Vegetation water content retrieval using MERIS and AATSR data over the Loess Plateau

Vegetation water content is an important indicator of the degree of stress experienced by plants. This paper explored the potential of using the remote sensing data of MERIS （Medium Resolution Imaging Spectrometer） and AATSR （Advanced Along-Track Scanning Radiometer） collected during the Loess Plateau land surface process field Experiment 2005 （LOPEX05） to map and monitor vegetation water content for corn canopies. By comparing with the daily ground observation to validate the satellite reflectance data, we established relationships between the vegetation water content and satellite remotely sensed indices. The two indices studied were the NDVI （Normalized Different Vegetation Index） from MERIS and the NDWI （Normalized Different Water Index） from AATSR. We used the daily ground observation to demonstrate that the NDVI was saturated during the study period while the NDWI continued to reflect the changes in VWC. We found that NDWI, based on near infrared channel （0.855-0.875μm） and short wave infrared wavelength channel （1.58-1.64μm）, is suggested to be more suitable and robust approach for retrieval of vegetation water content. The proposed method was validated with experimental field data with biases that are 1.0314 kg/m2 and 0.9413 kg/m2 respectively. Therefore the NDWI was recommended to retrieval the vegetation water content.

Evaluation of CMIP5 Earth System Models in Reproducing Leaf Area Index and Vegetation Cover over the Tibetan Plateau

The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.

Variations in net primary productivity and its relationships with warming climate in the permafrost zone of the Tibetan Plateau

Permafrost degradation triggered by a warming climate induces significant changes in soil conditions, and further contributes to apparent impacts on vegetation. However, much less is known regarding the difference in net primary productivity（NPP） and the relationships between NPP and warming temperature among different vegetation types and various types of permafrost zone on the Tibetan Plateau. Consequently, remotely sensed land surface temperature（LST） and NPP from the MODIS platform were used to investigate the response of vegetation NPP to warming climate, and the correlations were scaled up for the study region. Our results indicated a notable increase of NPP from west to east, and significantly increased annual NPP along with the increased LST from 2000 to 2010 in the permafrost zone of the Tibetan Plateau. Meanwhile, the increased NPP for various vegetation types and in different types of permafrost zone with relation to warming temperature was revealed. NPP in the continuous permafrost zone had the greatest sensitivity to the changing LST, and forest NPP presented the most obvious response. Positive correlations between NPP and LST at various scales indicated the enhanced effects of warming LST on vegetation carbon sequestration in the permafrost zone of the Tibetan Plateau. In view of the notable response of NPP to warming temperature on this plateau, remote sensing needs to be further employed to reveal the status of permafrost degradation and its related effects on vegetation.