Articles | Volume 29, issue 1
https://doi.org/10.5194/hess-29-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modelling convective cell life cycles with a copula-based approach
Chien-Yu Tseng
Department of Civil Engineering, National Taiwan University, Taipei, 106319, Taiwan
Department of Civil Engineering, National Taiwan University, Taipei, 106319, Taiwan
Imperial College London, London, SW7 2AZ, United Kingdom
Christian Onof
Imperial College London, London, SW7 2AZ, United Kingdom
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Hung-Ming Lin, Li-Pen Wang, and Jen-Yu Han
EGUsphere, https://doi.org/10.5194/egusphere-2025-4590, https://doi.org/10.5194/egusphere-2025-4590, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed a framework to improve short-term rainfall forecasts by combining radar data with rain gauge observations. This approach reduces errors and uncertainty, giving more reliable predictions of when and where rain will fall. Such improvements are valuable for flood warnings, stormwater management, and other decisions that depend on timely and accurate rainfall information.
Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang
Geosci. Model Dev., 18, 1357–1373, https://doi.org/10.5194/gmd-18-1357-2025, https://doi.org/10.5194/gmd-18-1357-2025, 2025
Short summary
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.
Abrar Habib, Athanasios Paschalis, Adrian P. Butler, Christian Onof, John P. Bloomfield, and James P. R. Sorensen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-27, https://doi.org/10.5194/hess-2023-27, 2023
Preprint withdrawn
Short summary
Short summary
Components of the hydrological cycle exhibit a “memory” in their behaviour which quantifies how long a variable would stay at high/low values. Being able to model and understand what affects it is vital for an accurate representation of the hydrological elements. In the current work, it is found that rainfall affects the fractal behaviour of groundwater levels, which implies that changes to rainfall due to climate change will change the periods of flood and drought in groundwater-fed catchments.
Y. K. Chen, Y. T. Lin, H. Y. Yen, N. H. Chang, H. M. Lin, K. H. Yang, C. S. Chen, L. P. Wang, H. K. Cheng, H. H. Wu, and J. Y. Han
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1091–1096, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1091-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1091-2022, 2022
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Short summary
This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
This study presents a new algorithm to model convective storms. We used advanced tracking...