Residual Analysis of Pressure Gradients and Wind Fields (2025)

Updated Description (v2): 2025 Residual Analysis Focus This dataset provides a detailed residual analysis of pressure gradients and wind fields for the year 2025, derived from the 2020–2025 ERA5 reanalysis dataset. Methodology: Using Principal Component Analysis (PCA), dominant synoptic-scale patterns were removed to isolate stochastic, local, and non-linear atmospheric variations. This approach allows for the identification of sub-synoptic phenomena that are often masked by large-scale pressure systems. Key Features: Identification of high-residual days in 2025. Comparative analysis between localized residuals and large-scale MSLP gradients. Illustrative examples of atmospheric anomalies independent of orographic forcing. Attribution & Versioning: Data Source: ERA5 data are formally attributed according to the Copernicus Climate Change Service (C3S) License [2026]. Revision Note: This version (v2) updates and expands upon the previous publication [DOI: 10.5281/zenodo.19231184] by incorporating 2025-specific analysis and formal attribution metadata.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-27
DOI
https://doi.org/10.5281/zenodo.19247894
Primary Topic
Meteorological Phenomena and Simulations
Type
article
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article

Residual Analysis of Pressure Gradients and Wind Fields (2025)

K.D. Pom
Zenodo (CERN European Organization for Nuclear Research)
Meteorological Phenomena and Simulations
article

Residual Analysis of Pressure Gradients and Wind Fields (2025)

K.D. Pom
article en

Abstract

Updated Description (v2): 2025 Residual Analysis Focus This dataset provides a detailed residual analysis of pressure gradients and wind fields for the year 2025, derived from the 2020–2025 ERA5 reanalysis dataset. Methodology: Using Principal Component Analysis (PCA), dominant synoptic-scale patterns were removed to isolate stochastic, local, and non-linear atmospheric variations. This approach allows for the identification of sub-synoptic phenomena that are often masked by large-scale pressure systems. Key Features: Identification of high-residual days in 2025. Comparative analysis between localized residuals and large-scale MSLP gradients. Illustrative examples of atmospheric anomalies independent of orographic forcing. Attribution & Versioning: Data Source: ERA5 data are formally attributed according to the Copernicus Climate Change Service (C3S) License [2026]. Revision Note: This version (v2) updates and expands upon the previous publication [DOI: 10.5281/zenodo.19231184] by incorporating 2025-specific analysis and formal attribution metadata.

Zenodo (CERN European Organization for Nuclear Research)
Climate action
Openalex Percentile: Top 3%
Meteorological Phenomena and Simulations
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