Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 61, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2023.3305194
Keywords
Algae; fluorescence; glacier; Greenland; ice; photosynthesis; Sentinel; solar-induced chlorophyll fluorescence (SIF); TROPOspheric monitoring instrument (TROPOMI)
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This study utilizes solar-induced chlorophyll fluorescence (SIF) data and a random walker algorithm to confirm the extent and timing of algae blooms on the Greenland ice sheet. The SIF-based maps are highly correlated with Sentinel-3 data.
Glacial algae blooms on the Greenland ice sheet darken the surface albedo, enhancing surface melt. Sentinel-3 data was the first to highlight the extent of these blooms, which are expected to become larger as climate changes. Here, we propose a novel use of solar-induced chlorophyll fluorescence (SIF) data from TROPOspheric monitoring instrument (TROPOMI) to confirm the Sentinel-based maps and extend the data to daily levels to understand year-to-year variations in algae blooms. We combine the SIF data with a random walker algorithm to identify algae-covered areas. The SIF-based maps are found to be highly correlated with the Sentinel-based ones. The extent and the timing of the algae bloom are consistent between 2018 and 2020. This work opens the door to a new, complementary method for the monitoring of algae blooms on ice sheets and improving our understanding of their impact on glacier melt rate.
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