Improving Simulation of the Terrestrial Carbon Cycle of China in Version 4.5 of the Community Land Model Using a Revised Vcmax Scheme

The maximum rate of carboxylation(Vcmax) is a key photosynthetic parameter for gross primary production(GPP) estimation in terrestrial biosphere models. A set of observation-based Vcmax values, which take the nitrogen limitation on photosynthetic rates into consideration, are used in version 4.5 of the Community Land Model(CLM4.5). However, CLM4.5 with carbon-nitrogen(CN) biogeochemistry(CLM4.5-CN) still uses an independent decay coefficient for nitrogen after the photosynthesis calculation. This means that the nitrogen limitation on the carbon cycle is accounted for twice when CN biogeochemistry is active. Therefore, to avoid this double nitrogen down-regulation in CLM4.5-CN, the original Vcmax scheme is revised with a new one that only accounts for the transition between Vcmax and its potential value(without nitrogen limitation). Compared to flux towerbased observations, the new Vcmax scheme reduces the root-mean-square error(RMSE) in GPP for mainland China by 13.7 g C m-2 yr-1, with a larger decrease over humid areas(39.2 g C m-2 yr-1). Moreover, net primary production and leaf area index are also improved, with reductions in RMSE by 0.8% and 11.5%, respectively.     

内蒙古地区下垫面变化对土壤湿度数值模拟的影响

利用第二次全国土壤调查土壤质地数据（SNSS）和中国区域陆地覆盖资料（CLCV）将陆面过程模式CLM3.5（Community Land Model version 3.5）中基于联合国粮食农业组织发展的土壤质地数据（FAO）和MODIS卫星反演的陆地覆盖数据（MODIS）进行了替换,使用中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）大气强迫场资料,分别驱动基于同时改进土壤质地和陆地覆盖数据的CLM3.5（CLM-new）、基于只改进陆地覆盖数据的CLM3.5（CLM-clcv）、基于只改进土壤质地数据的CLM3.5（CLM-snss）和基于原始下垫面数据的CLM3.5（CLM-ctl）,对内蒙古地区2011～2013年土壤湿度的时空变化进行模拟试验,研究下垫面改进对CLM3.5模拟土壤湿度的影响。将四组模拟结果与46个土壤水分站点观测数据进行对比分析,结果表明:相对于控制试验,CLM-clcv、CLM-snss和CLM-new都能不同程度地改进土壤湿度模拟,其中CLM-clcv主要在呼伦贝尔改进明显,CLM-snss则在除呼伦贝尔以外的大部地区改进显著,CLM-ctl模拟的土壤湿度在各层上均系统性偏大,而CLM-new模拟土壤湿度最好地反映出内蒙古地区观测的土壤湿度的时空变化特征,显著改善了土壤湿度的模拟,体现在与观测值有着更高的相关系数和更小的平均偏差与均方根误差。     

三个陆面过程模式在西北半干旱区的模拟性能对比

利用NOAH(The Community Noah Land Surface Model)、SHAW(Simultaneous Heat and Water)和CLM(Community Land Model)3个不同的陆面过程模式及兰州大学(Semi-Arid Climate Observatory and Laboratory,SACOL)2007年的观测资料,对黄土高原半干旱区的陆面过程进行了模拟研究。通过与观测值间的对比,考察不同陆面过程模式在半干旱区的适用性。研究结果表明:3个模式在半干旱区的模拟性能有较大差异。其中,CLM模式模拟的20 cm以上的浅层土壤温度最优,SHAW模式模拟的深层土壤温度最优;SHAW模式模拟的土壤含水量与观测值最为接近,而NOAH和CLM模式模拟值有较大偏差;3个模式均能较好地模拟地表反射辐射,其中SHAW模式模拟值与观测值的偏差最小;对地表长波辐射的模拟,CLM模式的模拟最优;3个模式均能较好地反映感热、潜热通量的变化趋势,其中CLM模式对感热的模拟性能优于其他两个模式,在有降水发生后的湿润条件下,CLM模式对潜热的模拟性能最优,而无降水的干燥条件下,CLM模式的模拟偏差最大,NOAH模式对冬季潜热的模拟最优。总体而言,CLM模式能够更好地再现半干旱区地气之间的相互作用,但模式对土壤含水量及干燥条件下的潜热通量的模拟较差,模式对半干旱区陆气间的水文过程还有待进一步的研究和改进。     

基于CMIP6模式优化集合平均预估21世纪全球陆地生态系统总初级生产力变化

利用国际耦合模式比较计划第六阶段(CMIP6)中18个地球系统模式总初级生产力(GPP)模拟数据,基于传统的多模式集合平均(MME)和可靠集合平均方法(REA),在4个未来情景(SSP1-2.6,SSP2-4.5,SSP3-7.0和SSP5-8.5)下预估了21世纪全球陆地生态系统GPP的变化量,并分析了GPP变化的驱动因子。研究结果表明：在4个未来情景下,基于REA方法预估的全球陆地生态系统年GPP在未来时期(2068—2100年)比历史时期(1982—2014年)分别增长了(14.85±3.32)、(28.43±4.97)、(37.66±7.61)和(45.89±9.21)Pg C,其增量大小和不确定性都明显低于MME方法。在4个情景下,大气CO₂浓度增长对GPP变化的贡献最大,基于REA方法计算的贡献占比分别为140%、137%、115%和75%;除SSP5-8.5(24%)外,其他情景下升温均导致全球陆地生态系统GPP降低(-42%、-37%、-16%),部分抵消了CO₂施肥效应的正面贡献。温度的影响存在纬度差异：升温在低纬度地区对GPP有负向贡献,在中高纬度地区为正向贡献。降水和辐射变化对GPP变化的贡献相对较小。     

基于中国植被数据的陆面覆盖及其对陆面过程模拟的影响

本文基于中国1:100万植被图、马里兰大学AVHRR森林覆盖资料和中国753个气象站点40年的降水气温资料, 发展了一套用于气候模拟的中国陆面覆盖资料(Chinese land cover derived from vegetation map, 简称CLCV)。该套资料与CLM(Community Land Model)原来所用的MODIS (Moderate Resolution Imaging Spectroradiometer) 陆面覆盖资料相比有较大不同: 其中裸土比例减少了14.5%, 森林、灌木、草原和农作物比例分别增加了3.3%、4.8%、4.4%和0.3%, 冰川、湖泊和湿地比例分别增加了0.4%、0.8%和0.6%。将CLCV和MODIS资料分别与全国土地资源概查汇总结果分省统计资料和基于中国1 km土地利用图的土地利用资料比较表明, CLCV与两者较为接近。最后, 利用CLM模式分别采用CLCV与MODIS陆面覆盖资料在中国区域内进行数值模拟, 结果显示, 使用CLCV资料所模拟的蒸散增加了约7.7 mm/a; 地表反照率、 感热和径流分别减小了约0.7%、 0.3 W/m2和7.6 mm/a; 与MODIS卫星反演地表反照率和GRDC (Global Runoff Data Centre) 径流资料比较表明, 利用CLCV资料所模拟的地表反照率有一定改进, 并能基本模拟出径流分布趋势。     

1981—2019年全球陆地生态系统碳通量变化特征及其驱动因子

陆地生态系统碳汇显著降低大气CO₂浓度上升和全球变暖的速率,受人类活动和气候变化的影响,陆地生态系统碳通量具有强烈的时空变化,其估算结果仍存在较大的不确定性,不同因子的贡献尚不清晰。为此,利用遥感驱动的陆地生态系统过程模型BEPS模拟分析了1981—2019年全球陆地生态系统碳通量的时空变化特征,评价了大气CO₂浓度、叶面积指数（Leaf Area Index,LAI）、氮沉降、气候变化对全球陆地生态系统碳收支变化的贡献。1981—2019年全球陆地生态系统总初级生产力（Gross Primary Productivity,GPP）、净初级生产力（Net Primary Productivity,NPP）和净生态系统生产力（Net Ecosystem Productivity,NEP）的平均值分别为115.3、51.3和2.7 Pg·a^-1（以碳质量计,下同）,上升速率分别为0.47、0.21和0.06 Pg·a^-1。全球大部分区域GPP和NPP显著增加,NEP显著上升（p<0.05）的区域明显少于GPP和NPP。1981—2019年,全球NEP累积为105.2 Pg,森林、稀树草原及灌木、农田和草地的贡献分别为76.4、15.8、9.4和3.6 Pg。CO₂浓度、LAI、氮沉降和气候变化各自对NEP的累积贡献分别为58.4、20.6、0.7和-43.6 Pg,全部4个因子变化对NEP的累积贡献为39.8 Pg,其中CO₂浓度上升是近40 a全球陆地生态系统NEP上升的主要贡献因子,其次为LAI。     

陆面过程模式CLM4.5在半干旱区退化草原站的模拟性能评估

利用国际协同强化观测期(CEOP)在中国半干旱区退化草地站——通榆站的观测资料,对一个较为完善的陆面过程模式NCAR_CLM4.5(Community Land Model 4.5)的模拟性能进行检验。模拟结果与观测资料的对比表明,CLM4.5能很好地模拟出观测站点的辐射通量、水热交换、土壤温湿的空间分布和时间变化特征。但地表吸收的辐射模拟值略低,土壤湿度偏低,地表吸收的辐射及土壤温度等日变化略大;大气强迫变量处于某些特定的形势下时,模拟存在较大误差,如8月底的模拟。此外,冬季辐射通量、水热交换以及土壤温湿的模拟均存在较大误差,说明CLM4.5模式在冬季地表物理过程的参数化方案上需要进一步改进。     

LPJ模型对1981～1998年中国区域潜在植被分布和碳通量的模拟

利用一个基于过程的动态植被模型LPJ DGVM（Lund Potsdam Jena Dynamic Global Vegetation Model）,模拟了中国区域潜在植被分布,考察了1981～1998年中国区域净初级生产〖JP〗力（NPP）、异养呼吸（Rh）和净生态系统生产力（NEP）的年际变化。模拟结果表明,在LPJ模型提供的植被功能类型（PFT）划分的条件下,中国区域除了分布裸土外,主要分布了6种潜在植被功能类型,即热带常绿阔叶林带、温带常绿阔叶林带、温带夏绿阔叶林带、北方常绿针叶林带、北方夏绿针叶林带和温带草本植物。在所考察的时间段内,中国区域总NPP从2.91 Gt · a-1（C）（1982年）变化到3.37 Gt · a-1（C）（1990年）,平均每年增加0.025 Gt（C）,其平均增长率为096%。中国区域总Rh从2.59 Gt · a-1（C）（1986年）变化到3.19 Gt · a-1（C）（1998年）,具有105% 的平均年增长率,即平均每年增加0.025 Gt（C）,并且中国区域温带草本植物相比其他植被功能类型,其NPP和Rh线性增加的趋势最为显著。研究结果还表明,LPJ模型在引入火灾机制后,中国区域总NEP的变化范围更加合理,即每年总NEP在-0.06 Gt · a-1（C）（1998年）和0.34 Gt · a-1（C）（1992年）之间变化,其平均值为0.12 Gt · a-1（C）。该结果表明,在所考察的时间段内,中国区域的陆地生态系统是碳汇。上述结果与其他研究结果基本一致,因而此模型模拟中国区域潜在植被分布和碳循环是有效的。       

无定河区域1981～2001年植被生产力和水量平衡对气候变化的响应

基于土壤-植被-大气系统过程模型(VIP模型)和NOAA-AVHRR遥感信息,模拟了1981～2001年黄土高原无定河区域(36～40°N,108～111°E)植被总第一性生产力(GPP)和水量平衡的时空变化特征及其对气候变化的响应.结果表明:该研究区域1981～2001年间气候有明显变暖趋势,斜率为0.08℃·a-1,降水量下降,斜率为-3.2 mm·a-1.GPP年总量1998年前呈上升趋势,之后呈下降趋势,平均值为289g·m-2·a-1(C),最大值和最小值分别为377 g·m-2·a-1(C)(1994年)和143 g·m-2·a-1(C)(2001年).年降水量、蒸散量和径流量随时间都呈下降趋势,且其空间分布有明显的由南向北梯度递减特征.     

陆面模式中土壤湿度影响蒸散参数化方案的评估

本文将四个常见陆面模式CLM3.5（Community Land Model Version 3.5）、Noah_LSM（The Noah Land Surface Model）、VIC（Variable Infiltration Capacity）以及SSiB（The Simplified Simple Biosphere Model）中土壤湿度影响蒸散的参数化方案进行简化,并利用实验观测资料对不同参数化方案进行评估,探究不同陆面模式对土壤湿度与蒸散关系的模拟差异,从而为提高模式的模拟能力提供依据。结果表明,（1）CLM与SSiB中计算土壤湿度影响裸土蒸发的参数化方案较Noah_LSM和VIC更接近真实的物理过程,同时CLM与SSiB模式中土壤湿度对蒸发的影响程度较Noah_LSM和VIC大;而对于下垫面有植被条件下的蒸散而言,CLM中包含了植被光合作用、呼吸作用等生物物理学过程,与实际情况更为接近,并且CLM与SSiB中土壤湿度对植被蒸散的影响程度大于VIC,Noah_LSM最低;（2）根据干旱区、半干旱区、半湿润区以及湿润区各站点的分析可知,CLM、SSiB与Noah_LSM中土壤湿度影响蒸散的参数化方案的拟合效果较VIC好,同时在部分站点CLM与SSiB的参数化方案稍优于Noah_LSM。区域之间比较说明,四个模式对干旱半干旱区的模拟效果明显较半湿润区和湿润区好。     

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model (DGVM) in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land ModelDGVM (CLM3.0-DGVM) with a submodel for temperate and boreal shrubs, as well as other revisions such as the two-leaf scheme for photosynthesis and the definition of fractional coverage of plant functional types (PFTs). Results show that the revised model may correctly reproduce the global distribution of tempera...     

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.     

Earth System Model FGOALS-s2: Coupling a dynamic global vegetation and terrestrial carbon model with the physical climate system model

Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.     

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.     

土壤质地对中国区域陆面过程模拟的影响

利用陆面过程模式(CLM3.5)和中国区域两种土壤质地数据(分别来自第二次中国土壤调查SNSS和联合国粮食农业组织FAO),研究了土壤质地变化对于模式模拟的陆表水热变量的影响。结果显示,土壤质地对土壤水文学变量的影响远大于对土壤热力学变量的影响,尤其是对于饱和土壤含水量和饱和水力传导率的影响。对于模式的输出,土壤质地影响比较明显的有土壤湿度、总径流和土壤渗透等水文学变量以及地表潜热、地表感热和土壤热通量等热力学变量,而影响相对较小的有地面吸收的太阳辐射和地表反照率。同时,发现基于SNSS模拟的土壤湿度与站点观测值更加接近。因此,本研究认为基于SNSS土壤质地数据可以有效地改进模式模拟结果,建议以后在陆面模式试验中尽可能使用以观测为基础的SNSS土壤质地数据。     

Simulation and Evaluation of Terrestrial Ecosystem NPP with M-SDGVM over Continental China

Using the regional terrestrial Net Primary Production (NPP) from different observations and models over China, we validated the NPP simulations and explored the relationship between NPP and climate variation at interannual and decadal scales in the Modified Sheffield Dynamic Global Vegetation Model (M-SDGVM) during 1981–2000. M-SDGVM shows agreement with the NPP data from 743 sites under the Global Primary Production Data Initiative (GPPDI). The spatial and the zonal averaged NPP of M-SDGVM agree well with ...     

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...     

Effects of a Remotely Sensed Land Cover Dataset with High Spatial Resolution on the Simulation of Secondary Air Pollutants over China Using the Nested-grid GEOS-Chem Chemical Transport Model简

A number of remotely sensed land cover datasets with spatial resolutions ~〈 1 km have recently become available or are in the process of being mapped. The application of these higher resolution and more up-to-date land cover datasets in chemical transport models （CTMs） is expected to improve the simulation of dry deposition and biogenic emissions of non-methane volatile organic compounds （NMVOCs）, which affect ozone and other secondary air pollutants. In the present study, we updated the land cover dataset in the nested-grid GEOS-Chem CTM with the 1 km resolution GLC2000 land cover map and examined the resulting changes in the simulation of surface ozone and sulfate over China in July 2007. Through affecting the dry deposition velocities of ozone and its precursors, using GLC2000 in the dry deposition module can decrease the simulated surface ozone by 3% （up to 6 ppb） over China. Simulated surface sulfate shows an increase of 3% in northwestern China and a decrease of 1% in northern China. Applying GLC2000 in the biogenic emissions of the NMVOC module can lead to a 0.5--4.5 ppb increase in simulated surface ozone over East China, mainly driven by the larger cove~：age of broadleaf trees in East China in the GLC2000 dataset. Our study quantifies the large sensitivity to land cover dataset~ with different spatial resolutions and time periods of simulated secondary air pollutants over China, supporting ongoing research efforts to produce high resolution and dynamically updated land cover datasets over China, as well as for the globe.     

Modeling Gross Primary Production by Integrating Satellite Data and Coordinated Flux Measurements in Arid and Semi-Arid China

Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes. Remote sensing-based models, which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics, improve spatially extended estimates of vegetation productivity with high accuracy. In this study, the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM), which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types. The field data were collected by coordinating observations at nine stations in 2008. The results indicate that in the region during the growing season GPP was highest in cropland sites, second highest in woodland sites, and lowest in grassland sites. VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas. Further, Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas, while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation. This study demonstrates the potential of satellite-driven models for scaling-up GPP, which is a key component for studying the carbon cycle at regional and global scales.