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https://doi.org/10.5194/egusphere-2024-1918
https://doi.org/10.5194/egusphere-2024-1918
22 Jul 2024
 | 22 Jul 2024

Modelling rainfall with a Bartlett-Lewis process: pyBL (v1.0.0), a Python software package and an application with short records

Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang

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 modeling 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 upon 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.

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Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1918', Nadav Peleg, 03 Aug 2024
    • AC1: 'Reply on RC1', Li-Pen Wang, 07 Sep 2024
  • RC2: 'Comment on egusphere-2024-1918', Anonymous Referee #2, 12 Aug 2024
    • AC2: 'Reply on RC2', Li-Pen Wang, 07 Sep 2024
Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang
Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang

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Short summary
pyBL is an open-source package for generating realistic rainfall time series based on the Bartlett-Lewis (BL) model. It can preserve not only standard but also extreme rainfall statistics across various timescales. Notably, compared to traditional frequency analysis methods, the BL model requires only half the record length (or even shorter) to achieve similar consistency in estimating sub-hourly rainfall extremes. This makes it a valuable tool for modelling rainfall extremes with short records.