“Large-Scale Data”: Cluster Analysis of Air Temperature and Relative Humidity Distribution Fields

The article presents the results of cluster analysis regarding air temperature and relative humidity distributions across four distinct climatic zones – temperate continental, subtropical, extremely cold and arctic. The significance of clustering analysis is in the importance of understanding the emerging combinations of meteorological factors across different climatic zones, depending on whether the raw data has undergone preprocessing. The number of days in clusters was analyzed considering the variant of preprocessing. The distribution of the number of days per month has been calculated depending on the climatic zone and cluster number. The most effective data normalization techniques for k-means clustering were identified. It was established that for all four studied climatic zones normalization method No. 3 proved to be the most appropriate, as it ensures a more structural cluster identification while accounting for potential mechanisms of climatic aging. The study provides a quantitative assessment of the temperature and relative humidity boundaries, categorized by climatic zone and cluster assignment.

T.A. NIZINA¹, Doctor of Sciences (Engineering), Professor (This email address is being protected from spambots. You need JavaScript enabled to view it.),
D.R. NIZIN¹, Candidate of Sciences (Engineering) (This email address is being protected from spambots. You need JavaScript enabled to view it.),
I.A. CHIBULAEV¹, Engineer (This email address is being protected from spambots. You need JavaScript enabled to view it.),
I.P. SPIRIN¹, Engineer (This email address is being protected from spambots. You need JavaScript enabled to view it.),
A.O. ANTONENKO¹, Research Engineer (This email address is being protected from spambots. You need JavaScript enabled to view it.);
L.K. BOGOMOLOVA², Candidate of Sciences (Chemical) (This email address is being protected from spambots. You need JavaScript enabled to view it.)

¹ National Research Mordovian State University (430005, Saransk, Bolshevistskaya Street, 68)
² Scientific-Research Institute of Building Physics of the Russian Academy Architecture and Construction Sciences (21, Lokomotivniy Driveway, Moscow, 127238, Russian Federation)

1. Nizina T.A., Nizin D.R., Selyaev V.P., et al. Big data in predicting the climatic resistance of building materials. I. Air temperature and humidity. Construction Materials and Products. 2023. Vol. 6. No. 3, pp. 18–30. (In Russian). EDN: ­HADNAF. https://doi.org/10.58224/2618-7183-2023-6-3-18-30
2. Nizina T.A., Selyaev V.P., Nizin D.R., et al. “Big data” in predicting the climatic resistance of building materials. Actinometric indicators. Academia. Arkhitektura i Stroitel’stvo. 2024. No. 4, pp. 124–133. (In Russian). EDN: ­XOOFME. https://doi.org/10.22337/2077-9038-2024-4-124-133
3. Ershova T.V., Khokhlov Yu.E., Shaposhnik S.B. Methodology for monitoring the development and use of big data technologies. Informatsionnoe Obshchestvo. 2021. No. 4–5, pp. 2–32. (In Russian). EDN: ­JNMDKO. https://doi.org/10.52605/16059921_2021_04_02
4. Kotlyarov D.A. Analysis of the climate continentality index in the territory of Northeast Russia. Vestnik of the Immanuel Kant Baltic Federal University. Series: Natural and Medical Sciences. 2024. No. 1, pp. 92–103. (In Russian). EDN: ­GKJDEY. https://doi.org/10.5922/gikbfu-2024-1-6
5. Ormeli E.I. Assessment of the degree of climate continentality of the Saratov region at the beginning of the 21st century. Vestnik of Udmurt University. Series: Biology. Geosciences. 2022. Vol. 32. Iss. 4, pp. 476–484. (In Russian). EDN: ­GLDFKH. https://doi.org/10.35634/2412-9518-2022-32-4-476-484
6. Zhou H., Ren H., Royer P., Hou H., Yu X.-Y. Big data analytics for long-term meteorological observations at hanford site. Atmosphere. 2022. Vol. 13. No. 1, pp. 136. EDN: ­GQMBNX. https://doi.org/10.3390/atmos13010136
7. Pampuch L.A., Negri R.G., Loikith P.C., Bortolozo C.A. A review on clustering methods for climatology analysis and its application over South America. International Journal of Geosciences. 2023. Vol. 14. No. 9, pp. 877–894.
https://doi.org/10.4236/ijg.2023.149047
8. Babanov B.A., Semenov V.A., Mokhov I.I. Compa-rison of various clustering methods for determining weather regimes in the Euro-Atlantic sector in winter and summer seasons. Izvestiya RAS. Atmospheric and Oceanic Physics. 2023. Vol. 59. No. 6, pp. 686–706. (In Russian). EDN: ­OSUIJZ. https://doi.org/10.31857/S0002351523060020
9. Chung E.N.M., Kittur M.I., Andriyana A., Ganesan P. On the thermo-oxidative aging of elastomers: A comprehensive review. Polymer. 2024. Vol. 304. 127109. EDN: ­VHGXTM. https://doi.org/10.1016/j.polymer.2024.127109
10. Qin G., Fan Q., Mi P., Li M., Mu W., Na J. Review of aging mechanisms, mechanical properties, and prediction models of fiber-reinforced composites in natural environments. Polymer Composites. 2024. Vol. 45. No. 16, pp. 14448–14474. EDN: ­MZVEYU. https://doi.org/10.1002/pc.28799
11. Nizin D.R., Nizina T.A., Selyaev V.P., Spirin I.P. Accounting for the moisture state of polymer materials in the development of machine learning models. Stroitel’nye Materialy [Construction Materials]. 2024. No. 12, pp. 57–67. (In Russian). EDN: ­ZEZZNU. https://doi.org/10.31659/0585-430X-2024-831-12-57-67
12. Ng L.F., Yahya M.Y., Rushdan I.A., Parameswaranpillai J., Muthukumar C. Effect of hygrothermal aging and water absorption on polymer composites. Aging and Durability of FRP Composites and Nanocomposites. 2024, pp. 17–42.
https://doi.org/10.1016/B978-0-443-15545-1.00008-1
13. Groß M., Mail M., Debastiani R., Scherer T., Braun M. Weathering of plastics in terrestrial environments. TrAC Trends in Analytical Chemistry. 2025. Vol. 190. 118281. EDN: ­XYDRQH. https://doi.org/10.1016/j.trac.2025.118281
14. Tian R., Li K., Lin Y., Lu C., Duan X. Characterization techniques of polymer aging: from beginning to end. Chemical Reviews. 2023. Vol. 123. No. 6, pp. 3007–3088. EDN: ­UTWQXG. https://doi.org/10.1021/acs.chemrev.2c00750
15. Nizina T.A., Selyaev V.P., Nizin D.R. Klimaticheskaya stoykost’ epoksidnykh polimerov v umerenno kontinental’nom klimate [Climatic resistance of epoxy polymers in a moderately continental climate]. Saransk: Mordovian University Publishing House, 2020. 188 p. EDN: ­EEGAGA