Soil temperature simulation results in Alaska (1980 - 2014) – Data archive for “Evaluation and enhancement of permafrost modeling with the NASA Catchment Land Surface Model”

• Main Authors: Tao, Jing, Reichle, Rolf, Koster, Randal, Forman, Barton, Xue, Yuan
• Format: Dataset
• Language: unknown
• Published: 2017
• Subjects: Soil temperature; Permafrost; NASA CLSM; Alaska; Merra; permafrost
• Online Access: http://hdl.handle.net/1903/20168; https://doi.org/10.13016/M2K649V0F

The datasets archived here include simulation results discussed in the paper, “Evaluation and enhancement of permafrost modeling with the NASA Catchment Land Surface Model”, to be published in Journal of Advances in Modeling Earth Systems. Specifically, subsurface soil temperatures for 1980-2014 across Alaska were produced by a baseline simulation with the NASA Catchment Land Surface Model (CLSM). Five sets of point simulations were also conducted at permafrost sites in Alaska, including 1) T1BC - the top layer temperature is prescribed to observations, 2) T1BC_OrgC – repeat of the T1BC simulation but using the updated model version that incorporates soil thermal impacts of organic carbon content, 3) T2BC - the temperatures of both the 1st and 2nd layer are prescribed to observations, 4) T2BC_OrgC – repeat of the T2BC simulation but using the updated model version, and 5) M2_OrgC – simulations with the updated model version driven by MERRA-2 forcing. Details about the model configuration and the changes defining the updated model version can be found in the paper. The major findings in this paper include: a) profile-average RMSE of simulated soil temperature versus in situ observations is reduced by using corrected local forcing and land cover; b) subsurface heat transport is mostly realistic, and when not, it is improved via treatment of soil organic carbon-related thermal properties; and c) mean bias and RMSE of climatological ALT between simulations and observations are significantly reduced with updated model version. NASA Interdisciplinary Science program https://doi.org/10.1002/2017MS001019