A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices

A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices

Mistry M.N., (2020), A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices, Atmosphere 2020, 11(8), 835, DOI: 10.3390/atmos11080835, webpage

Abstract

Meteorological human discomfort indices or bioclimatic indices are important metrics to gauge potential risks to human health under varying environmental thermal exposures. Derived using sub-daily meteorological variables from a quality-controlled reanalysis data product (Global Land Data Assimilation System—GLDAS), a new high-resolution global dataset referred to as “HDI_0p25_1970_2018” is presented in this study. The dataset includes the following daily indices at 0.25° × 0.25° gridded resolution: (i) Apparent Temperature indoors (ATind); (ii) two variants of Apparent Temperature outdoors in shade (ATot); (iii) Heat Index (HI); (iv) Humidex (HDEX); (v) Wet Bulb Temperature (WBT); (vi) two variants of Wet Bulb Globe Temperature (WBGT); (vii) Thom Discomfort Index (DI); and (viii) Windchill Temperature (WCT). Spanning 49 years over the period 1970–2018, HDI_0p25_1970_2018 fills gaps in existing climate indices datasets by being the only high-resolution historical global-gridded daily time-series of multiple human discomfort indices based on different meteorological parameters, thus offering applications in wide-ranging climate zones and thermal-comfort environments.

 

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