为了解2003—2009年中国的叶面积指数(Leaf Area Index,LAI)变化特征,以及不同数据产品的差别,利用基于MODIS数据反演的3组LAI产品,比较分析了中国地区LAI的时空变化特征及其与气候因子的相关。结果表明,3组数据具有总体一致的变化特点,增长区主要位于东北大兴安岭、华北、华中和西南等地;减少区则位于四川盆地、江南以及华南东部;但在云贵川和青藏高原东南部等地有明显差异。在量值上,中科院地理所反演的LAI(LAI1)总体比NASA反演的LAI(LAI2)和北京师范大学反演的LAI(LAI3)偏小,它们在中国常绿阔叶林区的差别可达1.0以上。LAI1与同期降水和气温都有显著的相关,相关系数的空间分布一致,但LAI1的相关系数比LAI3和LAI2偏低。3组数据的差异主要与采用的遥感源数据和反演方法等不同有关。尽管不同LAI数据产品局域和量值差异对定量分析有一定影响,但是它们在时空变化及与气候条件相关等方面的一致性证明了在气候及气候变化研究中的可用性。
Land cover is one of the most basic input elements of land surface and climate models. Currently, the direct and indirect effects of land cover data on climate and climate change are receiving increasing attentions. In this study, a high resolution(30 m) global land cover dataset(Globe Land30) produced by Chinese scientists was, for the first time, used in the Beijing Climate Center Climate System Model(BCC_CSM) to assess the influences of land cover dataset on land surface and climate simulations. A two-step strategy was designed to use the Globe Land30 data in the model. First, the Globe Land30 data were merged with other satellite remote sensing and climate datasets to regenerate plant functional type(PFT) data fitted for the BCC_CSM. Second, the up-scaling based on an area-weighted approach was used to aggregate the fine-resolution Globe Land30 land cover type and area percentage with the coarser model grid resolutions globally. The Globe Land30-based and the BCC_CSM-based land cover data had generally consistent spatial distribution features, but there were some differences between them. The simulation results of the different land cover type dataset change experiments showed that effects of the new PFT data were larger than those of the new glaciers and water bodies(lakes and wetlands). The maximum value was attained when dataset of all land cover types were changed. The positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere, were reduced when the Globe Land30-based data were used in the BCC_CSM atmosphere model. The results suggest that the Globe Land30 data are suitable for use in the BCC_CSM component models and can improve the performance of the land and atmosphere simulations.
The impacts of land cover changes on regional climate with RegCM3. Sensitivity experiments were conducted by in Shaan-Gan-Ning （SGN） in western China were simulated replacing crop grids with different new land cover types in the key area of SGN, where the returning cropland to tree/grass project has been carried out since 1999. The modified new land cover types include desert, forest, shrub and grass. They represent degraded, improved, and maintained vegetation cover with natural canopy in the key area. Results from three individual case studies show that the land cover change causes changes in temperature and terrestrial water variables especially within the key area, while changes in precipitation are found for a larger area. The strongest changes appear where the cropland is degraded to bare soil, leading to increasing temperature and decreases in rainfall, evaporation and soil water. Opposite changes occur when cropland changed into forests, especially with strong increases in soil water. When cropland changed to grass and shrub land, the climatic changes are closer to those with forest cover. This shows the importance of improving and maintaining the vegetation in SGN for the ecosystem and regional climate.
