The sensitivity of NPP to climate controls in northern China estimated by CLM model coupled with RS and GIS technology

The continuing rise in atmospheric CO2 is considered as a main cause of the future changes in global climate. Predicted climate changes include an increase in mean annual air temperature and alterations in precipitation pattern and cloud cover. Net primary productivity (NPP) measures products of major economic and social importance, such as agricultural crop yield and forest production. It is important to understand the response of vegetation to the possible climate changes. While the Global NPP is hard to be measured directly, its global spatial and temporal dynamics can be investigated by a combination of ecosystem process modeling and monitoring by remote sensing (RS). NPP has been linked to climatic patterns by approaches ranging from simple correlations to sophisticated simulation models. This study was conducted in a range where the productivity and climate exist along an east-west transect in northern China. We used modified Common Land Surface Model (CLM) to simulate the NPP combined with satellite data and assessed the response of NPP under different climate change controls with different land surface vegetation types in study areas. The feasibility of the CLM model was tested and parameterized based on the ecological characteristics. The response of NPP to increased temperature was more sensitive to the doubled CO2 climate because the temperature is the limited factor to vegetation growth in study areas. The responses of NPP to different climate controls were also influenced by different vegetation types and ecological characteristics