Abstract
Abstract. In the absence of high-resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a data set of land-surface energy and water fluxes on a monthly timescale from 2001 to 2010 at a 0.1 × 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The land-surface flux data set was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 11.2 Wm−2, RMSE = 22.7 Wm−2). The quality of the data product was also assessed against the GLDAS data set. The results show that our method is efficient for producing a high-resolution data set of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation data sets are needed to be able to estimate turbulent fluxes and evapotranspiration accurately when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the data set to provide spatial and temporal information on water-cycle and land–atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China.
Highlights
As China is one of the fastest growing and urbanizing economies in the world, changes in land cover and land use can significantly influence the environment by altering land– atmosphere energy and water exchanges (Suh and Lee, 2004; Lin et al, 2009)
We have developed the surface energy balance system (SEBS) further to produce a land-surface heat flux data set on a continental scale of higher resolution than data sets derived using other methods
The global surface energy flux data sets, including reanalysis data, do not have enough spatial and temporal resolution when looking at the national-level fluxes
Summary
As China is one of the fastest growing and urbanizing economies in the world, changes in land cover and land use can significantly influence the environment by altering land– atmosphere energy and water exchanges (Suh and Lee, 2004; Lin et al, 2009). The variability of surface energy balance and its partitioning may have an important impact on climate variability in China (Sun and Wu, 2001). Changes in surface energy fluxes have been shown to alter the intensity of the East Asian monsoon (Zhou and Huang, 2008; Qiu, 2013; Hsu and Liu, 2003). Understanding variation in energy fluxes is important for the study of climate change in China (Brauman et al, 2007). The spatial and temporal variability of China’s land-surface energy balance, and the magnitude of each, are still unknown
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