Measurement of Flare Size Distribution and Simulation of Seeding Effect with a Spectral Bin Parcel Model

Mahen Konwar*, Neelam Malap, Anupam Hazra, Duncan Axisa, Thara Prabhakaran, Alexander Khain

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Cloud seeding experiments were conducted during the Cloud Interaction and Precipitation Enhancement Experiment (CAIPEEX) near Hyderabad, India, in 2011. Here, we report both the background aerosol and hygroscopic flare size distributions measured during the airborne experiment. The size distributions were measured in the diameter (D) range of 0.02–50 µm; both ultra-fine (0.02 µm < D < 0.1 µm) and coarse mode (D > 0.5 µm) particles were in greater concentrations in flare than in the background aerosols. The sensitivity of cloud droplet growth to the flare particle size distribution is studied with the help of a 2000-spectral bin parcel model, where droplet growth, collisions, and formation of raindrops are represented. The simulation results indicate the rapid formation of warm rain in cloud due to the tail effect of activation of coarse mode aerosols into large size cloud droplets. At higher altitudes, in-cloud activation and a secondary mode in drop size distribution are noted. For a given cloud base updraft, the rain flux increases with the increase in the coarse mode aerosol concentrations. However, for a given coarse mode aerosol concentration, the rain flux decreases with increasing cloud base updrafts.

Original languageEnglish
Pages (from-to)3019-3034
Number of pages16
JournalPure and Applied Geophysics
Volume180
Issue number8
DOIs
StatePublished - Aug 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Keywords

  • CAIPEEX
  • Cloud seeding
  • Hygroscopic flare
  • Spectral-bin parcel model

Fingerprint

Dive into the research topics of 'Measurement of Flare Size Distribution and Simulation of Seeding Effect with a Spectral Bin Parcel Model'. Together they form a unique fingerprint.

Cite this