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| DOI：10.13522/j.cnki.ggps.2020488 |
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| Calculating Latent Heat Flux from Soil Surface using the Improved PT-hybrid Algorithm |
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ZHOU Yaokun, XING Wanqiu
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College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
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| Abstract: |
| 【Background】 Latent heat flux (LE) impacts carbon dynamics and energy budget in the terrestrial ecosystem. Its accurate estimation is essential to understanding energy budget and surface-atmosphere interactions on the Earth surface. Satellite imageries have been used to calculate LE at global scale, but most of them overlooked the impact of vegetation diversity at pixel scale.【Objective】Considering that carbon flow and heat flux in ecosystems are closely related through photosynthesis and that plants are diverse, calculating LE using sub-pixel data should improve its accuracy, especially for complex ecosystems.【Method】Here, a dynamic vegetation model, LPJ-GUESS, was proposed to improve the satellite-based PT-hybrid algorithm, by using a parameter fv to represent the proportions of different PFTs in a pixel.【Result】Validation against ground-true data obtained from 49 flux tower sites in the world showed that the proposed model increased the square of correlation coefficient from 0.63 to 0.74, and reduced the root mean square error from 17.1 W/m2 to 11.7 W/m2. Estimation of the global LE from 1982 to 2014 revealed the proposed method was more effective for low latitude areas than for other areas, and that for areas on the same latitude, the LE showed complicated spatial distribution.【Conclusion】Sub-pixel method was coupled with the LE algorithm for the first time to calculate surface latent heat flux. It significantly improved the accuracy and can be used to estimate spatiotemporal distribution of LE at different scales. |
| Key words: PT-hybrid algorithm; dynamic vegetation model; latent heat flux; sub-pixel; spatial-temporal evolution characteristics |
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