Premium
Soil Moisture‐Temperature Coupling in a Set of Land Surface Models
Author(s) -
Gevaert A. I.,
Miralles D. G.,
Jeu R. A. M.,
Schellekens J.,
Dolman A. J.
Publication year - 2018
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2017jd027346
Subject(s) - environmental science , forcing (mathematics) , coupling (piping) , water content , climate model , moisture , atmospheric sciences , flux (metallurgy) , vegetation (pathology) , climatology , climate change , meteorology , geology , chemistry , geography , geotechnical engineering , mechanical engineering , medicine , oceanography , organic chemistry , pathology , engineering
The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture‐temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off‐line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture‐temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower‐based results ( r = 0.5–0.7), with the multimodel mean performing similarly to the best‐performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.