A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface‐precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Interaction of multiple oscillations of different time scales may result in severe weather events. The presence of orography can modulate the intensity of these events even further. Kerala witnessed one such heavy rainfall event in August, 2018, claiming 483 lives and damages worth INR 200 billion. This study focuses on the peak rainfall duration (13–17 August) when the departure from normal was 42%. Segregating moisture transport into its mean and perturbation terms show that an anomalous moisture channel over the Arabian Sea supplied continuous moisture to the Western Ghats (WG), whereas anomalous wind due to a monsoon depression advected moisture towards the southern peninsula. It is evident in the form of Moisture Flux Convergence (MFC) towers traversing along the Eastern Ghats before merging with the semi-permanent MFC feature over the WG. The presence of positive quasi bi-weekly oscillations and of Intra Seasonal Oscillations (ISO) aggravated the event as they complemented the anomalous moisture transport, with ISO constantly providing winds of the order of 2–3 ms⁻¹. In addition, shedding of MFC towers by the depression is accredited to the synoptic scale oscillation.

In this study, a comprehensive investigation is carried out to examine the sensitivity of tropospheric relative humidity (RH) on monsoon depressions (MDs) under a changing climate regime through surrogate climate change approach over the Indian region. Composite analysis of four MDs show a persistent warming (RH2+) and cooling (RH2−) throughout the troposphere in the sensitivity experiments. In-depth analysis of a MD over the Arabian Sea (AS) exhibits sustained warming for RH2+, which is accredited to 2.6% increase in stratiform clouds accounting for 13% increment in heating, whereas 5% increment in convective clouds hardly contribute to total heating. Frozen hydrometeors (graupel and snow) are speculated to be the major contributors to this heating. Stratiform clouds showed greater sensitivity to RH perturbations in the lower troposphere (1000–750 hPa), albeit very less sensitivity for convective clouds, both in the lower and mid-troposphere (700–500 hPa). Precipitation is enhanced in a moist situation (RH2+) owing to positive feedbacks induced by moisture influx and precipitation efficiency, while negative feedbacks suppressed precipitation in a dry troposphere (RH2−). In a nutshell, it is inferred that under moist (dry) situations, it is highly likely that intense (weak) MDs will occur in the near future over the Indian region.

The present study is aimed to investigate sub-surface ocean processes and their contribution to the intensification of a tropical cyclone (TC) from a coupled-modeling perspective. The Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model was employed to simulate TC Phailin, which originated over the Bay of Bengal and made landfall on the eastern coast of India in October 2013. Three sub-surface ocean condition datasets—viz., (a) the European Centre for Medium-Range Weather Forecast (ECMWF) Ocean Reanalysis, (b) the Climate Forecast System Version 2 (CFSV2) Operational Analysis, and (c) the Hybrid Coordinate Ocean Model (HYCOM) Reanalysis datasets—were used for the initial and boundary conditions for the oceanic component of the coupled model in three different simulations of TC Phailin. All the simulations showed a delay in intensification compared to the observation, and ECMWF simulated the most intensified TC. CFSV2 simulated a deeper mixed layer (ML) and higher mixing, which hindered the intensification. Furthermore, higher entrainment of cold water in the ML led to cold water reaching the surface and, consequently, decreased sea surface temperature, which acted as negative feedback in the intensification of the storm in the cases of CFSV2 and HYCOM. ECMWF realistically simulated the interactions of the TC with a cold-core eddy before landfall. A sudden increase in ML heat content, the addition of heat in the ML due to entrainment, and the prevention of cold water reaching the surface were indicative of the breaking of the barrier layer (BL) in ECMWF, which was further corroborated by the spatial distribution of BL thickness in the simulation. This acted as positive feedback in the intensification of the TC. The findings of this study strongly suggest that not only the incorporation of physical oceanic sub-surface processes in the modeling of TCs but also the proper representation of prevailing mesoscale features and ocean sub-surface temperature, salinity, and current profiles in datasets is essential for realistic simulations of TCs.