An Updated Coupled Model for Land-Atmosphere Interaction. Part I： Simulations of Physical Processes

A new two-way land-atmosphere interaction model （R42_AVIM） is fulfilled by coupling the spectral atmospheric model （SAMIL_R42L9） developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences （LASG/IAP/CAS） with the land surface model, Atmosphere-Vegetation-Interaction-Model （AVIM）. In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere （SSIB） models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June-July-August （JJA） and December-January- February （DJF） land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.     

The Interactive Climate and Vegetation Along the Pole-Equator Belts Simulated by a Global Coupled Model

The interaction between climate and vegetation along four Pole-Equator-Pole （PEP） belts were explored using a global two-way coupled model, AVIM-GOALS, which links the ecophysiological processes at the land surface with the general circulation model （GCM）. The PEP belts are important in linking the climate change with the variation of sea and land, including terrestrial ecosystems. Previous PEP belts studies have mainly focused on the paleoclimate variation and its reconstruction. This study analyzes and discusses the interaction between modern climate and vegetation represented by leaf area index （LAI） and net primary production （NPP）. The results show that the simulated LAI variation, corresponding to the observed LAI variation, agrees with the peak-valley variation of precipitation in these belts. The annual mean NPP simulated by the coupled model is also consistent with PIK NPP data in its overall variation trend along the four belts, which is a good example to promote global ecological studies by coupling the climate and vegetation models. A large discrepancy between the simulated and estimated LAI emerges to the south of 15°N along PEP 3 and to the south of 18°S in PEP 1S, and the discrepancy for the simulated NPP and PIK data in the two regions is relatively smaller in contrast to the LAI difference. Precipitation is a key factor affecting vegetation variation, and the overall trend of LAI and NPP corresponds more obviously to precipitation variation than temperature change along most parts of these PEP belts.     

Prediction Research of Climate Change Trends over North China in the Future 30 Years

A simulation of climate change trends over North China in the past 50 years and future 30 years was performed with the actual greenhouse gas concentration and IPCC SRES B2 scenario concentration by IAP/LASG GOALS 4.0 （Global Ocean-Atmosphere-Land system coupled model）, developed by the State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics （LASG）, Institute of Atmospheric Physics （IAP）, Chinese Academy of Sciences （CAS）. In order to validate the model, the modern climate during 1951-2000 was first simulated by the GOALS model with the actual greenhouse gas concentration, and the simulation results were compared with observed data. The simulation results basically reproduce the lower temperature from the 1960s to mid-1970s and the warming from the 1980s for the globe and Northern Hemisphere, and better the important cold （1950 1976） and warm （1977-2000） periods in the past 50 years over North China. The correlation coefficient is 0.34 between simulations and observations （significant at a more than 0.05 confidence level）. The range of winter temperature departures for North China is between those for the eastern and western China＇s Mainland. Meanwhile, the summer precipitation trend turning around the 1980s is also successfully simulated. The climate change trends in the future 30 years were simulated with the CO2 concentration under IPCC SRES-B2 emission scenario. The results show that, in the future 30 years, winter temperature will keep a warming trend in North China and increase by about 2.5~C relative to climate mean （1960-1990）. Meanwhile, summer precipitation will obviously increase in North China and decrease in South China, displaying a south-deficit-north-excessive pattern of precipitation.     

Uncertainty of Climate Response to Natural and Anthropogenic Forcings Due to Different Land Use Scenarios

The A.M.Obukhov Institute of Atmospheric Physics,Russian Academy of Sciences (IAP RAS) climate model (CM) of intermediate complexity is extended by a spatially explicit terrestrial carbon cycle module.Numerical experiments with the IAP RAS CM are performed forced by the reconstructions of anthropogenic and natural forcings for the 16th to the 20th centuries and by combined SRES (Special Report on Emission Scenarios) A2-LUH (Land Use Harmonization) anthropogenic scenarios for the 21st century.Hereby,the impact of uncertainty in land-use scenarios on results of simulations with a coupled climate-carbon cycle model is tested.The simulations of the model realistically reproduced historical changes in carbon cycle characteristics.In the IAP RAS CM,climate warming reproduced in the 20th and 21st centuries enhanced terrestrial net primary production but terrestrial carbon uptake was suppressed due to an overcompensating increase in soil respiration.Around year 2100,the simulations the model forced by different land use scenarios diverged markedly,by about 70 Pg (C) in terms of biomass and soil carbon stock but they differed only by about 10 ppmv in terms of atmospheric carbon dioxide content.     

An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and its simulated influence of El Niño on East Asian-western North Pacific climate

This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

Coupled Model Simulations of Climate Changes in the 20th Century and Beyond

Several scenario experiments of the IPCC 4th Assessment Report （AR4） are performed by version g1.0 of a Flexible coupled Ocean-Atmosphere-Land System Model （FGOALS） developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences （IAP/CAS）, including the ＂Climate of the 20th century experiment＂, ＂CO2 1% increase per year to doubling experiment＂ and two separate IPCC greenhouse gases emission scenarios AIB and B1 experiments. To distinguish between the different impacts of natural variations and human activities on the climate change, three-member ensemble runs are performed for each scenario experiment. The coupled model simulations show： （1） from 1900 to 2000, the global mean temper- ature increases about 0.5℃ and the major increase occurs during the later half of the 20th century, which is in consistent with the observations that highlights the coupled model＇s ability to reproduce the climate changes since the industrial revolution; （2） the global mean surface air temperature increases about 1.6℃ in the CO2 doubling experiment and 1.5℃ and 2.4℃ in the A1B and B1 scenarios, respectively. The global warming is indicated by not only the changes of the surface temperature and precipitation but also the temperature increase in the deep ocean. The thermal expansion of the sea water would induce the rise of the global mean sea level. Both the control run and the 20th century climate change run are carried out again with version g1.1 of FGOALS, in which the cold biases in the high latitudes were removed. They are then compared with those from version g1.0 of FGOALS in order to distinguish the effect of the model biases on the simulation of global warming.     

Evaluation of the WRF Model with Different Land Surface Schemes： A Drought Event Simulation in Southwest China during 2009–10

The authors examined the performance of version 3.4.1 of the Weather Research and Forecasting Model（WRF） with various land surface schemes in simulating a severe drought event in Southwest China. Five numerical experiments were completed using the Noah land surface scheme, the Pleim-Xiu land surface scheme, the Noah-MP land surface schemes, the Noah- MP scheme with dynamic vegetation, and the Noah-MP scheme with dynamic vegetation and groundwater processes. In general, all the simulations reasonably reproduced the spatial and temporal variations in precipitation, but significant bias was also found, especially for the spatial pattern of simulated precipitation. The WRF simulations with the Noah-MP series land surface schemes performed slightly better than the WRF simulation with the Noah and Pleim-Xiu land surface schemes in reproducing the severe drought events in Southwest China. The leaf area index（LAI） simulated by the different land surface schemes showed significant deviations in Southwest China. The Pleim-Xiu scheme overestimated the value of LAI by a factor of two. The Noah-MP scheme with dynamical vegetation overestimated the magnitude of the annual cycle of the LAI, although the annual mean LAI was close to observations. The simulated LAI showed a long-term lower value from autumn 2009 to spring 2010 relative to normal years. This indicates that the LAI is a potential indictor to monitor drought events.     

Progress in the Development and Application of Climate Ocean Models and Ocean-Atmosphere Coupled Models in China

A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.     

An Updated Coupled Model for Land-Atmosphere Interaction. Part Ⅱ: Simulations of Biological Processes

In Part Ⅰ, the authors succeeded in coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM) and analyzed the climate basic state and land surface physical fluxes simulated by R42_AVIM. In this Part Ⅱ, we further evaluate the simulated results of the biological processes, including leaf area index (LAI), biomass and net primary productivity (NPP) etc. Results indicate that R42_AVIM can simulate the global distribution of LAI and has good consistency with the monthly mean LAI provided by Max Planck Institute for Meteorology. The simulated biomass corresponds reasonably to the vegetation classifications. In addition, the simulated annual mean NPP has a consistent distribution with the data provided by IGBP and MODIS, and compares well with the work in literature. This land-atmosphere coupled model will offer a new experiment tool for the research on the two-way interaction between climate and biosphere, and the global terrestrial ecosystem carbon cycle.     

An Updated Coupled Model for Land-Atmosphere Interaction. Part Ⅰ: Simulations of Physical Processes

A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral at- mospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmo- spheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sci- ences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM). In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere (SSIB) models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June-July-August (JJA) and December-January- February (DJF) land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.     

Climate simulations based on a different-grid nested and coupled model

An atmosphere-vegetation interaction model (AVIM) has been coupled with a nine-layer General Circulation Model (GCM) of Institute of Atmospheic Physics / State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. AVIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having longitude 7.5° and latitude 4.5°, the vegetation is given a high resolution of 1.5° by 1.5° to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15years and its last ten-year mean of outputs was chosen for analysis.Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteristics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simulated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.     

基于一个不同网格相互嵌套的陆气耦合模式的气候模拟研究

将一个大气植被相互作用模式(AVIM)与大气所LASG的R15九层大气环流模式GOALS相耦合．用来模拟多年平均的全球气候状况。AVIM是一个陆地表面陆面和生理过程相互反馈的模型。作为陆气耦合的第一步,暂不考虑AVIM中的生理过程,而首光将其物理过程[相当于通常的SVAT(土壤—植被—大气—传输方案)模型]与大气所LASG的九层大气环流模式耦合起来．其中海洋模式部分不参与积分,海面温度是多年平均的气候伯。考虑到GCM的分辨率较低(7．5°×4．5°)而植被分布必须有较高的分辨率(1.5°×1.5°),采取广大气与地表面粗细网格的嵌套耦合。模式积分15年,取最后10年的平均值作分析。将模拟的气候要素场与观测值和NCEP再分析资料作了比较,气候模拟结果反映了全球环流与温湿场的主要特征,特别是降水和地面气温的模拟效果较好。这为今后气候模式与生物圈的耦合奠定广一个良好的基础。     

青藏高原大气—植被相互作用的模拟试验Ⅱ.植被叶面积指数和净初级生产力

利用大气－植被相互作用模式AVIM对青藏高原上30个站点进行模拟计算，给出了青藏高原上植被叶面积指数和净初级生产力的分布特征。模拟结果表明，高原上叶面积指数、净初级生产力由东南向西北减少，模拟和观测的分布相一致。分析指出，青藏高原净初级生产力的分布决定于水热条件的共同作用，降水充沛、温度适宜的青藏高原东南部净初级生产力较高，而青藏高原西北部由于降水过少或温度过低，初级生产力很低。     

印度洋海温异常对南亚区域净初级生产力影响的数值模拟

利用中国科学院大气物理研究所发展的全球海洋-大气-动态植被耦合气候模式 (GOALS-AVIM) 的模拟结果, 分析了印度洋海表温度 (SST) 变化及其与南亚陆面净初级生产力 (NPP) 的关系。模式连续运行50年, 取后40年结果分析。对模拟的印度洋海表温度距平 (SSTA) 的经验正交分解 (EOF) 进行分析, 发现第一特征向量在全区域表现为一致变化的趋势, 表明在春夏秋冬四季中印度洋海温都有一致增暖或降温的趋势, 同时赤道印度洋海温一致变化与赤道太平洋Niño3指数有滞后的正相关, 太平洋的Niño3指数变化超前印度洋海温一致变化8个月左右。第二特征向量则表现为热带印度洋SST存在着东西方向振荡的偶极子型振荡特征, 而且偶极子强度有明显季节变化, 并有很明显的季节相位锁定。印度洋SSTA的一致变化的异常趋势与南亚地区的季节和年平均NPP变化表现出很强的同期和滞后相关性; 与南亚地区年平均NPP相关性较高的印度洋夏季SST的EOF第一模态正负相位对应着不同的850 hPa流场、 500 hPa高度场以及南亚地区降水场的异常。分析表明, 印度洋及南亚地区的夏季风加强或减弱导致受南亚地区降水异常, 并使该地区NPP产生异常的增加或减少。     

The Performance of Atmospheric Component Model R42L9 of GOALS／LASG

This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). It is a spectral model truncated at R42(2.8125°long×1.66°lat) resolution and with nine vertical levels, and referred to as R42L9/LASG hereafter. It is also the new version of atmospheric component model R15L9 of the global ocean-atmosphere-land system (GOALS/LASG). A 40-year simulation in which the model is forced with the climatological monthly mean sea surface temperature is compared with the 40-year (1958-97) U.S. National Center for Environmental Prediction (NGEP) global reanalysis and the 22-year (1979-2000) Xie-Arkin monthly precipitation climatology. The mean DJF and JJA geographical distributions of precipitation, sea level pressure, 500-hPa geopotential height, 850-hPa and 200-hPa zonal wind, and other fields averaged for the last 30-year integrat     

Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model

The coupled models of both the Global Ocean-Atmosphere-Land System (GOALS) and the Atmosphere-Vegetation Interaction Model (GOALS-AVIM) are used to study the main characteristics of interannual variations. The simulated results are also used to investigate some significant interannual variability and correlation analysis of the atmospheric circulation and terrestrial ecosystem. By comparing the simulations of the climate model GOALS-AVIM and GOALS, it is known that the simulated results of the interannual variations of the spatial and temporal distributions of the surface air temperatures and precipitation are generally improved by using AVIM in GOALS-AVIM. The interannual variation displays some distinct characteristics of the geographical distribution. Both the Net Primary Production (NPP) and the Leap Area Index (LAI) have quasi 1-2-year cycles. Meanwhile, precipitation and the surface temperatures have 2--4-year cycles. Conditions when the spectrum density values of GOALS are less than those of GOALS-AVIM, tell us that the model coupled with AVIM enhances the simulative capability for interannual variability and makes the annual cycle variability more apparent. Using Singular Value Decomposition (SVD) analysis, the relationship between the ecosystem and the atmospheric circulation in East Asia is explored. The result shows that the strengthening and weakening of the East Asian monsoon, characterized by the geopotential heights at 500 hPa and the wind fields at 850 hPa, correspond to the spatiotemporal pattern of the NPP. The correlation between NPP and the air temperature, precipitation and solar radiation are different in interannual variability because of the variation in vegetation types.