Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling

The Snow Ensemble Uncertainty Project (SEUP) is an effort to establish a baseline characterization of snow water equivalent (SWE) uncertainty across North America with the goal of informing global snow observational needs. An ensemble-based modeling approach, encompassing a suite of current operatio...

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Published in:The Cryosphere
Main Authors: R. S. Kim, S. Kumar, C. Vuyovich, P. Houser, J. Lundquist, L. Mudryk, M. Durand, A. Barros, E. J. Kim, B. A. Forman, E. D. Gutmann, M. L. Wrzesien, C. Garnaud, M. Sandells, H.-P. Marshall, N. Cristea, J. M. Pflug, J. Johnston, Y. Cao, D. Mocko, S. Wang
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2021
Subjects:
Online Access:https://doi.org/10.5194/tc-15-771-2021
https://doaj.org/article/e5567893cba84c9c880ad4c8c81c14e9
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spelling ftdoajarticles:oai:doaj.org/article:e5567893cba84c9c880ad4c8c81c14e9 2023-05-15T18:30:59+02:00 Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling R. S. Kim S. Kumar C. Vuyovich P. Houser J. Lundquist L. Mudryk M. Durand A. Barros E. J. Kim B. A. Forman E. D. Gutmann M. L. Wrzesien C. Garnaud M. Sandells H.-P. Marshall N. Cristea J. M. Pflug J. Johnston Y. Cao D. Mocko S. Wang 2021-02-01T00:00:00Z https://doi.org/10.5194/tc-15-771-2021 https://doaj.org/article/e5567893cba84c9c880ad4c8c81c14e9 EN eng Copernicus Publications https://tc.copernicus.org/articles/15/771/2021/tc-15-771-2021.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-15-771-2021 1994-0416 1994-0424 https://doaj.org/article/e5567893cba84c9c880ad4c8c81c14e9 The Cryosphere, Vol 15, Pp 771-791 (2021) Environmental sciences GE1-350 Geology QE1-996.5 article 2021 ftdoajarticles https://doi.org/10.5194/tc-15-771-2021 2022-12-31T10:47:16Z The Snow Ensemble Uncertainty Project (SEUP) is an effort to establish a baseline characterization of snow water equivalent (SWE) uncertainty across North America with the goal of informing global snow observational needs. An ensemble-based modeling approach, encompassing a suite of current operational models is used to assess the uncertainty in SWE and total snow storage (SWS) estimation over North America during the 2009–2017 period. The highest modeled SWE uncertainty is observed in mountainous regions, likely due to the relatively deep snow, forcing uncertainties, and variability between the different models in resolving the snow processes over complex terrain. This highlights a need for high-resolution observations in mountains to capture the high spatial SWE variability. The greatest SWS is found in Tundra regions where, even though the spatiotemporal variability in modeled SWE is low, there is considerable uncertainty in the SWS estimates due to the large areal extent over which those estimates are spread. This highlights the need for high accuracy in snow estimations across the Tundra. In midlatitude boreal forests, large uncertainties in both SWE and SWS indicate that vegetation–snow impacts are a critical area where focused improvements to modeled snow estimation efforts need to be made. Finally, the SEUP results indicate that SWE uncertainty is driving runoff uncertainty, and measurements may be beneficial in reducing uncertainty in SWE and runoff, during the melt season at high latitudes (e.g., Tundra and Taiga regions) and in the western mountain regions, whereas observations at (or near) peak SWE accumulation are more helpful over the midlatitudes. Article in Journal/Newspaper taiga The Cryosphere Tundra Directory of Open Access Journals: DOAJ Articles The Cryosphere 15 2 771 791
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
R. S. Kim
S. Kumar
C. Vuyovich
P. Houser
J. Lundquist
L. Mudryk
M. Durand
A. Barros
E. J. Kim
B. A. Forman
E. D. Gutmann
M. L. Wrzesien
C. Garnaud
M. Sandells
H.-P. Marshall
N. Cristea
J. M. Pflug
J. Johnston
Y. Cao
D. Mocko
S. Wang
Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description The Snow Ensemble Uncertainty Project (SEUP) is an effort to establish a baseline characterization of snow water equivalent (SWE) uncertainty across North America with the goal of informing global snow observational needs. An ensemble-based modeling approach, encompassing a suite of current operational models is used to assess the uncertainty in SWE and total snow storage (SWS) estimation over North America during the 2009–2017 period. The highest modeled SWE uncertainty is observed in mountainous regions, likely due to the relatively deep snow, forcing uncertainties, and variability between the different models in resolving the snow processes over complex terrain. This highlights a need for high-resolution observations in mountains to capture the high spatial SWE variability. The greatest SWS is found in Tundra regions where, even though the spatiotemporal variability in modeled SWE is low, there is considerable uncertainty in the SWS estimates due to the large areal extent over which those estimates are spread. This highlights the need for high accuracy in snow estimations across the Tundra. In midlatitude boreal forests, large uncertainties in both SWE and SWS indicate that vegetation–snow impacts are a critical area where focused improvements to modeled snow estimation efforts need to be made. Finally, the SEUP results indicate that SWE uncertainty is driving runoff uncertainty, and measurements may be beneficial in reducing uncertainty in SWE and runoff, during the melt season at high latitudes (e.g., Tundra and Taiga regions) and in the western mountain regions, whereas observations at (or near) peak SWE accumulation are more helpful over the midlatitudes.
format Article in Journal/Newspaper
author R. S. Kim
S. Kumar
C. Vuyovich
P. Houser
J. Lundquist
L. Mudryk
M. Durand
A. Barros
E. J. Kim
B. A. Forman
E. D. Gutmann
M. L. Wrzesien
C. Garnaud
M. Sandells
H.-P. Marshall
N. Cristea
J. M. Pflug
J. Johnston
Y. Cao
D. Mocko
S. Wang
author_facet R. S. Kim
S. Kumar
C. Vuyovich
P. Houser
J. Lundquist
L. Mudryk
M. Durand
A. Barros
E. J. Kim
B. A. Forman
E. D. Gutmann
M. L. Wrzesien
C. Garnaud
M. Sandells
H.-P. Marshall
N. Cristea
J. M. Pflug
J. Johnston
Y. Cao
D. Mocko
S. Wang
author_sort R. S. Kim
title Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
title_short Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
title_full Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
title_fullStr Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
title_full_unstemmed Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
title_sort snow ensemble uncertainty project (seup): quantification of snow water equivalent uncertainty across north america via ensemble land surface modeling
publisher Copernicus Publications
publishDate 2021
url https://doi.org/10.5194/tc-15-771-2021
https://doaj.org/article/e5567893cba84c9c880ad4c8c81c14e9
genre taiga
The Cryosphere
Tundra
genre_facet taiga
The Cryosphere
Tundra
op_source The Cryosphere, Vol 15, Pp 771-791 (2021)
op_relation https://tc.copernicus.org/articles/15/771/2021/tc-15-771-2021.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-15-771-2021
1994-0416
1994-0424
https://doaj.org/article/e5567893cba84c9c880ad4c8c81c14e9
op_doi https://doi.org/10.5194/tc-15-771-2021
container_title The Cryosphere
container_volume 15
container_issue 2
container_start_page 771
op_container_end_page 791
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