Disdrometer, Drop Size Distribution, Rainfall Rate, Correlation Coefficients


Rainfall prediction is crucial for various aspects of human life, environmental sustainability, and agriculture. Understanding rainfall intensity and its dependence on factors such as drop size distribution (DSD) is essential. This study investigates the relationship between drop size distribution and rainfall rate at Shillong station, Meghalaya, India, utilizing RD-80 disdrometer data for the year 2005. DSD plays a pivotal role in quantitative precipitation estimation, impacting rainfall properties like water content, intensity, and kinetic energy. Moreover, it is integral to satellite communication, aiding in the prediction of wave attenuation. We analyze the data to ascertain the correlation between rainfall rate and DSD, with an assumption of an exponential form for DSD. The analysis categorizes the daytime into four segments: Morning (6:00 AM-12:00 PM), Afternoon (12:00 PM-6:00 PM), Evening (6:00 PM-12:00 AM), and Night (12:00 AM-6:00 AM) to observe rain's diurnal variations. Notably, variations in correlation coefficients suggest differing rainfall patterns and intensity levels throughout the day and across months. These insights contribute to a deeper understanding of rainfall dynamics in the region, which is critical for effective water resource management and disaster preparedness.


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ARM, Atmospheric Radiation Measurement Climate Research Facility, (2016, March).

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How to Cite

Shah, N. H., Chahal, J., & Paul Shukla, B. (2024). EXPLORING DIURNAL PATTERNS: DROP SIZE AND RAINFALL RATE DYNAMICS AT SHILLONG STATION. International Journal of Engineering Science Technologies, 8(2), 1–11. https://doi.org/10.29121/ijoest.v8.i2.2024.583