Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling

Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to pa...

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Main Authors: Vega, Greta C., Pertierra, Luis R., Olalla-Tárraga, Miguel Ángel
Format: Article in Journal/Newspaper
Language:unknown
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10255/dryad.120152
https://doi.org/10.5061/dryad.s2v81.1
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spelling ftdryad:oai:v1.datadryad.org:10255/dryad.120152 2023-05-15T13:31:23+02:00 Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling Vega, Greta C. Pertierra, Luis R. Olalla-Tárraga, Miguel Ángel Global 2017-06-15T17:15:29Z http://hdl.handle.net/10255/dryad.120152 https://doi.org/10.5061/dryad.s2v81.1 unknown doi:10.5061/dryad.s2v81.1/1.1 doi:10.5061/dryad.s2v81.1/2.1 doi:10.5061/dryad.s2v81.1/3.1 doi:10.5061/dryad.s2v81.1/4.1 doi:10.5061/dryad.s2v81.1/5.1 doi:10.5061/dryad.s2v81.1/6.1 doi:10.5061/dryad.s2v81.1/7.1 doi:10.5061/dryad.s2v81.1/8.1 doi:10.5061/dryad.s2v81.1/9.1 doi:10.5061/dryad.s2v81.1/10.1 doi:10.5061/dryad.s2v81.1/11.1 doi:10.5061/dryad.s2v81.1/12.1 doi:10.5061/dryad.s2v81.1/13.1 doi:10.5061/dryad.s2v81.1/14.1 doi:10.5061/dryad.s2v81.1/15.1 doi:10.5061/dryad.s2v81.1/16.1 doi:10.5061/dryad.s2v81.1/17.1 doi:10.5061/dryad.s2v81.1/18.1 doi:10.5061/dryad.s2v81.1/19.1 doi:10.5061/dryad.s2v81.1/20.1 doi:10.5061/dryad.s2v81.1/21.1 doi:10.5061/dryad.s2v81.1/22.1 doi:10.5061/dryad.s2v81.1/23.1 doi:10.5061/dryad.s2v81.1/24.1 doi:10.5061/dryad.s2v81.1/25.1 doi:10.5061/dryad.s2v81.1/26.1 doi:10.5061/dryad.s2v81.1/27.1 doi:10.1038/sdata.2017.78 doi:10.5061/dryad.s2v81.1 Vega GC, Pertierra LR, Olalla-Tárraga MÁ (2017) MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling. Scientific Data 4: 170078. 2052-4463 http://hdl.handle.net/10255/dryad.120152 bioclimatic MERRAclim macroecology biogeography Article 2017 ftdryad https://doi.org/10.5061/dryad.s2v81.1 https://doi.org/10.5061/dryad.s2v81.1/1.1 https://doi.org/10.5061/dryad.s2v81.1/2.1 https://doi.org/10.5061/dryad.s2v81.1/3.1 https://doi.org/10.5061/dryad.s2v81.1/4.1 https://doi.org/10.5061/dryad.s2v81.1/5 2020-01-01T15:37:04Z Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe. Article in Journal/Newspaper Antarc* Antarctic Antarctica Dryad Digital Repository (Duke University) Antarctic The Antarctic
institution Open Polar
collection Dryad Digital Repository (Duke University)
op_collection_id ftdryad
language unknown
topic bioclimatic
MERRAclim
macroecology
biogeography
spellingShingle bioclimatic
MERRAclim
macroecology
biogeography
Vega, Greta C.
Pertierra, Luis R.
Olalla-Tárraga, Miguel Ángel
Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
topic_facet bioclimatic
MERRAclim
macroecology
biogeography
description Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.
format Article in Journal/Newspaper
author Vega, Greta C.
Pertierra, Luis R.
Olalla-Tárraga, Miguel Ángel
author_facet Vega, Greta C.
Pertierra, Luis R.
Olalla-Tárraga, Miguel Ángel
author_sort Vega, Greta C.
title Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
title_short Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
title_full Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
title_fullStr Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
title_full_unstemmed Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
title_sort data from: merraclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
publishDate 2017
url http://hdl.handle.net/10255/dryad.120152
https://doi.org/10.5061/dryad.s2v81.1
op_coverage Global
geographic Antarctic
The Antarctic
geographic_facet Antarctic
The Antarctic
genre Antarc*
Antarctic
Antarctica
genre_facet Antarc*
Antarctic
Antarctica
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doi:10.5061/dryad.s2v81.1
Vega GC, Pertierra LR, Olalla-Tárraga MÁ (2017) MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling. Scientific Data 4: 170078.
2052-4463
http://hdl.handle.net/10255/dryad.120152
op_doi https://doi.org/10.5061/dryad.s2v81.1
https://doi.org/10.5061/dryad.s2v81.1/1.1
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https://doi.org/10.5061/dryad.s2v81.1/3.1
https://doi.org/10.5061/dryad.s2v81.1/4.1
https://doi.org/10.5061/dryad.s2v81.1/5
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