Virtual Rain v1.0: a unified toolkit for high-resolution rainfall simulation and disaggregation
- 1Università degli Studi della Tuscia (Viterbo, Italy)
Abstract
Stochastic simulation models are essential for investigating hydrological processes and supporting water resource management. In this study, we introduce Virtual Rain, a software toolkit that first generates synthetic daily rainfall time series and then disaggregates them to a user-defined temporal resolution. The toolkit implements and integrates the approaches recently proposed by some of the authors, ensuring a realistic representation of rainfall dynamics while preserving key statistical properties. The framework is implemented through a set of Python and R routines designed to facilitate practical application. In addition to providing observed rainfall time series and the scaling exponent n (Intensity–Duration–Frequency slope), users can configure key modelling components, including the marginal distribution, autocorrelation structure, number of lags, and target temporal resolution. The routines generate both graphical and quantitative outputs, enabling direct comparison between observed and simulated series. Rather than introducing new stochastic rainfall methodologies, Virtual Rain provides the first publicly available implementation of an integrated workflow combining the CoSMoS-2s daily rainfall generator and the MRC rainfall disaggregation model within a unified software environment. Virtual Rain is demonstrated through a real-world case study, illustrating the functionality and usability of the implemented workflow. The toolkit is also available through an interactive web-based platform, facilitating its use by a broad range of users.
Versions
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BibTeX
@article{cappelli2026virtual,
title = {{Virtual Rain v1.0: a unified toolkit for high-resolution rainfall simulation and disaggregation}},
author = {Francesco Cappelli and Salvatore Grimaldi and Andrea Petroselli and Emanuele Santinami},
journal = {Geoscientific Model Development},
year = {2026},
month = oct,
doi = {10.5194/gmd-19-9489-2026},
url = {https://gmd.copernicus.org/articles/19/9489/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Virtual Rain v1.0: a unified toolkit for high-resolution rainfall simulation and disaggregation
AU - Francesco Cappelli
AU - Salvatore Grimaldi
AU - Andrea Petroselli
AU - Emanuele Santinami
PY - 2026
DA - 2026/10/07
JO - Geoscientific Model Development
DO - 10.5194/gmd-19-9489-2026
UR - https://gmd.copernicus.org/articles/19/9489/2026/
AB - Stochastic simulation models are essential for investigating hydrological processes and supporting water resource management. In this study, we introduce Virtual Rain, a software toolkit that first generates synthetic daily rainfall time series and then disaggregates them to a user-defined temporal resolution. The toolkit implements and integrates the approaches recently proposed by some of the authors, ensuring a realistic representation of rainfall dynamics while preserving key statistical properties. The framework is implemented through a set of Python and R routines designed to facilitate practical application. In addition to providing observed rainfall time series and the scaling exponent n (Intensity–Duration–Frequency slope), users can configure key modelling components, including the marginal distribution, autocorrelation structure, number of lags, and target temporal resolution. The routines generate both graphical and quantitative outputs, enabling direct comparison between observed and simulated series. Rather than introducing new stochastic rainfall methodologies, Virtual Rain provides the first publicly available implementation of an integrated workflow combining the CoSMoS-2s daily rainfall generator and the MRC rainfall disaggregation model within a unified software environment. Virtual Rain is demonstrated through a real-world case study, illustrating the functionality and usability of the implemented workflow. The toolkit is also available through an interactive web-based platform, facilitating its use by a broad range of users.
SN - 1991-9603
ER -