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ERI and DPT-EC datasets
ERI dataset is location data (xyz) and resistivity data in excel format. DPT-EC dataset is depth, resistivity, and rate of penetration in excel format. This dataset is associated with the following publication: Fields, J., T. Tandy, T. Halihan, R. Ross, D. Beak, R. Neill, and J. Groves. Electrical Resistivity Imaging of an Enhanced Aquifer Recharge Site. Journal of Geophysics and Engineering. Oxford University Press, OXFORD, UK, 19(5): 1095-1110, (2022).
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ERI and DPT-EC datasets
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ERI dataset is location data (xyz) and resistivity data in excel format. DPT-EC dataset is depth, resistivity, and rate of penetration in excel format. This dataset is associated with the following publication: Fields, J., T. Tandy, T. Halihan, R. Ross, D. Beak, R. Neill, and J. Groves. Electrical Resistivity Imaging of an Enhanced Aquifer Recharge Site. Journal of Geophysics and Engineering. Oxford University Press, OXFORD, UK, 19(5): 1095-1110, (2022).
EPA Dynamically Downscaled Ensemble (EDDE), Version 1
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The EPA Dynamically Downscaled Ensemble (EDDE) datasets were prepared by EPA/ORD staff and by contract staff who worked under the technical guidance of EPA/ORD staff. The dataset here represents a subset of data that were dynamically downscaled by EPA from the fifth Coupled Model Intercomparison Project (CMIP5) using the Weather Research and Forecasting (WRF) model using the EPA High-End Scientific Computing platforms. Scenarios were downscaled from the Community Earth System Model (CESM) and the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model version 3 (CM3). Simulations followed the historical periods 1975-2005 (CESM only) and 1995-2005 (both CESM and CM3), and Representative Concentration Pathways (RCP) 4.5 for 2025-2100 (CESM only), RCP6.0 for 2025-2055 (CESM only), and RCP8.5 for 2025-2100 (both CESM and CM3). The original downscaling was conducted during 2013-2018. Subsets of the original dataset were prepared using postprocessing software developed by EPA/ORD staff. This dataset is not publicly accessible because: Dataset is too large to be hosted in ScienceHub. It is ~5 terabytes. It can be accessed through the following means: Ideally, this dataset will be publicly accessible from the Cloud. Negotiations are underway to support that hosting venue. Format: Data are in Network Common Data Form (netCDF; https://unidata.ucar.edu/software/netcdf) version 4, which is commonly used and consumed by practitioners in the atmospheric modeling community. The EDDE data in netCDF are further written to adhere to principles of Climate and Forecasting System (CF) Compliance, as outlined at https://cfconventions.org. The files to be hosted are self-describing with metadata included in the netCDF header.
Simplified Surface Energy Balance Actual Evapotranspiration data for the Conterminous U.S.
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Actual ET (ETa) is produced using the operational Simplified Surface Energy Balance (SSEBop) model (Senay and others, 2013) for the period 2000 to present. The SSEBop setup is based on the Simplified Surface Energy Balance (SSEB) approach (Senay and others, 2007, 2011) with unique parameterization for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, acquired every 8 days, with reference ET using a thermal index approach. The unique feature of the SSEBop parameterization is that it uses pre-defined, seasonally dynamic, boundary conditions that are unique to each pixel for the hot/dry and cold/wet reference points. Reference: Senay, G. B., Bohms, S., Singh, R. K., Gowda, P. H., Velpuri, N. M., Alemu, H., et al. (2013). Operational evapotranspirationmapping using remote sensing andweather datasets: A new parameterization for the SSEB approach. Journal of the American Water Resources Association, 1-2013;15, http://dx.doi.org/10.1111/jawr.12057. Reference: Velpuri, N. M., Senay, G. B., Singh, R. K., Bohms, S., and Verdin, J. P.: A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: Using point and gridded FLUXNET and water balance ET, Remote Sensing of Environment, 139, 35-49, http://dx.doi.org/10.1016/j.rse.2013.07.013, 2013.