Soil moisture–temperature coupling during extreme warm conditions in 2018 in Sweden: a case study with WRF-CTSM

Abstract. Soil moisture–temperature coupling (SM–T) significantly influences the frequency and amplitude of heat extremes. It describes how variations in soil moisture affect surface air temperature conditions and vice versa. This study aims to determine the spatial extent and duration of SM–T in southern and central Sweden, an area increasingly recognized as a coupling hot spot, during the extreme warm conditions between May and August 2018 (MJJA 2018). The assessment of coupling is based on a multi-correlation overlay analysis of key coupling variables: surface soil moisture, evaporative fraction, and daily maximum 2 m temperature from four different simulations of the coupled regional climate model WRF-CTSM, along with a merged gridded GLEAM-E-OBS observational–reanalysis dataset. These datasets demonstrate robust precision in representing the magnitude and variability of the key coupling variables during the MJJA 2018 compared to in situ observations, though the precise timing and duration of the coupling are challenging to reproduce at the local scale. WRF-CTSM provides a more realistic depiction of the key coupling variables and their interactions when recent CTSM advancements are incorporated. On average, across the study region and all five datasets, SM–T persisted for 22 d throughout the MJJA period. The atmospheric leg alone (involving daily evaporative fraction and maximum 2 m temperature), averaged across datasets, contributed 92 % to the regional coupling duration.

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Publication Details

Journal
Advances in statistical climatology, meteorology and oceanography
Published
2025-12-02
DOI
https://doi.org/10.5194/ascmo-11-273-2025
Primary Topic
Climate variability and models
Type
article
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article

Soil moisture–temperature coupling during extreme warm conditions in 2018 in Sweden: a case study with WRF-CTSM

Paul A. Dirmeyer, Jana Sillmann, Øivind Hodnebrog, Yeliz A. Yılmaz et al.
Advances in statistical climatology, meteorology and oceanography
Climate variability and models
article

Soil moisture–temperature coupling during extreme warm conditions in 2018 in Sweden: a case study with WRF-CTSM

Paul A. Dirmeyer, Jana Sillmann, Øivind Hodnebrog, Yeliz A. Yılmaz, David M. Lawrence, Iris Mužić, Terje K. Berntsen
article en

Abstract

Abstract. Soil moisture–temperature coupling (SM–T) significantly influences the frequency and amplitude of heat extremes. It describes how variations in soil moisture affect surface air temperature conditions and vice versa. This study aims to determine the spatial extent and duration of SM–T in southern and central Sweden, an area increasingly recognized as a coupling hot spot, during the extreme warm conditions between May and August 2018 (MJJA 2018). The assessment of coupling is based on a multi-correlation overlay analysis of key coupling variables: surface soil moisture, evaporative fraction, and daily maximum 2 m temperature from four different simulations of the coupled regional climate model WRF-CTSM, along with a merged gridded GLEAM-E-OBS observational–reanalysis dataset. These datasets demonstrate robust precision in representing the magnitude and variability of the key coupling variables during the MJJA 2018 compared to in situ observations, though the precise timing and duration of the coupling are challenging to reproduce at the local scale. WRF-CTSM provides a more realistic depiction of the key coupling variables and their interactions when recent CTSM advancements are incorporated. On average, across the study region and all five datasets, SM–T persisted for 22 d throughout the MJJA period. The atmospheric leg alone (involving daily evaporative fraction and maximum 2 m temperature), averaged across datasets, contributed 92 % to the regional coupling duration.

Advances in statistical climatology, meteorology and oceanographyVol. 11(2)
NSF National Center for Atmospheric Research (US), Universität Hamburg (DE), George Mason University (US), University of Oslo (NO), CICERO Center for International Climate Research (NO)
Openalex Percentile: Top 65%
Climate variability and models
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