Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID

Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical model,the Simplified Simple Biosphere Model(SSi B)version 2(GFS/SSi B2),and it was also coupled with a biophysical and dynamic vegetation model,SSi B version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(TRIFFID)(GFS/SSi B4/TRIFFID).The effects of dynamic vegetation processes on the simulation of precipitation,near-surface temperature,and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSi B4/TRIFFID and GFS/SSi B2 results against the satellite-derived leaf area index(LAI)and albedo and the observed land surface temperature and precipitation.The results show that compared with the GFS/SSiB2 model,the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System(GIMMS)/Global Land Surface Satellite(GLASS)LAI in the GFS/SSi B4/TRIFFID simulation increased from 0.31/0.29(SSiB2)to 0.47/0.46(SSiB4).The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50(Africa),0.35(Southeast Asia),and 0.39(South America)to 0.56,0.41,and 0.44,respectively.The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19(Africa),0.22(South Asia),and 0.22(East Asia)to 0.25,0.27,and 0.28,respectively.The greatest improvement occurred over arid and semiarid areas.The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations.The dynamic vegetation processes contributed to the surface energy and water balance and in turn,improved the annual variations in the simulated regional temperature and precipitation.The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux.This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.

流域植被与土壤导水系数对青弋江流域水文影响的数值试验

为了揭示植被覆盖以及土壤导水系数变化对流域水文的影响,用陆面模式SSiB4与动态植被模型TRIFFID和流域地形指数水文模型TOPMODEL的耦合模型(SSiBT/TRIFFID)进行流域植被覆盖与土壤导水系数变化对流域水文影响的数值试验。结果表明:①植被类型明显影响流域地表能量平衡和水量平衡;②流域森林植被能明显减小一般洪峰流量,但对大的洪峰流量没有减弱作用;③减小土壤导水系数将明显增加地表径流和减小基流。

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau:Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorological Forcing Data(PMFD)and the high spatial resolution and upscaled China Meteorological Forcing Data(CMFD)were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(SSiB4/TRIFFID)and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau(TP),a region with complex topography and sparse observations.By comparing the monthly Leaf Area Index(LAI)and Gross Primary Production(GPP)against observations,we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP,reducing RMSEs by 24.3%and 20.5%,respectively.The multi-year averaged GPP decreased from 364.68 gC m^(-2)yr^(-1)to 241.21 gC m^(-2)yr^(-1)with the percentage bias dropping from 50.2%to-1.7%.When using the high spatial resolution CMFD,the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5%and 9.5%,respectively.This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

Numerical simulation of the effects of global warming on vegetation in Asia

The response of vegetation to global warming is closely related to human living environment,and uncertainty in understanding the response remains.This study aims to investigate the effects of CO_(2),temperature and precipitation changes under global warming on natural vegetation in Asia.The biophysical/dynamic vegetation model SSiB4/TRIFFID was employed to perform numerical experiments under different climate scenarios for Asia using the Princeton global forcing dataset(1948–2006).The results showed that precipitation and CO_(2) were the key factors for vegetation growth.The effect of temperature on natural vegetation varied among the study regions.Generally,an increase in temperature was conducive to vegetation growth in eastern Asia,but not in the arid and semi-arid areas of western Asia.In arid and semi-arid areas or in the vicinity of desert,the forcing effects of temperature,precipitation and CO_(2) were more remarkable,which led to a noticeable change in the area of bare land.In terms of the distribution of vegetation species,the above forcing had a greater impact on shrubs,C3 grasses and C4 plants,but less of an impact on broadleaf and coniferous forest.It was also found that,although there was a notable positive correlation between precipitation and vegetation leaf area index in northern high latitudes,the vegetation cover did not increase with precipitation,which was countered by the negative effect of surface cooling in summer.