Clustering of temporal profiles in US climate change data using logistic mixture of spatial multivariate linear models

• Published in: Stochastic environmental research and risk assessment 2024-09, Vol.38 (9), p.3719-3733
• Main Authors: Lee, Seonwoo, Lee, Keunbaik, Park, Ju-Hyun, Kyung, Minjung, Yun, Seong-Taek, Lee, Jieun, Joo, Yongsung
• Format: Article
• Language: English
• Subjects: Air temperature; Alternations; Annual precipitation; Aquatic Pollution; Chemistry and Earth Sciences; Climate change; Climate models; Climatic data; Clustering; Cold weather construction; Computational Intelligence; Computer Science; Earth and Environmental Science; Earth Sciences; Environment; Hydrologic cycle; Math. Appl. in Environmental Science; Mixtures; Multivariate analysis; Original Paper; Physics; Precipitation; Probability Theory and Stochastic Processes; Regression models; Spatial data; Statistical analysis; Statistical models; Statistics for Engineering; Surface temperature; Waste Water Technology; Water Management; Water Pollution Control; Weather; Weather stations
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-024-02779-z

In recent decades, the annual mean temperature has increased, with unusual alternations of hot and cold years. In addition, the changes in temporal precipitation patterns are caused by complex interactions between temperature change, the global water cycle, and other components of the Earth’s systems. To construct a statistical model of these temporal patterns in terms of temperature and precipitation, we propose a logistic mixture of spatial multivariate penalized regression splines for temporal profiles and apply this model to the contiguous United States climate data over 123 years (1900 to 2022) at 252 weather stations. The results reveal that the proposed model identifies climatologically meaningful clusters of weather stations in the contiguous United States with two important meteorological variables, temperature and precipitation, identifying the climate change patterns of each climate zone. The surface air temperature increased in the Northeast and West (Mountain and Pacific) regions, where the climate is affected by the continental Arctic air. A notable increment of precipitation also occurred in the Northeast. In contrast, the South region, where the climate is affected by the tropical Atlantic Ocean, is more stable than other regions in terms of year-to-year variations in temperature and precipitation.