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Evaluation of the Snow Regime in Dynamic Vegetation Land Surface Models Using Field Measurements : Volume 7, Issue 3 (05/06/2013)

By Kantzas, E.

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Book Id: WPLBN0004022846
Format Type: PDF Article :
File Size: Pages 40
Reproduction Date: 2015

Title: Evaluation of the Snow Regime in Dynamic Vegetation Land Surface Models Using Field Measurements : Volume 7, Issue 3 (05/06/2013)  
Author: Kantzas, E.
Volume: Vol. 7, Issue 3
Language: English
Subject: Science, Cryosphere, Discussions
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Zakharova, E., Quegan, S., Kantzas, E., & Lomas, M. (2013). Evaluation of the Snow Regime in Dynamic Vegetation Land Surface Models Using Field Measurements : Volume 7, Issue 3 (05/06/2013). Retrieved from

Description: Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation, University of Sheffield, Hicks Building, Hounsfield Rd, Sheffield S37RH, UK. An increasing number of studies have demonstrated the 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 the systems processes and its initial state. This study focuses on snow-related variables and extensively utilizes a historical data set (1966–1996) of field snow measurements acquired across the extend of the Former Soviet Union (FSU) to evaluate a range of simulated snow metrics produced by a variety of land surface models, most of them embedded in IPCC-standard climate models. We reveal model-specific issues in simulating snow dynamics such as magnitude and timings of SWE as well as evolution of snow density. We further employ the field snow measurements alongside novel and model-independent methodologies to extract for the first time (i) a fresh snow density value (57–117 kg m–3) for the region and (ii) mean monthly snowpack sublimation estimates across a grassland-dominated western (November–February) [9.2, 6.1, 9.15, 15.25] mm and forested eastern sub-sector (November–March) [1.53, 1.52, 3.05, 3.80, 12.20] mm; we subsequently use the retrieved values to assess relevant model outputs. The discussion session consists of two parts. The first describes a sensitivity study where field data of snow depth and snow density are forced directly into the surface heat exchange formulation of a land surface model to evaluate how inaccuracies in simulating snow metrics affect important modeled variables and carbon fluxes such as soil temperature, thaw depth and soil carbon decomposition. The second part showcases how the field data can be assimilated with ready-available optimization techniques to pinpoint model issues and improve their performance.

Evaluation of the snow regime in dynamic vegetation land surface models using field measurements

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