Gross primary production (GPP) is the largest flux and a crucial player in the terrestrial carbon cycle and has been studied extensively, yet large uncertainties remain in the spatiotemporal patterns of GPP in both observations and simulations. This study evaluates the performance of the second version of the Beijing Climate Center Atmosphere−Vegetation Interaction Model (BCC_AVIM2.0) in simulating GPP on multiple spatial and temporal scales in the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiments. Model simulations driven by two meteorological datasets were compared with two observation-based GPP products covering 1982–2008. Spatial patterns of annual GPP show a significant latitudinal gradient in each dataset, increasing from cold (tundra) and dry (desert) biomes to warm (temperate) and humid (tropical rainforest) biomes. BCC_AVIM2.0 overestimates GPP in most parts of the globe, especially in boreal forest regions and Southeast China, while underestimating GPP in subhumid regions in eastern South America and tropical Africa. The four datasets broadly agree on the GPP seasonal cycle, but BCC_AVIM2.0 predicts an earlier beginning of spring growth and a larger amplitude of seasonal variations than those in the observations. The observation-based datasets exhibit slight interannual variability (IAV) and weak GPP linear trends, while the BCC_AVIM2.0 simulations demonstrate relatively large year-to-year variability and significant trends in the low-latitudes and temperate monsoon regions in North America and East Asia. Regarding the possible relationships between annual means of GPP and climate factors, BCC_AVIM2.0 predicts more extensive regions of the globe where the IAV of annual GPP is dominated by precipitation, especially in mid-to-high latitudes of the Northern Hemisphere and tropical Africa, while the observed GPP in the above regions is temperature- or radiation-dominant. The positive GPP biases due to earlier spring growth in boreal forest regions and negative GPP biases in off-equator tropical areas in the BCC_AVIM2.0 simulations imply that cold stress on biomes in boreal mid-to-high latitudes should be strengthened to restrain plant growth, while drought stress in low-latitude regions might be eased to enhance plant production in the future version of BCC_AVIM.

Carbon cycle is constantly influenced by a combination of factors such as climate change,atmospheric CO 2 concentrations,human activities and the nitrogen cycle.However,under the emission scenario of carbon emission peak and carbon emission neutral,there is still great uncertainty about the carbon sink of China,which affects the formulation and implementation of relevant policies for carbon emission reduction and carbon sequestration.Clarifying the scientific understanding of the evolution of carbon and nitrogen cycles in atmospheric science will provide strong scientific support for the realization of carbon peak and carbon neutrality in China.Here,this study reviews the basis and current status of carbon and nitrogen cycle research in atmospheric science,and analyzes the key impacts of current climate change,atmospheric CO 2 increase,carbon and nitrogen cycle interaction,and human activities on the study of carbon and nitrogen cycle in the earth system.The influence of nitrogen nutrients on the carbon cycle fully indicates that biological nitrogen fixation and atmospheric nitrogen deposition have important impacts on China’s carbon sinks,which can reduce the uncertainty of carbon sink simulated by Earth System Models.In addition,since climate change is a comprehensive result of the fast response and slow response of the climate system,it is necessary to distinguish the impact of fast and slow responses on China’s carbon sink,and analyze the changes in carbon sink and carbon sequestration rate of China after anthropogenic carbon emissions are neutral.Finally,on this basis,it would provide a strategical reference for the implementation of the national carbon neutral strategy.

The spatiotemporal features of carbon and nitrogen fluxes over China between 1979 and 2015 were simulated by the Atmosphere–Vegetation Interaction Model (AVIM). The carbon fluxes of gross primary production and net primary production captured the distribution pattern in China better than MODIS and TRENDY data. The results for nitrogen deposition and biological nitrogen fixation show the good performance of the AVIM simulation compared with the CMIP6 and CABLE data, with a deposition rate >4 g N m−2 yr−1 in south China. The variation in the gross primary production and net primary production can be up to 300 and 200 g C m−2 yr−1 in south and southeast China, respectively, and there is a discrepancy between the AVIM and the data from MODIS and TRENDY. This shows the difficulty in simulating the carbon flux in a monsoon climate region and the importance of coupling the nitrogen–carbon fluxes. The standard deviation of nitrogen deposition and biological nitrogen fixation is simulated well by the AVIM and there is a large range in nitrogen deposition of 0.8–1.2 g N m−2 yr−1 in south China. The climatological mean of the fluxes performs better than the variation in the standard deviation and anomaly and this variation in the carbon–nitrogen flux is the key to decreasing bias in future modeling studies.

The improvements and validation of several parameterization schemes in the second version of the Beijing Climate Center Atmosphere-Vegetation Interaction Model (BCC_AVIM2.0) are introduced in this study. The main updates include a replacement of the water-only lake module by the common land model lake module (CoLM-lake) with a more realistic snow-ice-water-soil framework, a parameterization scheme for rice paddies added in the vegetation module, renewed parameterizations of snow cover fraction and snow surface albedo to accommodate the varied snow aging effect during different stages of a snow season, a revised parameterization to calculate the threshold temperature to initiate freeze (thaw) of soil water (ice) rather than being fixed at 0°C in BCC_AVIM1.0, a prognostic phenology scheme for vegetation growth instead of empirically prescribed dates for leaf onset/fall, and a renewed scheme to depict solar radiation transfer through the vegetation canopy. The above updates have been implemented in BCC_AVIM2.0 to serve as the land component of the BCC Climate System Model (BCC_CSM). Preliminary results of BCC_AVIM in the ongoing Land Surface, Snow, and Soil Moisture Model Intercomparison Project (LS3MIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) show that the overall performance of BCC_AVIM2.0 is better than that of BCC_AVIM1.0 in the simulation of surface energy budgets at the seasonal timescale. Comparing the simulations of annual global land average before and after the updates in BCC_AVIM2.0 reveals that the bias of net surface radiation is reduced from −12.0 to −11.7 W m−2 and the root mean square error (RMSE) is reduced from 20.6 to 19.0 W m−2; the bias and RMSE of latent heat flux are reduced from 2.3 to −0.1 W m−2 and from 15.4 to 14.3 W m−2, respectively; the bias of sensible heat flux is increased from 2.5 to 5.1 W m−2 but the RMSE is reduced from 18.4 to 17.0 W m−2.

Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes. However, nutrient cycling is not taken into account in most land surface models for climate change. In this study, a nitrogen model, based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem, was incorporated into the Atmosphere-Vegetation Interaction Model (AVIM) to simulate the carbon cycle under nitrogen limitation. This new model, AVIM-CN, was evaluated against site-scale eddy covariance-based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset. Results showed that the annual mean gross primary production simulated by AVIM-CN (0.7073 gC m(-2)d(-1)) was in better agreement with the corresponding flux data (0.5407 gC m(-2)d(-1)) than the original AVIM (1.1403 gC m(-2)d(-1)) at Damxung station. Similarly, ecosystem respiration was also down-regulated, from 1.7695 gC m(-2)d(-1) to 1.0572 gC m(-2)d(-1), after the nitrogen processes were introduced, and the latter was closer to the observed vales (0.8034 gC m(-2)d(-1). Overall, the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics. A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.

Regional impacts assessment model is an indispensable tool for the study on environmental and economical change and the impacts on ecosystems. In this paper a regional impact assessment model AVIMia, which is an extended version of AVIM is designed. AVIMia is consists of two components: original AVIM (AtmosphereVegetation Interaction Model) and an impact assessment model. Over past 50 year the arid/semi-arid grassland of North China degraded severely due to the change in Climate and social economy. AVIMia is applied to assess the impacts of climatic changes and human activities on grassland in North China, based on historical data, and the different climatic and social scenarios for this region. For the assessment of grassland, specially, the following impact facts are taken into consideration: grazing, cultivation on grassland communities and soil attributes from plot to regional scale. The model is validated by observed data of Inner Mongolia semi-arid grassland. Both the data analysis and model assessment show that: Total aboveground NPP of Inner Mongolia grassland is 771.7*10 kg /yr. Edible aboveground biomass is 498.1*10 kg /yr. Typical steppe and meadow steppe dominate the production of this region. Total estimated livestock holding capacity is 45.51million sheep unit. The grassland is overgrazed more than 100% in Inner Mongolia. Overgrazing is one of the most important reasons inducing the widespread degradation and desertification.

东亚夏季风可显著影响中国季风区气候变化,但是季风区植被净初级生产力(NPP)对夏季风气候变化的响应机理尚不明确.利用大气—植被相互作用模型(AVIM2)模拟了中国季风区植被NPP,分析了其与夏季风指数的相关关系,探讨了其对夏季风变化的响应机理.研究发现,我国南、北方植被对夏季风强度变化的响应方式和机理并不相同.强夏季风年北方植被NPP增加,而南方植被NPP减少.东亚夏季风对中国华北平原植被生长季NPP的作用主要是通过影响该地降水量实现的;京、津、冀地区植被NPP受东亚夏季风带来的气温和降水量变化的叠加影响,因而成为北方对夏季风变化最敏感的区域.东亚夏季风对我国南方江苏、安徽、湖南、湖北、江西植被NPP的作用是通过影响太阳辐射实现的,强夏季风导致太阳辐射减弱,从而使各省植被NPP减少.南方沿海的浙江和福建,强季风年带来的弱太阳辐射和低温是该地植被NPP减少的原因.广东、台湾植被NPP则主要受强夏季风带来的低温影响.

This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model (BCC_CSM) and its four component models (atmosphere, land surface, ocean, and sea ice). Two recent versions are described: BCC_CSM1.1 with coarse resolution (approximately 2.8125°×2.8125°) and BCC_CSM1.1(m) with moderate resolution (approximately 1.125°×1.125°). Both versions are fully coupled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation. Both models well simulate the concentration and temporal evolution of atmospheric CO2 during the 20th century with anthropogenic CO2 emissions prescribed. Simulations using these two versions of the BCC_CSM model have been contributed to the Coupled Model Intercomparison Project phase five (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections.

Extreme precipitation events are expected to increase in frequency and magnitude in future due to global warming, but relevant impacts on tree plantation ecosystem carbon cycle are unknown. In this study, we use an atmosphere–vegetation interaction model (AVIM2) to estimate the likely impacts of extreme precipitation events on carbon fluxes and carbon stocks of a tree plantation in south China. Our results indicate that shifting from moderate precipitation events to extreme precipitation events whilst keeping monthly precipitation unchanged could decrease the tree plantation carbon accumulation. Tree plantation net primary productivity, net ecosystem productivity, soil carbon stock and vegetation carbon stock could decrease by 4.2, 28, 4.3 and 1.4 % during the studying period of 1962–2004, respectively. Though reductions in net primary productivity and net ecosystem productivity are relatively smaller than their annual variations, our sensitivity test shows that the tree plantation carbon stock could decrease by 3.3 % if the assumed extreme precipitation regime lasts for 500 years. Observed and simulated gross primary productivity, ecosystem respiration and net ecosystem productivity have significant positive correlation with soil water content (SWC), especially the deep SWC. The mechanism for the extreme precipitation effect is that the increase in extreme precipitation events will cause SWC to decrease, consequently, reducing carbon fluxes and stocks.

This paper presents an overview on progress in the development of the Beijing Climate Center Climate System Model (BCC_CSM)and its four components:atmosphere,land surface,ocean and sea ice.It focuses on the two recent versions,i. e.,BCC_CSM1.1 with a coarse atmospheric resolution (approximately 2.8125°×2.8125°)and BCC_CSM1.1(m)with a medi-um atmospheric resolution (approximately 1 .125°×1 .125°).Both versions of BCC_CSM are fully-coupled climate-carbon cycle models involving terrestrial and oceanic carbon cycle and vegetation dynamics.They can well simulate the atmospheric CO2 con-centration and its temporal evolution when forced by anthropogenic emissions of CO2 .They contribute to the CMIP5 efforts supporting the IPCC AR5 .A large amount of simulations from BCC_CSM1 .1 and BCC_CSM1 .1 (m)are available for studies on global climate and future climate projection. <br> This paper also shows a few examples using BCC_CSM.There is an evaluation of BCC_CSM1 .1 and BCC_CSM1 .1 (m)in reproducing present-day climate (especially the spatial pattern and seasonal feature of precipitation and surface air temperature, at global scale and in East Asia),in simulating paleoclimate during the last millennium,and in projecting climate change up to 2100.The results show that both BCC_CSM1.1 and BCC_CSM1.1 (m)have good performances compared with the other CMIP5 models.It seems that BCC_CSM1.1(m)with a higher horizontal resolution has a better performance for climate mean state at regional scales than BCC_CSM1.1 does.

The paper examines terrestrial and oceanic carbon budgets from preindustrial time to present day in the version of Beijing Climate Center Climate System Model (BCC_CSM1.1) which is a global fully coupled climate-carbon cycle model. Atmospheric CO2 concentration is calculated from a prognostic equation taking into account global anthropogenic CO2 emissions and the interactive CO2 exchanges of land-atmosphere and ocean-atmosphere. When forced by prescribed historical emissions of CO2 from combustion of fossil fuels and land use change, BCC_CSM1.1 can reproduce the trends of observed atmospheric CO2 concentration and global surface air temperature from 1850 to 2005. Simulated interannual variability and long-term trend of global carbon sources and sinks and their spatial patterns generally agree with other model estimates and observations, which shows the following: (1) Both land and ocean in the last century act as net carbon sinks. The ability of carbon uptake by land and ocean is enhanced at the end of last century. (2) Interannual variability of the global atmospheric CO2 concentration is closely correlated with the El Nino-Southern Oscillation cycle, in agreement with observations. (3) Interannual variation of the land-to-atmosphere net carbon flux is positively correlated with surface air temperature while negatively correlated with soil moisture over low and midlatitudes. The relative contribution of soil moisture to the interannual variation of land-atmosphere CO2 exchange is more important than that of air temperature over tropical regions, while surface air temperature is more important than soil moisture over other regions of the globe.

The temporal and spatial variability of the terrestrial ecosystem in the East Asia monsoon region reveals an obvious response characteristic to the monsoon climate. The Empirical Orthogonal Function (EOF) method is used to analyze the temporal and spatial distribution characteristics of Gross Primary Production (GPP), Net Primary Production (NPP), Net Ecosystem Production (NEP), and vegetation and soil respiration in the summer terrestrial ecosystem of the East Asian monsoon region obtained for the period 1953–2004 by off-line simulation of the Atmosphere Vegetation Interaction Model version 2 (AVIM2). In addition, the mechanism of influences of the East Asian monsoon on the terrestrial carbon cycle is discussed. Results show that during strong monsoon years with lower amounts of rainfall and higher temperatures in the Yangtze–Huaihe River basin, such restricted rainfall limits photosynthesis, which leads to lower GPP values. In southern China, however, rainfall amounts and temperatures are higher, which leads to stronger vegetation and, thus, higher GPP values. Because the East Asia summer monsoon does not significantly influence both plant and soil respiration, the changes in NPP, which marks the difference between GPP and vegetation respiration, and in NEP, which marks the difference between NPP and soil respiration, are consistent with that of GPP. During the strong summer monsoon years a hot and dry climate condition in the Yangtze-Huaihe River basin reduces NPP and NEP, whereas in Southern China the hot but wet climate increases NPP and NEP.

The Atmosphere Vegetation Interaction Model version 2(AVIM2)is used to make an offline simula-tion of terrestrial carbon cycle and its response to climatic variation under the forcing of the meteorological reanalysis data from the National Center for Environmental Prediction.The spatial distribution and its tempo-ral characteristics of global net primary production(NPP)and net ecosystem production(NEP)in the terres-trial ecosystem are simulated from 1953to 2004.Results show that 52-year averaged global NPP and NEP from 1953to 2004are 65Pgc/a and 1.2Pgc/a respectively,and reveal that NPP obviously increases with time,while the trend of increase in NEP is not statistically significant.Although the trends of decadal increases in NPP and NEP are different,in the middle of the 1970stheir decadal changes all revealed an abrupt change.Their growing trends were all decreased after the abrupt point.This is because the Pacific decadal oscillation(PDO)affected the decadal change of El Nin～o-Southern Oscillation(ENSO),which also affected the decadal variation of NPP and NEP.Before 1976,when PDO was in the cool phase,the strength and frequency of the cool phase of ENSO was increased,which led to the cooler and humid climate in the tropical region so that it was beneficial to the increase in NPP and NEP.On the contrary,while the PDO was in a warm phase after 1976,El Nin～o took place frequently,so that in the equatorial region the drier and warmer climate reduced the increasing trends of NPP and NEP.

To examine the potential sensitivity of the Huang‐Huai‐Hai Plain (3H) region of China to potential changes in future precipitation and temperature, a hydrological evaluation using the VIC hydrological model under different climate scenarios was carried out. The broader perspective is providing a scientific background for the adaptation in water resource management and rural development to climate change. Twelve climate scenarios were designed to account for possible variations in the future with respect to the baseline of historic climate patterns. Results from the six representative types of climate scenarios (+2°C and +5°C warming, and 0%, +15%, −15% change in precipitation) show that rising temperatures for normal precipitation and for wet scenarios (+15% precipitation) yield greater increased evapotranspiration in the south than in the north, which is confirmed by the remaining six scenarios described below. For a 15% change in precipitation, the largest increase or decrease of evapotranspiration occurs between 33 and 36°N and west of 118°E, a region where evapotranspiration is sensitive to precipitation variation and is affected by the amount of water available for evaporation. Rising temperatures can lead to a south‐to‐north decreasing gradient of surface runoff. The six scenarios yield a large variation of runoff in the southern end of the 3H, which means that this zone is sensitive to climate change through surface runoff change. The Jiangsu province in the southeastern part of the 3H region shows an obvious sensitivity in soil moisture to climate change. On a regional mean scale, the hydrological change induced by the increasing precipitation from 15% to 30% is more obvious than that induced by greater warming of +5°C relative to +2°C. These simulations identify key regions of sensitivity in hydrological variation to climate change in the provinces of 3H, which can be used as guides in implementing adaptation.

The authors adopt a new two-way land-atmosphere coupled model R42_AVIM. By contrast of experiments with and without vegetation cover, the possible impact of global vegetation distribution on climate and atmosphere circulation is discussed. The results show that the actual vegetation coverage on land can alter the surface characteristic parameters obviously on planetary scale, especially for tropical rainforest and boreal forest. Under the distribution of actual vegetation, the surface net radiation and the latent heat flux will increase, while the surface sensible heat flux will decrease. In the areas where the leaf area index (LAI) is relatively large, the surface temperature will decrease. Moreover, this effect can also extend to the middle and upper troposphere. In addition, the present vegetation distribution enhances the evaporation as well as the corresponding condensation latent heating in the tropics and mid-high latitudes, which makes the meridional circulation stronger. And then, the precipitation increases in the tropics and mid-high latitudes, while decreases in the subtropics. Meanwhile, vegetation can also reduce the sea-land temperature contrast and weaken the Asian summer monsoon.

Global climate change may impact grain production as atmospheric conditions and water supply change, particularly intensive cropping, such as double wheat–maize systems. The effects of climate change on grain production of a winter wheat–summer maize cropping system were investigated, corresponding to the temperature rising 2 and 5°C, precipitation increasing and decreasing by 15% and 30%, and atmospheric CO2 enriching to 500 and 700ppmv. The study focused on two typical counties in the Huang-Huai-Hai (3H) Plain (covering most of the North China Plain), Botou in the north and Huaiyuan in the south, considering irrigated and rain-fed conditions, respectively. Climate change scenarios, derived from available ensemble outputs from general circulation models and the historical trend from 1996 to 2004, were used as atmospheric forcing to a bio-geo-physically process-based dynamic crop model, Vegetation Interface Processes (VIP). VIP simulates full coupling between photosynthesis and stomatal conductance, and other energy and water transfer processes. The projected crop yields are significantly different from the baseline yield, with the minimum, mean (±standardized deviation, SD) and maximum changes being −46%, −10.3±20.3%, and 49%, respectively. The overall yield reduction of −18.5±22.8% for a 5°C increase is significantly greater than −2.3±13.2% for a 2°C increase. The negative effect of temperature rise on crop yield is partially mitigated by CO2 fertilization. The response of a C3 crop (wheat) to the temperature rise is significantly more sensitive to CO2 fertilization and less negative than the response of C4 (maize), implying a challenge to the present double wheat–maize systems. Increased precipitation significantly mitigated the loss and increased the projected gain of crop yield. Conversely, decreased precipitation significantly exacerbated the loss and reduced the projected gain of crop yield. Irrigation helps to mitigate the decreased crop yield, but CO2 enrichment blurs the role of irrigation. The crops in the wetter southern 3H Plain (Huaiyuan) are significantly more sensitive to climate change than crops in the drier north (Botou). Thus CO2 fertilization effects might be greater under drier conditions. The study provides suggestions for climate change adaptation and sound water resources management in the 3H Plain.

Leaf area index (LAI) is an important parameter to characterize the canopy characteristics. It has significant influence on ecosystem carbon cycle researches since its critical factor to determine ecosystem net primary productivity. The large scale leaf area index can be obtained by both remote sensing reversion and ecosystem modeling though uncertainties exist in the two methods. The atmosphere-vegetation interaction model (AVIM2) was used in this study to generate China-wide leaf area index at the resolution of 0.1 grid degree. The spatial distribution and seasonal cycles of model-generated LAI were compared with two datasets. One is satellite-derived LAI which was deduced by Myneni (1997) based on the physical principles of radiative transfer in vegetation and atmosphere. The other was deduced by Hagemann (2002) based on Advanced Very High Resoulution Radiometer (AVHRR) dataset by using heuristic corrective method. Hagemann's dataset has being wildly used in general circulation models (GCMs). The comparison shows that the spatial distribution of China's vegetation LAI is mainly restricted by water conditions, which appears an overall trend of high in southeast and low in northwest. The seasonal cycle of China's LAI is closely correlated with the monsoon's movement in a year. It is identical with seasonal variation trends of temperature and surface solar radiation. The seasonal cycle of LAI in China-wide appears a trend of high in summer, moderate in spring and autumn and low in winter.

A new concept,'anthropocene',was proposed in recent years to emphasize that the Earth environment entered a new epoch in association with the Industrial Revolution,when human activities became able to influence the Earth environment at a global scale.However,human activity not only influences the environment,but also adapts itself to the changing natural surroundings.In order to characterize the interaction between human activity and natural environment,it is necessary to induce an interactive 'anthroposphere' in the Earth system model.Challenges in association with construction of the Earth system model including this new component are discussed.

Based on the American NASA monthly precipitation grid data,the monthly mean surface temperature anomalies grid data from the CO2 Information Analyses Centre,USA,the NCEP/NCAR reanalysis global grid data and the stations observational soil temperature data from the Cold and Arid Regions Environmental and Engineering Research Institute of the Chinese Academy of Sciences,the authors study the Asian-African summer monsoon meridional circulation weakening in the mid-1960s on interdecadal time scale and the related global climatic anomalies phenomena. The results show that the tropospheric temperature reduced obviously and the global oceanic temperature abnormal changes in the mid-1960s are mainly characterized by SST increasing in the Indian Ocean and SST decreasing in the northern Pacific Ocean and the northern Atlantic Ocean. Simultaneously,the soil temperatures at 1.6-m and 3.2-m depths in Chinese continent and the surface temperature in the Tibetan Plateau decreased respectively and remarkably in the mid-1960s,which reduces the thermal contrast between Asian continent and the Indian Ocean. Accordingly,the easterly jet weakened,finally the Asian-African summer monsoon weakened too and the monsoon meridional circulation weakened obviously.