A Scalable and Automated Recurrence Plot Method for Detecting Climate Change: The Case of the UTCI Bioclimatic Index in Central Europe

Recent decades have brought increasing effects of climate change and variation. Climate changes, indicated by various bioclimatic indices, influence the functioning of living organisms, including humans. Previous studies have documented multi-year fluctuations in such indices. In this study, we employ the Universal Thermal Climate Index (UTCI), a recently developed bioclimatic indicator designed to condense complex thermodynamic and meteorological conditions into a single value representing specific categories of thermal stress. The average annual UTCI values for the period 1826–2021 in Kraków, Poland, increased at a rate of 0.27°C per decade, with the most pronounced rise observed during the winter season, as documented in prior studies. However, when considering the more recent period of 1951–2023, the trend intensifies significantly, reaching 0.61°C per decade, indicating a clear acceleration in bioclimatic warming. In the present study, we apply an automatic recurrence plot analysis method to investigate these changes in human bioclimate. We introduce a novel approach by automating recurrence plot interpretation with a genetic algorithm and statistical deterministic analysis, thereby providing readers with ready-to-use algorithms. The research focuses on a univariate time series of UTCI recorded from 1951 to 2023 in three locations in Poland – a key region of Central Europe where air masses from different parts of the continent interact. The main conclusion from the analyzed data is the identification of a date range (1980–1990), making a phase-transition-type passage between two periods that differ in statistical behaviors of UTCI. This bioclimatic change led to an increase in the frequency of very strong heat stress events and a decrease in the occurrence of very strong cold stress days. The recurrence plots analysis demonstrates that the data from 1990 differ most from data from the preceding period 1952–1965. This provides details of the findings reported in previous research regarding climate change in Poland. This discovery of a distinct transitional period marking a shift in the climatic regime in Poland, based on recurrence plot analysis, enriches existing knowledge on regional climate change with new empirical evidence.

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Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3597503
Primary Topic
Climate variability and models
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article
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article

A Scalable and Automated Recurrence Plot Method for Detecting Climate Change: The Case of the UTCI Bioclimatic Index in Central Europe

Natalia Kruszewska, Krzysztof Błażejczyk, Monika Okoniewska, Piotr Sionkowski et al.
IEEE Transactions on Geoscience and Remote Sensing
Climate variability and models
article

A Scalable and Automated Recurrence Plot Method for Detecting Climate Change: The Case of the UTCI Bioclimatic Index in Central Europe

Natalia Kruszewska, Krzysztof Błażejczyk, Monika Okoniewska, Piotr Sionkowski, Krzysztof Domino
article en

Abstract

Recent decades have brought increasing effects of climate change and variation. Climate changes, indicated by various bioclimatic indices, influence the functioning of living organisms, including humans. Previous studies have documented multi-year fluctuations in such indices. In this study, we employ the Universal Thermal Climate Index (UTCI), a recently developed bioclimatic indicator designed to condense complex thermodynamic and meteorological conditions into a single value representing specific categories of thermal stress. The average annual UTCI values for the period 1826–2021 in Kraków, Poland, increased at a rate of 0.27°C per decade, with the most pronounced rise observed during the winter season, as documented in prior studies. However, when considering the more recent period of 1951–2023, the trend intensifies significantly, reaching 0.61°C per decade, indicating a clear acceleration in bioclimatic warming. In the present study, we apply an automatic recurrence plot analysis method to investigate these changes in human bioclimate. We introduce a novel approach by automating recurrence plot interpretation with a genetic algorithm and statistical deterministic analysis, thereby providing readers with ready-to-use algorithms. The research focuses on a univariate time series of UTCI recorded from 1951 to 2023 in three locations in Poland – a key region of Central Europe where air masses from different parts of the continent interact. The main conclusion from the analyzed data is the identification of a date range (1980–1990), making a phase-transition-type passage between two periods that differ in statistical behaviors of UTCI. This bioclimatic change led to an increase in the frequency of very strong heat stress events and a decrease in the occurrence of very strong cold stress days. The recurrence plots analysis demonstrates that the data from 1990 differ most from data from the preceding period 1952–1965. This provides details of the findings reported in previous research regarding climate change in Poland. This discovery of a distinct transitional period marking a shift in the climatic regime in Poland, based on recurrence plot analysis, enriches existing knowledge on regional climate change with new empirical evidence.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Bydgoszcz University of Science and Technology (PL), Kazimierz Wielki University in Bydgoszcz (PL), Institute of Geography and Spatial Organization, Polish Academy of Sciences (PL), Institute of Theoretical and Applied Informatics (PL), AGH University of Krakow (PL), Polish Academy of Sciences (PL)
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Climate variability and models
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