Ramifications of Atmospheric Humidity on Monsoon Depressions over the Indian Subcontinent

Abstract

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.

Using Megha‐Tropiques satellite data to constrain humidity in regional convective simulations: A northern Australian test case

“…Here, simulations were run for only 48 hr, hence there is a strong dependence on initial conditions, so we attempt to remove the bias by perturbing the initial conditions in all domains. This approach has been used in several studies in the past (Keil et al ., 2008; Blazquez et al ., 2013; Li and Pu, 2014; Baisya et al ., 2018; Dipankar et al ., 2019), mostly with the same perturbations applied at all model levels. This approach can compensate for the moisture bias at all levels in the model while preserving spatial variability.…”

Orographic effect and multiscale interactions during an extreme rainfall event

“…Krishnamurti et al (2017b) described it as streams of buoyant elements marching through a moist boundary layer towards the extreme orographic region, while Rajesh et al (2016) held potential vorticity shedding from both upper air westerlies and northerly moving monsoon depression that merged over Uttarakhand responsible for the catastrophic event. Baisya et al (2018) have also found the role of enhanced low-mid tropospheric moisture in facilitating the rainfall intensity of monsoon depressions over the Indian region in surrogate climate change experiments. The extreme precipitation event causing flood over the Indus valley of Pakistan in late July, 2010, exemplified yet another multiscale interaction between the Russian heat wave, convective outflow associated with the active phase of the Madden-Julian Oscillation (MJO), and a low level barrier jet in conjunction with a monsoon depression (Houze et al 2011, Galarneau et al 2012.…”

Role of cloud microphysics and energetics in regulating different phases of the monsoon low‐pressure systems over the Indian region

“…The Weather Research and Forecasting (WRF) model is one of the next‐generation (computationally efficient) mesoscale numerical weather prediction (NWP) models, which has a large number of registered users worldwide {collaboration between the National Center for Atmospheric Research (NCAR), the National Centers for Environmental Prediction (NCEP), and the Earth System Research Laboratory (ESRL)}. Different studies have used WRF to simulate tropical cyclones and MD over the Indian region (Baisya et al ., 2018; Hazra et al ., 2020; Chakraborty et al ., 2021). The cloud microphysics is one of the significant parameterization schemes (among others such as radiation, planetary boundary layer, land surface, soil moisture, etc.)…”