Heat stress is one of the main factors limiting the efficiency and sustainability of dairy production in tropical and subtropical regions, impairing animal welfare, as well as productive and reproductive performance. Among mitigation technologies, evaporative cooling stands out as a widely adopted strategy in intensive production systems. However, there are still no consolidated metrics capable of quantifying, in a comparative and regionalized manner, the theoretical potential for using this technique under different climatic conditions. In this context, the objective of this study was to develop an innovative modeling-based metric to estimate the potential for evaporative cooling based on thermal environment indices and heat transfer principles. Sixteen-year time series of hourly meteorological data from three Brazilian municipalities located in major dairy-producing regions [Uberlândia (MG), Luziânia (GO), and Uruguaiana (RS)], encompassing representative tropical and subtropical conditions, were used to calculate the Temperature–Humidity Index (THI) and to develop the metric termed Radiant Heat Load Reduction under Evaporative Cooling (ΔRHL). Based on the results obtained, THI values were found to frequently exceed the thermal comfort thresholds between September and April, corresponding to the warmest period of the year in Brazil. However, the relationship between the intensity of heat stress and the theoretical potential for evaporative cooling varied significantly among the locations, indicating that the potential efficiency of evaporative cooling is strongly dependent on regional climatic conditions and is more consistent in subtropical environments. It is concluded that the proposed metric constitutes an innovative tool for the spatial and temporal quantification of the potential efficiency of evaporative cooling, with applicability in decision support and in the planning of thermal mitigation strategies in intensive dairy production systems.

Heat stress poses a challenge to dairy production under increasing climate variability, highlighting the need for long-term assessments of thermal risk. This study assessed heat stress risk across major dairy-producing regions of Minas Gerais, Brazil, using ERA5-Land reanalysis data and the Temperature–Humidity Index (THI). Daily air temperature and dew point temperature data from 2004 to 2024 were used to calculate THI. ERA5-Land-derived THI was validated against observations from 63 INMET automatic weather stations using the modified Kling–Gupta Efficiency (KGE′). At the regional scale, heat stress risk was characterized based on the frequency, spatial distribution, seasonality, and temporal trends of THI-defined climatic heat-stress categories. Temporal trends were assessed using Pearson’s correlation between year and annual frequency for each THI category, with significance evaluated using a t-test at the 5% significance level. KGE′ values were predominantly between 0.80 and 0.90, indicating high agreement between observed and ERA5-Land-derived data. Heat stress conditions (THI ≥ 68) accounted for 69.72% of the observations, with the highest seasonal frequencies occurring in summer (24.23%) and spring (22.25%). Temporal analysis indicated an average increase of 2.23 days year⁻¹ in heat-stress conditions, mainly due to moderate heat stress, while thermoneutral days showed predominantly decreasing trends. These findings demonstrate that integrating climate reanalysis data with bioclimatic indicators provides a robust framework for assessing heat stress risk and supporting regional planning of livestock facilities, cooling strategies, and climate change adaptation.