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© 2025. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

The Bartlett–Lewis (BL) model is a stochastic framework for representing rainfall based upon Poisson cluster point process theory. This model has been used for over 30 years in the stochastic modelling of daily and hourly rainfall time series. Historically, the BL model was known to underestimate sub-daily rainfall extremes, but recent advancements have addressed this issue, making it a viable alternative to traditional rainfall frequency analysis methods, such as those based on annual maxima time series. Despite its potential, calibrating the BL model is a not a trivial task. The model's formulation is complex, and calibrating it involves a nonlinear optimisation process that can be numerically unstable, which has limited its broader application. To promote the use of the BL model and demonstrate its capabilities in modelling sub-hourly rainfall – both standard and extreme statistics – we have developed an open-source Python package called pyBL. This paper details the design of the BL model and summarises the key features of the pyBL package. It includes a brief explanation of how to use the package in selected user scenarios. In addition, we report on scientific experiments that resemble real-world situations to showcase pyBL's ability to model sub-hourly rainfall extremes with short records and its flexibility in utilising records of various timescales and lengths.

Details

Title
Modelling rainfall with a Bartlett–Lewis process: pyBL (v1.0.0), a Python software package and an application with short records
Author
Chi-Ling, Wei 1 ; Pei-Chun, Chen 1 ; Chien-Yu, Tseng 1 ; Ting-Yu, Dai 2 ; Yun-Ting, Ho 1 ; Ching-Chun Chou 1 ; Onof, Christian 3   VIAFID ORCID Logo  ; Li-Pen, Wang 4   VIAFID ORCID Logo 

 Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan 
 Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan; Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78705, USA 
 Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK 
 Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan; Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK 
Pages
1357-1373
Publication year
2025
Publication date
2025
Publisher
Copernicus GmbH
ISSN
1991962X
e-ISSN
19919603
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3173678678
Copyright
© 2025. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.