Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing
Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 million square km of Earth's surface (31 % of the land area) each year, and is thus an important expression of and driver of the Earth’s climate. In recent years, Northern Hemisphere...
Published in: | The Cryosphere |
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Format: | Article in Journal/Newspaper |
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Copernicus Publications
2022
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Online Access: | https://nrl.northumbria.ac.uk/id/eprint/49828/ https://doi.org/10.5194/tc-16-3531-2022 https://nrl.northumbria.ac.uk/id/eprint/49828/8/Tsang_2022.pdf https://nrl.northumbria.ac.uk/id/eprint/49828/1/Tsang_2022_TCD.pdf |
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ftunivnorthumb:oai:nrl.northumbria.ac.uk:49828 2023-05-15T15:15:04+02:00 Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing Tsang, Leung Durand, Michael Derksen, Chris Barros, Ana P. Kang, Do-Hyuk Lievens, Hans Marshall, Hans-Peter Zhu, Jiyue Johnson, Joel King, Joshua Lemmetyinen, Juha Sandells, Melody Rutter, Nick Siqueira, Paul Nolin, Anne Osmanoglu, Batu Vuyovich, Carrie Kim, Edward J. Taylor, Drew Merkouriadi, Ioanna Brucker, Ludovic Navari, Mahdi Dumont, Marie Kelly, Richard Kim, Rhae Sung Liao, Tien-Hao Xu, Xiaolan 2022-09-02 text https://nrl.northumbria.ac.uk/id/eprint/49828/ https://doi.org/10.5194/tc-16-3531-2022 https://nrl.northumbria.ac.uk/id/eprint/49828/8/Tsang_2022.pdf https://nrl.northumbria.ac.uk/id/eprint/49828/1/Tsang_2022_TCD.pdf en eng Copernicus Publications https://nrl.northumbria.ac.uk/id/eprint/49828/8/Tsang_2022.pdf https://nrl.northumbria.ac.uk/id/eprint/49828/1/Tsang_2022_TCD.pdf Tsang, Leung, Durand, Michael, Derksen, Chris, Barros, Ana P., Kang, Do-Hyuk, Lievens, Hans, Marshall, Hans-Peter, Zhu, Jiyue, Johnson, Joel, King, Joshua, Lemmetyinen, Juha, Sandells, Melody, Rutter, Nick, Siqueira, Paul, Nolin, Anne, Osmanoglu, Batu, Vuyovich, Carrie, Kim, Edward J., Taylor, Drew, Merkouriadi, Ioanna, Brucker, Ludovic, Navari, Mahdi, Dumont, Marie, Kelly, Richard, Kim, Rhae Sung, Liao, Tien-Hao and Xu, Xiaolan (2022) Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing. The Cryosphere, 16. pp. 3531-3573. ISSN 1994-0416 cc_by_4_0 CC-BY F800 Physical and Terrestrial Geographical and Environmental Sciences Article PeerReviewed 2022 ftunivnorthumb https://doi.org/10.5194/tc-16-3531-2022 2022-09-25T06:16:02Z Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 million square km of Earth's surface (31 % of the land area) each year, and is thus an important expression of and driver of the Earth’s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (~ −13 %/decade) as Arctic summer sea ice. More than one-sixth of the world’s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth’s cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of snow stored on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations will not be able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high socio-economic value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-Band Synthetic Aperture Radar (SAR) for global monitoring of SWE. We describe radar interactions with snow-covered landscapes, characterization of snowpack properties using radar measurements, and refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimetre-scale snow grains. Inference of global snow ... Article in Journal/Newspaper Arctic Sea ice The Cryosphere Northumbria University, Newcastle: Northumbria Research Link (NRL) Arctic The Cryosphere 16 9 3531 3573 |
institution |
Open Polar |
collection |
Northumbria University, Newcastle: Northumbria Research Link (NRL) |
op_collection_id |
ftunivnorthumb |
language |
English |
topic |
F800 Physical and Terrestrial Geographical and Environmental Sciences |
spellingShingle |
F800 Physical and Terrestrial Geographical and Environmental Sciences Tsang, Leung Durand, Michael Derksen, Chris Barros, Ana P. Kang, Do-Hyuk Lievens, Hans Marshall, Hans-Peter Zhu, Jiyue Johnson, Joel King, Joshua Lemmetyinen, Juha Sandells, Melody Rutter, Nick Siqueira, Paul Nolin, Anne Osmanoglu, Batu Vuyovich, Carrie Kim, Edward J. Taylor, Drew Merkouriadi, Ioanna Brucker, Ludovic Navari, Mahdi Dumont, Marie Kelly, Richard Kim, Rhae Sung Liao, Tien-Hao Xu, Xiaolan Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
topic_facet |
F800 Physical and Terrestrial Geographical and Environmental Sciences |
description |
Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 million square km of Earth's surface (31 % of the land area) each year, and is thus an important expression of and driver of the Earth’s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (~ −13 %/decade) as Arctic summer sea ice. More than one-sixth of the world’s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth’s cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of snow stored on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations will not be able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high socio-economic value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-Band Synthetic Aperture Radar (SAR) for global monitoring of SWE. We describe radar interactions with snow-covered landscapes, characterization of snowpack properties using radar measurements, and refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimetre-scale snow grains. Inference of global snow ... |
format |
Article in Journal/Newspaper |
author |
Tsang, Leung Durand, Michael Derksen, Chris Barros, Ana P. Kang, Do-Hyuk Lievens, Hans Marshall, Hans-Peter Zhu, Jiyue Johnson, Joel King, Joshua Lemmetyinen, Juha Sandells, Melody Rutter, Nick Siqueira, Paul Nolin, Anne Osmanoglu, Batu Vuyovich, Carrie Kim, Edward J. Taylor, Drew Merkouriadi, Ioanna Brucker, Ludovic Navari, Mahdi Dumont, Marie Kelly, Richard Kim, Rhae Sung Liao, Tien-Hao Xu, Xiaolan |
author_facet |
Tsang, Leung Durand, Michael Derksen, Chris Barros, Ana P. Kang, Do-Hyuk Lievens, Hans Marshall, Hans-Peter Zhu, Jiyue Johnson, Joel King, Joshua Lemmetyinen, Juha Sandells, Melody Rutter, Nick Siqueira, Paul Nolin, Anne Osmanoglu, Batu Vuyovich, Carrie Kim, Edward J. Taylor, Drew Merkouriadi, Ioanna Brucker, Ludovic Navari, Mahdi Dumont, Marie Kelly, Richard Kim, Rhae Sung Liao, Tien-Hao Xu, Xiaolan |
author_sort |
Tsang, Leung |
title |
Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
title_short |
Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
title_full |
Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
title_fullStr |
Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
title_full_unstemmed |
Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing |
title_sort |
global monitoring of snow water equivalent using high frequency radar remote sensing |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://nrl.northumbria.ac.uk/id/eprint/49828/ https://doi.org/10.5194/tc-16-3531-2022 https://nrl.northumbria.ac.uk/id/eprint/49828/8/Tsang_2022.pdf https://nrl.northumbria.ac.uk/id/eprint/49828/1/Tsang_2022_TCD.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice The Cryosphere |
genre_facet |
Arctic Sea ice The Cryosphere |
op_relation |
https://nrl.northumbria.ac.uk/id/eprint/49828/8/Tsang_2022.pdf https://nrl.northumbria.ac.uk/id/eprint/49828/1/Tsang_2022_TCD.pdf Tsang, Leung, Durand, Michael, Derksen, Chris, Barros, Ana P., Kang, Do-Hyuk, Lievens, Hans, Marshall, Hans-Peter, Zhu, Jiyue, Johnson, Joel, King, Joshua, Lemmetyinen, Juha, Sandells, Melody, Rutter, Nick, Siqueira, Paul, Nolin, Anne, Osmanoglu, Batu, Vuyovich, Carrie, Kim, Edward J., Taylor, Drew, Merkouriadi, Ioanna, Brucker, Ludovic, Navari, Mahdi, Dumont, Marie, Kelly, Richard, Kim, Rhae Sung, Liao, Tien-Hao and Xu, Xiaolan (2022) Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing. The Cryosphere, 16. pp. 3531-3573. ISSN 1994-0416 |
op_rights |
cc_by_4_0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/tc-16-3531-2022 |
container_title |
The Cryosphere |
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16 |
container_issue |
9 |
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