A Lagrangian Perspective on the Growth of Midlatitude Storms

Abstract Extratropical storms dominate midlatitude climate and weather and are known to grow baroclinically and decay barotropically. Traditionally, quantitative climatic measures of storm activity have been mostly based on Eulerian measures, taking into account the mean state of the atmosphere and how those affect Eulerian eddy activity, but they do not consider the Lagrangian growth of the storms themselves. Here, using ERA‐5 reanalysis data and tracking all extratropical storms (cyclones and anticyclones) from 83 years of data, we examine the actual growth of the storms and compare it to the Eulerian characteristics of the background state as the storms develop. In the limit of weak baroclinicity, we find that baroclinicity provides a good measure for storm maximum intensity. However, this monotonic relationship breaks for high baroclinicity levels. We show that although the actual growth rate of individual storms monotonically increases with baroclinicity, the reduction in maximum intensity at high baroclinicity is caused by a decrease in storm growth time. Based on the Lagrangian analysis, we suggest a nonlinear correction to the traditional linear connection between baroclinicity and storms' activity. Then, we show that a simplified model of storm growth, incorporating the baroclinicity effect on the vertical tilt of anomalies, reproduces the observed nonlinear relationship. Expanding the analysis to include the mean flow's barotropic properties highlights their marginal effect on storm growth rate, but the crucial impact on growth time. Our results emphasize the potential of Lagrangianly studying storm dynamics to advance understanding of the midlatitude climate.

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Publication Details

Journal
AGU Advances
Published
2025-04-29
DOI
https://doi.org/10.1029/2024av001555
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
4.42

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article

A Lagrangian Perspective on the Growth of Midlatitude Storms

Yohai Kaspi, Or Hadas
4 citations
AGU Advances
Climate variability and models
4.42
article

A Lagrangian Perspective on the Growth of Midlatitude Storms

Yohai Kaspi, Or Hadas
article en
4 citations

Abstract

Abstract Extratropical storms dominate midlatitude climate and weather and are known to grow baroclinically and decay barotropically. Traditionally, quantitative climatic measures of storm activity have been mostly based on Eulerian measures, taking into account the mean state of the atmosphere and how those affect Eulerian eddy activity, but they do not consider the Lagrangian growth of the storms themselves. Here, using ERA‐5 reanalysis data and tracking all extratropical storms (cyclones and anticyclones) from 83 years of data, we examine the actual growth of the storms and compare it to the Eulerian characteristics of the background state as the storms develop. In the limit of weak baroclinicity, we find that baroclinicity provides a good measure for storm maximum intensity. However, this monotonic relationship breaks for high baroclinicity levels. We show that although the actual growth rate of individual storms monotonically increases with baroclinicity, the reduction in maximum intensity at high baroclinicity is caused by a decrease in storm growth time. Based on the Lagrangian analysis, we suggest a nonlinear correction to the traditional linear connection between baroclinicity and storms' activity. Then, we show that a simplified model of storm growth, incorporating the baroclinicity effect on the vertical tilt of anomalies, reproduces the observed nonlinear relationship. Expanding the analysis to include the mean flow's barotropic properties highlights their marginal effect on storm growth rate, but the crucial impact on growth time. Our results emphasize the potential of Lagrangianly studying storm dynamics to advance understanding of the midlatitude climate.

AGU AdvancesVol. 6(3)
Weizmann Institute of Science (IL)
Israel Science Foundation, Azrieli Foundation
Openalex Percentile: Top 6%
Climate variability and models
4.42
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