Citation

BibTex format

@article{Smith:2022:10.1016/j.dib.2022.108438,
author = {Smith, T and Stemkovski, M and Koontz, A and Pearse, W},
doi = {10.1016/j.dib.2022.108438},
journal = {Data in Brief},
title = {AREAdata: a worldwide climate dataset averaged across spatial units at different scales through time},
url = {http://dx.doi.org/10.1016/j.dib.2022.108438},
volume = {43},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - In an era of increasingly cross-discipline collaborative science, it is imperative to produce data resources which can be quickly and easily utilised by non-specialists. In particular, climate data often require heavy processing before they can be used for analyses. Here we describe AREAdata, a continually updated, free-to-use online global climate dataset, pre-processed to provide the averages of various climate variables across different administrative units (e.g., countries, states). These are daily estimates, based on the Copernicus Climate Data Store’s ERA-5 data, regularly updated to the near-present and provided as direct downloads from our website (https://pearselab.github.io/areadata/). The daily climate estimates from AREAdata are consistent with other openly available data, but at much finer-grained spatial and temporal scales than available elsewhere. AREAdata complements the existing suite of climate resources by providing these data in a form more readily usable by researchers unfamiliar with GIS data-processing methods, and we anticipate these resources being of particular use to environmental and epidemiological researchers.
AU - Smith,T
AU - Stemkovski,M
AU - Koontz,A
AU - Pearse,W
DO - 10.1016/j.dib.2022.108438
PY - 2022///
SN - 2352-3409
TI - AREAdata: a worldwide climate dataset averaged across spatial units at different scales through time
T2 - Data in Brief
UR - http://dx.doi.org/10.1016/j.dib.2022.108438
UR - http://hdl.handle.net/10044/1/97974
VL - 43
ER -