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Priestley-Taylor Jet Propulsion Laboratory Soil Moisutre Evapotranspiration Model

Project description

ECOSTRESS Collection 2 Calibration/Validation Data Tables (Python Package)

This Python package provides calibration and validation data tables used in the evaluation of the ECOSTRESS Collection 2 Evapotranspiration (ET) data products. The included datasets and loader functions support reproducible research and validation workflows for ET modeling and remote sensing studies.

Authors

Zoe Pierrat (she/her)
zoe.a.pierrat@jpl.nasa.gov
NASA Jet Propulsion Laboratory 329G

Gregory H. Halverson (they/them)
gregory.h.halverson@jpl.nasa.gov
NASA Jet Propulsion Laboratory 329G

Installation

Install the package directly from PyPI using pip. Note that the package name uses dashes (-) for installation:

pip install ECOv002-calval-tables

Usage

Import the loader functions to access the data tables as pandas DataFrames. Note that the importable package name uses underscores (_):

from ECOv002_calval_tables import load_combined_eco_flux_ec_filtered, load_metadata_ebc_filt

df_flux = load_combined_eco_flux_ec_filtered()
df_metadata = load_metadata_ebc_filt()

Data Tables

  • combined_eco_flux_EC_filtered: Filtered eddy covariance flux data for ECOSTRESS validation.
  • metadata_ebc_filt: Metadata for the filtered flux sites.

Citation

If you use these data tables or code in your research, please cite:

Pierrat, Zoe A.; Purdy, Adam J.; Halverson, Gregory H.; Fisher, Joshua B.; et al. (2024). Evaluation of ECOSTRESS Collection 2 Evapotranspiration Products: Strengths and Uncertainties for Evapotranspiration Modeling. Water Resources Research. https://doi.org/10.1029/2024WR039404

BibTeX:

@article{Pierrat2024,
  author       = {Pierrat, Zoe A. and Purdy, Adam J. and Halverson, Gregory H. and Fisher, Joshua B. and et al.},
  title        = {Evaluation of ECOSTRESS Collection 2 Evapotranspiration Products: Strengths and Uncertainties for Evapotranspiration Modeling},
  journal      = {Water Resources Research},
  year         = {2024},
  doi          = {10.1029/2024WR039404}
}

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