Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID
Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID
复制标题
使用 NCEP GFS 和 SSiB4/TRIFFID 动态植被对全球气候模拟的影响
DOI：
10.1007/s13351-021-1099-6
复制
发表时间：
2021
影响因子：
3.2
通讯作者：
Deng, Huiping
中科院分区：
文献类型：
--
作者：
Zhang, Zhengqiu;Xue, Yongkang;Zhai, Panmao;Deng, Huiping
在1948 ~ 2008年进行了两个全球试验，研究了植被动态过程对数值气候模拟的影响。NCEP全球预报系统（GFS）与生物物理模型简化简单生物圈模型（SSiB） version 2 （GFS/SSiB2）、生物物理和动态植被模型SSiB version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics （GFS/SSiB4/TRIFFID）进行了耦合。利用GFS/SSiB4/TRIFFID和GFS/SSiB2卫星叶面积指数（LAI）、反照率以及观测到的地表温度和降水，在月尺度和年尺度上分析了植被动态过程对降水、近地表温度和地表能量收支的影响。结果表明：与GFS/SSiB2模式相比，GFS/SSiB4/TRIFFID模式下全球月平均LAI与全球库存监测与建模系统(GIMMS)/全球陆地表面卫星（GLASS） LAI的时间相关系数从0.31/0.29 （SSiB2）增加到0.47/0.46 (SSiB4)；月平均近地面气温模拟值与观测值的相关系数分别由非洲的0.50、东南亚的0.35和南美洲的0.39增加到0.56、0.41和0.44。月平均降水模拟值与观测值的相关系数分别从0.19（非洲）、0.22（南亚）和0.22（东亚）增加到0.25、0.27和0.28。最大的改善发生在干旱和半干旱地区。GFS采用植被动态模式模拟的植被和地表反照率的时空变异性和变化与观测值更为吻合。植被动态过程促进了地表能量和水分平衡，进而改善了模拟区域温度和降水的年际变化。植被动态过程对潜热通量的时空变化影响最大。研究表明，地球系统模式中的植被动态过程显著改善了气候平均状态的模拟结果。
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 (SSiB) version 2 (GFS/SSiB2), and it was also coupled with a biophysical and dynamic vegetation model, SSiB version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) (GFS/SSiB4/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/SSiB4/TRIFFID and GFS/SSiB2 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/SSiB4/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.