Downscaled climate projections at 800m spatial resolution for the north central United States based on the Multivariate Adaptive Constructed Analog (MACA) method from selective CMIP5 models
Dates
Publication Date
2018-03-26
Citation
Rangwala, I. and Dewes, C.F., 2018-03-26, Downscaled climate projections at 800m spatial resolution for the north central United States based on the Multivariate Adaptive Constructed Analog (MACA) method from selective CMIP5 models: https://doi.org/10.21429/C9704J.
Summary
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 12 Coupled Model Intercomparison Project - Phase 5 (CMIP5) climate model simulations (6GCMs x 2RCPs) 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. [...]
Summary
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 12 Coupled Model Intercomparison Project - Phase 5 (CMIP5) climate model simulations (6GCMs x 2RCPs) 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. Six GCMs were selected for developing this dataset. This selection was done to facilitate availability of several divergent future scenarios for the north central US region, and are selected based on (a) divergence found for future changes in annual temperature and precipitation for the region based on the projections from 34 CMIP5 GCMs for both RCP 4.5 and RCP 8.5 emissions scenarios, as well as (b) their relatively higher accuracy in representing the historic climate for the western and central US region. The six GCMs include CanESM2, CCSM4, CNRM-CM5, GFDL-ESM2M, HadGEM2-ES and IPSL-CM5A-MR. 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. A datafile on the elevation of a grid cell at 800m is also made available in this archive.
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Purpose
This fine spatial scale climate dataset is created for ecologists and natural resource managers in the north central US region (between 35.5N-49N latitude and 88W-118W longitude) to evaluate ecosystem response for a specific ecological target to climate change during different periods of the 21st century under different climate scenarios that capture the uncertainty envelope of climate projections from CMIP5 under a moderate (RCP 4.5) and high (RCP 8.5) emissions scenarios.
