High-resolution projections of outdoor thermal stress in the twenty-first century: a Tasmanian case study

被引:1
作者
Weeding, Ben [1 ,2 ]
Love, Peter [2 ]
Beyer, Kathleen [1 ,2 ]
Lucieer, Arko [1 ]
Remenyi, Tom [3 ]
机构
[1] Univ Tasmania, Sch Geog Planning & Spatial Sci, Sandy Bay, Tas 7001, Australia
[2] Univ Tasmania, Climate Futures Res Grp, Sandy Bay, Tas 7001, Australia
[3] Acclimatised Pty Ltd, Blackmans Bay, Tas 7052, Australia
关键词
Bioclimatology; Thermal stress; Multivariate bias correction; MEAN RADIANT TEMPERATURE; HEAT-STRESS; CLIMATE-CHANGE; URBAN; INDEX; MODEL; MORTALITY; RADIATION; TREES;
D O I
10.1007/s00484-024-02622-8
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
To adapt to Earth's rapidly changing climate, detailed modelling of thermal stress is needed. Dangerous stress levels are becoming more frequent, longer, and more severe. While traditional measurements of thermal stress have focused on air temperature and humidity, modern measures including radiation and wind speed are becoming widespread. However, projecting such indices has presented a challenging problem, due to the need for appropriate bias correction of multiple variables that vary on hourly timescales. In this paper, we aim to provide a detailed understanding of changing thermal stress patterns incorporating modern measurements, bias correction techniques, and hourly projections to assess the impact of climate change on thermal stress at human scales. To achieve these aims, we conduct a case study of projected thermal stress in central Hobart, Australia for 2040-2059, compared to the historical period 1990-2005. We present the first hourly metre-scale projections of thermal stress driven by multivariate bias-corrected data. We bias correct four variables from six dynamically downscaled General Circulation Models. These outputs drive the Solar and LongWave Environmental Irradiance Geometry model at metre scale, calculating mean radiant temperature and the Universal Thermal Climate Index. We demonstrate that multivariate bias correction can correct means on multiple time scales while accurately preserving mean seasonal trends. Changes in mean air temperature and UTCI by hour of the day and month of the year reveal diurnal and annual patterns in both temporal trends and model agreement. We present plots of future median stress values in the context of historical percentiles, revealing trends and patterns not evident in mean data. Our modelling illustrates a future Hobart that experiences higher and more consistent numbers of hours of heat stress arriving earlier in the year and extending further throughout the day.
引用
收藏
页码:777 / 793
页数:17
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共 87 条
  • [1] Quantifying the Effect of Building Shadowing and Cloudiness on Mean Radiant Temperature in Singapore
    Acero, Juan A.
    Koh, Elliot J. Y.
    Tan, Yon Sun
    Norford, Leslie K.
    [J]. ATMOSPHERE, 2021, 12 (08)
  • [2] A 41-year bioclimatology of thermal stress in Europe
    Antonescu, Bogdan
    Marmureanu, Luminita
    Vasilescu, Jeni
    Marin, Cristina
    Andrei, Simona
    Boldeanu, Mihai
    Ene, Dragos
    Tilea, Alexandru
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2021, 41 (07) : 3934 - 3952
  • [3] The American Football Uniform: Uncompensable Heat Stress and Hyperthermic Exhaustion
    Armstrong, Lawrence E.
    Johnson, Evan C.
    Casa, Douglas J.
    Ganio, Matthew S.
    McDermott, Brendon P.
    Yamamoto, Linda M.
    Lopez, Rebecca M.
    Emmanuel, Holly
    [J]. JOURNAL OF ATHLETIC TRAINING, 2010, 45 (02) : 117 - 127
  • [4] Future Changes in Thermal Bioclimate Conditions over West Bengal, India, Based on a Climate Model
    Bal, Sourabh
    Kirchner, Ingo
    [J]. ATMOSPHERE, 2023, 14 (03)
  • [5] Present and future Koppen-Geiger climate classification maps at 1-km resolution
    Beck, Hylke E.
    Zimmermann, Niklaus E.
    McVicar, Tim R.
    Vergopolan, Noemi
    Berg, Alexis
    Wood, Eric F.
    [J]. SCIENTIFIC DATA, 2018, 5
  • [6] URock 2023a: an open-source GIS-based wind model for complex urban settings
    Bernard, Jeremy
    Lindberg, Fredrik
    Oswald, Sandro
    [J]. GEOSCIENTIFIC MODEL DEVELOPMENT, 2023, 16 (20) : 5703 - 5727
  • [7] Short-Term Heat Stress Exposure Limits Based on Wet Bulb Globe Temperature Adjusted for Clothing and Metabolic Rate
    Bernard, Thomas E.
    Ashley, Candi D.
    [J]. JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL HYGIENE, 2009, 6 (10) : 632 - 638
  • [8] AN INTRODUCTION TO THE UNIVERSAL THERMAL CLIMATE INDEX (UTCI)
    Blazejczyk, Krzysztof
    Jendritzky, Gerd
    Broede, Peter
    Fiala, Dusan
    Havenith, George
    Epstein, Yoram
    Psikuta, Agnieszka
    Kampmann, Bernhard
    [J]. GEOGRAPHIA POLONICA, 2013, 86 (01) : 5 - 10
  • [9] UTCI climatology and its future change in Germany - an RCM ensemble approach
    Brecht, Benedict Manuel
    Schaedler, Gerd
    Schipper, Janus Willem
    [J]. METEOROLOGISCHE ZEITSCHRIFT, 2020, 29 (02) : 97 - 116
  • [10] Thermofeel: A python']python thermal comfort indices library
    Brimicombe, Chloe
    Di Napoli, Claudia
    Quintino, Tiago
    Pappenberger, Florian
    Cornforth, Rosalind
    Cloke, Hannah L.
    [J]. SOFTWAREX, 2022, 18