Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12
datasets available to search
ShareScore release 0.7.1
Dataset results
12 results for “the US Great Plains”
Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains
<p>Dec 15, 2021</p> <p> </p> <p><strong>Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains</strong></p> <p> </p> <p>Carlos M. Carrillo and Francisco Muñoz-Arriola</p> <p> </p> <p><strong>Motivation</strong></p> <p>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).</p> <p> </p> <p><strong>License </strong></p> <p>Creative Commons CC-BY</p> <p><strong>Disclaimer</strong></p> <p>The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous.</p> <p><strong>Description of the dataset</strong></p> <p>Files are provided with the following features:</p> <p><strong>List of cases: </strong></p> <p> files.0.00.dy.txt</p> <p><strong>Low-level jet (or the GP-LLJ index)</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> from CFS models,</p> <p> eof1.v850.cfs.1982-2009.dy.tar</p> <p> pc1.v850.cfs.1982-2009.dy.tar</p> <p> from NARR model,</p> <p> pc1.vwnd.narr.1982-2009.tar</p> <p><strong>The geopotential height (or CGT index): </strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar</p> <p> xt-reco-z200.Full.z200.narr.1982-2009.bin.tar</p> <p><strong>Precipitation at the US Great Plains:</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/clim/yrcases</p> <p>Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong></p> <p>With input data:</p> <p> prec.cfs.MW.1982-2009.tar</p> <p> prec.cpc.MW.1982-2009.tar</p> <p><strong>Correlation patterns:</strong></p> <p> Precipitation: PREC.NGP.corr.txt</p> <p> LLJ: LLJ.pcs.corr.narr.pdf.txt</p> <p> Z200: Z200.pcs.corr.narr.pdf.txt</p> <p> </p> <p><strong>Disclaimer</strong></p> <p>The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous.</p> <p><strong>Description of the dataset</strong></p> <p>Files are provided with the following features:</p> <p><strong>List of cases: </strong></p> <p> files.0.00.dy.txt</p> <p><strong>Low-level jet (or the GP-LLJ index)</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> from CFS models,</p> <p><strong> </strong>eof1.v850.cfs.1982-2009.dy.tar</p> <p> pc1.v850.cfs.1982-2009.dy.tar</p> <p> from NARR model,</p> <p> pc1.vwnd.narr.1982-2009.tar</p> <p><strong>The geopotential height (or CGT index): </strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar</p> <p> xt-reco-z200.Full.z200.narr.1982-2009.bin.tar</p> <p><strong>Precipitation at the US Great Plains:</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/clim/yrcases</p> <p>Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong></p> <p>With input data:</p> <p> prec.cfs.MW.1982-2009.tar</p> <p> prec.cpc.MW.1982-2009.tar</p> <p><strong>Correlation patterns:</strong></p> <p> Precipitation: PREC.NGP.corr.txt</p> <p> LLJ: LLJ.pcs.corr.narr.pdf.txt</p> <p> Z200: Z200.pcs.corr.narr.pdf.txt</p> <p><strong>Credit</strong></p> <p>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.</p> <p><strong>Grant funding</strong></p> <p>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.</p>
Planetary Boundary Layer Height Retrievals from the Cloud-Aerosol Transport System (CATS) around the US Southern Great Plains and the Eastern North Atlantic
<p>Planetary Boundary Layer Height (PBLH) retrievals in kilometers from the Cloud-Aerosol Transport System (CATS) around the DOE ARM US Southern Great Plains (SGP) and the Eastern North Atlantic (ENA), using a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm. Quality control Flags are included as follows:</p> <ul> <li>0 = 'Good Quality'</li> <li>1 = 'Mediate Quality'</li> <li>2 = 'Bad Quality'</li> </ul> <p>In addition, -999 values in the dataset represent no data. <br>The PBLH for daytime denoised CATS photon counts at SGP is named: "daytime-denoised-dtds-pblh-sgp.csv"<br>The PBLH for the original daytime and nighttime data at SGP and ENA, without denoising the data, are named: "original-cats-dtds-pblh-daytime-nighttime-sgp.csv" and "original-cats-dtds-pblh-daytime-nighttime-ena.csv"</p> <p>References: </p> <p>Roldán-Henao, N., Yorks, J., Su, T., Selmer, P., & Li, Z. (2024). Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data. <em>Remote Sensing. </em></p> <p>Su, T., Li, Z., & Kahn, R. (2020). A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. <em>Remote Sensing of Environment</em>, <em>237</em>, 111519.</p>
SGS-LTER Graduate Student Research: Aboveground Net Primary Production as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Belowground Net Primary Production as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Decomposition Rates as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Soil Respiration Rates as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Annual Nitrogen Mineralization Rates as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Monthly Nitrogen Mineralization Rates as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
SGS-LTER Graduate Student Research: Phospholipid fatty acid (PFLA) as Biochemical Responses of US Great Plains Grasslands to Regional and Interannual Variability in Precipitation (1999-2001)
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/85531. Carbon (C) sequestration potential in grasslands is thought to be high due to the large soil organic carbon pools characteristic of these ecosystems. Inputs of C (aboveground net primary productivity) are highly correlated to precipitation across the Great Plains region; however, changes in C pool size at a specific site are governed by the relative input and output rates across time. Our objective was to quantify the ecosystem C response of three grassland community types (shortgrass steppe, mixed grass and tallgrass prairie) to interannual variation in precipitation. At five sites across a precipitation gradient in the Great Plains, we measured net primary production (NPP), soil respiration (SRESP), and litter decomposition rates for three consecutive years. NPP, SRESP, and litter decomposition increased from shortgrass steppe (175, 454, and 47 g C m-2 yr-1) to tallgrass prairie (408, 1221, and 348 g C m-2 yr-1 for NPP, SRESP, and litter decomposition respectively). Increased growing season precipitation between study years resulted in increased NPP, SRESP, and litter decomposition at almost all sites. However, the regional patterns of the interannual NPP, SRESP, and lit
Data from: Intraspecific variation of a dominant grass and local adaptation in reciprocal garden communities along a US Great Plains’ precipitation gradient: implications for grassland restoration with climate change
Open the record for dataset details and reuse information.
Data from: Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains' climate gradient: Implications for climate change and restoration
<p>Plant response to climate depends on a species' adaptive potential. To address this, we used reciprocal gardens to detect genetic and environmental plasticity effects on phenotypic variation and combined with genetic analyses. Four reciprocal garden sites were planted with three regional ecotypes of <i>Andropogon gerardii</i>, a dominant Great Plains prairie grass, using dry, mesic, wet ecotypes originating from western KS to Illinois that span 500 to 1,200 mm rainfall year<sup>-1</sup>. We aimed to answer: (1) What is the relative role of genetic constraints and phenotypic plasticity in controlling phenotypes? 2) When planted in the home site, is there a trait syndrome for each ecotype? 3) How are genotypes and phenotypes structured by climate? (4) What are implications of these results for response to climate change and use of ecotypes for restoration? Surprisingly, we did not detect consistent local adaptation. Rather, we detected co-gradient variation primarily for most vegetative responses. All ecotypes were stunted in western KS. Eastward, the wet ecotype was increasingly robust relative to other ecotypes. In contrast, fitness showed evidence for local adaptation in wet and dry ecotypes with wet and mesic ecotypes producing little seed in western KS. Earlier flowering time in the dry ecotype suggests adaptation to end of season drought. Considering ecotype traits in home site, the dry ecotype was characterized by reduced canopy area and diameter, short plants, and low vegetative biomass and putatively adapted to water limitation. The wet ecotype was robust, tall with high biomass and wide leaves putatively adapted for the highly competitive, light-limited Eastern Great Plains. Ecotype differentiation was supported by random forest classification and PCA. We detected genetic differentiation and outlier genes associated primarily with precipitation. We identified candidate gene GA1 for which allele frequency associated with plant height. Sourcing of climate adapted ecotypes should be considered for restoration.</p>
Data from: Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains’ climate gradient: Implications for climate change and restoration
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.