Feasibility of climate reanalysis data as a proxy for onsite weather measurements in outdoor thermal comfort surveys

Abstract

Outdoor thermal comfort (OTC) surveys require synchronous monitoring of meteorological variables for direct comparisons against subjective thermal perception. The Universal Thermal Climate Index (UTCI) is a feasible index as it integrates meteorological conditions as a single value irrespective of urban morphological attributes or biological sex, age and body mass. ERA5-HEAT (Human thErmAl comforT) is a downloadable reanalysis dataset providing hourly grids of UTCI climate records at 0.25° × 0.25° spatial resolution from 1979 to present. We here evaluate for the first time whether it is possible to use ERA5-HEAT data as a proxy for the UTCI measured onsite during OTC surveys. A dataset comprising 1640 survey responses gathered over 14 OTC campaigns in Curitiba, Brazil (25°26′S, 49°16′W) was analysed. We assessed the bias obtained between the Dynamic Thermal Sensation, an index derived from the UTCI, and the thermal sensation reported by survey participants by considering locally measured meteorological variables and ERA5-HEAT reanalysis data. As ERA5-HEAT data are given on an hourly basis, prediction bias can be greatly reduced when accounting for survey responses close to the hour. In terms of seasons, the fall and winter seasons have diminished mean bias, though with larger spread than in summer. In terms of UTCI stress categories, prediction bias is lower for the thermal comfort range. When comparing reanalysis data against WMO station data as proxy candidates for survey field data, the former presented lower bias, less spread in terms of standard deviation and higher correlation to in situ data.

Investigating the Relationship between Climate and Hospital Admissions for Respiratory Diseases before and during the COVID-19 Pandemic in Brazil

“…It is surprising that the correlations follow a similar trend, as reanalysis data follow a grid that does not fully correspond to that of the WMO meteorological station, where field data came from. A previous work, however, suggests that UTCI reanalysis data are reasonable surrogates for missing field data in OTC studies involving questionnaire surveys [24]. Despite the fact that there were some discrepancies between Ta and UTCI data in terms of correlation strength (as in Manaus, for the children group in 2020, improving correlations when UTCI data are accounted for), for the two age groups at the location with marked seasons and with the strongest correlations in 2018 (Porto Alegre), there was no noticeable improvement in the correlations when UTCI data were used instead of the ambient temperature data.…”

“…The multi-node, outdoor thermal comfort index UTCI has been used in a number of studies on heat stress in urban areas across the world, and has been found suitable to Brazilian climates [23]. ERA5-HEAT reanalysis data proved to be meaningful for urban-related studies [24].…”

The role of global reanalyses in climate services for health: Insights from the Lancet Countdown

“… Resolution : Health and epidemiological data are often aggregated to administrative units (i.e., district and province levels). They are thus at much finer scales than global climate reanalysis data, challenging the ability of the latter to resolve the urban or neighbourhood scales at which microclimates can cause large disparities in the ambient environment (Fletcher et al, 2021; Krüger & Di Napoli, 2022). In indicator 1.3, the climate suitability for the transmission of four infectious diseases (dengue, chikungunya, zika and malaria) is calculated from ERA5‐Land variables (Romanello et al, 2022b).…”

Spatiotemporal characteristics of human thermal comfort across southern Africa: An analysis of the Universal Thermal Climate Index for 1971–2021

“…Thus, where possible it is necessary to validate the ERA5‐HEAT dataset, or at least the ERA5 inputs, to determine reliability thereof as a proxy for southern African observations. Results from Curitiba, southern Brazil and selected European regions already suggest good reliability, given a good degree of comparability evident between ERA5‐HEAT and observation‐based UTCI calculations (Urban et al ., 2021; Krüger and Di Napoli, 2022). Nonetheless, advantages of good and/or improved agreement with observations of temperature, wind conditions and UTCI scores (Ramon et al ., 2019; Gleixner et al ., 2020; Di Napoli et al ., 2021; Urban et al ., 2021), a globally fine spatial grid resolution, temporal completeness and free availability, for instance, outweigh disadvantages associated with the ERA5/ERA5‐HEAT reanalysis.…”