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Shailendra Kumar Shweta Srivastava

Abstract

An index-based approach is applied to investigate the climatology of precipitating cloud systems (PCSs) during different phases of evolution over twelve tropical oceanic areas using Precipitation Radar (PR) onboard at the satellite. In the present study, a Precipitating cloud system (PCS) is defined as the connecting pixels having radar reflectivity (Ze) ≥ 17 dBZ using composite Ze field. The three-dimensional structure of PCS is observed using all the PR beams contributing to horizontal PCS pixels. An average vertical profile is drawn and then converted it into the liquid water content using the relation M=3.44 x Z(4/7) x10(-6) (where M is in gm-3 and Z is in mm6 m-3). A dimensionless ratio, namely, the ratio for maturity levels (RMLs) is defined by dividing the normalized cloud liquid water at 4 km to 2 km for each PCSs. These RMLs values are used to classify the PCSs into different phases of development. Further the PCSs are also divided with (RML<0.75) and without bright band (BB, RML≥ 0.75), which indicates the latter phase of cloud evolution. The results reveal that initial stage PCSs have higher Ze at higher vertical level, and once the bright band is observed, Ze decreases rapidly above the BB. Regional differences have similar trends in Ze profiles during different RMLs. Similar average vertical profiles over different tropical areas lead to that understanding the microphysics of PCSs in one area could use in other areas too. The convective precipitation area dominates during the initial stage and decreases as the PCSs mature. This is the first time the TRMM data is used to investigate the evolution of PCSs using the indexing approach.

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Keywords

Bright band, Convective precipitation, Life-cycle of MCS, Stratiform precipitation TRMM PR, Vertical profile of reflectivity

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Section
Research Articles

How to Cite

A Vertical characteristics of precipitating cloud systems during different phases of life cycle of cloud systems using satellite-based radar over tropical oceanic areas. (2022). Journal of Applied and Natural Science, 14(4), 1272-1285. https://doi.org/10.31018/jans.v14i4.3691