Human-caused climate change is increasing daily-scale extreme temperature events in urban areas worldwide. This study examines this heat hazard in five Taiwanese cities: Taipei City, Hsinchu County, Taichung City, Tainan City, and Kaohsiung City. Two temperature thresholds were analyzed, assuming a relative humidity of 75%: dangerous hot days (daily maximum temperature ≥ 32 °C) and extremely dangerous hot days (daily maximum temperature ≥ 36 °C). Historical data from 1996 to 2025 showed a statistically significant upward trend: dangerous hot days increased significantly in all five cities, while extremely dangerous hot days increased significantly in Taipei, Hsinchu, and Taichung but showed no significant trend in Tainan or Kaohsiung.
Future trends for the same thresholds were then projected from daily climate series generated with the stochastic weather generator LARS-WG 8.0 under SSP2-4.5 and SSP5-8.5 for 2041–2060, 2061–2080, and 2081–2100, using an eight-model IPCC AR6 ensemble with equilibrium climate sensitivities from 1.83 to 4.83 °C (mean ≈ 3.2 °C). Both thresholds are projected to increase across all cities, more strongly under SSP5-8.5, and to rise sharply toward the end of the century. The warmer central and southern cities show the most dangerous hot days, while Taipei is the hotspot for extremely dangerous hot days, likely due to its basin setting and urban heat island effect. Under SSP5-8.5, by the end of the century, extremely dangerous hot days in Taipei rise from about 20 to nearly 100 per year, while dangerous hot days in the southern cities exceed 210 per year. Projection uncertainty across models widens over time, especially for the higher threshold under SSP5-8.5. The LARS-WG projections agree in direction with Taiwan's official TCCIP projections but are more severe, likely owing to differences in spatial resolution. Overall, this study provides city-level heat-hazard projections to support heat adaptation and public health planning in Taiwan.

Amnuaylojaroen, T. (2025). Intensification of heat extremes in Southeast Asia: Spatial-temporal analysis of temperature trends and heat events (1940-2023). International Journal of Climatology, 45(10). https://doi.org/10.1002/joc.8907
Arnfield, A. J. (2003). Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology, 23(1), 1–26. https://doi.org/10.1002/joc.859
ASRAD. (n.d.). Surface manned station daily data. Atmospheric Science Research and Application Database, Chinese Culture University. https://asrad.pccu.edu.tw/
Avila, F. B., Dong, S., Menang, K. P., Rajczak, J., Renom, M., Donat, M. G., & Alexander, L. V. (2015). Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima. Weather and Climate Extremes, 9, 6–16. https://doi.org/10.1016/j.wace.2015.06.003
Bowler, D. E., Buyung-Ali, L., Knight, T. M., & Pullin, A. S. (2010). Urban greening to cool towns and cities: A systematic review of the empirical evidence. Landscape and Urban Planning, 97(3), 147–155. https://doi.org/10.1016/j.landurbplan.2010.05.006
Boyles, R., Nikiel, C. A., Miller, B. W., Littell, J., Terando, A. J., Rangwala, I., Alder, J. R., Rosendahl, D. H., & Wootten, A. M. (2024). Approaches for using CMIP projections in climate model ensembles to address the "hot model" problem (U.S. Geological Survey Open-File Report 2024-1008). https://doi.org/10.3133/ofr20241008
Bröde, P., Fiala, D., Blazejczyk, K., Holmer, I., Jendritzky, G., Kampmann, B., Tinz, B., & Havenith, G. (2012). Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). International Journal of Biometeorology, 56(3), 481–494. https://doi.org/10.1007/s00484-011-0454-1
Brunner, L., Pendergrass, A. G., Lehner, F., Merrifield, A. L., Lorenz, R., & Knutti, R. (2020). Reduced global warming from CMIP6 projections when weighting models by performance and independence. Earth System Dynamics, 11(4), 995–1012. https://doi.org/10.5194/esd-11-995-2020
Bunker, A., Wildenhain, J., Vandenbergh, A., Henschke, N., Rocklov, J., Hajat, S., & Sauerborn, R. (2016). Effects of air temperature on climate-sensitive mortality and morbidity outcomes in the elderly. EBioMedicine, 6, 258–268. https://doi.org/10.1016/j.ebiom.2016.02.034
Canadian Centre for Occupational Health and Safety. (2020). Hot environments: Health effects and first aid. https://www.ccohs.ca/oshanswers/phys_agents/heat/heat_health.html
Central Weather Administration. (n.d.). Heat information product description. Retrieved June 4, 2026, from https://www.cwa.gov.tw/V8/assets/pdf/HeatInformation_ ProductDescription_En.pdf
Chen, C.-T., Tung, Y.-S., Wang, C., & Lin, S.-L. (2024). Future climate change in Taiwan using CMIP6 empirical-statistical downscaling. ESS Open Archive. https://doi.org/10.22541/essoar.173325198.81911088/v1
Chung, J. Y., Kim, H., & Honda, Y. (2009). Ambient temperature and mortality: An international study in four capital cities of East Asia. Epidemiology, 20, S133–S134. https://doi.org/10.1097/01.ede.0000362459.93891.48
Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836. https://doi.org/10.1080/01621459.1979.10481038
Climate Change Administration. (2025). Overview of resource status: Executive summary. Ministry of Environment. https://service.cca.gov.tw/
Directorate-General of Budget, Accounting and Statistics. (2024). Statistical yearbook of the Republic of China 2023. Executive Yuan, Republic of China. https://ws.dgbas.gov.tw/001/Upload/466/relfile/11503/233937/yearbook2023.pdf
Domeisen, D. I. V., Eltahir, E. A. B., Fischer, E. M., Knutti, R., Perkins-Kirkpatrick, S. E., Schar, C., Seneviratne, S. I., Weisheimer, A., & Wernli, H. (2022). Prediction and projection of heatwaves. Nature Reviews Earth & Environment, 4(1), 36–50. https://doi.org/10.1038/s43017-022-00371-z
Donat, M. G., Sillmann, J., Wild, S., Alexander, L. V., Lippmann, T., & Zwiers, F. W. (2014). Consistency of temperature and precipitation extremes across various global gridded in situ and reanalysis datasets. Journal of Climate, 27(13), 5019–5035. https://doi.org/10.1175/JCLI-D-13-00405.1
Flouris, A. D., Dinas, P. C., Ioannou, L. G., Nybo, L., Havenith, G., Kenny, G. P., & Kjellstrom, T. (2018). Workers' health and productivity under occupational heat strain. The Lancet Planetary Health, 2(12), e521–e531. https://doi.org/10.1016/S2542-5196(18)30237-7
Gasparrini, A., Guo, Y., Hashizume, M., Lavigne, E., Zanobetti, A., Schwartz, J., Tobias, A., Tong, S., Rocklov, J., Forsberg, B., Leone, M., De Sario, M., Bell, M. L., Guo, Y.-L., Wu, C., Kan, H., Yi, S.-M., de Sousa Zanotti Stagliorio Coelho, M., Saldiva, P. H. N., Armstrong, B. (2015). Mortality risk attributable to high and low ambient temperature. The Lancet, 386(9991), 369–375. https://doi.org/10.1016/S0140-6736(14)62114-0
Gould, C. F., Heft-Neal, S., Heaney, A. K., Bendavid, E., Callahan, C. W., Kiang, M. V., Graff Zivin, J., & Burke, M. (2025). Temperature extremes impact mortality and morbidity differently. Science Advances, 11(31). https://doi.org/10.1126/sciadv.adr3070
Guo, Y., Gasparrini, A., Armstrong, B., Li, S., Tawatsupa, B., Tobias, A., Lavigne, E., de Sousa Zanotti Stagliorio Coelho, M., Leone, M., Pan, X., Tong, S., Tian, L., Kim, H., Hashizume, M., Honda, Y., Guo, Y.-L. L., Wu, C.-F., Punnasiri, K., Yi, S.-M., ... Williams, G. (2014). Global variation in the effects of ambient temperature on mortality. Epidemiology, 25(6), 781–789. https://doi.org/10.1097/EDE.0000000000000165
Hausfather, Z., Drake, H. F., Abbott, T., & Schmidt, G. A. (2020). Evaluating the performance of past climate model projections. Geophysical Research Letters, 47(1). https://doi.org/10.1029/2019GL085378
Hsinchu Science Park Bureau. (n.d.). Introduction to the Hsinchu Science Park. National Science and Technology Council. Retrieved July 16, 2026, from https://web.sipa.gov.tw/CSRWeb/eng/about01.jsp
Hsu, H.-H., & Chen, C.-T. (2002). Observed and projected climate change in Taiwan. Meteorology and Atmospheric Physics, 79(1-2), 87–104. https://doi.org/10.1007/s703-002-8230-x
Huang, J. M., & Chen, L. C. (2020). A numerical study on mitigation strategies of urban heat islands in a tropical megacity. Sustainability, 12(10). https://doi.org/10.3390/su12103952
Huang, K., Li, X., Liu, X., & Seto, K. C. (2019). Projecting global urban land expansion and heat island intensification through 2050. Environmental Research Letters, 14(11), 114037. https://doi.org/10.1088/1748-9326/ab4b71
Iizumi, T., Semenov, M. A., Nishimori, M., Ishigooka, Y., & Kuwagata, T. (2012). ELPIS-JP: A dataset of local-scale daily climate change scenarios for Japan. Philosophical Transactions of the Royal Society A, 370(1962), 1141–1155. https://doi.org/10.1098/rsta.2011.0305
IPCC. (2021). Climate change 2021: The physical science basis (V. Masson-Delmotte et al., Eds.). Cambridge University Press. https://doi.org/10.1017/9781009157896
IPCC. (2022). Climate change 2022: Impacts, adaptation and vulnerability (H.-O. Portner et al., Eds.). Cambridge University Press. https://doi.org/10.1017/9781009325844
IPCC. (2023). Climate change 2023: Synthesis report (Core Writing Team, H. Lee, & J. Romero, Eds.). IPCC. https://doi.org/10.59327/IPCC/AR6-9789291691647
Knutti, R., Sedlacek, J., Sanderson, B. M., Lorenz, R., Fischer, E. M., & Eyring, V. (2017). A climate model projection weighting scheme accounting for performance and interdependence. Geophysical Research Letters, 44(4), 1909–1918. https://doi.org/10.1002/2016GL072012
Kong, J., Zhao, Y., Carmeliet, J., & Lei, C. (2021). Urban heat island and its interaction with heatwaves. Sustainability, 13(19), 10923. https://doi.org/10.3390/su131910923
Lamb, W. F., Wiedmann, T., Pongratz, J., Andrew, R., Crippa, M., Olivier, J. G. J., Wiedenhofer, D., Mattioli, G., Al Khourdajie, A., House, J., ... Minx, J. (2021). A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018. Environmental Research Letters, 16(7), 073005. https://doi.org/10.1088/1748-9326/abee4e
Lee, W.-L., Wang, Y.-C., Shiu, C.-J., Tsai, I., Tu, C.-Y., Lan, Y.-Y., Chen, J.-P., Pan, H.-L., & Hsu, H.-H. (2020). Taiwan Earth System Model version 1: Description and evaluation of mean state. Geoscientific Model Development, 13(9), 3887–3904. https://doi.org/10.5194/gmd-13-3887-2020
Lee, W.-S., Huang, J.-C., Chang, C.-T., Chan, S.-C., Liao, Y.-S., Liao, C.-S., Lee, L.-C., Lee, J.-Y., Shih, Y.-T., Lu, M.-C., & Chen, P.-H. (2020). Interaction among controlling factors on riverine DIN export in small mountainous rivers of Taiwan. Water, 12(11), Article 2981. https://doi.org/10.3390/w12112981
Lin, C.-Y., Chen, F., Huang, J. C., Chen, W.-C., Liou, Y.-A., Chen, W.-N., & Liu, S.-C. (2008). Urban heat island effect and its impact on boundary layer development and land-sea circulation over northern Taiwan. Atmospheric Environment, 42(22), 5635–5649. https://doi.org/10.1016/j.atmosenv.2008.03.015
Lin, C.-Y., Chen, W.-C., Liu, S. C., Liou, Y. A., Liu, G. R., & Lin, T. H. (2008). Numerical study of the impact of urbanization on the precipitation over Taiwan. Atmospheric Environment, 42, 2934–2947. https://doi.org/10.1016/j.atmosenv.2007.12.054
Lin, C.-Y., Chien, Y.-Y., Su, C.-J., Kueh, M.-T., & Lung, S.-C. C. (2017). Climate variability of heat wave and projection of warming scenario in Taiwan. Climatic Change, 145(3), 305–320. https://doi.org/10.1007/s10584-017-2091-0
Lin, L.-Y., Lin, C.-T., Chen, Y.-M., Cheng, C.-T., Li, H.-C., & Chen, W.-B. (2022). The Taiwan Climate Change Projection Information and Adaptation Knowledge Platform: A decade of climate research. Water, 14(3), 358. https://doi.org/10.3390/w14030358
Lin, R.-T., & Chan, C.-C. (2009). Effects of heat on workers' health and productivity in Taiwan. Global Health Action, 2(1), Article 2024. https://doi.org/10.3402/gha.v2i0.2024
Lin, T. P., Chen, Y. C., & Matzarakis, A. (2017). Urban thermal stress climatic mapping: Combination of long-term climate data and thermal stress risk evaluation. Sustainable Cities and Society, 34, 12–21. https://doi.org/10.1016/j.scs.2017.05.022
Lin, Y.-K., Maharani, A. T., Chang, F.-T., & Wang, Y.-C. (2018). Mortality and morbidity associated with ambient temperatures in Taiwan. Science of the Total Environment, 627, 540–548. https://doi.org/10.1016/j.scitotenv.2018.09.161
Liou, Y.-A., Tran, D.-P., & Nguyen, K.-A. T. (2024). Spatio-temporal patterns and driving forces of surface urban heat island in Taiwan. Urban Climate, 53, Article 101806. https://doi.org/10.1016/j.uclim.2024.101806
Luo, M., Wu, S., Lau, G. N.-C., Pei, T., Liu, Z., Wang, X., Ning, G., Chan, T. O., Yang, Y., & Zhang, W. (2024). Anthropogenic forcing has increased the risk of longer-traveling and slower-moving large contiguous heatwaves. Science Advances, 10(13). https://doi.org/10.1126/sciadv.adl1598
Mabon, L., & Shih, W.-Y. (2022). Identifying factors contributing to social vulnerability through a deliberative Q-sort process. Natural Hazards, 112(1), 2609–2623. https://doi.org/10.1007/s11069-022-05280-4
Manoli, G., Fatichi, S., Schlapfer, M., Yu, K., Crowther, T. W., Meili, N., Burlando, P., Katul, G. G., & Bou-Zeid, E. (2019). Magnitude of urban heat islands largely explained by climate and population. Nature, 573(7772), 55–60. https://doi.org/10.1038/s41586-019-1512-9
Meinshausen, M., Nicholls, Z., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., ... Wang, H. J. (2019). The SSP greenhouse gas concentrations and their extensions to 2500. https://doi.org/10.5194/gmd-2019-222
Ministry of Environment. (2021). 2021 National Communications of the Republic of China (Taiwan) under the United Nations Framework Convention on Climate Change. https://unfccc.moenv.gov.tw/
Minx, J. C., Lamb, W. F., Andrew, R. M., Canadell, J. G., Crippa, M., Dobbeling, N., Forster, P. M., Guizzardi, D., Olivier, J., Peters, G. P., Pongratz, J., Reisinger, A., Rigby, M., Saunois, M., Smith, S. J., Solazzo, E., & Tian, H. (2021). A comprehensive dataset for global, regional and national greenhouse gas emissions by sector 1970-2019. Earth System Science Data Discussions. https://doi.org/10.5194/essd-2021-228
Mudelsee, M. (2019). Trend analysis of climate time series: A review of methods. Earth-Science Reviews, 190, 310–322. https://doi.org/10.1016/j.earscirev.2018.12.005
National Science and Technology Council & Ministry of Environment. (2024). Climate change in Taiwan: National scientific report 2024 (H.-H. Hsu & M.-H. Li, Eds.). https://www.nera.gov.tw/
National Weather Service. (n.d.). Heat index chart. National Oceanic and Atmospheric Administration. https://www.weather.gov/ffc/hichart
National Weather Service. (2023). Heat index statistics. National Oceanic and Atmospheric Administration. https://www.weather.gov/tbw/heatindex
Nijsse, F. J. M. M., Cox, P. M., & Williamson, M. S. (2020). An emergent constraint on transient climate response from simulated historical warming in CMIP6 models. Earth System Dynamics Discussions. https://doi.org/10.5194/esd-2019-86
Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502
O'Neill, B. C., Tebaldi, C., Van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G. C., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R. H., Riahi, K., & Sanderson, B. M. (2016). The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9(9), 3461–3482. https://doi.org/10.5194/gmd-9-3461-2016
Perkins, S. E., & Alexander, L. V. (2013). On the measurement of heat waves. Journal of Climate, 26(13), 4500–4517. https://doi.org/10.1175/JCLI-D-12-00383.1
Perkins-Kirkpatrick, S. E., & Lewis, S. C. (2020). Increasing trends in regional heatwaves. Nature Communications, 11(1), 3357. https://doi.org/10.1038/s41467-020-16970-7
Racsko, P., Szeidl, L., & Semenov, M. (1991). A serial approach to local stochastic weather models. Ecological Modeling, 57(1-2), 27–41. https://doi.org/10.1016/0304-3800(91)90053-4
Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O'Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., ... Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications. Global Environmental Change, 42, 153–168. https://doi.org/10.1016/j.gloenvcha.2016.05.009
Ripple, W. J., Wolf, C., Mann, M. E., Rockstrom, J., Gregg, J. W., Xu, C., Wunderling, N., Perkins-Kirkpatrick, S. E., Schaeffer, R., Broadgate, W. J., Newsome, T. M. Shuckburgh, E., & Gleick, P. H. (2025). The 2025 state of the climate report: A planet on the brink. BioScience, 75(12), 1016–1027. https://doi.org/10.1093/biosci/biaf149
Russo, S., Sillmann, J., & Sterl, A. (2017). Humid heat waves at different warming levels. Scientific Reports, 7, Article 7477. https://doi.org/10.1038/s41598-017-07536-7
Santamouris, M. (2014). Cooling the cities: A review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environments. Solar Energy, 103, 682–703. https://doi.org/10.1016/j.solener.2012.07.003
Santamouris, M. (2015). Analyzing the heat island magnitude and characteristics in one hundred Asian and Australian cities and regions. Science of the Total Environment, 512–513, 582–598. https://doi.org/10.1016/j.scitotenv.2015.01.060
Santamouris, M. (2020). Recent progress on urban overheating and heat island research: Integrated assessment of the energy, environmental, vulnerability and health impact. Energy and Buildings, 207, 109482. https://doi.org/10.1016/j.enbuild.2019.109482
Semenov, M. A. (2008). Simulation of extreme weather events by a stochastic weather generator. Climate Research, 35(3), 203–212. https://doi.org/10.3354/cr00731
Semenov, M. A. (2024). LARS-WG 8.0 (Version 8.0) [Computer software]. Rothamsted Research. https://zenodo.org/records/10632391
Semenov, M. A., & Barrow, E. M. (1997). Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 35(4), 397–414. https://doi.org/10.1023/A:1005342632279
Semenov, M. A., & Barrow, E. M. (2002). LARS-WG: A stochastic weather generator for use in climate impact studies [User manual].
Semenov, M. A., & Stratonovitch, P. (2010). Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research, 41(1), 1–14. https://doi.org/10.3354/cr00836
Semenov, M., Brooks, R., Barrow, E., & Richardson, C. (1998). Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research, 10, 95–107. https://doi.org/10.3354/cr010095
Shaw, R., Luo, Y., Cheong, T. S., Abdul Halim, S., Chaturvedi, S., Hashizume, M., Insarov, G. E., Ishikawa, Y., Jafari, M., Kitoh, A., Pulhin, J., Singh, C., Vasant, K., & Zhang, Z. (2022). Asia. In H.-O. Portner et al. (Eds.), Climate change 2022: Impacts, adaptation and vulnerability (pp. 1457–1580). Cambridge University Press. https://doi.org/10.1017/9781009325844.012
Sherwood, S. C., & Huber, M. (2010). An adaptability limit to climate change due to heat stress. Proceedings of the National Academy of Sciences, 107(21), 9552–9555. https://doi.org/10.1073/pnas.0913352107
Shih, W. Y., & Mabon, L. (2021). Understanding heat vulnerability in the subtropics: Insights from expert judgements. International Journal of Disaster Risk Reduction, 63, Article 102463. https://doi.org/10.1016/j.ijdrr.2021.102463
Stott, P. A., Christidis, N., Otto, F. E. L., Sun, Y., Vanderlinden, J., Van Oldenborgh, G. J., Vautard, R., von Storch, H., Walton, P., Yiou, P., & Zwiers, F. W. (2016). Attribution of extreme weather and climate-related events. WIREs Climate Change, 7(1), 23–41. https://doi.org/10.1002/wcc.380
Sung, T. I., Wu, P. C., Lung, S. C., Lin, C. Y., Chen, M. J., & Su, H. J. (2012). Relationship between heat index and mortality of 6 major cities in Taiwan. Science of the Total Environment, 442, 275–281. https://doi.org/10.1016/j.scitotenv.2012.09.068
Taiwan Climate Change Projection Information and Adaptation Knowledge Platform. (n.d.). Home. National Science and Technology Center for Disaster Reduction. Retrieved June 4, 2026, from https://tccip.ncdr.nat.gov.tw/
Tebaldi, C., & Knutti, R. (2007). The use of the multi-model ensemble in probabilistic climate projections. Philosophical Transactions of the Royal Society A, 365(1857), 2053–2075. https://doi.org/10.1098/rsta.2007.2076
Tsai, C. W., Lin, M.-L., & Tung, J. Y. (2024). Spatial and temporal evolution of heatwaves in Taiwan in a changing climate. Ecological Informatics, 81, Article 102585. https://doi.org/10.1016/j.ecoinf.2024.102585
Van Oldenborgh, G. J., van der Wiel, K., Kew, S., Philip, S., Otto, F., Vautard, R., King, A., Lott, F., Arrighi, J., Singh, R., & van Aalst, M. (2021). Pathways and pitfalls in extreme event attribution. Climatic Change, 166(1-2), Article 13. https://doi.org/10.1007/s10584-021-03071-7
Venter, Z. S., Chakraborty, T., & Lee, X. (2021). Crowdsourced air temperatures contrast satellite measures of the urban heat island and its mechanisms. Science Advances, 7(22). https://doi.org/10.1126/sciadv.abb9569
Vicedo-Cabrera, A. M., de Schrijver, E., Schumacher, D. L., Ragettli, M. S., Fischer, E. M., & Seneviratne, S. I. (2023). The footprint of human-induced climate change on heat-related deaths in the summer of 2022 in Switzerland. Environmental Research Letters, 18(7), 074037. https://doi.org/10.1088/1748-9326/ace0d0
Vicedo-Cabrera, A. M., Scovronick, N., Sera, F., Roye, D., Schneider, R., Tobias, A., Astrom, C., Guo, Y., Honda, Y., Hondula, D. M., ... Gasparrini, A. (2021). The burden of heat-related mortality attributable to recent human-induced climate change. Nature Climate Change, 11(6), 492–500. https://doi.org/10.1038/s41558-021-01058-x
Visual Data Tools. (2026). DataGraph (Version 5.5) [Computer software]. https://www.visualdatatools.com/DataGraph
Wang, S., Zhan, W., Zhou, B., Tong, S., Chakraborty, T. C., Wang, Z., Huang, K., Du, H., & Middel, A. (2025). Dual impact of global urban overheating on mortality. Nature Climate Change. https://doi.org/10.1038/s41558-025-02303-3
Wang, Y. C., Lin, Y. K., Chuang, C. Y., Li, M. H., Chou, C. H., Liao, C. H., & Sung, F. C. (2011). Associating emergency room visits with first and prolonged extreme temperature event in Taiwan. Science of the Total Environment, 416, 97–104. https://doi.org/10.1016/j.scitotenv.2011.11.073
Wilks, D. S. (2006). Statistical methods in the atmospheric sciences (2nd ed., International Geophysics Series, Vol. 91). Academic Press.
Wilks, D. S. (2010). Use of stochastic weather generators for precipitation downscaling. WIREs Climate Change, 1(6), 898–907. https://doi.org/10.1002/wcc.85
World Meteorological Organization. (2017). WMO guidelines on the calculation of climate normals (WMO-No. 1203). https://library.wmo.int/
World Meteorological Organization. (2026). WMO confirms 2025 was one of the warmest years on record. https://wmo.int/news/media-centre/wmo-confirms-2025-was-one-of-warmest-years-record
World Meteorological Organization, & World Health Organization. (2015). Heatwaves and health: Guidance on warning-system development (G. R. McGregor, P. Bessemoulin, K. Ebi, & B. Menne, Eds.; WMO-No. 1142). https://www.who.int/publications/
Wu, H. (2026). Quantifying physical climate risks for key industrial sectors in Taiwan: A financial impact assessment of flood hazards under multiple climate scenarios [Conference presentation]. EGU General Assembly 2026, Vienna, Austria. https://doi.org/10.5194/egusphere-egu26-3704
Wu, W.-T., Kono, M., Lee, C.-P., Chang, Y.-Y., Yang, Y.-H., Lin, C.-C., Liu, T.-M., Li, H.-C., Chen, Y.-M., & Chen, P.-C. (2024). Climate change projections for stroke incidence in Taiwan: Impact of 2°C and 4°C global warming levels. Journal of Epidemiology and Global Health, 14(3), 1319–1331. https://doi.org/10.1007/s44197-024-00289-3
Yang, H.-Y., Wu, C.-F., & Tsai, K.-H. (2024). Projections of climate change impact on acute heat illnesses in Taiwan: A case-crossover study. JMIR Public Health and Surveillance, 10, Article e57948. https://doi.org/10.2196/57948
Yu, P.-S., Yang, T.-C., Kuo, C.-M., Tseng, H.-W., & Chen, S.-T. (2015). Climate change impacts on streamflow drought: A case study in Tseng-Wen Reservoir catchment in southern Taiwan. Climate, 3(1), 42–62. https://doi.org/10.3390/cli3010042
Zhang, X., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson, T. C., Trewin, B., & Zwiers, F. W. (2011). Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Climate Change, 2(6), 851–870. https://doi.org/10.1002/wcc.147
Zhang, Z., Paschalis, A., Mijic, A., Meili, N., Manoli, G., van Reeuwijk, M., & Fatichi, S. (2022). A mechanistic assessment of urban heat island intensities and drivers across climates. Urban Climate, 44, 101215. https://doi.org/10.1016/j.uclim.2022.101215
Zhou, D., Sun, S., Li, Y., Zhang, L., & Huang, L. (2023). A multi-perspective study of atmospheric urban heat island effect in China based on national meteorological observations. Science of the Total Environment, 854, 158638. https://doi.org/10.1016/j.scitotenv.2022.158638