Characterization of land-surface precipitation feedback regimes with remote sensing

Abstract

A simple methodology for characterizing the land surface's response to precipitation is proposed based on the average behavior of coarse resolution remote sensing data. Feedback regimes are designated based on the temporal correlations between the vegetation and precipitation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land–atmosphere interactions. The resultant feedback regimes are well localized spatially. In addition, the temporal dynamics are assessed in terms of lagged covariances and phase–space plots. The two dominant feedback regimes are distinguishable by the vegetation–precipitation correlation, implying that vegetative control may be the dominant factor in influencing surface-precipitation feedbacks. These zones are not easily distinguished in the NDVI-surface temperature correlations, but exhibit different behavior in their NDVI-precipitation and surface temperature–precipitation correlations. In addition, these zones can be distinguished in phase plots of both temperature and NDVI. These results suggest a methodology for quantifying the rate of the hydrological cycle in different regions of the globe as well as identifying areas where human induced land cover change may have the most effect transitioning between different feedback zones, and therefore altering the rate of the hydrologic cycle.