TY - JOUR
T1 - Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region
AU - Wang, Wenli
AU - Rinke, Annette
AU - Moore, John C.
AU - Ji, Duoying
AU - Cui, Xuefeng
AU - Peng, Shushi
AU - Lawrence, David M.
AU - McGuire, A. David
AU - Burke, Eleanor J.
AU - Chen, Xiaodong
AU - Decharme, Bertrand
AU - Koven, Charles
AU - MacDougall, Andrew
AU - Saito, Kazuyuki
AU - Zhang, Wenxin
AU - Alkama, Ramdane
AU - Bohn, Theodore J.
AU - Ciais, Philippe
AU - Delire, Christine
AU - Gouttevin, Isabelle
AU - Hajima, Tomohiro
AU - Krinner, Gerhard
AU - Lettenmaier, Dennis P.
AU - Miller, Paul A.
AU - Smith, Benjamin
AU - Sueyoshi, Tetsuo
AU - Sherstiukov, Artem B.
N1 - Publisher Copyright:
© Author(s) 2016.
PY - 2016/8/11
Y1 - 2016/8/11
N2 - A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C-1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
AB - A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C-1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.
UR - https://www.scopus.com/pages/publications/84982132334
U2 - 10.5194/tc-10-1721-2016
DO - 10.5194/tc-10-1721-2016
M3 - Article
AN - SCOPUS:84982132334
SN - 1994-0416
VL - 10
SP - 1721
EP - 1737
JO - Cryosphere
JF - Cryosphere
IS - 4
ER -