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. 2021 Sep 21;18(18):9940.
doi: 10.3390/ijerph18189940.

Performances of Limited Area Models for the WORKLIMATE Heat-Health Warning System to Protect Worker's Health and Productivity in Italy

Affiliations

Performances of Limited Area Models for the WORKLIMATE Heat-Health Warning System to Protect Worker's Health and Productivity in Italy

Daniele Grifoni et al. Int J Environ Res Public Health. .

Abstract

Outdoor workers are particularly exposed to climate conditions, and in particular, the increase of environmental temperature directly affects their health and productivity. For these reasons, in recent years, heat-health warning systems have been developed for workers generally using heat stress indicators obtained by the combination of meteorological parameters to describe the thermal stress induced by the outdoor environment on the human body. There are several studies on the verification of the parameters predicted by meteorological models, but very few relating to the validation of heat stress indicators. This study aims to verify the performance of two limited area models, with different spatial resolution, potentially applicable in the occupational heat health warning system developed within the WORKLIMATE project for the Italian territory. A comparison between the Wet Bulb Globe Temperature predicted by the models and that obtained by data from 28 weather stations was carried out over about three summer seasons in different daily time slots, using the most common skill of performance. The two meteorological models were overall comparable for much of the Italian explored territory, while major limits have emerged in areas with complex topography. This study demonstrated the applicability of limited area models in occupational heat health warning systems.

Keywords: climate change; high-resolution forecasts; limited area model (LAM); meteorological model performance; occupational health and safety; personalized forecasts for workers; wet-bulb globe temperature (WBGT).

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Distribution of the Italian weather stations analysed for the creation of the observation dataset. The chosen stations were identified by the name of the location.
Figure 2
Figure 2
Elevation of the weather stations and the closest meteorological model grid points. Green line, weather station; Red line, BOL model; blue line, MOL model.
Figure 3
Figure 3
In red the areas of Italian peninsula where the models grid points (BOL on the left, MOL on the right) have an elevation higher than at least 200 m respect to that of a digital terrain model (DTM) with a spatial resolution of 90 m.
Figure 4
Figure 4
Probability of detection (POD2) of the Day2-WBGT-shade for the 12–18 time slot for each location of the three macro-geographical areas. (A), Northern inland plain areas; (B) Coastal areas; (C), Other central-southern inland areas; white, MOL-G; black, MOL-E; gray, BOL.
Figure 5
Figure 5
Normalized lack alarm (NA*) of the WBGT-shade for the 12–18 time band for each locality of the three macro-geographical areas. (A), Northern inland plain areas; (B), Coastal areas; (C), other central-southern inland areas; white, MOL-G; black, MOL-E; gray, BOL.

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