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...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:afe2e102b1394b339e50ab5e43188adf 2023-05-15T15:10:13+02:00 Evaluation of the snow regime in dynamic vegetation land surface models using field measurements E. Kantzas S. Quegan M. Lomas E. Zakharova 2014-03-01 https://doi.org/10.5194/tc-8-487-2014 http://www.the-cryosphere.net/8/487/2014/tc-8-487-2014.pdf https://doaj.org/article/afe2e102b1394b339e50ab5e43188adf en eng Copernicus Publications 1994-0416 1994-0424 doi:10.5194/tc-8-487-2014 http://www.the-cryosphere.net/8/487/2014/tc-8-487-2014.pdf https://doaj.org/article/afe2e102b1394b339e50ab5e43188adf undefined The Cryosphere, Vol 8, Iss 2, Pp 487-502 (2014) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2014 fttriple https://doi.org/10.5194/tc-8-487-2014 2023-01-22T17:53:05Z 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 The Cryosphere Unknown Arctic The Cryosphere 8 2 487 502 |
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geo envir E. Kantzas S. Quegan M. Lomas E. Zakharova Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
topic_facet |
geo envir |
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 |
E. Kantzas S. Quegan M. Lomas E. Zakharova |
author_facet |
E. Kantzas S. Quegan M. Lomas E. Zakharova |
author_sort |
E. Kantzas |
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 |
Copernicus Publications |
publishDate |
2014 |
url |
https://doi.org/10.5194/tc-8-487-2014 http://www.the-cryosphere.net/8/487/2014/tc-8-487-2014.pdf https://doaj.org/article/afe2e102b1394b339e50ab5e43188adf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic The Cryosphere |
genre_facet |
Arctic The Cryosphere |
op_source |
The Cryosphere, Vol 8, Iss 2, Pp 487-502 (2014) |
op_relation |
1994-0416 1994-0424 doi:10.5194/tc-8-487-2014 http://www.the-cryosphere.net/8/487/2014/tc-8-487-2014.pdf https://doaj.org/article/afe2e102b1394b339e50ab5e43188adf |
op_rights |
undefined |
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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1766341256147894272 |