Evaluation of the snow regime in dynamic vegetation land surface models using field measurements
An increasing number of studies have demonstrated significant climatic and ecological changes occurring in the northern latitudes over the past decades. As coupled Earth-system models attempt to describe and simulate the dynamics and complex feedbacks of the Arctic environment, it is important to re...
Published in: | The Cryosphere |
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Format: | Article in Journal/Newspaper |
Language: | English |
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European Geosciences Union
2014
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Online Access: | https://eprints.whiterose.ac.uk/86265/ https://eprints.whiterose.ac.uk/86265/7/WRRO_86265.pdf https://doi.org/10.5194/tc-8-487-2014 |
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ftleedsuniv:oai:eprints.whiterose.ac.uk:86265 2023-05-15T15:09:36+02:00 Evaluation of the snow regime in dynamic vegetation land surface models using field measurements Kantzas, E. Quegan, S. Lomas, M. Zakharova, E. 2014-03-24 text https://eprints.whiterose.ac.uk/86265/ https://eprints.whiterose.ac.uk/86265/7/WRRO_86265.pdf https://doi.org/10.5194/tc-8-487-2014 en eng European Geosciences Union https://eprints.whiterose.ac.uk/86265/7/WRRO_86265.pdf Kantzas, E., Quegan, S., Lomas, M. et al. (1 more author) (2014) Evaluation of the snow regime in dynamic vegetation land surface models using field measurements. Cryosphere, 8 (2). 487 - 502. ISSN 1994-0416 Article PeerReviewed 2014 ftleedsuniv https://doi.org/10.5194/tc-8-487-2014 2023-01-30T21:32:46Z An increasing number of studies have demonstrated significant climatic and ecological changes occurring in the northern latitudes over the past decades. As coupled Earth-system models attempt to describe and simulate the dynamics and complex feedbacks of the Arctic environment, it is important to reduce their uncertainties in short-term predictions by improving the description of both system processes and its initial state. This study focuses on snow-related variables and makes extensive use of a historical data set (1966–1996) of field snow measurements acquired across the extent of the former Soviet Union to evaluate a range of simulated snow metrics produced by several land surface models, most of them embedded in IPCC-standard climate models. We reveal model-specific failings in simulating snowpack properties such as magnitude, inter-annual variability, timings of snow water equivalent and evolution of snow density. We develop novel and model-independent methodologies that use the field snow measurements to extract the values of fresh snow density and snowpack sublimation, and exploit them to assess model outputs. By directly forcing the surface heat exchange formulation of a land surface model with field data on snow depth and snow density, we evaluate how inaccuracies in simulating snow metrics affect soil temperature, thaw depth and soil carbon decomposition. We also show how field data can be assimilated into models using optimization techniques in order to identify model defects and improve model performance. Article in Journal/Newspaper Arctic White Rose Research Online (Universities of Leeds, Sheffield & York) Arctic The Cryosphere 8 2 487 502 |
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Open Polar |
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White Rose Research Online (Universities of Leeds, Sheffield & York) |
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ftleedsuniv |
language |
English |
description |
An increasing number of studies have demonstrated significant climatic and ecological changes occurring in the northern latitudes over the past decades. As coupled Earth-system models attempt to describe and simulate the dynamics and complex feedbacks of the Arctic environment, it is important to reduce their uncertainties in short-term predictions by improving the description of both system processes and its initial state. This study focuses on snow-related variables and makes extensive use of a historical data set (1966–1996) of field snow measurements acquired across the extent of the former Soviet Union to evaluate a range of simulated snow metrics produced by several land surface models, most of them embedded in IPCC-standard climate models. We reveal model-specific failings in simulating snowpack properties such as magnitude, inter-annual variability, timings of snow water equivalent and evolution of snow density. We develop novel and model-independent methodologies that use the field snow measurements to extract the values of fresh snow density and snowpack sublimation, and exploit them to assess model outputs. By directly forcing the surface heat exchange formulation of a land surface model with field data on snow depth and snow density, we evaluate how inaccuracies in simulating snow metrics affect soil temperature, thaw depth and soil carbon decomposition. We also show how field data can be assimilated into models using optimization techniques in order to identify model defects and improve model performance. |
format |
Article in Journal/Newspaper |
author |
Kantzas, E. Quegan, S. Lomas, M. Zakharova, E. |
spellingShingle |
Kantzas, E. Quegan, S. Lomas, M. Zakharova, E. Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
author_facet |
Kantzas, E. Quegan, S. Lomas, M. Zakharova, E. |
author_sort |
Kantzas, E. |
title |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
title_short |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
title_full |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
title_fullStr |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
title_full_unstemmed |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
title_sort |
evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
publisher |
European Geosciences Union |
publishDate |
2014 |
url |
https://eprints.whiterose.ac.uk/86265/ https://eprints.whiterose.ac.uk/86265/7/WRRO_86265.pdf https://doi.org/10.5194/tc-8-487-2014 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
https://eprints.whiterose.ac.uk/86265/7/WRRO_86265.pdf Kantzas, E., Quegan, S., Lomas, M. et al. (1 more author) (2014) Evaluation of the snow regime in dynamic vegetation land surface models using field measurements. Cryosphere, 8 (2). 487 - 502. ISSN 1994-0416 |
op_doi |
https://doi.org/10.5194/tc-8-487-2014 |
container_title |
The Cryosphere |
container_volume |
8 |
container_issue |
2 |
container_start_page |
487 |
op_container_end_page |
502 |
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1766340756515061760 |