The Research Product Clearinghouse portion of the EPSCoR website provides access to a diverse body of resources from the OK NSF EPSCoR Research Infrastructure Improvement Award No. OIA-1301789 (2013-2018), “Adapting Socio-Ecological Systems to Increased Climate Variability.” Resources include a variety of datasets that researchers around the world will be able to access and build upon in future climate-related research. The Data Repository page provides access to all of the data available as a result of this project. The data described below are an important part of the OK NSF EPSCoR research team's work, which was produced in collaboration with contributing programs and agencies.
Cybercommons Data Repository
The Cybercommons Data Repository holds datasets related to the OK NSF EPSCoR project, including rasters for major Oklahoma watersheds, a collection of statistically downscaled time series for the Red River Basin, Kiamichi archival material, and more.
M-SISNet Seasonal Survey Overviews and Codebooks
Researchers at the University of Oklahoma’s Center for Risk and Crisis Management have surveyed Oklahomans' perceptions of weather in our state, as well as those individuals' views on government policies and societal issues, to help understand how perceptions and views might shape water and energy use. Public access to codebooks of the survey data, along with a variable usage reference sheet, is available via this website.
Oklahoma Water Survey Data Portal
The Oklahoma Water Survey Data Portal provides an online, integrated source of water information gathered from more than 20 different government agencies, tribes and organizations with water management interests and responsibilities. The portal's overriding goal is to provide water resource managers and other users with an efficient and effective method to obtain, organize and interpret local water quantity and water quality data.
Red River Basin Statistically Downscaled Ensemble
This collection contains three statistically downscaled time series datasets for the Red River Basin (South Central U.S.), and one dataset used as historical observations. Three different Global Climate Models (MPI-ESM-LR, CCSM4 and MIROC5) were downscaled using three different quantile mapping methods (CDFt, EDQM and BCQM). The variables of interest are daily maximum and minimum temperature, and daily precipitation.