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.

为了适应地球快速变化的气候，需要对热应力进行详细的建模。危险的压力水平正变得越来越频繁、持续时间越来越长、也越来越严重。虽然传统的热应力测量主要集中在空气温度和湿度上，但包括辐射和风速在内的现代测量方法正在变得越来越普遍。然而，由于需要对每小时时间尺度上变化的多个变量进行适当的偏差校正，预测此类指数提出了一个具有挑战性的问题。在本文中，我们的目标是结合现代测量、偏差校正技术和每小时预测来详细了解不断变化的热应力模式，以评估气候变化对人类尺度热应力的影响。为了实现这些目标，我们对 2040 年至 2059 年澳大利亚霍巴特中部的预计热应力进行了案例研究，并与 1990 年至 2005 年的历史时期进行了比较。我们提出了由多元偏差校正数据驱动的第一个每小时米尺度的热应力预测。我们从六个动态缩小的大气环流模型中修正了四个变量。这些输出驱动米级太阳和长波环境辐照度几何模型，计算平均辐射温度和通用热气候指数。我们证明，多变量偏差校正可以校正多个时间尺度上的均值，同时准确地保留平均季节性趋势。一年中每天和每月的平均气温和 UTCI 的变化揭示了时间趋势和模型一致性的日间和年度模式。我们在历史百分位数的背景下绘制未来中位压力值的图，揭示平均数据中不明显的趋势和模式。我们的模型展示了未来的霍巴特将经历更高、更一致的热应激小时数，在一年中早些时候到达，并在一天中进一步延长。