| 摘要: |
| 潜热通量(LE)影响陆地生态系统的水量平衡和能量收支,提高不同植被类型对应的地表潜热通量的反演精度对于探究生态水文过程具有重要的现实意义。本研究采用动态植被模型——LPJ-GUESS模型,引入表征植被占比的参数对PT-hybrid潜热通量算法加以改进,从而提高陆面蒸散发的反演能力。根据全球49个通量站点的地面观测LE验证改进后的算法,改进算法所得LE值与实测值的决定系数R2从0.63增加到0.74,均方根误差RMSE从17.1降低到11.7。进一步分析1982-2014年全球陆地LE变化特征,发现低纬度地区的LE均高于高纬度地区,并且LE在同一纬度上也呈现出不同的分布趋势。本文首次将亚像元法与LE算法进行耦合,改进后的模型对地表潜热通量模拟精度显著提高,有助于精细刻画地表LE的时空分布特征。 |
| 关键词: PT-hybrid算法、动态植被模型、潜热通量、亚像元、时空演变特性 |
| DOI： |
| 分类号:P343 |
| 基金项目:国家自然科学基金(51809073) 、中央高校基本科研业务费专项资金资助(B200201005) |
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| Analysis of terrestrial latent heat flux based on improved PT-hybrid algorithm |
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Zhou Yaokun, XING Wanqiu
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Hohai University
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| Abstract: |
| Latent heat flux () impacts the terrestrial ecosystem carbon dynamics and energy budget. It is of great practical significance to improve the inversion accuracy of surface latent heat flux corresponding to plant functional type (PFTs) for exploring the eco-hydrological process. Here a dynamic vegetation model-LPJ-GUESS model is applied to improve satellite-based PT-hybrid algorithm, with a parameter , which represents proportions of different PFTs, introduced to characterize the proportions of different PFTs. Validation results showed that the square of correlation coefficient (R2) increased from 0.63 to 0.74 and the root mean square error (RMSE) decreased from 17.1 to 11.7 based on the globally distributed 49 flux tower sites. In addition, we estimated the global LE during 1982-2014 by the improved algorithm and found that the LE in low latitudes was generally higher than that in middle and high latitudes. Meanwhile, LE also showed complex distributions at the same latitude. In this paper, the sub-pixel method is coupled with LE algorithm for the first time. The improved model significantly improves the simulation accuracy of surface latent heat flux, which is helpful to describe the spatial-temporal distribution characteristics of surface LE. |
| Key words: PT-hybrid algorithm; dynamic vegetation model; latent heat flux; sub-pixel; spatial-temporal evolution characteristics |
