NEOPRENE: Neyman-Scott Process Rainfall EmulatorThe 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 Spatio-temporal 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/w11010125del 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/10.1002/2015WR016935ContentsDirectoryContentsNSRPPython code to calibrate the NSRPM (Neyman-Scott Rectangular Pulse Model) and simulate synthetic rainfall series.STNSRPPython code for calibrate the STNSRPM (Spatio-Temporal Neyman-Scott Rectangular Pulse Model) and simulate multisite rainfall series (in progress).docDescription of the model.notebooksJupyter 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 is also included.RequirementsScripts and (jupyter) notebooks are provided in Python to ensure reproducibility and reusability of the results. The simplest way to match all these requirements is by using a dedicated conda environment, which can be easily installed by issuing:conda create -n NEOPRENE pip jupyterconda activate NEOPRENEpip install NEOPRENEExamples of useExamples of use of the NEOPRENE library are available in the form of jupyter notebooks. To run the examples follow the following steps:Download the folder notebooks from the github repository, or navigate to the folder should you have cloned the repo.Open jupyter notebook of Jupyter Lab (type jupyter notebook or jupyter lab in the terminal)Open one of the tests available in the notebooks folder with jupyter notebook (e.g. NSRP_test.ipynb)Errata and problem reportingTo report an issue with the library, please fill a GitHub issue.ContributorsThe original version of the library was developed by:Javier Díez-SierraSalvador NavasManuel del JesusLicenseCopyright 2021 Instituto de Hidráulica Ambiental "IHCantabria". Universidad de Cantabria.Licensed under the Apache License, Version 2.0 (the "License"); you may not use this library except in compliance with the License. You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.