Algorithm for detecting cyclone and anticyclone centres from mean sea level pressure layer

Prantl, Martin; Žák, Michal; Prantl, David

doi:10.1080/14498596.2022.2134221

Cited by 2 publications

(1 citation statement)

References 29 publications

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“…An anticyclone (a depression respectively) is a closed isobaric system which atmospheric pressure value increases (decreases in case of a depression) towards the interior [3] [4]. Traditionally, the middle of high pressure corresponds to the center of the anticyclone [5]. The anticyclone (respectively depression) is generally associated with clear skies (respectively cloudy skies with meteorological phenomena) [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System Modelling of the Mascarenes Anticyclone center Trajectory

2023

AIS

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This work objective is to determine the parameters of the fuzzy inference system model that best models the Mascarenes anticyclone trajectory. Our study area extends from 20°E to 110°E longitude and from 15°S to 50°S latitude. We start from the atmospheric pressure reanalysis data in grid point to determine the Mascarene anticyclone center. This center is none other than the center of the last closed Anticyclone's isobar. The monthly climatological mean value of the center coordinates are the data to be modeled by fuzzy inference system. The considered model parameters are the partitions number of the discourse universe and the model order. After evaluating the deviation between the input data and the simulated data, the minimum deviation is obtained with order model 2 by using 50 numbers of partitions.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System Modelling of the Mascarenes Anticyclone center Trajectory

2023

AIS

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An algorithm to analyse long‐term tendencies of pressure systems over Europe

Varga‐Balogh,

Leelőssy,

Varga

et al. 2024

Intl Journal of Climatology

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Climate change is associated with the modification of the polar jet stream, cyclone tracks and corresponding circulation patterns over midlatitudes. To apply these synoptic changes on regional climate, the changing sensitivity of a specific location to different pressure centre regions must be studied. An automated, objective circulation pattern detection method was developed to investigate the evolution of cyclonic and anticyclonic influence at any specific point within the European domain. The algorithm was used to assign each location to influencing low‐ or high‐pressure centres within the domain. Pressure centre displacements and the frequency redistribution among different centres were studied for each location. The 180‐year (January 1836–December 2015) mean sea level pressure dataset on the European domain with a 0.703° × 0.702° spatial and daily temporal resolution was obtained from NOAA 20th Century Reanalysis project. The presented method can apply the continental‐scale changes to specific locations. A significant increase of anticyclonic influence was found in southern and central Europe, in line with the northward displacement of Atlantic cyclones. Hundred and eighty year (180‐year) change of the number of days with anticyclonic versus cyclonic influence was found to be between +10% and 15% in the Mediterranean and +2% and 10% in most of Europe. The increasing anticyclonic influence in central Europe was strongest in the spring and the winter and was most attributable to the eastern European anticyclone. Results highlight the importance of research on the dynamical climate response of anticyclonic pressure systems.

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Algorithm for detecting cyclone and anticyclone centres from mean sea level pressure layer

Cited by 2 publications

References 29 publications

Fuzzy Inference System Modelling of the Mascarenes Anticyclone center Trajectory

Fuzzy Inference System Modelling of the Mascarenes Anticyclone center Trajectory

An algorithm to analyse long‐term tendencies of pressure systems over Europe

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