Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1153-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1153-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
12 Feb 2024
Development and technical paper |
| 12 Feb 2024
| 12 Feb 2024
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, Colorado, USA
Andrew W. Wood
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, Colorado, USA
Civil and Environmental Engineering, Colorado School of Mines, Golden, Colorado, USA
Andrew J. Newman
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Martyn P. Clark
Department of Civil Engineering, University of Calgary, Calgary, Alberta, Canada
Simon Michael Papalexiou
Department of Civil Engineering, University of Calgary, Calgary, Alberta, Canada
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Guoqiang Tang, Martyn P. Clark, Andrew J. Newman, Andrew W. Wood, Simon Michael Papalexiou, Vincent Vionnet, and Paul H. Whitfield
Earth Syst. Sci. Data, 12, 2381–2409, https://doi.org/10.5194/essd-12-2381-2020, https://doi.org/10.5194/essd-12-2381-2020, 2020
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Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting...
