DOI: 10.5281/zenodo.5784507
title: Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains

description: Dec 15, 2021 <strong>Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains</strong> Carlos M. Carrillo and Francisco Muñoz-Arriola <strong>Motivation</strong> The data presented here was used to investigate the uskills of precipitation in the US northern Great Plains, and it can be cited as described below. The original data for producing this data is from the Climate Forecast System (CFS) retrospective reanalysis and reforecast as well as precipitation data from the Climate Prediction Center (CPC) from the National Oceanic and Atmospheric Administration (NOAA). Also, gridded data is from the North American Regional Reanalysis (NARR) from the National Centers for Environmental Prediction (NCEP). <strong>License </strong> Creative Commons CC-BY <strong>Disclaimer</strong> The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous. <strong>Description of the dataset</strong> Files are provided with the following features: <strong>List of cases: </strong> files.0.00.dy.txt <strong>Low-level jet (or the GP-LLJ index)</strong> Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/ Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong> With input data from CFS models, eof1.v850.cfs.1982-2009.dy.tar pc1.v850.cfs.1982-2009.dy.tar from NARR model, pc1.vwnd.narr.1982-2009.tar <strong>The geopotential height (or CGT index): </strong> Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/ Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong> With input data xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar xt-reco-z200.Full.z200.narr.1982-2009.bin.tar <strong>Precipitation at the US Great Plains:</strong> Originally located at /home/cmc542/2019/sum-pred/clim/yrcases Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong> With input data: prec.cfs.MW.1982-2009.tar prec.cpc.MW.1982-2009.tar <strong>Correlation patterns:</strong> Precipitation: PREC.NGP.corr.txt LLJ: LLJ.pcs.corr.narr.pdf.txt Z200: Z200.pcs.corr.narr.pdf.txt <strong>Disclaimer</strong> The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous. <strong>Description of the dataset</strong> Files are provided with the following features: <strong>List of cases: </strong> files.0.00.dy.txt <strong>Low-level jet (or the GP-LLJ index)</strong> Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/ Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong> With input data from CFS models, <strong> </strong>eof1.v850.cfs.1982-2009.dy.tar pc1.v850.cfs.1982-2009.dy.tar from NARR model, pc1.vwnd.narr.1982-2009.tar <strong>The geopotential height (or CGT index): </strong> Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/ Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong> With input data xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar xt-reco-z200.Full.z200.narr.1982-2009.bin.tar <strong>Precipitation at the US Great Plains:</strong> Originally located at /home/cmc542/2019/sum-pred/clim/yrcases Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong> With input data: prec.cfs.MW.1982-2009.tar prec.cpc.MW.1982-2009.tar <strong>Correlation patterns:</strong> Precipitation: PREC.NGP.corr.txt LLJ: LLJ.pcs.corr.narr.pdf.txt Z200: Z200.pcs.corr.narr.pdf.txt <strong>Credit</strong> Carlos M. Carrillo and Francisco Muñoz-Arriola, 2021: “Sources of Subseasonal Predictability of Rainfall in the Northern Great Plains”, <em>Journal of Applied Meteorology and Climatology</em>. In review. <strong>Grant funding</strong> This research was funded by the U.S. Geological Survey (USGS), the U.S. Department of Agriculture (USDA), the Daugherty Water for Food Global Institute (DWFI) at the University of Nebraska-Lincoln (UNL), and the UNL’s Layman Award.