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大气科学  2011 

Seasonal and Interannual Variations of Boreal Vegetation Simulated by an Improved Interactive Canopy Model (ICM)
动态冠层模型ICM的改进及其对中高纬地区植被季节和年际变化的模拟试验

Keywords: interactive canopy model (ICM),carbon allocation,phenological model,model improvement,middle and high latitude regions
植被动态冠层模型,碳分配,物候模型,模型改进,中高纬地区

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Abstract:

The dynamic vegetation model, Interactive Canopy Model (ICM), which includes the ecosystem carbon and nitrogen cycling processes, is able to model the vegetation variations on short time scales. A reproductive organs carbon pool that constitutes flowers and fruits has been added into the original carbon and nitrogen reservoirs. It is assumed that the reproductive organs carbon pool will be a main carbon sink from the dates of vegetation flowering. A phenological model, ForcSar, is used to predict the flowering dates when the main partitioning positions of carbon and nitrogen change. The simulated LAI (Leaf Area Index) from the modified ICM is compared with the observations from satellite data in boreal middle and high latitudes where the vegetation varies the most severely all the year round. It shows that the seasonal variations of boreal vegetation can be better simulated than before. The modified ICM represents its maximal LAI in July, conforming to the reality, so that the problem of modeled vegetation growth lag in the original ICM has been rectified. The correlation coefficients of observed and simulated seasonal LAI are obviously higher than before. And the errors are decreased for all types of boreal vegetations. Besides, the correlation of observed and simulated interannual LAI is increased to some extent, even not very prominent. The changeable LAI from the ICM will alter the land surface conditions such as energy balance and water cycle. Solar radiation absorbed by vegetation, sensible heat fluxes and latent heat fluxes change significantly before the blossom of vegetation in the case of temperate deciduous broadleaf trees in eastern USA. And therefore the modeled physical properties of land surface will be influenced.

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