The Evaluation of Hydroclimatic Variables Over Nordic Fennoscandia Using WRF-CTSM

Iris Mužić, Øivind Hodnebrog, Yeliz A. Yilmaz, Terje K. Berntsen, David M. Lawrence, Negin Sobhani

Research output: Contribution to journalArticlepeer-review

Abstract

This study is the first to evaluate the state-of-the-art coupled land-atmosphere regional climate model WRF-CTSM. It comprises the Weather Research and Forecasting model, WRF, and the Community Terrestrial Systems Model, CTSM (using a configuration that is the same as the Community Land Model Version 5, CLM5). The evaluation is conducted over Nordic Fennoscandia (Norway, Sweden, and Finland) since there is uncertainty in climate models' representation of key hydroclimatic variables in high-latitude regions as they experience accelerated transformation in a changing climate. A 13-year WRF-CTSM simulation (2010–2022) is performed using a 10.5 km horizontal grid spacing to assess the model biases in simulating mean, minimum, and maximum 2 m temperature, precipitation, snow cover (snow depth, snow water equivalent, fractional snow-covered duration), and surface energy balance components. The analysis is based on annual, seasonal, monthly, and daily mean comparisons against openly available observational data sets, comprising regional scale gridded station-based and satellite-based data sets, as well as point scale observations from ground stations. The model shows robust agreement with the evaluation data sets across all considered variables. Furthermore, in situ scale conditions in 2 m temperature, precipitation, snow cover variables, and latent heat are captured with considerable precision. WRF-CTSM is thus considered a powerful research tool for the assessment of land-atmosphere interactions over Nordic Fennoscandia.

Original languageEnglish
Article numbere2024JD043103
JournalJournal of Geophysical Research: Atmospheres
Volume130
Issue number9
DOIs
StatePublished - May 16 2025
Externally publishedYes

Keywords

  • Nordic Fennoscandia
  • WRF-CTSM
  • land-atmosphere interactions
  • model evaluation

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