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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Bibliographic Details
Main Authors: Vega, Greta C., Pertierra, Luis R., Olalla-Tárraga, Miguel Ángel
Format: Dataset
Language:unknown
Published: 2018
Subjects:
Online Access:https://zenodo.org/record/5013939
https://doi.org/10.5061/dryad.s2v81
Description
Summary: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_00sMERRAclim 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.zipMERRAclim. 10m_max_90sMERRAclim 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 water/kg ...