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The U.S. Great Plains is known for frequent hazardous convective weather and climate extremes. Across this region, climate change is expected to cause more severe droughts, more intense heavy rainfall events, and subsequently more flooding episodes. These potential changes in climate will adversely affect habitats, ecosystems, and landscapes as well as the fish and wildlife they support. Better understanding and simulation of regional precipitation can help natural resource managers mitigate and adapt to these adverse impacts. In this project, we aim to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model and use the high quality dynamic downscaling results...
Categories: Data;
Types: NetCDF OPeNDAP Service;
Tags: Red River,
climatologyMeteorologyAtmosphere,
dataset,
downscaling,
service
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. In particular, three different Global Climate Models (MPI-ESM-LR, CCSM4 and MIROC5) were downscaled using three different quantile mapping methods (CDFt, EDQM and BCQM). We do not recommend the use of the BCQM method, as the CDFt method is considered an improvement of it. The datasets created using the BCQM method are published as a demonstration of the risks of using flawed methods. The variables of interest are: daily maximum and minimum temperature, and daily precipitation. The spatial resolution of the datasets in the collection is 1/10th...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
NetCDF OPeNDAP Service,
Raster;
Tags: CMIP5,
David Blodgett,
air_temperature,
climatologyMeteorologyAtmosphere,
dataset,
Precipitation-related indicators for seasonal precipiation, extreme precipiation, and drought have been generated for 8701 weather stations covering the entire United States, and for a 198x337 grid (on a resolution of 1/16 th degree) covering the South Central region from the future downscaled projections using the Asynchronous Regional Regression Model. The data covers the period from 1950 to 2100. The high-resolution future projections are statistically downscaled from simulations by 12 global climate models from the Coupled Model Intercomparison Project phase 5 (ACCESS1-0, ACCESS1-3, CCSM4, CMCC-CM, CNRM-CM5, CSIRO-Mk3.6.0, MPI-ESM-LR, HadGEM2-CC, INMCM4, IPSL-CM5A-LR, MIROC5 and MRI-CGCM under the lower Representative...
Categories: Data;
Types: NetCDF OPeNDAP Service;
Tags: climatologyMeteorologyAtmosphere,
dataset,
drought,
extreme precipitation,
high-resolution precipitation projections,
Global climate models (GCMs) are numerically complex, computationally intensive, physics-based research tools used to simulate our planet’s inter-connected climate system. In addition to improving the scientific understanding of how the large-scale climate system works, GCM simulations of past and future climate conditions can be useful in applied research contexts. When seeking to apply information from global-scale climate projections to address local- and regional-scale climate questions, GCM-generated datasets often undergo statistical post-processing generally known as statistical downscaling (hereafter, SD). There are many different SD techniques, with all using information from observations to address GCM...
Categories: Data;
Types: NetCDF OPeNDAP Service;
Tags: climate,
climate change,
climate projections,
climatologyMeteorologyAtmosphere,
dataset,
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