Estimating Coalescence Time in Disdrometer Drop Size Distributions: A PYSDM Cloud Modeling Approach

Authors

  • N. H. Shah Department of Mathematics and School of Emerging Science & Technology, Gujarat University, Ahmedabad-380009, India
  • J. Chahal Department of Mathematics, Gujarat University, Ahmedabad-380009, India
  • B. P. Shukla Environment Sciences Division, Space Applications Centre, ISRO, Ahmedabad-380015 Gujarat, India
  • A. Priamvada Department of Mathematics, Gujarat University, Ahmedabad-380009, India

DOI:

https://doi.org/10.3329/jsr.v17i1.74290

Abstract

Cloud droplet evolution is influenced by microphysical processes such as nucleation, condensation, evaporation, and coalescence, all of which impact precipitation. Models simulating droplet growth help improve rainfall predictions by providing insight into these processes. In this study, we investigate the coalescence time of droplets, using ground truth data from Disdrometer Observations with a size range of 156.5 to 2800.25 µm, applying the Python Super Droplet Model (PySDM) to simulate the evolution of droplet size over time. Focusing on the coalescence process, we analyzed the time-dependent progression of droplet formation. Our results revealed a relationship between coalescence time (CT) and drop size distribution (DSD). Larger droplets were found to coalesce rapidly upon impact, quickly reaching a precipitation-ready state, while smaller droplets experienced more frequent bouncing, requiring more time for coalescence. The mean coalescence time was estimated to be approximately 12,550 sec.

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Published

2025-01-01

How to Cite

Shah, N. H., Chahal, J., Shukla, B. P., & Priamvada, A. (2025). Estimating Coalescence Time in Disdrometer Drop Size Distributions: A PYSDM Cloud Modeling Approach. Journal of Scientific Research, 17(1), 133–140. https://doi.org/10.3329/jsr.v17i1.74290

Issue

Vol. 17 No. 1 (2025)

Section

Section A: Physical and Mathematical Sciences

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

© Journal of Scientific Research

Creative Commons License

Articles published in the "Journal of Scientific Research" are Open Access articles under a Creative Commons Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0). This license permits use, distribution and reproduction in any medium, provided the original work is properly cited and initial publication in this journal. In addition to that, users must provide a link to the license, indicate if changes are made and distribute using the same license as original if the original content has been remixed, transformed or built upon.