Analysis of raindrop size distribution from the double moment cloud microphysics scheme for monsoon over a tropical station

Abstract. Accurate precipitation forecasting hinges on the representation of microphysical processes within numerical models. A key approach to understanding these processes is through the analysis of hydrometeor drop size distribution (DSD). The characteristics of DSD bulk parameters – Mass Weighted Mean Diameter (Dm) and the Normalized Intercept Parameter (Nw), are estimated from the double moment cloud microphysical scheme (CASIM: Cloud-Aerosol Interacting Microphysics) employed in the operational convection permitted model of National Centre for Medium-Range Weather Forecasting (NCUM-R). The observations from the Joss-Valdvogel Disdrometer (JWD) and the Global Precipitation Mission – Dual Frequency Precipitation Radar (GPM-DPR) are analyzed for providing essential validation. An algorithm for separating the monsoon precipitation into convective and stratiform types in NCUM-R and a new parameter estimation module to obtain DSD parameters from the CASIM are established in the study. The model exhibits agreement with the characteristics of the DSD of raindrops with Dm ranging from 0.5 to 2.5 mm marking the majority of the monsoon precipitation events. However, the underestimation when it comes to the larger drops (with Dm > 3.25 mm and Rainrate ≥ 8 mm h−1) demands a reassessment in microphysical parameterizations. The advanced autoconversion parameterization scheme applied in CASIM favored the growth of large drops compared to the existing scheme. The enhanced growth of larger drops is reflected in the increased accuracy in the prediction of extreme precipitation associated with a convective event. The current study underscores the importance of refining microphysical parameterizations to improve the accuracy of precipitation forecasts offering a pathway for enhanced model performance in future operational forecasting systems.

Authors

Institutions

Publication Details

Journal
Atmospheric chemistry and physics
Published
2025-09-26
DOI
https://doi.org/10.5194/acp-25-11423-2025
Citations
1
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
1.30
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of raindrop size distribution from the double moment cloud microphysics scheme for monsoon over a tropical station

Saji Mohandas, V. S. Prasad, Thara Prabhakaran, A. Jayakumar et al.
1 citations
Atmospheric chemistry and physics
Precipitation Measurement and Analysis
1.30
article

Analysis of raindrop size distribution from the double moment cloud microphysics scheme for monsoon over a tropical station

Saji Mohandas, V. S. Prasad, Thara Prabhakaran, A. Jayakumar, T. J. Anurose, Mahen Konwar, Paul R. Field, Kadavathu Sreekumar Apsara
article en
1 citations

Abstract

Abstract. Accurate precipitation forecasting hinges on the representation of microphysical processes within numerical models. A key approach to understanding these processes is through the analysis of hydrometeor drop size distribution (DSD). The characteristics of DSD bulk parameters – Mass Weighted Mean Diameter (Dm) and the Normalized Intercept Parameter (Nw), are estimated from the double moment cloud microphysical scheme (CASIM: Cloud-Aerosol Interacting Microphysics) employed in the operational convection permitted model of National Centre for Medium-Range Weather Forecasting (NCUM-R). The observations from the Joss-Valdvogel Disdrometer (JWD) and the Global Precipitation Mission – Dual Frequency Precipitation Radar (GPM-DPR) are analyzed for providing essential validation. An algorithm for separating the monsoon precipitation into convective and stratiform types in NCUM-R and a new parameter estimation module to obtain DSD parameters from the CASIM are established in the study. The model exhibits agreement with the characteristics of the DSD of raindrops with Dm ranging from 0.5 to 2.5 mm marking the majority of the monsoon precipitation events. However, the underestimation when it comes to the larger drops (with Dm > 3.25 mm and Rainrate ≥ 8 mm h−1) demands a reassessment in microphysical parameterizations. The advanced autoconversion parameterization scheme applied in CASIM favored the growth of large drops compared to the existing scheme. The enhanced growth of larger drops is reflected in the increased accuracy in the prediction of extreme precipitation associated with a convective event. The current study underscores the importance of refining microphysical parameterizations to improve the accuracy of precipitation forecasts offering a pathway for enhanced model performance in future operational forecasting systems.

Atmospheric chemistry and physicsVol. 25(18)
Met Office (GB), National Centre for Medium Range Weather Forecasting (IN), Indian Institute of Tropical Meteorology (IN), Indian Institute of Science Education and Research, Tirupati (IN)
Openalex Percentile: Top 18%
Precipitation Measurement and Analysis
1.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.