaf area index, derived from climate-soil-leaf area equilibrium and actual leaf area index obtained from satellite data were used to estimate changes in land cover.Forest clearing for agriculture and irrigated farming in arid and semi-arid lands are found to be two major sources of climatically important land cover changes. Satellite derived Spectral Vegetation indices (SV I) and surface temperatures (T s) show strong impact of land cover changes on climatic processes. Irrigated agriculture in dry areas increased energy absorption and evapotranspiration (ET) compared to natural vegetation. On the other hand, forest clearing for crops decreased energy absorption andET. A land cover classification and monitoring system is proposed using satellite derivedSV I andT s that simultaneously characterize energy absorption and exchange processes. This completely remote sensing based approach is useful for monitoring land cover changes as well as their impacts on climate. Monitoring the spatio-temporal dynamics of land cover is possible with current operational satellites, and could be substantially improved with the Earth Observing System (EOS) era satellite sensors.     

COSMO-CLM2: a new version of the COSMO-CLM model coupled to the Community Land Model

This study presents an evaluation of a new biosphere-atmosphere Regional Climate Model. COSMO-CLM² results from the coupling between the non-hydrostatic atmospheric model COSMO-CLM version 4.0 and the Community Land Model version 3.5 (CLM3.5). In this coupling, CLM3.5 replaces a simpler land surface parameterization (TERRA_ML) used in the standard COSMO-CLM. Compared to TERRA_ML, CLM3.5 comprises a more complete representation of land surface processes including hydrology, biogeophysics, biogeochemistry and vegetation dynamics. Historical climate simulations over Europe with COSMO-CLM and with the new COSMO-CLM² are evaluated against various data products. The simulated climate is found to be substantially affected by the coupling with CLM3.5, particularly in summer. Radiation fluxes as well as turbulent fluxes at the surface are found to be more realistically represented in COSMO-CLM². This subsequently leads to improvements of several aspects of the simulated climate (cloud cover, surface temperature and precipitation). We show that a better partitioning of turbulent fluxes is the central factor allowing for the better performances of COSMO-CLM² over COSMO-CLM. Despite these improvements, some model deficiencies still remain, most notably a substantial underestimation of surface net shortwave radiation. Overall, these results highlight the importance of land surface processes in shaping the European climate and the benefit of using an advanced land surface model for regional climate simulations.     

陆面过程模式研发中的问题

陆面过程研究是充分理解天气/气候/地球系统过程不可或缺的重要主题。本文全面梳理了当前用于数值天气/气候/地球系统模式的陆面过程模式研制的问题,建议了当前陆面过程模式研制中需加强和改进完善的关键内容。特别强调在新一代模式研发中建立包含人类活动的高分辨率全球陆面过程模式;特别强调与其他学科相结合,形成不同行业的预报预测系统或研究方法和工具。建议建设中国的集模式发展、数据分析、模拟方法、高性能计算、数据可视化和应用示范为一体的陆面模拟综合集成平台,为天气/气候/地球系统模式提供陆面过程模式,为开展精细化的全球和区域陆面水文-气象-生态的预报预测提供科技支撑。     

应用风云气象卫星及融合降水资料改进地表参数模拟

气象卫星资料不仅对天气、气候研究非常重要, 对于地表参数模拟和预报也具有重要意义。本文首次将全国自动站观测、卫星降水估计和地面观测融合降水资料(CMORPH)以及风云二号D星(FY-2D)积雪覆盖率数据应用到了高分辨率陆面资料同化系统(u-HRLDAS)。融合降水资料用于驱动u-HRLDAS, 同时用于计算雪水当量;积雪覆盖率资料作为u-HRLDAS强迫变量。区域模拟结果表明, 积雪覆盖率对于地表反照率、地表温度以及地气交换通量模拟有极其重要的影响。密云站土壤湿度模拟结果表明, 融合降水资料准确度优于全球陆面资料同化系统(GLDAS)再分析资料。小汤山站单点验证结果表明, 应用融合降水资料及卫星积雪覆盖率资料可以改进地表温度及地气交换通量的模拟。     

Quantifying uncertainties in projections of extremes��a perturbed land surface parameter experiment

Uncertainties in the climate response to a doubling of atmospheric CO₂ concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO₂. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO₂ is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions.     

Modeling land use and cover as part of global environmental change

Land use and cover changes are important elements of the larger problem of global environmental change. Landuse patterns result in landcover changes that cumulatively affect the global biosphere and climate. We describe efforts to analyze the driving forces behind land transformations and to create land use models that can be linked to other types of global change models. Two efforts to model land use in the U.S. are reviewed. One projects aggregate agricultural, forest, and range land, and the other attempts to model forest land use change at the parcel scale in two mountain landscapes. We conclude with suggestions for new approaches that could clarify the role of land use/cover change in global change and in natural resources management.     

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM) parameterization schemes, meteorological forcing, and land surface parameters on land surface hydrological simulations, and explore to what extent the quality can be improved, a series of experiments with different LSMs, forcing datasets, and parameter datasets concerning soil texture and land cover were conducted. Six simulations are run for the Chinese mainland on 0.1° × 0.1° grids from 1979 to 2008, and the simulated mon...     

Regional and Global Land Data Assimilation Systems: Innovations,Challenges, and Prospects

Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.     

基于EOS/MODIS资料的中国黄土高原西部土地覆盖分类

土地利用和覆盖信息不仅是全球及区域气候模式中所需的重要信息,也是描述生态系统的重要基础数据;获取其现状和变化信息,对于揭示土地覆盖的特征和变化规律,探讨变化的驱动因子,分析评价区域生态环境具有重要现实意义。采用多时相和多光谱遥感资料进行土地覆盖分类已成为一种行之有效的方法。植被类型的差异除了可表现为光谱差异外,还可表现为植被生长规律的差异;植被生长以年为周期,在这个周期内不同植被类型有着各自的生繁衰枯的物候节律,表现出不同的生长规律,其规律性极强,这种规律性也可以作为植被分类的一个出发点。于是,NDVI的时间序列分析成为基于生物气候特征的地表覆盖分类的一种手段。基于MODIS资料,首先对2003年植被生长季内共9个月的NDVI时间序列数据进行离散傅立叶变换,取得该时间序列的均值和前4个频率分量的振幅和相位后;采用ISODATA算法对中国黄土高原西部及其周边地区进行了分层土地覆盖分类,并采用现有的土地覆盖数据集,进行了类别归并和精度评估,分类结果的总体精度达到了81.3%,Kappa系数达到了75.4%,结果证明了这种方法的可行性。     

AN IMPROVED LAND-SURFACE PROCESS MODEL AND ITS SIMULATION EXPERIMENT——PART Ⅰ:LAND-SURFACE PROCESS MODEL AND ITS“OFF-LINE”TESTS AND PERFORMANCE ANALYSES

Based on the existing land-surface schemes and models,an improved Land-surface Process Model(LPM-ZD)has been developed.It has the following major characteristics:(1)The combination of physical equations and empirical analytical formulae are used to construct the governing equations of soil temperature and moisture.Higher resolution of model level and physical equations are adopted for the upper soil layers,and for the lower soil layers,lower resolution of model level is adopted and empirical analytical formulae are used.(2)In land surface hydrological process,the sub-grid distribution of rainfall and its effects are taken into account.(3)A simple snow cover submodel has been used,which includes effects of snow cover on soil thermodynamics and hydrology,as well as albedo.By use of this model and three groups of point observation data,a series of "off-line" tests have been carried out.The simulation results indicate that land-surface process model has good performance and can well simulate diurnal and seasonal variation of land surface processes for many kinds of land surface covers(forest,grass,crops and desert) in different climate zone.The results simulated by the model are consistent with the observations.Later,by use of one group of observation data and the model,a series of sensitivity experiments have been done.It is shown that the model is much sensitive to some parameters,such as initial soil moisture,vegetation physical parameters as well as the proportion of the grid covered with rain.Therefore it is much important for land-surface process model to define these parameters as accurately as possible.     

The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986–2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.     

城市陆面模式设计及检验

针对城市冠层模式(Urban Canopy Model,UCM)的各种局限性,本文首次提出整体城市陆面模式(Bulk Urbanized Land Surface Model,BULSM)的概念,即在现有先进的陆面模式的基础上直接构建城市陆面模式。本文在通用陆面模式(Common Land Model,CoLM)基础上构建整体城市陆面模式,根据城市的特点对CoLM进行了发展和重新参数化。模式采用高分辨率地表分类数据;改进了模式的地表能量平衡方程与水分平衡方程;对反照率、城市地表粗糙度、城市大气廓线、城市人为热、不透水面水分蒸发及积水深度等进行了重新参数化。模式保留了CoLM在自然下垫面的全部特性,加强了CoLM在城市或人为下垫面的模拟和预报能力。区域验证以及与CoLM对比结果表明整体城市陆面模式模拟结果能够显示出北京城区各参数的空间精细化分布情况,能够反映出地表分类对模拟结果的影响。单站点验证以及与CoLM和高分辨率城市陆面同化系统(u-HRLDAS)对比结果表明整体城市陆面模式地表温度模拟结果与CoLM相比有很大提高;和u-HRLDAS相比大部分站点地表温度模拟结果也有一定的改进。     

陆面水文过程研究进展

本文回顾了近年来中国科学院大气物理研究所在陆面水文过程的观测、模式发展以及陆气相互作用研究等方面所取得的重要研究成果。首先概述了近年来在中国区域所开展的陆气相互作用野外观测试验,通过资料分析揭示了国际上现有陆面模式对干旱／半干旱地区陆气相互作用模拟的偏差,指出典型干旱／半干旱区陆面过程参数修正的必要性;随后重点描述了陆面过程模式中积雪覆盖度和冻土参数化方案的发展,中国区域土壤湿度的时空分布特征及其对区域气候的影响,以及中国区域大尺度水文模式的研制和应用等;最后给出了陆面水文过程研究的趋势和发展方向的展望。     

FY-3A陆表温度反演及高温天气过程动态监测

采用FY-3A/VIRR数据,利用Becker局地分裂窗改进算法反演得到逐日陆表温度 (LST), 对2009年一次高温天气过程进行动态监测, 并分析不同下垫面的热环境变化。结果显示:此过程中可见光红外扫描辐射计 (VIRR) 陆表温度产品在敦煌辐射校正场地两次验证的误差为-0.17 K和1.77 K,与同时间过境的MODIS产品均方根误差为2.64 K,直方图对比陆表温度的频数分布基本一致;对高温天气过程监测发现,此次出现以华北的石家庄、郑州、北京等地和西北地区东部的西安等地为中心的两个陆表温度高值区, 部分地区达到了320.2 K以上;城市剖面资料证实城市热岛现象存在,并发现工矿用地的热岛效应不容忽视,主要是大面积的工矿用地周围植被破坏严重,地表增温更为显著。     

A 10-Yr Global Land Surface Reanalysis Interim Dataset (CRA-Interim/Land): Implementation and Preliminary Evaluation

A land surface reanalysis dataset covering the most recent decades is able to provide temporally consistent initial conditions for weather and climate models, and thus is crucial to verifying/improving numerical weather/climate forecasts/predictions. In this paper, we report the development of a 10-yr China Meteorological Administration (CMA) global Land surface ReAnalysis Interim dataset (CRA-Interim/Land; 2007–2016, 6-h intervals, approximately 34-km horizontal resolution). The dataset was produced and evaluated by using the Global Land Data Assimilation System (GLDAS) and NCEP Climate Forecast System Reanalysis (CFSR) global land surface reanalysis datasets, as well as in situ observations in China. The results show that the global spatial patterns and monthly variations of the CRA-Interim/Land, GLDAS, and CFSR climatology are highly consistent, while the soil moisture and temperature values of the CRA-Interim/Land dataset are in between those of the GLDAS and CFSR datasets. Compared with ground observations in China, CRA-Interim/Land soil moisture is comparable to or better than that of GLDAS and CFSR datasets for the 0-10-cm soil layer and has higher correlations and slightly lower root mean square errors (RMSE) for the 10-40-cm soil layer. However, CRA-Interim/Land shows negative biases in 10-40-cm soil moisture in Northeast China and north of central China. For ground temperature and the soil temperature in different layers, CRA-Interim/Land behaves better than the CFSR, especially in East and central China. CRA-Interim/Land has added value over the land components of CRA-Interim due to the introduction of global precipitation observations and improved soil/vegetation parameters. Therefore, this dataset is potentially a critical supplement to the CRA-Interim. Further evaluation of the CRA-Interim/Land, assimilation of near-surface atmospheric forcing variables, and extension of the current dataset to 40 yr (1979–2018) are in progress.     

Satellite Monitoring of the Surface Water and Energy Budget in the Central Tibetan Plateau

The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP （Coordinated Enhanced Observing Period）-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system （LDAS-UT） to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.     

Climate response to introduction of the ESA CCI land cover data to the NCAR CESM

The European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC, from 1992 to 2015) is introduced to the National Center for Atmospheric Research Community Earth System Model version 1.2.1 (NCAR CESM1.2.1). In comparison with the original land surface data in the Community Land Model version 4 (ORG), the new data features notable land use and land cover change (LULCC) with increased forests over northeastern Asia and Alaska by decreasing shrublands and grasslands. Overestimated bare land cover over the Tibetan Plateau (TP) and the Rocky Mountains in the ORG are corrected with the replacements by grasslands and shrublands respectively in the new data. The model simulation results show that with the introduction of the ESA CCI-LC, the simulated surface albedo, surface net radiation flux, sensible and latent heat fluxes are relatively improved over the regions where significant LULCC exists, such as northeastern Asia, Alaska, the TP, and Australia. Surface air temperature, precipitation, and atmospheric circulation are improved in boreal winter but degraded in summer. The winter warming over northeastern Asia results from increased longwave downwelling flux and adiabatic heating while the notable winter cooling over Alaska is attributed to strong cold advection followed by reduced longwave downwelling flux. LULCC alters precipitation by influencing water vapor content. In winter, LULCC affects atmospheric circulation via modulating baroclinicity while in summer, it influences land-sea thermal contrast, thus affecting the intensity of East Asian summer monsoon. LULCC also alters the simulated dust burden.

     

陆面过程模式BCC_AVIM中地表覆盖数据现状

地表覆盖是陆面和气候模式中的一个重要基础数据。以陆面过程模式BCC_AVIM为例,介绍模式中的地表覆盖数据变量、数据分辨率、不同类型数据的来源,重点比较分类方法差异巨大且类型众多的植被覆盖。综述比较了国际和国内常用的几套全球地表覆盖数据的来源、分类系统和分类方法以及空间分辨率,根据陆面过程模式的地表覆盖数据需求,确定不同全球土地覆盖数据在模式中的应用方法,讨论分析了全球地表覆盖产品在模式应用中存在的差距,提出不同遥感数据产品之间一致性较差的可能解决方案,探讨遥感数据产品在模式中应用的可能方式,以期更好地发挥全球地表覆盖数据产品的作用。     

Performance of RegCM4 over Major River Basins in China

A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.