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Article

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

1
Department of Economics, Ca’ Foscari University of Venice, 30121 Venice, Italy
2
Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 30175 Venice, Italy
Atmosphere 2020, 11(8), 835; https://doi.org/10.3390/atmos11080835
Received: 1 July 2020 / Revised: 24 July 2020 / Accepted: 29 July 2020 / Published: 7 August 2020
(This article belongs to the Special Issue Challenges in Applied Human Biometeorology)
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. View Full-Text
Keywords: human discomfort indices; bioclimatic indices; thermal discomfort; GLDAS human discomfort indices; bioclimatic indices; thermal discomfort; GLDAS
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MDPI and ACS Style

Mistry, M.N. A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices. Atmosphere 2020, 11, 835. https://doi.org/10.3390/atmos11080835

AMA Style

Mistry MN. A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices. Atmosphere. 2020; 11(8):835. https://doi.org/10.3390/atmos11080835

Chicago/Turabian Style

Mistry, Malcolm N. 2020. "A High Spatiotemporal Resolution Global Gridded Dataset of Historical Human Discomfort Indices" Atmosphere 11, no. 8: 835. https://doi.org/10.3390/atmos11080835

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