Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset
Seasonal snowpack is an essential component in the hydrological cycle and plays a significant role in supplying water resources to downstream users. Yet the snow water equivalent (SWE) in seasonal snowpacks, and its space–time variation, remains highly uncertain, especially over mountainous areas wi...
Published in: | The Cryosphere |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2021
|
Subjects: | |
Online Access: | https://doi.org/10.5194/tc-15-5261-2021 https://doaj.org/article/71f3875eab774a13a7deb2196cf44860 |
id |
ftdoajarticles:oai:doaj.org/article:71f3875eab774a13a7deb2196cf44860 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:71f3875eab774a13a7deb2196cf44860 2023-05-15T18:32:26+02:00 Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset Y. Liu Y. Fang S. A. Margulis 2021-11-01T00:00:00Z https://doi.org/10.5194/tc-15-5261-2021 https://doaj.org/article/71f3875eab774a13a7deb2196cf44860 EN eng Copernicus Publications https://tc.copernicus.org/articles/15/5261/2021/tc-15-5261-2021.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-15-5261-2021 1994-0416 1994-0424 https://doaj.org/article/71f3875eab774a13a7deb2196cf44860 The Cryosphere, Vol 15, Pp 5261-5280 (2021) Environmental sciences GE1-350 Geology QE1-996.5 article 2021 ftdoajarticles https://doi.org/10.5194/tc-15-5261-2021 2022-12-31T09:28:13Z Seasonal snowpack is an essential component in the hydrological cycle and plays a significant role in supplying water resources to downstream users. Yet the snow water equivalent (SWE) in seasonal snowpacks, and its space–time variation, remains highly uncertain, especially over mountainous areas with complex terrain and sparse observations, such as in High Mountain Asia (HMA). In this work, we assessed the spatiotemporal distribution of seasonal SWE, obtained from a new 18-year HMA Snow Reanalysis (HMASR) dataset, as part of the recent NASA High Mountain Asia Team (HiMAT) effort. A Bayesian snow reanalysis scheme previously developed to assimilate satellite-derived fractional snow-covered area (fSCA) products from Landsat and MODIS platforms has been applied to develop the HMASR dataset (at a spatial resolution of 16 arcsec ( ∼500 m) and daily temporal resolution) over the joint Landsat–MODIS period covering water years (WYs) 2000–2017. Based on the results, the HMA-wide total SWE volume is found to be around 163 km 3 on average and ranges from 114 km 3 (WY2001) to 227 km 3 (WY2005) when assessed over 18 WYs. The most abundant snowpacks are found in the northwestern basins (e.g., Indus, Syr Darya and Amu Darya) that are mainly affected by the westerlies, accounting for around 66 % of total seasonal SWE volume. Seasonal snowpack in HMA is depicted by snow accumulating through October to March and April, typically peaking around April and depleting in July–October, with variations across basins and WYs. When examining the elevational distribution over the HMA domain, seasonal SWE volume peaks at mid-elevations (around 3500 m), with over 50 % of the volume stored above 3500 m. Above-average amounts of precipitation causes significant overall increase in SWE volumes across all elevations, while an increase in air temperature ( ∼1.5 K) from cooler to normal conditions leads to an redistribution in snow storage from lower elevations to mid-elevations. This work brings new insight into understanding the climatology ... Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 15 11 5261 5280 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 Y. Liu Y. Fang S. A. Margulis Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Seasonal snowpack is an essential component in the hydrological cycle and plays a significant role in supplying water resources to downstream users. Yet the snow water equivalent (SWE) in seasonal snowpacks, and its space–time variation, remains highly uncertain, especially over mountainous areas with complex terrain and sparse observations, such as in High Mountain Asia (HMA). In this work, we assessed the spatiotemporal distribution of seasonal SWE, obtained from a new 18-year HMA Snow Reanalysis (HMASR) dataset, as part of the recent NASA High Mountain Asia Team (HiMAT) effort. A Bayesian snow reanalysis scheme previously developed to assimilate satellite-derived fractional snow-covered area (fSCA) products from Landsat and MODIS platforms has been applied to develop the HMASR dataset (at a spatial resolution of 16 arcsec ( ∼500 m) and daily temporal resolution) over the joint Landsat–MODIS period covering water years (WYs) 2000–2017. Based on the results, the HMA-wide total SWE volume is found to be around 163 km 3 on average and ranges from 114 km 3 (WY2001) to 227 km 3 (WY2005) when assessed over 18 WYs. The most abundant snowpacks are found in the northwestern basins (e.g., Indus, Syr Darya and Amu Darya) that are mainly affected by the westerlies, accounting for around 66 % of total seasonal SWE volume. Seasonal snowpack in HMA is depicted by snow accumulating through October to March and April, typically peaking around April and depleting in July–October, with variations across basins and WYs. When examining the elevational distribution over the HMA domain, seasonal SWE volume peaks at mid-elevations (around 3500 m), with over 50 % of the volume stored above 3500 m. Above-average amounts of precipitation causes significant overall increase in SWE volumes across all elevations, while an increase in air temperature ( ∼1.5 K) from cooler to normal conditions leads to an redistribution in snow storage from lower elevations to mid-elevations. This work brings new insight into understanding the climatology ... |
format |
Article in Journal/Newspaper |
author |
Y. Liu Y. Fang S. A. Margulis |
author_facet |
Y. Liu Y. Fang S. A. Margulis |
author_sort |
Y. Liu |
title |
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
title_short |
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
title_full |
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
title_fullStr |
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
title_full_unstemmed |
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset |
title_sort |
spatiotemporal distribution of seasonal snow water equivalent in high mountain asia from an 18-year landsat–modis era snow reanalysis dataset |
publisher |
Copernicus Publications |
publishDate |
2021 |
url |
https://doi.org/10.5194/tc-15-5261-2021 https://doaj.org/article/71f3875eab774a13a7deb2196cf44860 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 15, Pp 5261-5280 (2021) |
op_relation |
https://tc.copernicus.org/articles/15/5261/2021/tc-15-5261-2021.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-15-5261-2021 1994-0416 1994-0424 https://doaj.org/article/71f3875eab774a13a7deb2196cf44860 |
op_doi |
https://doi.org/10.5194/tc-15-5261-2021 |
container_title |
The Cryosphere |
container_volume |
15 |
container_issue |
11 |
container_start_page |
5261 |
op_container_end_page |
5280 |
_version_ |
1766216552874508288 |