This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the National Centre of Meteorological Research (France) model, CNRM-CM5, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the National Centre of Meteorological Research (France) model, CNRM-CM5, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Institut Pierre Simon Laplace (France) model, IPSL-CM5A-MR, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Institut Pierre Simon Laplace (France) model, IPSL-CM5A-MR, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the NOAA Geophysical Fluid Dynamics Laboratory (USA) model, GFDL-ESM2M, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Canadian Centre for Climate Modeling and Analysis model, CanESM2, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Canadian Centre for Climate Modeling and Analysis model, CanESM2, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Met Office Hadley Center (UK) model, HadGEM2-ES, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the Met Office Hadley Center (UK) model, HadGEM2-ES, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.

Global climate models (GCMs) are computationally intensive, physics-based research tools used to simulate the climate system. GCM can also be useful in applied research contexts with the use of statistical downscaling techniques. This collection of statistically downscaled climate projections includes 7 sets of SD-processed CMIP5 projections of daily high temperature, daily low temperature, and daily total precipitation across the Edwards Aquifer Region (EAR) in south central Texas. These sets of projections were created using four GCMs from the CMIP5 archive (CMCC-CM, HadGEM2-CC, inmcm4, MRI-ESM1), each of which simulated 21st century climate responses for multiple future emissions scenarios. The CMIP5 GCMs simulated response under the representative concentration pathways (RCPs) 4.5 and 8.5. The equi-distant quantile mapping method (EDQM) was used for statistical downscaling with the Daymet v. 4 as the observational data used for training. The resulting SD-processed projections are on a 1 km by 1 km grid covering the EAR in south central Texas (100.75 degress E to 97.5 degrees E, 28.75 degrees N to 30.50 degrees N). Both historical baseline files (1980-2005) and future projections (2006-2100) are provided. Applied researchers may explore aspects of potential changes in the EAR using these high resolution projections, including as inputs to additional modelling (e.g. hydrology modeling, crop modeling, etc.). This collection should not be considered comprehensive in spanning the entire scope of SD processed climate projections for the EAR. These climate projection data products are provided as is without any warranty and no agreement to support subsequent projects based on this dataset, beyond providing the data to public domain.