Systematic comparison of the Lorenz energy cycle in four reanalysis datasets

In this study, the global mean characteristics and spatial distribution differences of the Lorenz energy cycle (LEC) were investigated using four atmospheric reanalysis datasets over 44 years from 1980 to 2023. The global mean values show that the energy terms exhibit relatively small differences among the datasets, with values ranging from − 7.4 to + 3.7% relative to the multi-reanalysis mean. In contrast, substantial discrepancies are found in most conversion, generation, and dissipation terms: Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) displayed relatively high values, whereas National Centers for Environmental Prediction-Department of Energy Atmospheric Model Intercomparison Project II Reanalysis (R2) (NCEP_R2) had low values. Among the conversion terms, the large differences were observed in the conversion from eddy available potential energy to eddy kinetic energy (C(PE, KE)), which exhibits deviations of approximately ± 13% relative to the multi-reanalysis mean. The generation term of eddy available potential energy (G(PE)) and the dissipation term of zonal mean kinetic energy (D(KM)) exhibit deviations of up to approximately + 50% and + 21%, respectively. Spatially, the most pronounced differences among the datasets occur in the polar regions, stratosphere, and jet stream zones. These patterns reflect the combined influence of uncertainties in thermodynamic structure, eddy activity, and energy transfer processes, which can be attributable to differences in horizontal resolution, data assimilation frameworks, and observational constraints. Consequently, the choice of reanalysis datasets may lead to an overestimation or underestimation of the associated physical processes, particularly in regions exhibiting large interdataset discrepancies in LEC components.

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Publication Details

Journal
Climate Dynamics
Published
2026-05-01
DOI
https://doi.org/10.1007/s00382-026-08153-9
Primary Topic
Climate variability and models
Type
article
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article

Systematic comparison of the Lorenz energy cycle in four reanalysis datasets

Maeng‐Ki Kim, Doo‐Sun R. Park, Hyo‐Seok Park, Ji-Seon Oh et al.
Climate Dynamics
Climate variability and models
article

Systematic comparison of the Lorenz energy cycle in four reanalysis datasets

Maeng‐Ki Kim, Doo‐Sun R. Park, Hyo‐Seok Park, Ji-Seon Oh, Yeon-Hee Kim, Seung-Ki Min, Jong-Yeon Park
article en

Abstract

In this study, the global mean characteristics and spatial distribution differences of the Lorenz energy cycle (LEC) were investigated using four atmospheric reanalysis datasets over 44 years from 1980 to 2023. The global mean values show that the energy terms exhibit relatively small differences among the datasets, with values ranging from − 7.4 to + 3.7% relative to the multi-reanalysis mean. In contrast, substantial discrepancies are found in most conversion, generation, and dissipation terms: Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) displayed relatively high values, whereas National Centers for Environmental Prediction-Department of Energy Atmospheric Model Intercomparison Project II Reanalysis (R2) (NCEP_R2) had low values. Among the conversion terms, the large differences were observed in the conversion from eddy available potential energy to eddy kinetic energy (C(PE, KE)), which exhibits deviations of approximately ± 13% relative to the multi-reanalysis mean. The generation term of eddy available potential energy (G(PE)) and the dissipation term of zonal mean kinetic energy (D(KM)) exhibit deviations of up to approximately + 50% and + 21%, respectively. Spatially, the most pronounced differences among the datasets occur in the polar regions, stratosphere, and jet stream zones. These patterns reflect the combined influence of uncertainties in thermodynamic structure, eddy activity, and energy transfer processes, which can be attributable to differences in horizontal resolution, data assimilation frameworks, and observational constraints. Consequently, the choice of reanalysis datasets may lead to an overestimation or underestimation of the associated physical processes, particularly in regions exhibiting large interdataset discrepancies in LEC components.

Climate DynamicsVol. 64(5)
Pohang University of Science and Technology (KR), Korea Meteorological Administration (KR), Kongju National University (KR), Kyungpook National University (KR), Korea Golf University (KR), National Institute of Meteorological Sciences (KR), Hanyang University (KR), Jeonbuk National University (KR)
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Openalex Percentile: Top 5%
Climate variability and models
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