Observational evidence of impact of heavy rainfall events on surface energetics and soil variables over a tropical station Tirupati

Two back-to-back heavy rainfall events (HREs) produced enormous rainfall over a pilgrim city, Tirupati, located in the southern peninsular India, during 10–12 November 2021 (149.2 mm) and 17–19 November 2021 (234.2 mm). Surface measurements at Yerpedu, Tirupati (13.74°, 79.60°E) showed a drop of 2–3 °C in temperature and 8 hPa in pressure during HREs, indicating that these HREs were associated with two landfalling tropical depressions from the Bay of Bengal. The sporadic HREs in the past three decades caused floods over Tirupati and devastated landslides in the sacred Tirumala hills especially during the second HRE. Fundamental understanding of diurnal cycle of surface radiation is critical to model the climate. The effect of HREs on the surface essential climate variables at diurnal scale indicate a reduction in peak solar and net radiations by 500 W m−2 (> 62.5 %). Similar to observations, ERA5 reanalysis also indicates a significant reduction in net surface solar and thermal radiations, which are nearly equal in terms of % but vary in magnitude. Net solar and thermal radiations show dominant diurnal cycles with a reduced (66.7 % and 74.4 % respectively) diurnal amplitudes from no-rain to HREs. Soil moisture drydown curves at 5- and 10-cm depths shows 3 h long e-folding decay time for HREs, indicating an enhanced soil moisture memory after HREs. The soil drying process takes longer time at 10 cm than at 5 cm depth. Soil temperatures are significantly low at 5 cm to 30 cm depths and less than the 50 cm depth with weak diurnal variation during the events. The reflectivity (Z)-rain rate (R) and shape (μ)-slope (Λ) relations show variations from HREs to normal rain events. Knowing the importance of land-atmospheric processes feedbacks in model predictions at diurnal scale, this study quantified the HREs impact on surface essential climate variables, especially the energy balance and soil variables.