Climate Change Research

Climate Change Research

Clustering and synoptic analysis of heat waves during the warm period of the year in Selected Cities of Ardabil province over the past four decades

Document Type : Original Article

Authors
Roghayeh Maleki Meresht
Mahnaz Saber
Postdoctoral Researcher of Climatology, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
10.30488/ccr.2025.543766.1301
Abstract
This study aimed to identify and analyze the synoptic patterns influencing the formation of heatwaves in selected cities of Ardabil Province (Ardabil, Meshginshahr, and Parsabad) during the warm season over the period 1980–2020. For this purpose, daily maximum temperature data from the synoptic stations of Ardabil, Parsabad, and Meshginshahr were utilized. Heat waves were defined using the 95th percentile of maximum temperature, with a minimum duration of three consecutive days. To examine the related atmospheric conditions, sea level pressure and 500 hPa geopotential height data from the NCEP/NCAR reanalysis were employed, and dominant patterns were classified using Ward’s hierarchical clustering method. The results indicated that during the study period, Parsabad station experienced the highest frequency of heat waves (41 events), followed by Ardabil (24 events) and Meshginshahr (23 events). The duration of heat waves varied across stations: 3–5 days in Ardabil, 3–6 days in Meshginshahr, and 3–7 days in Parsabad. Accordingly, Parsabad recorded both the highest frequency and the longest-lasting heat waves. Heat waves with a minimum duration of five days were selected for synoptic analysis, and two representative cases were examined: the first pattern (1–5 August 2015), characterized by the development of a surface anticyclone accompanied by a 500 hPa ridge over the region; and the second pattern (8–12 October 2002), in which Ardabil was located to the west of an omega-blocking system over western Russia. A common feature of both patterns was increased atmospheric thickness, subsidence, and warming during heat wave events. These findings highlight that synoptic analysis can significantly contribute to improve forecasting and early warning of heat waves.
Keywords
Ardabil Pressure Patterns Heat Waves Clustering

Subjects

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