How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?
Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily...
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ftdoajarticles:oai:doaj.org/article:65e671fc316e4e5581794b0a48ac854a 2023-07-30T04:07:15+02:00 How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? E. H. Bair J. Dozier K. Rittger T. Stillinger W. Kleiber R. E. Davis 2023-07-01T00:00:00Z https://doi.org/10.5194/tc-17-2629-2023 https://doaj.org/article/65e671fc316e4e5581794b0a48ac854a EN eng Copernicus Publications https://tc.copernicus.org/articles/17/2629/2023/tc-17-2629-2023.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-17-2629-2023 1994-0416 1994-0424 https://doaj.org/article/65e671fc316e4e5581794b0a48ac854a The Cryosphere, Vol 17, Pp 2629-2643 (2023) Environmental sciences GE1-350 Geology QE1-996.5 article 2023 ftdoajarticles https://doi.org/10.5194/tc-17-2629-2023 2023-07-09T00:34:13Z Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale ( ≤30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: (1) a fused MODIS–Landsat product with daily 30 m spatial resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with 3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing techniques are applied to surface reflectance products from 1 and 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size) but greater mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts, e.g., basin boundary delineation. Other explanations are (1) the importance of daily acquisitions and (2) the limitations of downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models and (2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations, but existing ... Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 17 7 2629 2643 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
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Environmental sciences GE1-350 Geology QE1-996.5 E. H. Bair J. Dozier K. Rittger T. Stillinger W. Kleiber R. E. Davis How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale ( ≤30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: (1) a fused MODIS–Landsat product with daily 30 m spatial resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with 3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing techniques are applied to surface reflectance products from 1 and 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size) but greater mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts, e.g., basin boundary delineation. Other explanations are (1) the importance of daily acquisitions and (2) the limitations of downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models and (2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations, but existing ... |
format |
Article in Journal/Newspaper |
author |
E. H. Bair J. Dozier K. Rittger T. Stillinger W. Kleiber R. E. Davis |
author_facet |
E. H. Bair J. Dozier K. Rittger T. Stillinger W. Kleiber R. E. Davis |
author_sort |
E. H. Bair |
title |
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
title_short |
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
title_full |
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
title_fullStr |
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
title_full_unstemmed |
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
title_sort |
how do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction? |
publisher |
Copernicus Publications |
publishDate |
2023 |
url |
https://doi.org/10.5194/tc-17-2629-2023 https://doaj.org/article/65e671fc316e4e5581794b0a48ac854a |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 17, Pp 2629-2643 (2023) |
op_relation |
https://tc.copernicus.org/articles/17/2629/2023/tc-17-2629-2023.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-17-2629-2023 1994-0416 1994-0424 https://doaj.org/article/65e671fc316e4e5581794b0a48ac854a |
op_doi |
https://doi.org/10.5194/tc-17-2629-2023 |
container_title |
The Cryosphere |
container_volume |
17 |
container_issue |
7 |
container_start_page |
2629 |
op_container_end_page |
2643 |
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1772820468726759424 |