Abstract

Accurately estimating the surface fluxes of over the heterogeneous land surface in Tibetan Plateau will be helpful to advance the understanding of its influence on regional climate and hydrology. This paper presents a study on the spatial heterogeneity of land surface parameters in terms of the spatial variability and spatial structure of land surface parameters and the influence on surface fluxes over a typical land surface in Tibetan Plateau. The results suggest that the sensible heat fluxes (H) and latent heat fluxes (LE) in the study area in the rain and dry seasons show apparent spatial variabilities due to the spatial heterogeneity in the leaf area index (LAI) and land surface undulations. The relative frequency distribution of H and LE at the spatial resolution of 30 m suggests that the spatial variability of surface fluxes has a close relationship with the spatial heterogeneity of land surface temperature (LST) and LAI. The variogram analyses of LST, LAI, H, and LE in the study area in rain season indicate that the spatial structures of LST and LAI are different and the spatial structures of H and LE are strongly influenced by the spatial structures of LST and LAI in both rain and dry seasons. The optimal pixel sizes for LST, LAI, H, and LE in the study area are 506, 156, 500, and 225 m in the rain season. The optimal pixel sizes for LST, H, and LE in the study area are 165, 165, and 162 m in the dry season. An analysis of the relative frequency distributions (RFDs) of the LST, LAI, H, and LE at different spatial resolutions in the rain and dry seasons reveals that their values at the maximum relative frequency keep stable although their spatial variabilities become weak as the spatial resolution decreases. The averages of LST, LAI, H, and LE of different spatial resolutions of the study area in rain and dry seasons vary within small ranges, suggesting that the influence of spatial resolution on the averaged land surface parameters and surface fluxes in the study area is small. This work will be helpful for the accurate estimation of the surface fluxes over a large heterogeneous land surface for regional climate modeling in Tibetan Plateau.

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