Characterization of hazardous weather in Mexican airports based on in-situ observations and reanalysis data

Abstract Severe weather in airports represents a latent hazard to the population and economy. Meteorological hazards, such as hailstorms and thunderstorms, significantly impact airport operations worldwide, including in Mexico. In this context, the present research analyses the spatial and temporal characteristics of thunderstorms and hailstorms in 57 airports distributed throughout the Mexican territory. To this end, METAR and SPECI data were employed to obtain the general characteristics, frequency, and severity of thunderstorms and hailstorms from 1990 to 2020. Then, using the ERA5 reanalysis data, diverse thermodynamic, kinematic, and composite parameters of the pre-convective environments are analyzed. Furthermore, using the K-means clustering method, such environments were classified. In this sense, three types of thunderstorm environments in Mexican airports were identified, each one with particular characteristics: Coastal Thunderstorms (CoaT), Northeast Thunderstorms (NorT), and Continental Thunderstorms (ConT). Likewise, three hailstorm types were identified: Highlands Hailstorms (HigH), Coastal Hailstorms (CoaH), and Central-Region Hailstorms (CenH). This research provides valuable insights into the severe weather conditions at Mexican airports, which can be utilized to enhance their forecasting capabilities and mitigate associated losses. Additionally, they help characterize the environments in which these phenomena developed and generate a baseline that can be used in future studies to analyze the impact of climate change on severe weather.

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Publication Details

Journal
Theoretical and Applied Climatology
Published
2025-08-30
DOI
https://doi.org/10.1007/s00704-025-05723-5
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Characterization of hazardous weather in Mexican airports based on in-situ observations and reanalysis data

José Francisco León‐Cruz, Isaac Miranda-Alcántara
Theoretical and Applied Climatology
Meteorological Phenomena and Simulations
article

Characterization of hazardous weather in Mexican airports based on in-situ observations and reanalysis data

José Francisco León‐Cruz, Isaac Miranda-Alcántara
article en

Abstract

Abstract Severe weather in airports represents a latent hazard to the population and economy. Meteorological hazards, such as hailstorms and thunderstorms, significantly impact airport operations worldwide, including in Mexico. In this context, the present research analyses the spatial and temporal characteristics of thunderstorms and hailstorms in 57 airports distributed throughout the Mexican territory. To this end, METAR and SPECI data were employed to obtain the general characteristics, frequency, and severity of thunderstorms and hailstorms from 1990 to 2020. Then, using the ERA5 reanalysis data, diverse thermodynamic, kinematic, and composite parameters of the pre-convective environments are analyzed. Furthermore, using the K-means clustering method, such environments were classified. In this sense, three types of thunderstorm environments in Mexican airports were identified, each one with particular characteristics: Coastal Thunderstorms (CoaT), Northeast Thunderstorms (NorT), and Continental Thunderstorms (ConT). Likewise, three hailstorm types were identified: Highlands Hailstorms (HigH), Coastal Hailstorms (CoaH), and Central-Region Hailstorms (CenH). This research provides valuable insights into the severe weather conditions at Mexican airports, which can be utilized to enhance their forecasting capabilities and mitigate associated losses. Additionally, they help characterize the environments in which these phenomena developed and generate a baseline that can be used in future studies to analyze the impact of climate change on severe weather.

Theoretical and Applied ClimatologyVol. 156(9)
Autonomous University of Yucatán (MX), Universidad Nacional Autónoma de México (MX)
Universidad Nacional Autónoma de México
Openalex Percentile: Top 72%
Meteorological Phenomena and Simulations
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