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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ftzenodo:oai:zenodo.org:5013939 2024-09-15T17:41:41+00:00 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 2018-05-23 https://doi.org/10.5061/dryad.s2v81 unknown Zenodo https://doi.org/10.1038/sdata.2017.78 https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.s2v81 oai:zenodo.org:5013939 info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode MERRAclim bioclimatic info:eu-repo/semantics/other 2018 ftzenodo https://doi.org/10.5061/dryad.s2v8110.1038/sdata.2017.78 2024-07-26T15:35:56Z 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 2 m 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. MERRAclim. 10m_max_00s MERRAclim Dataset. 19 global bioclimatic variables from the 2000s decade at 10 arcminutes resolution in GEOtiff format. The humidity version used is the maximum. The variables have been built using the same protocol as WorldClim with data from MERRA. Temperature layers (BIO1-BIO11) are in degree Celsius multiplied by 10, humidity layers (BIO12-BIO19) are in kg of water/kg of air multiplied by 100000. 10m_max_00s.zip MERRAclim. 10m_max_90s MERRAclim Dataset. 19 global bioclimatic variables from the 1990s decade at 10 arcminutes resolution in GEOtiff format. The humidity version used is the maximum. The variables have been built using the same protocol as WorldClim with data from MERRA. Temperature layers (BIO1-BIO11) are in degree Celsius multiplied by 10, humidity layers(BIO12-BIO19) are in kg of ... Other/Unknown Material Antarc* Antarctic Antarctica Zenodo |
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MERRAclim bioclimatic |
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MERRAclim bioclimatic 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 |
MERRAclim bioclimatic |
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 2 m 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. MERRAclim. 10m_max_00s MERRAclim Dataset. 19 global bioclimatic variables from the 2000s decade at 10 arcminutes resolution in GEOtiff format. The humidity version used is the maximum. The variables have been built using the same protocol as WorldClim with data from MERRA. Temperature layers (BIO1-BIO11) are in degree Celsius multiplied by 10, humidity layers (BIO12-BIO19) are in kg of water/kg of air multiplied by 100000. 10m_max_00s.zip MERRAclim. 10m_max_90s MERRAclim Dataset. 19 global bioclimatic variables from the 1990s decade at 10 arcminutes resolution in GEOtiff format. The humidity version used is the maximum. The variables have been built using the same protocol as WorldClim with data from MERRA. Temperature layers (BIO1-BIO11) are in degree Celsius multiplied by 10, humidity layers(BIO12-BIO19) are in kg of ... |
format |
Other/Unknown Material |
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 |
publisher |
Zenodo |
publishDate |
2018 |
url |
https://doi.org/10.5061/dryad.s2v81 |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_relation |
https://doi.org/10.1038/sdata.2017.78 https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.s2v81 oai:zenodo.org:5013939 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode |
op_doi |
https://doi.org/10.5061/dryad.s2v8110.1038/sdata.2017.78 |
_version_ |
1810487927494410240 |