Discrepancies in the Representation of Surface and Layered Soil Moisture in Earth System Models

Surface soil moisture (mrsos) and vertically integrated soil moisture (mrsol) over the top 10 cm should, by definition, be physically consistent in Earth System Models (ESMs). However, an evaluation of nine CMIP6 models reveals substantial inconsistencies: in some models, mrsos and integrated mrsol agree globally; in others, they align only in specific regions; and in a few, they diverge across all grid cells. These discrepancies arise from a combination of factors, including metadata errors, inconsistent variable definitions, or diagnostic sequencing within the model. We demonstrate how such issues can lead to significant biases, even when both variables are present and seemingly well-defined. As model complexity increases and multi-model comparisons become more common, assumptions about variable equivalence may lead to flawed conclusions. This study highlights the need for routine consistency checks, improved metadata standards, and community-wide practices that ensure reliability of derived variables across ESM outputs, particularly in preparation for CMIP7.

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Published
2025-08-14
DOI
https://doi.org/10.22541/essoar.175520260.03075714/v1
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
0.00

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article

Discrepancies in the Representation of Surface and Layered Soil Moisture in Earth System Models

Nathan Collier, Elias Massoud, Mingjie Shi, Min Xu et al.
Geophysics and Gravity Measurements
article

Discrepancies in the Representation of Surface and Layered Soil Moisture in Earth System Models

Nathan Collier, Elias Massoud, Mingjie Shi, Min Xu, Forrest M. Hoffman
article en

Abstract

Surface soil moisture (mrsos) and vertically integrated soil moisture (mrsol) over the top 10 cm should, by definition, be physically consistent in Earth System Models (ESMs). However, an evaluation of nine CMIP6 models reveals substantial inconsistencies: in some models, mrsos and integrated mrsol agree globally; in others, they align only in specific regions; and in a few, they diverge across all grid cells. These discrepancies arise from a combination of factors, including metadata errors, inconsistent variable definitions, or diagnostic sequencing within the model. We demonstrate how such issues can lead to significant biases, even when both variables are present and seemingly well-defined. As model complexity increases and multi-model comparisons become more common, assumptions about variable equivalence may lead to flawed conclusions. This study highlights the need for routine consistency checks, improved metadata standards, and community-wide practices that ensure reliability of derived variables across ESM outputs, particularly in preparation for CMIP7.

Oak Ridge National Laboratory (US), Pacific Northwest National Laboratory (US)
U.S. Department of Energy, Battelle, UT-Battelle, Directorate for Biological Sciences, Office of Science, Biological and Environmental Research, Laboratory Directed Research and Development, Pacific Northwest National Laboratory
Openalex Percentile: Top 78%
Geophysics and Gravity Measurements
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