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动态植被模型模拟的植被季节变化及其评估
引用本文:俞淼,陈海山,孙照渤.动态植被模型模拟的植被季节变化及其评估[J].气候与环境研究,2011,16(1):47-59.
作者姓名:俞淼  陈海山  孙照渤
作者单位:南京信息工程大学气象灾害省部共建教育部重点实验室,南京,210044
基金项目:国家自然科学基金项目40875057,公益性行业科研专项GYHY(QX)2007-25,江苏省研究生培养创新工程创新计划项目CX08B_018Z,江苏省“六大人才高峰”项目
摘    要:利用MODIS卫星观测资料,对一个考虑了生态系统碳氮循环过程的动态植被模型ICM的模拟性能进行了评估.重点对反映植被动力学的关键参数--叶面积指数(LAI)的模拟结果与观测进行了对比分析,评估了ICM对LAI季节变化特征的模拟能力.结果表明,ICM基本能够模拟出植被的季节变化特征.总体而言,模拟值在低纬度和高纬度地区大...

关 键 词:陆面过程模拟  动态植被  季节变化  模式评估

Seasonal Cycle of Terrestrial Vegetation Simulated by a Dynamic Vegetation Model and Its Assessment
YU Miao,CHEN Haishan and SUN Zhaobo.Seasonal Cycle of Terrestrial Vegetation Simulated by a Dynamic Vegetation Model and Its Assessment[J].Climatic and Environmental Research,2011,16(1):47-59.
Authors:YU Miao  CHEN Haishan and SUN Zhaobo
Institution:YU Miao,CHEN Haishan,and SUN Zhaobo Key Laboratory of Meteorological Disaster of Ministry of Education,Nanjing University of Information Science and Technology,Nanjing 210044
Abstract:Based on the MODIS observations, the performance of Interactive Canopy Model(ICM), a dynamic vegetation model including the carbon and nitrogen cycles of the terrestrial ecosystem, has been assessed. The Leaf Area Index (LAI), a key parameter with seasonal variation in vegetation dynamics, is simulated by ICM and compared with the MODIS data. The results show that ICM can simulate the main characteristics of the seasonal LAI fluctuations. Compared to the observation, LAI is overestimated in high and low latitudes, but underestimated in middle latitudes by the model. The underestimation of the LAI in middle latitudes is followed by the vegetation sprout for the reason that the modeled growth is always slower than the observed one. The bimodal distributions for the tropical evergreen broadleaf trees and crops have not been well captured. In addition, the simulated results for the grassland are more reasonable than other Plant Function Types (PFTs). The results will provide important clues for the parameterization improvement and parameters optimization of the ICM.
Keywords:land surface modeling  dynamic vegetation  seasonal cycle  model assessment
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