U.S. Department of EnergyOffice of Scientific and Technical Information
Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling
Abstract
This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file thatmore »
- Authors:
-
;
- Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
- Lawrence Berkeley National Laboratory
- Publication Date:
- Research Org.:
- Environmental System Science Data Infrastructure for a Virtual Ecosystem; Watershed Function SFA
- Sponsoring Org.:
- U.S. DOE > Office of Science > Biological and Environmental Research (BER)
- Subject:
- 54 ENVIRONMENTAL SCIENCES; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; Meteorological data; hourly; model input; precipitation; relative humidity; solar radiation; temperature; wind speed
- OSTI Identifier:
- 2502101
- DOI:
- https://doi.org/10.15485/2502101
Citation Formats
Faybishenko, Boris, and O'Ryan, Dylan. Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling. United States: N. p., 2024.
Web. doi:10.15485/2502101.
Faybishenko, Boris, & O'Ryan, Dylan. Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling. United States. doi:https://doi.org/10.15485/2502101
Faybishenko, Boris, and O'Ryan, Dylan. 2024.
"Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling". United States. doi:https://doi.org/10.15485/2502101. https://www.osti.gov/servlets/purl/2502101. Pub date:Tue Dec 31 23:00:00 EST 2024
@article{osti_2502101,
title = {Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling},
author = {Faybishenko, Boris and O'Ryan, Dylan},
abstractNote = {This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.},
doi = {10.15485/2502101},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Dec 31 23:00:00 EST 2024},
month = {Tue Dec 31 23:00:00 EST 2024}
}