Validation of Hi-GLASS products for latent heat flux based on Ameriflux observation data

FAN Jiahui; YAO Yunjun; YANG Junming; YU Ruiyang; LIU Lu; ZHANG Xueyi; XIE Zijing; NING Jing

doi:10.6046/zrzyyg.2022492

2024 Vol. 36, No. 1

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Article navigation > Remote Sensing for Natural Resources > 2024 > 36(1): 146-153

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FAN Jiahui, YAO Yunjun, YANG Junming, YU Ruiyang, LIU Lu, ZHANG Xueyi, XIE Zijing, NING Jing. 2024. Validation of Hi-GLASS products for latent heat flux based on Ameriflux observation data. Remote Sensing for Natural Resources, 36(1): 146-153. doi: 10.6046/zrzyyg.2022492

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FAN Jiahui, YAO Yunjun, YANG Junming, YU Ruiyang, LIU Lu, ZHANG Xueyi, XIE Zijing, NING Jing. 2024. Validation of Hi-GLASS products for latent heat flux based on Ameriflux observation data. Remote Sensing for Natural Resources, 36(1): 146-153. doi: 10.6046/zrzyyg.2022492

Validation of Hi-GLASS products for latent heat flux based on Ameriflux observation data

1. State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China
;2. Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions,CMA,Yinchuan 750002,China

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Corresponding author: YAO Yunjun

Received Date: 26 December 2022

Revised Date: 20 March 2023

Publish Date: 13 March 2024

Abstract

Abstract

The validation and analysis of latent heat flux products are critical for research on climate change and energy circulation. High-resolution global land surface satellite evapotranspiration (Hi-GLASS ET) products, which integrate five traditional evapotranspiration algorithms, can produce high-precision products for land surface latent heat flux. However, these products are yet to be validated. This study obtained multiple sets of valid validation data by comparing the latent heat flux observed values from Ameriflux flux observation sites with the corresponding estimated values of Hi-GLASS land surface latent heat flux products. The validation results yielded a squared correlation coefficient (R²) of 0.6, a root mean square error (RMSE) of 34.4 W/m², an average bias of -13.4 W/m², and Kling-Gupta efficiency (KGE) of 0.49. These suggest that Hi-GLASS latent heat flux products boast high precision and that their algorithms enjoy satisfactory fitting results. In addition, spatial distributions imply that Hi-GLASS latent heat flux products conform to normal natural laws. Due to data acquisition limitations, the validation of this study was conducted based on data from only 18 sites in the U.S., and further validation using data from other areas is required.
- land surface latent heat flux /
- Ameriflux sites /
- Hi-GLASS products /
- precision validation