Assessing the performance of the community terrestrial system model in simulating arctic permafrost

Our study aims to evaluate the performance of the Community Terrestrial System Model (CTSM) in simulating Arctic permafrost areas. We compare (1) soil temperatures against an extensive network of 554 in-situ stations, (2) the active layer thickness against the Circumpolar Active Layer Monitoring Net...

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Bibliographic Details
Main Author: Damseaux, A.
Format: Conference Object
Language:English
Published: 2023
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5015922
Description
Summary:Our study aims to evaluate the performance of the Community Terrestrial System Model (CTSM) in simulating Arctic permafrost areas. We compare (1) soil temperatures against an extensive network of 554 in-situ stations, (2) the active layer thickness against the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, the active layer thickness, and the permafrost extent against the grid-based product from the ESA Climate Change Initiative covering 1980 to 2021. To overcome the limitation of using average depth to assess land models, we introduce a new interpolation method called Partial Curve Mapping. Unlike traditional methods, this approach allows us to evaluate the land model without losing the soil depth variability, which we find essential to accurately assess any land model's capabilities. In addition, we run the model in three different configurations. The first is the (1) default mode with ERA5 atmospheric forcings. The second is the (2) GSWP3 mode with GSWP3 atmospheric forcings. The third is the (3) adaptative soil mode, where we change some soil characteristics based on local PFTs rather than using regional maps in the (1) default mode. Our results provide valuable insights on the performance of CTSM against the current largest land-model evaluation dataset over the Arctic region. In particular, we provide effective tools to measure the model's permafrost features and variability in terms of geographic space, time and depth. Furthermore, the different configurations allows us to test the impact of different forcings and soil characteristics in the model.