A climate region classification for California's warm season: apparent temperature clustering to support heat-health epidemiology.

Marinelle Villanueva, Sydney Monte-Sano, Scott Sheridan, Michael Allen, Laurence Kalkstein, Michael Jerrett, David P Eisenman

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In one paragraph

Article in International journal of biometeorology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Marinelle VillanuevaDepartment of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA. msvillanueva@ucla.edu.ORCID http://orcid.org/0009-0008-1727-8662

Sydney Monte-SanoCenter for Public Health and Disasters and Center for Healthy Climate Solutions, University of California, Los Angeles, Los Angeles, CA, USA.

Scott SheridanDepartment of Geography, Kent State University, Kent, OH, USA.ORCID http://orcid.org/0000-0002-6928-6524

Michael AllenDepartment of Geography and Environmental Planning, Towson University, Towson, MD, USA.ORCID http://orcid.org/0000-0002-8897-3901

Laurence KalksteinApplied Climatologists, Inc., Marco Island, FL, USA.ORCID http://orcid.org/0000-0002-4596-1062

Michael JerrettDepartment of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-4121-0587

David P EisenmanCenter for Public Health and Disasters and Center for Healthy Climate Solutions, University of California, Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0003-4320-1331

Funding

California Office of Environmental Health Hazard Assessment 22-E0034

6 · The paper itself

Abstract

Climate classification enhances our understanding of regional climate patterns and enables a science-based framework for assessing environmental and public health relationships. Prior climate classification systems are limited in their ability to capture variation across dynamic subclimates, particularly in the context of complex topographical, elevation, and meteorological characteristics such as California, United States. In this study, we spatially classified climate regions in California during the warm season (May through September) in 2021 and 2022. We applied principal component analysis with k-means clustering algorithms to gridded data consisting of apparent temperature during the study period as a monthly time series. We then performed statistical and spatial analysis to delineate the geographical extent of climate regions with shared apparent temperature distributions. The results of this study include a statewide map of 30 warm season climate regions based on meteorological data characterized by homogenous temperature patterns that are distinct from one another. The climate regions demonstrate highly variable spatial patterns of heat exposures and often span across and within multiple county boundaries. The methods we present within a complex geography can be readily adapted to other regional settings and updated to other temporal periods. This study informs our understanding of regional climate patterns during the warm season and is applicable to the development of early warning systems and quantifying extreme heat impacts across statewide populations.

Indexed as

ClimateHeat Stress DisordersHot TemperatureCaliforniaCluster AnalysisClustering AlgorithmsHumansSeasonsTemperatureClimateGISMeteorologySpatial analysis

Identifiers

PMID42008041

DOI10.1007/s00484-026-03200-w

PMCPMC13095919

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.