Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models
Snow and ice albedo is a critical geographical indicator that reflects climate change on Earth. Quantifying the albedo in Greenland ice sheet, which is extensively covered with snow and ice, is key to studying changes in the energy budget in the Northern Hemisphere. Earth observation satellites have...
Published in: | International Journal of Applied Earth Observation and Geoinformation |
---|---|
Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Elsevier
2023
|
Subjects: | |
Online Access: | https://doi.org/10.1016/j.jag.2023.103519 https://doaj.org/article/6694c2e30bbb4fbd91c63f9ae714d56f |
id |
ftdoajarticles:oai:doaj.org/article:6694c2e30bbb4fbd91c63f9ae714d56f |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:6694c2e30bbb4fbd91c63f9ae714d56f 2023-12-10T09:49:02+01:00 Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models Fan Ye Qing Cheng Weifeng Hao Dayu Yu Chao Ma Dong Liang Huanfeng Shen 2023-11-01T00:00:00Z https://doi.org/10.1016/j.jag.2023.103519 https://doaj.org/article/6694c2e30bbb4fbd91c63f9ae714d56f EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S1569843223003436 https://doaj.org/toc/1569-8432 1569-8432 doi:10.1016/j.jag.2023.103519 https://doaj.org/article/6694c2e30bbb4fbd91c63f9ae714d56f International Journal of Applied Earth Observations and Geoinformation, Vol 124, Iss , Pp 103519- (2023) Albedo Gap-filling Snow and ice Greenland Physical geography GB3-5030 Environmental sciences GE1-350 article 2023 ftdoajarticles https://doi.org/10.1016/j.jag.2023.103519 2023-11-12T01:37:57Z Snow and ice albedo is a critical geographical indicator that reflects climate change on Earth. Quantifying the albedo in Greenland ice sheet, which is extensively covered with snow and ice, is key to studying changes in the energy budget in the Northern Hemisphere. Earth observation satellites have been regularly providing surface albedo products. However, optical satellite-derived albedo products have many voids due to the persistent cloud cover over the Greenland ice sheet. Consequently, seamless reconstruction of albedo on the spatial and temporal scales is essential. Surface albedo, as a geographical element, is spatially and temporally correlated. In addition, the broadband albedo of snow and ice is significantly modified by changes in the spectral distribution of solar irradiance caused by clouds. On the basis of such facts, this study proposes a reconstruction method for snow and ice albedo that combines spatiotemporal information with a physics-informed model. This method uses spatiotemporal nonlocal filtering to generate the initial reference albedo for missing pixels. Then, the hypothetical clear-sky albedo is reconstructed using the Whittaker iterator. Finally, cloudy albedo is obtained on the basis of the empirical relationship between clear-sky and cloudy-sky albedos. We reconstruct albedo based on MOD10A1 for the whole Greenland region from 2001 to 2020. A comparison between the reconstruction results and ground measurements exhibits satisfactory accuracy with an R-value of 0.8162, a root-mean-square error of 0.0669, a mean absolute error of 0.0486, and a bias of 0.00001. Moreover, the proposed method demonstrates the advantages of being more accurate and robust than other classical methods. Therefore, this study will be valuable for generating 500 m daily remotely sensed albedo of snow and ice in large regions. Article in Journal/Newspaper Greenland Ice Sheet Directory of Open Access Journals: DOAJ Articles Greenland International Journal of Applied Earth Observation and Geoinformation 124 103519 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Albedo Gap-filling Snow and ice Greenland Physical geography GB3-5030 Environmental sciences GE1-350 |
spellingShingle |
Albedo Gap-filling Snow and ice Greenland Physical geography GB3-5030 Environmental sciences GE1-350 Fan Ye Qing Cheng Weifeng Hao Dayu Yu Chao Ma Dong Liang Huanfeng Shen Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
topic_facet |
Albedo Gap-filling Snow and ice Greenland Physical geography GB3-5030 Environmental sciences GE1-350 |
description |
Snow and ice albedo is a critical geographical indicator that reflects climate change on Earth. Quantifying the albedo in Greenland ice sheet, which is extensively covered with snow and ice, is key to studying changes in the energy budget in the Northern Hemisphere. Earth observation satellites have been regularly providing surface albedo products. However, optical satellite-derived albedo products have many voids due to the persistent cloud cover over the Greenland ice sheet. Consequently, seamless reconstruction of albedo on the spatial and temporal scales is essential. Surface albedo, as a geographical element, is spatially and temporally correlated. In addition, the broadband albedo of snow and ice is significantly modified by changes in the spectral distribution of solar irradiance caused by clouds. On the basis of such facts, this study proposes a reconstruction method for snow and ice albedo that combines spatiotemporal information with a physics-informed model. This method uses spatiotemporal nonlocal filtering to generate the initial reference albedo for missing pixels. Then, the hypothetical clear-sky albedo is reconstructed using the Whittaker iterator. Finally, cloudy albedo is obtained on the basis of the empirical relationship between clear-sky and cloudy-sky albedos. We reconstruct albedo based on MOD10A1 for the whole Greenland region from 2001 to 2020. A comparison between the reconstruction results and ground measurements exhibits satisfactory accuracy with an R-value of 0.8162, a root-mean-square error of 0.0669, a mean absolute error of 0.0486, and a bias of 0.00001. Moreover, the proposed method demonstrates the advantages of being more accurate and robust than other classical methods. Therefore, this study will be valuable for generating 500 m daily remotely sensed albedo of snow and ice in large regions. |
format |
Article in Journal/Newspaper |
author |
Fan Ye Qing Cheng Weifeng Hao Dayu Yu Chao Ma Dong Liang Huanfeng Shen |
author_facet |
Fan Ye Qing Cheng Weifeng Hao Dayu Yu Chao Ma Dong Liang Huanfeng Shen |
author_sort |
Fan Ye |
title |
Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
title_short |
Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
title_full |
Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
title_fullStr |
Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
title_full_unstemmed |
Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physics-informed models |
title_sort |
reconstructing daily snow and ice albedo series for greenland by coupling spatiotemporal and physics-informed models |
publisher |
Elsevier |
publishDate |
2023 |
url |
https://doi.org/10.1016/j.jag.2023.103519 https://doaj.org/article/6694c2e30bbb4fbd91c63f9ae714d56f |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_source |
International Journal of Applied Earth Observations and Geoinformation, Vol 124, Iss , Pp 103519- (2023) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S1569843223003436 https://doaj.org/toc/1569-8432 1569-8432 doi:10.1016/j.jag.2023.103519 https://doaj.org/article/6694c2e30bbb4fbd91c63f9ae714d56f |
op_doi |
https://doi.org/10.1016/j.jag.2023.103519 |
container_title |
International Journal of Applied Earth Observation and Geoinformation |
container_volume |
124 |
container_start_page |
103519 |
_version_ |
1784893294542585856 |