Discovering Optimal Triplets for Assessing the Uncertainties of Satellite-Derived Evapotranspiration Products
(2023) In Remote Sensing 15(13).- Abstract
Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validation of measurements. Triple collocation (TC) methods can assess the inherent uncertainties of the above ET products using just three independent variables as a triplet input. However, both the severity with which the variables in the triplet violate the assumptions of zero error correlations and the corresponding impact on the error estimation are unknown. This study proposed a cross-correlation analysis approach to discover the optimal triplet of satellite-derived ET products with regard to... (More)
Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validation of measurements. Triple collocation (TC) methods can assess the inherent uncertainties of the above ET products using just three independent variables as a triplet input. However, both the severity with which the variables in the triplet violate the assumptions of zero error correlations and the corresponding impact on the error estimation are unknown. This study proposed a cross-correlation analysis approach to discover the optimal triplet of satellite-derived ET products with regard to providing the most reliable error estimation. All possible triple collocation solutions for the same product were first evaluated by the extended triple collocation (ETC), among which the optimum was selected based on the correlation between ETC-based and in-situ-based error metrics, and correspondingly, a statistic experiment based on ranked triplets demonstrated how the optimal triplet was valid for all pixels of the product. Six popular products (MOD16, PML_V2, GLASS, SSEBop, ERA5, and GLEAM) that were produced between 2003 to 2018 and which cover China’s mainland were chosen for the experiment, in which the error estimates were compared with measurements from 23 in-situ flux towers. The findings suggest that (1) there exists an optimal triplet in which a product as an input of TC with other collocating inputs together violate TC assumptions the least; (2) the error characteristics of the six ET products varied significantly across China, with GLASS performing the best (median error: 0.1 mm/day), followed by GLEAM, ERA5, and MOD16 (median errors below 0.2 mm/day), while PML_V2 and SSEBop had slightly higher median errors (0.24 mm/day and 0.27 mm/day, respectively); and (3) removing seasonal variations in ET signals has a substantial impact on enhancing the accuracy of error estimations.
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- author
- He, Yan ; Wang, Chen ; Hu, Jinghao ; Mao, Huihui ; Duan, Zheng LU ; Qu, Cixiao ; Li, Runkui ; Wang, Mingyu and Song, Xianfeng
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- cross-correlation analysis, error assessment, extended triple collocation, optimal triplet, satellite-derived evapotranspiration products
- in
- Remote Sensing
- volume
- 15
- issue
- 13
- article number
- 3215
- publisher
- MDPI AG
- external identifiers
-
- scopus:85165066938
- ISSN
- 2072-4292
- DOI
- 10.3390/rs15133215
- language
- English
- LU publication?
- yes
- id
- 69b79ca0-9727-422b-bb3c-73eb3b2dbe96
- date added to LUP
- 2023-09-11 12:42:35
- date last changed
- 2023-09-11 12:42:35
@article{69b79ca0-9727-422b-bb3c-73eb3b2dbe96,
abstract = {{<p>Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validation of measurements. Triple collocation (TC) methods can assess the inherent uncertainties of the above ET products using just three independent variables as a triplet input. However, both the severity with which the variables in the triplet violate the assumptions of zero error correlations and the corresponding impact on the error estimation are unknown. This study proposed a cross-correlation analysis approach to discover the optimal triplet of satellite-derived ET products with regard to providing the most reliable error estimation. All possible triple collocation solutions for the same product were first evaluated by the extended triple collocation (ETC), among which the optimum was selected based on the correlation between ETC-based and in-situ-based error metrics, and correspondingly, a statistic experiment based on ranked triplets demonstrated how the optimal triplet was valid for all pixels of the product. Six popular products (MOD16, PML_V2, GLASS, SSEBop, ERA5, and GLEAM) that were produced between 2003 to 2018 and which cover China’s mainland were chosen for the experiment, in which the error estimates were compared with measurements from 23 in-situ flux towers. The findings suggest that (1) there exists an optimal triplet in which a product as an input of TC with other collocating inputs together violate TC assumptions the least; (2) the error characteristics of the six ET products varied significantly across China, with GLASS performing the best (median error: 0.1 mm/day), followed by GLEAM, ERA5, and MOD16 (median errors below 0.2 mm/day), while PML_V2 and SSEBop had slightly higher median errors (0.24 mm/day and 0.27 mm/day, respectively); and (3) removing seasonal variations in ET signals has a substantial impact on enhancing the accuracy of error estimations.</p>}},
author = {{He, Yan and Wang, Chen and Hu, Jinghao and Mao, Huihui and Duan, Zheng and Qu, Cixiao and Li, Runkui and Wang, Mingyu and Song, Xianfeng}},
issn = {{2072-4292}},
keywords = {{cross-correlation analysis; error assessment; extended triple collocation; optimal triplet; satellite-derived evapotranspiration products}},
language = {{eng}},
number = {{13}},
publisher = {{MDPI AG}},
series = {{Remote Sensing}},
title = {{Discovering Optimal Triplets for Assessing the Uncertainties of Satellite-Derived Evapotranspiration Products}},
url = {{http://dx.doi.org/10.3390/rs15133215}},
doi = {{10.3390/rs15133215}},
volume = {{15}},
year = {{2023}},
}