Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset

Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset We curated a dataset of post-processed in situ evapotranspiration (ET) measurements, primarily from eddy covariance flux towers, from stations located within the contiguous United States. The dataset includes daily and monthly aggregated ET, energy balance metrics, and micrometeorological data that were post-processed from 148 flux towers, 4 weighing lysimters, and 8 Bowen Ration stations. Original data was retrieved from the AmeriFlux network and other networks and partners. The dataset is oriented towards ET and includes both ET that has been corrected for energy balance closure error as well as the uncorrected values. Energy balance components (latent and sensble heat flux, soil heat flux, and net radiation) were subject to limited gap-filling and latent energy (ET) was subject to additional visual quality control. Other meteorological measurements such as air temperature, precipitation, humidity, etc. are included for most stations depending on availability, and some additional variables were calculated. Interactive graphics of most post-processed data are also included. The dataset has many potential uses including evaluation of regional hydrologic and atmospheric models, energy balance analysis, and more. Description of the Data and file structure The dataset is in a compressed (zipped) archive titled "flux_ET_dataset", so first it needs to be downloaded and extracted. Once extracted there are four major components within: 1. A collection of time series files with daily aggregated data (one for each station), these are in the directory named "daily_data_files" and are in CSV format. 2. A similar collection of time series files for monthly aggregated data in "monthly_data_files". 3. Interactive graphic files (HTML format) for each station which are in the "graphical_files" directory. 4. Two additional tables in the root directory, including a metadata file named "station_metadata.xlsx" with site information such as site ID, coordinates, land cover type, principal investigator information, etc. The other table named "variable_explanation.xlsx" lists all variables that were post-processed in the flux dataset and gives a short description of each as well as their units. Each data and plot file starts with the station's ID or site ID which are listed in the station_metadata.xlsx file. Here is a visual of the file structure: flux_ET_dataset │ README.md │ variable_explanation.xlsx │ station_metadata.xlsx │ └───daily_data_files │ │ [site ID]_daily_data.csv │ │ ... └───monthly_data_files │ │ [site ID]_monthly_data.csv │ │ ... └───graphical_files │ │ [site ID]_plots.html │ │ ... ``` The variable names in the daily and monthly data files as well as the graphics all follow the same naming scheme which are defined in the variable_explanation.xlsx file. For example, LE stands for latent energy flux and is in units of W/m2. Sharing/access Information Currently, this repository (Dryad) is the only location where the data are hosted. Original data, prior to post-processing, were retrieved from multiple providers listed below: * AmeriFlux network (https://ameriflux.lbl.gov/) * California State University, Monterey Bay, Seaside, CA, USA * Desert Research Institute, Reno, NV, USA * gridMET, Northwest Knowledge Network at the University of Idaho (https://thredds.northwestknowledge.net/) * United States Geological Survey Nevada Water Science Center, Carson City, NV, USA * Delta-Flux network, Arkansas, Louisiana, MS, USA * United States Department of Agriculture Agricultural Research Service (USDS-ARS): * Sustainable Water Management Research Unit, Stoneville, MS, USA * US Salinity Laboratory, Agricultural Water Efficiency and Salinity Research Unit, Riverside, CA, USA * Conservation & Production Research Laboratory, Bushland, TX, USA * US Arid-Land Agricultural Research Center, Maricopa, AZ, USA * Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA Further contact information for each station as well as DOI's for original AmeriFlux data are included in the "station_metadata.xlsx" file. Code/Software All files that comprise this dataset were generated using the "flux-data-qaqc" open-source Python package version 0.1.6. The package is hosted on GitHub and PyPI, it also has online documentation including an in depth user tutorial