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Meteorological trend analysis and atmospheric coupling using multi model assessment of urban climate dynamics for weather forecasting.

Created on 25 Jun 2026

Authors

Abdulla Al Kafy, Hamad Ahmed Altuwaijri, Tekalign Ketema Bahiru

Published in

Scientific reports. Jun 24, 2026. Epub Jun 24, 2026.

Abstract

Understanding urban meteorological patterns and their coupling with larger atmospheric systems is crucial for improving weather forecasting and climate modeling. This study presents a comprehensive meteorological trend analysis of Kuwait City from 1982 to 2021, employing multiple analytical models to examine atmospheric parameters and their interconnections. Our analysis reveals significant trends in key meteorological variables: annual rainfall (-1.869 mm/year, Z = -2.55), relative humidity (-0.09%/year, Z = -2.06), maximum temperature (+ 0.047 °C/year, Z = + 2.23), and minimum temperature (+ 0.068 °C/year, Z = + 2.37). Seasonal analysis shows that rainfall decline is most pronounced during winter (-0.897 mm/year) and spring (-0.504 mm/year), which represent the main precipitation seasons in Kuwait. Temperature increases observed across most months and seasons, indicating a persistent warming trend. The Innovative Trend Analysis method revealed additional distributional changes in several meteorological variables that complement the results of the Mann-Kendall test and linear regression, providing insights into long term variability of key meteorological parameters that traditional methods missed. These findings indicate a shift in local atmospheric dynamics, with potential implications for urban heat island effects and regional weather patterns. Our multi-model approach offers an advanced methodology for assessing complex meteorological trends in urban environments, contributing to improved weather forecasting capabilities and understanding of urban-atmosphere interactions in arid regions.

PMID:
42343106
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.

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