Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition
State-of-the-art numerical snowpack models essentially rely on observational data for initialization, forcing, parametrization, and validation. Such data are available in increasing amounts, but the propagation of related uncertainties in simulation results has received rather limited attention so f...
Published in: | Geoscientific Model Development |
---|---|
Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2015
|
Subjects: | |
Online Access: | https://doi.org/10.5194/gmd-8-3911-2015 https://doaj.org/article/15e9f5390a124d90a4f2082cce572be5 |
id |
ftdoajarticles:oai:doaj.org/article:15e9f5390a124d90a4f2082cce572be5 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:15e9f5390a124d90a4f2082cce572be5 2023-05-15T15:00:52+02:00 Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition T. Sauter F. Obleitner 2015-12-01T00:00:00Z https://doi.org/10.5194/gmd-8-3911-2015 https://doaj.org/article/15e9f5390a124d90a4f2082cce572be5 EN eng Copernicus Publications http://www.geosci-model-dev.net/8/3911/2015/gmd-8-3911-2015.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 1991-959X 1991-9603 doi:10.5194/gmd-8-3911-2015 https://doaj.org/article/15e9f5390a124d90a4f2082cce572be5 Geoscientific Model Development, Vol 8, Iss 12, Pp 3911-3928 (2015) Geology QE1-996.5 article 2015 ftdoajarticles https://doi.org/10.5194/gmd-8-3911-2015 2022-12-30T21:31:49Z State-of-the-art numerical snowpack models essentially rely on observational data for initialization, forcing, parametrization, and validation. Such data are available in increasing amounts, but the propagation of related uncertainties in simulation results has received rather limited attention so far. Depending on their complexity, even small errors can have a profound effect on simulations, which dilutes our confidence in the results. This paper aims at quantification of the overall and fractional contributions of some archetypical measurement uncertainties on snowpack simulations in arctic environments. The sensitivity pattern is studied at two sites representing the accumulation and ablation area of the Kongsvegen glacier (Svalbard), using the snowpack scheme Crocus. The contribution of measurement errors on model output variance, either alone or by interaction, is decomposed using global sensitivity analysis. This allows one to investigate the temporal evolution of the fractional contribution of different factors on key model output metrics, which provides a more detailed understanding of the model's sensitivity pattern. The analysis demonstrates that the specified uncertainties in precipitation and long-wave radiation forcings had a strong influence on the calculated surface-height changes and surface-energy balance components. The model output sensitivity patterns also revealed some characteristic seasonal imprints. For example, uncertainties in long-wave radiation affect the calculated surface-energy balance throughout the year at both study sites, while precipitation exerted the most influence during the winter and at the upper site. Such findings are valuable for identifying critical parameters and improving their measurement; correspondingly, updated simulations may shed new light on the confidence of results from snow or glacier mass- and energy-balance models. This is relevant for many applications, for example in the fields of avalanche and hydrological forecasting. Article in Journal/Newspaper Arctic glacier Svalbard Directory of Open Access Journals: DOAJ Articles Arctic Svalbard Kongsvegen ENVELOPE(12.657,12.657,78.854,78.854) Geoscientific Model Development 8 12 3911 3928 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Geology QE1-996.5 |
spellingShingle |
Geology QE1-996.5 T. Sauter F. Obleitner Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
topic_facet |
Geology QE1-996.5 |
description |
State-of-the-art numerical snowpack models essentially rely on observational data for initialization, forcing, parametrization, and validation. Such data are available in increasing amounts, but the propagation of related uncertainties in simulation results has received rather limited attention so far. Depending on their complexity, even small errors can have a profound effect on simulations, which dilutes our confidence in the results. This paper aims at quantification of the overall and fractional contributions of some archetypical measurement uncertainties on snowpack simulations in arctic environments. The sensitivity pattern is studied at two sites representing the accumulation and ablation area of the Kongsvegen glacier (Svalbard), using the snowpack scheme Crocus. The contribution of measurement errors on model output variance, either alone or by interaction, is decomposed using global sensitivity analysis. This allows one to investigate the temporal evolution of the fractional contribution of different factors on key model output metrics, which provides a more detailed understanding of the model's sensitivity pattern. The analysis demonstrates that the specified uncertainties in precipitation and long-wave radiation forcings had a strong influence on the calculated surface-height changes and surface-energy balance components. The model output sensitivity patterns also revealed some characteristic seasonal imprints. For example, uncertainties in long-wave radiation affect the calculated surface-energy balance throughout the year at both study sites, while precipitation exerted the most influence during the winter and at the upper site. Such findings are valuable for identifying critical parameters and improving their measurement; correspondingly, updated simulations may shed new light on the confidence of results from snow or glacier mass- and energy-balance models. This is relevant for many applications, for example in the fields of avalanche and hydrological forecasting. |
format |
Article in Journal/Newspaper |
author |
T. Sauter F. Obleitner |
author_facet |
T. Sauter F. Obleitner |
author_sort |
T. Sauter |
title |
Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
title_short |
Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
title_full |
Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
title_fullStr |
Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
title_full_unstemmed |
Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition |
title_sort |
assessing the uncertainty of glacier mass-balance simulations in the european arctic based on variance decomposition |
publisher |
Copernicus Publications |
publishDate |
2015 |
url |
https://doi.org/10.5194/gmd-8-3911-2015 https://doaj.org/article/15e9f5390a124d90a4f2082cce572be5 |
long_lat |
ENVELOPE(12.657,12.657,78.854,78.854) |
geographic |
Arctic Svalbard Kongsvegen |
geographic_facet |
Arctic Svalbard Kongsvegen |
genre |
Arctic glacier Svalbard |
genre_facet |
Arctic glacier Svalbard |
op_source |
Geoscientific Model Development, Vol 8, Iss 12, Pp 3911-3928 (2015) |
op_relation |
http://www.geosci-model-dev.net/8/3911/2015/gmd-8-3911-2015.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 1991-959X 1991-9603 doi:10.5194/gmd-8-3911-2015 https://doaj.org/article/15e9f5390a124d90a4f2082cce572be5 |
op_doi |
https://doi.org/10.5194/gmd-8-3911-2015 |
container_title |
Geoscientific Model Development |
container_volume |
8 |
container_issue |
12 |
container_start_page |
3911 |
op_container_end_page |
3928 |
_version_ |
1766332923020050432 |