Projections of the urban and intra-urban scale thermal effects of climate change in the 21st century for cities in the Carpathian Basin
Abstract
This study evaluates the pattern of a nighttime climate index namely the tropical nights (Tmin ≥ 20ºC) during the 21st century in several different sized cities in the Carpathian Basin. For the modelling, MUKLIMO_3 microclimatic model and the cuboid statistical method were applied. In order to ensure the proper representation of the thermal characteristics of an urban landscape, the Local Climate Zone (LCZ) system was used as landuse information. For this work, LCZ maps were produced using WUDAPT methodology. The climatic input of the model was the Carpatclim dataset for the reference period (1981–2010) and EURO-CORDEX regional model outputs for the future time periods (2021–2050, 2071–2100) and emission scenarios (RCP4.5, RCP8.5). As results show, there would be a remarkable increase in the number of tropical nights along the century, and there is a clearly recognizable increase owing to urban landform. In the near past, the number of the index was 6–10 nights higher in the city core than the rural area where the number of this index was negligible. In the near future this urban-rural trend is the same, however, there is a slight increase (2–5 nights) in the index in city cores. At the end of the century, the results of the two emission scenarios become distinct. In the case of RCP4.5 the urban values are about 15–25 nights, what is less stressful compared to the 30–50 nights according to RCP8.5. The results clearly highlight that the effect of urban climate and climate change would cause serious risk for urban dwellers, therefore it is crucial to perform climate mitigation and adaptation actions on both global and urban scales.
References
Baccini, M., Biggeri, A., Accetta, G., Kosatsky, T., Katsouyanni, K., Analitis, A., Anderson, H.R., Bisanti, L., D'Ippoliti, D., Danova, J., Forsberg, B., Medina, S., Paldy, A., Rabczenko, D., Schindler, C. and Michelozzi, P. 2008. Heat effects on mortality in 15 European cities. Epidemiology 19. 711-719. https://doi.org/10.1097/EDE.0b013e318176bfcd
Bartholy, J. and Pongrácz, R. 2018. A brief review of health-related issues occurring in urban areas related to global warming of 1.5 °C. Current Opinion in Environmental Sustainability 30. 123-132. https://doi.org/10.1016/j.cosust.2018.05.014
Bechtel, B., Alexander, P.J., Böhner, J., Ching, J., Conrad, O., Feddema, J., Mills, G., See, L. and Stewart, I. 2015. Mapping local climate zones for a worldwide database of the form and function of cities. ISPRS International Journal of Geo-Information 4. 199-219. https://doi.org/10.3390/ijgi4010199
Bechtel, B., Alexander, P.J., Beck, C., Böhner, J., Broussed, O., Ching, J., Demuzere, M., Fonteg, C., Gál, T., Hidalgo, J., Hoffmann, P., Middel, A., Mills, G., Ren, C., See, L., Sismanidis, P., See, L. Verdonck, M-L., Xu, G. and Xu, Y. 2019. Generating WUDAPT Level 0 data - Current status of production and evaluation. Urban Climate 27. 24-45. https://doi.org/10.1016/j.uclim.2018.10.001
Bokwa, A., Dobrovolný, P., Gál, T., Geletič, J., Gulyás, Á., Hajto, M.J., Holec, J., Hollósi, B., Kielar, R., Lehnert, M., Skarbit, N., Šťastný, P., Švec, M., Unger, J., Walawender, J.P. and Žuvela Aloise, M. 2018. Urban climate in Central European cities and global climate change. Acta Climatologica 51-52. 7-35. https://doi.org/10.14232/acta.clim.2018.52.1
Bruse, M. and Fleer, H. 1998. Simulating surface-plant-air interactions inside urban environments with a three dimensional numerical model.Environmental Modelling & Software 13. 373−384. https://doi.org/10.1016/S1364-8152(98)00042-5
Früh, B., Becker, P., Deutschländer, T., Hessel, J.D., Kossmann, M., Mieskes, I., Namyslo, J., Roos, M., Sievers, U., Steigerwald, T., Turau, H. andWienert, U. 2011. Estimation of climate-change impacts on the urban heat load using an urban climate model and regional climate projections.Journal of Applied Meteorology and Climatology 50. 167-184. https://doi.org/10.1175/2010JAMC2377.1
IPCC 2018. Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Eds.: Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, P.R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J.B.R., Chen, Y., Zhou, X., Gomis, M.I., Lonnoy, E., Maycock, T., Tignor, M. and Waterfield, T. Available at https://www.ipcc.ch/sr15/
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B. and Yiou, P. 2014. EURO-CORDEX: new high-resolution climate change projections for European impact research. Regional Environmental Change 14. 563-578. https://doi.org/10.1007/s10113-013-0499-2
Kusaka, H., Kondo, H., Kikegawa, Y. and Kimura, F. 2001. A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Boundary-Layer Meteorology 101. 329-358. https://doi.org/10.1023/A:1019207923078
Kwok, Y.T., Schoetter, R., Lau, K.K-L., Hidalgo, J., Ren, C., Pigeon, G. and Masson, V. 2019. How well does the local climate zone scheme discern the thermal environment of Toulouse (France)? An analysis using numerical simulation data. International Journal of Climatology 39. 5292-5315. https://doi.org/10.1002/joc.6140
Lee, S.-H., Lee, H., Park, S.B., Woo, J.W., Lee, D.I. and Baik, J.J. 2016. Impacts of in-canyon vegetation and canyon aspect ratio on the thermal environment of street canyons: numerical investigation using a coupled WRF-VUCM model. Quarterly Journal of the Royal Meteorological Society 142. 2562-2578. https://doi.org/10.1002/qj.2847
Lehnert, M., Geletič, J., Husák, J. and Vysoudil, M. 2015. Urban field classification by "local climate zones" in a medium-sized Central European city: the case of Olomouc (Czech Republic). Theoretical and Applied Climatology 122. 531-541. https://doi.org/10.1007/s00704-014-1309-6
Lelovics, E., Unger, J., Gál, T. and Gál, C.V. 2014. Design of an urban monitoring network based on Local Climate Zone mapping and temperature pattern modelling. Climate Research 61. 51-62. https://doi.org/10.3354/cr01220
Lemonsu, A., Masson, V., Shashua-Bar, L., Erell, E. and Pearlmutter, D. 2012. Inclusion of vegetation in the Town Energy Balance model for modelling urban green areas. Geoscientific Model Development 5. 1377-1393. https://doi.org/10.5194/gmd-5-1377-2012
Martilli, A., Clappier, A. and Rotach, M.W. 2002. An urban surface exchange parameterisation for mesoscale models. Boundary-Layer Meteorology 104. 261-304. https://doi.org/10.1023/A:1016099921195
Masson, V. 2000. A physically-based scheme for the urban energy budget in atmospheric models. Boundary-Layer Meteorology 94. 357−397. https://doi.org/10.1023/A:1002463829265
Ministry of the Interior of Hungary. Available at https://nyilvantarto.hu (last accessed: 16.11.2020)
Molnár, G., Kovács, A. and Gál, T. 2020. How does anthropogenic heating affect the thermal environ ment in a medium-sized Central European city? A case study in Szeged, Hungary. Urban Climate 34.100673. https://doi.org/10.1016/j.uclim.2020.100673
Oke, T.R., Mills, G., Christen, A. and Voogt, J.A. 2017. Urban Climates. Cambridge, Cambridge University Press. https://doi.org/10.1017/9781139016476
Pieczka, I., Pongrácz, R. and Bartholy, J. 2018. Future temperature projections for Hungary based on RegCM4.3 simulations using new Representative Concentration Pathways scenarios. International Journal of Global Warming 15. 277-292. https://doi.org/10.1504/IJGW.2018.093121
Ryu, Y.H., Bou-Zeid, E., Wang, Z.-H. and Smith, J.A. 2016. Realistic representation of urban trees in an urban canopy model. Boundary-Layer Meteorology 159. 193-220. https://doi.org/10.1007/s10546-015-0120-y
Sievers, U. and Zdunkowski, W. 1985. A numerical simulation scheme for the albedo of city street canyons. Boundary-Layer Meteorology 33. 245-257. https://doi.org/10.1007/BF00052058
Sievers, U. 1995. Verallgemeinerung der Stromfunktionsmethode auf drei Dimensionen.Meteorologische Zeitschrift 4. 3-15. https://doi.org/10.1127/metz/4/1995/3
Siu, L.W. and Hart, M.A. 2013. Quantifying urban heat island intensity in Hong Kong SAR, China. Environmental Monitoring and Assessment 185. 4383-4398. https://doi.org/10.1007/s10661-012-2876-6
Skarbit, N. and Gál, T. 2016. Projection of intra-urban modification of nighttime climate indices during the 21st century. Hungarian Geographical Bulletin65. (2): 181-193. https://doi.org/10.15201/hungeobull.65.2.8
Stocker, T.F., Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V. and Midgley, P.M. 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate. Cambridge and New York, Cambridge University Press.
Stewart, I.D. and Oke, T.R. 2012. Local Climate Zones for urban temperature studies. Bulletin of American Meteorological Society 93. 1879-1900. https://doi.org/10.1175/BAMS-D-11-00019.1
Stewart, I.D., Oke, T.R. and Krayenhoff, E.S. 2014. Evaluation of the 'local climate zone' scheme using temperature observations and model simulations. International Journal of Climatology 34. 1062-1080. https://doi.org/10.1002/joc.3746
Szalai, S., Auer, I., Hiebl, J., Milkovich, J., Radim, T., Stepanek, P., Zahradnicek, P., Bihari, Z., Lakatos, M., Szentimrey, T., Limanowka, D., Kilar, P., Cheval, S., Deak, Gy., Mihic, D., Antolovic, I., Mihajlovic, V., Nejedlik, P., Stastny, P., Mikulova, K., Nabyvanets, I., Skyryk, O., Krakovskaya, S., Vogt, J., Antofie, T. and Spinoni, J. 2013. Climate of the Greater Carpathian Region. Final Technical Report. Available at http://www.carpatclim-eu.org/pages/download/
Van Vuuren, D.P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S.J. and Rose, S.K. 2011. The representative concentration pathways: an overview. Climatic Change 109. 5-31. https://doi.org/10.1007/s10584-011-0148-z
World Population Review. Available at https://world populationreview.com/ (last accessed: 06.11.2020)
Zheng, Y., Ren, C., Xu, Y., Wang, R., Ho, J., Lau, K. and Ng, E. 2018. GIS-based mapping of Local Climate Zone in the high-density city of Hong Kong. Urban Climate 24. 419-448. https://doi.org/10.1016/j.uclim.2017.05.008
Žuvela-Aloise, M., Koch, R., Neureiter, A., Böhm, R. and Buchholz, S. 2014. Reconstructing urban climate of Vienna based on historical maps dating to the early instrumental period. Urban Climate 10. 490-508. https://doi.org/10.1016/j.uclim.2014.04.002
Žuvela-Aloise, M. 2017. Enhancement of urban heat load through social inequalities on an example of a fictional city King's Landing. International Journal of Biometeorology 61. 527-539. https://doi.org/10.1007/s00484-016-1230-z
Copyright (c) 2021 Tamás Gál, Nóra Skarbit, Gergely Molnár, János Unger
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.