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NEOPRENE: Neyman-Scott Process Rainfall Emulator [version 0.0.16]

Abstract: The NEOPRENE library implements a rectangular pulses model for rainfall emulation based on the Neyman-Scott process. The emulator may be used to generate synthetic rainfall time series that reproduce observed statistics at different temporal aggregations. It has been designed with rainfall dissaggregation and extreme rainfall analysis in mind.

The description of the Neyman-Scott Process -or Space-time Neyman-Scott Rectangular Pulses Model- can be found in the doc folder. A paper describing the library has been sent for review to Environmental Modelling & Software. Other papers by the authors where -previous incarnations of- the NEOPRENE library has been used and the mathematical model has been described are: -Diez-Sierra, J.; del Jesus, M. Subdaily Rainfall Estimation through Daily Rainfall Downscaling Using Random Forests in Spain. Water 2019, 11, 125. https://doi.org/10.3390/w11010125 -del Jesus, M.; Rinaldo, A.; Rodriguez-Iturbe, I. Point rainfall statistics for ecohydrological analyses derived from satellite integrated rainfall measurements. Water Resources Research 2015, 51(4), 2974-2985. https://doi.org/10.1002/2015WR016935 Contents NSRP - Python code to calibrate the NSRPM (Neyman-Scott Rectangular Pulse Model) and simulate single-site synthetic rainfall series. STNSRP - Python code for calibrate the STNSRPM (Space-Time Neyman-Scott Rectangular Pulse Model) and simulate multi-site synthetic rainfall series. doc - Description of the model. notebooks - Jupyter notebooks with examples on how to calibrate, simulate and validate a Neyman-Scott model using the library. Examples on how to perform a daily-to-hourly rainfall disaggregation using the synthetic series are also included. (...)

Repositorio: Zenodo

 Año de publicación: 2021

 DOI: 10.5281/zenodo.5552146

 Citación completa: Diez-Sierra, J., Navas, S., & Del Jesus, M. (2021). NEOPRENE: Neyman-Scott Process Rainfall Emulator. [Dataset]. (Version 0.0.16). Zenodo. https://doi.org/10.5281/zenodo.5552146