Fig 1.
Conceptual diagram illustrating various attributes extracted from the T-re curve:
Cloud base temperature (Tb), cloud base particle size (rb), depth of the diffusional zone (Dz), cloud height in terms of temperature exceeding the 14 µm precipitation threshold (T14), and mixed-phase initiation height (TL).
Fig 2.
Cloud droplet size distribution during normal-, heavy-, and extreme-rainfall events.
The heavy- and extreme-rainfall events exhibit dual peaks compared to normal rainfall events: the first peak is around 14 µm (D14), and the second is around 70 µm (D70).
Table 1.
Details of various data used in this study.
Fig 3.
Overall workflow of the development of the proposed nowcasting model.
Fig 4.
Rainfall characteristics over the study area.
(A) one-day maximum rainfall (2001 to 2018) based on the IMD gridded (0.25° x 0.25°) rainfall dataset for the Indian sub-continent, (B) temporal distribution* of normal-, heavy-, and extreme-rainfall events in terms of their frequencies of occurrence, and (C) frequency of EREs in the analyzed domain (enclosed by the black rectangle) during the period. *Only rainfall values exceeding 64.5 mm are plotted in (b).
Fig 5.
Variation of the T-re profiles between normal-, heavy-, and extreme-rainfall events.
Cloud RGB composite image during (A) normal-, (B) heavy-, and (C) extreme-rainfall events. The color composition includes red for visible reflectance, green for 3.9 µm solar infrared temperature, and blue for 10.8 µm brightness temperature. The cloud clusters analyzed are bounded by the white polygon. Vertical cloud microphysical structures of (D) normal-, (E) heavy-, and (F) extreme-rainfall events are shown. The 10th, 25th, 50th, 75th, and 90th percentiles of re are plotted. The vertical bars denote the vertical extent of the microphysical zones labeled as D - diffusion, C - collision-coalescence, R - warm rainout, M - mixed phase, and G - glaciation. The continuous red line is for visual representation only and does not carry any reference or implication related to the analysis or data presented.
Fig 6.
Modelling the occurrence of EREs.
(A) modeled probability for normal- and heavy/extreme-rainfall events during August 2018, and (B) the receiver operating characteristic curve for the logistic regression model.
Table 2.
95% confidence intervals for the parameters of the nowcasting model.
Table 3.
Metrics used to assess the accuracy of the nowcasting model.
Fig 7.
Nowcasting the heavy/extreme rainfall events of (A) 8 August 2018 and (B) 15 August 2018. The half-hourly gauge calibrated precipitation product from the IMERG was used to plot the temporal variation of rainfall intensity.
Fig 8.
Effect of moisture availability and aerosol loading on EREs.
(A) variability of moisture availability (in terms of TPWV) during normal-, heavy-, and extreme-rainfall events from 2001 to 2018, (B) daily mean values of TPWV, rainfall, and AOD during August 2018, and (C) mean rainfall profile for the different percentile classes of AOD and TPWV.
Table 4.
Independent and interaction effects of aerosols and moisture availability on rainfall over Kerala.