The roles of leaf area index and albedo in vegetation induced temperature changes across China using modelling and observations

The biophysical effects of vegetation changes are important in determining future climate changes using climate model. However, compared to observations, model has biases in energy exchange between vegetation and the lower atmosphere modulated by leaf area index and albedo. In this study, land-use induced anthropogenic influences, estimated as the differences between present land-use and idealized natural vegetation, on near-surface temperature were investigated using a regional climate model. Results show that present land-use transitions over China brings a cooler summer and winter accompanied by reduced diurnal temperature ranges by 0.11 °C and 0.25 °C respectively, which are mainly determined by the overwhelming increased evaporation and latent heat flux in summer and reduced net radiation in winter. Three vegetation pairs (i.e., forest and cropland, grassland and cropland, grassland and forest) were selected using observational datasets to evaluate vegetation induced climatic impact without atmospheric feedbacks across various climatic regimes. Albedo led absorbed radiation plays a dominate role in middle to north region while both LAI and albedo are significant below 30° N for latitudinal temperature changes between cropland and forest transitions. Model results have inconsistencies with observations on temperature trends caused by vegetation pairs, indicating summer cropland and forest over southern China is the most sensitive to the atmosphere conditions and forest and grassland pair is the least. These findings demonstrate the heterogeneous biophysical effect of vegetation in different climate zones and imply that a region-oriented parameterization of vegetation types should be applied in the land surface model to reduce uncertainties in future climate prediction.