Performance Assessment of Tailored Split-Window Coefficients for the Retrieval of Lake Surface Water Temperature from AVHRR Satellite Data

Lieberherr, Gian-Duri; Riffler, Michael; Wunderle, Stefan (2017). Performance Assessment of Tailored Split-Window Coefficients for the Retrieval of Lake Surface Water Temperature from AVHRR Satellite Data. Remote sensing, 9(12), pp. 1-22. Molecular Diversity Preservation International MDPI 10.3390/rs9121334

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Although lake surface water temperature (LSWT) is defined as an essential climate variable (ECV) within the global climate observing system (GCOS), current satellite-based retrieval techniques do not fulfill the GCOS accuracy requirements. The split-window (SW) retrieval method is well-established, and the split-window coefficients (SWC) are the key elements of its accuracy. Performances of SW depends on the degree of SWC customization with respect to its application, where accuracy increases when SWC is tailored for specific situations. In the literature, different SWC customization approaches have been investigated, however, no direct comparisons have been conducted among them. This paper presents the results of a sensitivity analysis to address this gap. We show that the performance of SWC is most sensitive to customizations for specific time-windows (Sensitivity Index SI of 0.85) or spatial extents (SI 0.27). Surprisingly, the study highlights that the use of separated SWC for daytime and night-time situations has limited impact (SI 0.10). The final validation with AVHRR satellite data showed that the subtle differences among different SWC customizations were not traceable to the final uncertainty of the LSWT product. Nevertheless, this study provides a basis to critically evaluate current assumptions regarding SWC generation by directly comparing the performance of multiple customization approaches for the first time.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Geography > Physical Geography > Unit Remote Sensing
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Institute of Geography > Physical Geography

Graduate School:

Graduate School of Climate Sciences

UniBE Contributor:

Lieberherr, Gian-Duri; Riffler, Michael and Wunderle, Stefan

ISSN:

2072-4292

Publisher:

Molecular Diversity Preservation International MDPI

Language:

English

Submitter:

Helga Weber

Date Deposited:

22 Dec 2017 10:04

Last Modified:

22 Dec 2017 10:04

Publisher DOI:

10.3390/rs9121334

BORIS DOI:

10.7892/boris.108355

URI:

https://boris.unibe.ch/id/eprint/108355

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