【摘要】 气候要素的定量化是古气候研究的重要方向。为了充分考虑环境条件（如大气CO₂浓度）对植被生长的影响,利用孢粉数据更加准确的重建古气候要素,尤其是与现代气候条件具有很大差异的冰期气候要素,我们对第一代植被反演方法进行了改进,增强了植被类型的模拟,并利用转换矩阵实现了模型模拟植被类型和孢粉的生物群区类型的对接。将新方法运用于东亚季风区古气候要素的定量化重建,利用我国现代表土孢粉的生物群区化数据和气候实测资料,对植被反演方法重建的气候要素进行了检验。结果表明:该方法能较好地反演植被类型,并重建各气候要素;其中,最冷月温度、生物有效积温（>5℃）、有效湿度、年均温度和年降水重建值与实测值之间的相关系数（R）分别为0.95、0.89、0.82、0.89和0.94,均在显著相关的水平上。因此,该方法可用于古气候要素的重建,为下一步更好揭示东亚季风气候演化历史提供了新的手段。更多还原

【Abstract】 Knowledge of quantitative palaeoclimates is a crucial for the evaluation of climate changes for the earth system.In order to improve the reliability of climate reconstruction,especially the climatologies during the glacial periods outside the modern observed climate space,an improved inverse vegetation model has been designed to quantitatively reconstruct past climates,based on pollen biome scores from the BIOME 6000 project.The method has been validated with surface pollen spectra from China by reconstructing the modern climate at each site and comparing it with the observed values.There are no systematically regional errors between pollen biomes and reconstructed biomes by inverse vegetation method.The high correlation coefficients(R) between the actual and reconstructed climate for the present-day pollen sites are 0.95,0.89,0.82,0.89,and 0.94 for the mean temperature of the coldest month,the growing degree-days above 5℃,the ratio of actual to equilibrium evaportranspiration,the annual mean temperature and the annual precipitation,respectively.It demonstrated that the inversion method worked well for most climate variables in China.This new approach can improve our understanding on the climate changes of East Asian monsoon evolution.更多还原