Turbulence-induced droplet grouping and augmented rain formation in cumulus clouds.

This paper provides the first observational analysis of how droplet separation is impacted by the flinging action of microscale vortices in turbulent clouds over a select radii range and how they vary over cloud cores and along the peripheral edges. It is premised that this mechanism initiates droplet separation within a cloud volume soon after condensational growth, largely in the cloud core, and operates until the cloud droplet radii exceed 20-30 µm when this effect fades rapidly. New observations are presented showing how microscale vortices also impact the settling rates of droplets over a critical size range (6-18 µm) causing them to sediment faster than in still air affecting swept volumes and thereby impacting the rain initiation and formation. Large-scale atmospheric models ignore these microscale effects linked to rapid droplet growth during the early stages of cloud conversion. Previous studies on droplet spatial organization along the cloud edges and inside the deep core have shown that homogeneous Poisson statistics, indicative of the presence of a vigorous in-cloud mixing process at small scales obtained, in contrast to an inhomogeneous distribution along the edges. In this paper, it is established that this marked core region, homogeneity can be linked to microscale vortical activity which flings cloud droplets in the range of 6-18 µm outward. The typical radius of the droplet trajectories or the droplet flung radii around the vortices correlates with the interparticle distance strongly. The correlation starts to diminish as one proceeds from the central core to the cloud fringes because of the added entrainment of cloud-free air. These first results imply that droplet growth in the core is first augmented with this small-scale interaction prior to other more large-scale processes involving entrainment mixing. This first study, combining these amplified velocities are included in a Weather Research and Forecasting- LES case study. Not only are significant differences observed in the cloud morphology when compared to a baseline case, but the 'enhanced' case also shows early commencement of rainfall along with intense precipitation activity compared to the 'standard' baseline case. It is also shown that the modelled equilibrium raindrop spectrum agrees better with observations when the enhanced droplet sedimentation rates mediated by microscale vortices are included in the calculations compared to the case where only still-air terminal velocities are used.

Generalized Scaling and Model for Friction in Wall Turbulence.

We present a novel generalized scaling framework and predictive model for wall friction in turbulent flows. The scaling is derived from the dynamical equations, and total mean-flow kinetic energy and the velocity profile shape factor are used as surrogates for dynamical and boundary condition effects. Veracity of the present approach is assessed using data from the literature spanning unprecedented ranges of flow types, Reynolds numbers, accelerations, and history effects. Unlike previous models that solely apply to standard flows, the present framework reconciles nonstandard flows with standard flows and enables accurate estimates of wall friction in numerical simulations and experiments without resolving the viscous sublayer or using the law of the wall.

Characteristics of elevated aerosol layer over the Indian east coast, Kattankulathur (12.82oN, 80.04°E): A northeast monsoon region.

The elevated aerosol layer (EAL) plays a vital role in weather and climate by modifying the Earth's radiation budget. In the present study, the EAL occurrence and its characteristics in the pre-monsoon season using micropulse lidar (MPL) observations during 2016-2018 and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during 2007-2018 over Kattankulathur is being reported. We have collected 147 days (101 cases) of MPL (CALIPSO) observations during clear sky conditions in the pre-monsoon 2016-2018 (2007-2018), out of which EAL is observed for 56 days (61 cases). The EAL width is generally found to be ~2.0 km and occurs between ~1.0 km and 5.0 km. Three different types of EALs are categorized based on their altitudinal occurrence using the zero-crossing method. The EALs with their base at ~1.0-1.5 km, ~1.5-2.0 km, and ~ 2.0-3.0 km are taken as types I, II, and III, which occur for 9, 20, and 27 days, respectively. The EAL significantly modifies the total columnar aerosol optical depth (AOD). It is found that AOD, in total, within ABL and EAL, are ~0.72 (0.61), 0.28 (0.25), and 0.45 (0.36) using MPL (CALIPSO), respectively. The aerosols within ABL contribute ~38 % (41 %) while EAL ~ 62 % (59 %) to the total AOD obtained using MPL (CALIPSO). We observed that the ABL and EAL are characterized by different aerosol subtypes, such as dust marine (31 %) and smoke (~ 27 %) aerosols. Other aerosol subtypes, such as dust and polluted dust, commonly occur within the ABL (54 %) and EAL (52 %).

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations.

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

Characterization of atmospheric trace gases and water soluble inorganic chemical ions of PM1 and PM2.5 at Indira Gandhi International Airport, New Delhi during 2017-18 winter.

Water soluble inorganic chemical ions of PM1 and PM2.5 and atmospheric trace gases were monitored simultaneously on hourly resolution at Indira Gandhi International Airport (IGIA), Delhi during 8 December 2017-10 February 2018. Monitoring was made by MARGA (Monitoring AeRosol and Gases in ambient Air) under winter fog experiment (WIFEX) program of the Ministry of Earth Sciences (MoES), Government of India. The result based on the analysis of the data so generated reveals that Cl-, NH4+, NO3- and SO42- were dominant ions in order which collectively constituted 96.8 and 97.3% of the of the total measured ionic mass in PM1 and PM2.5 respectively. Their overall average concentrations in PM1 were 19.5 ± 19.7, 18.4 ± 10.5, 16.6 ± 8.7 and 10.3 ± 5.7 µg/m3 and in PM2.5 were 36.0 ± 33.9, 32.7 ± 17.2, 28.5 ± 13.6 and 19.9 ± 13.9 µg/m3. Average concentrations of HCl, HNO3, HNO2, SO2 and NH3 trace gases were 0.7 ± 0.3, 2.7 ± 1.1, 6.6 ± 4.7, 22.0 ± 12.3 and 25.7 ± 9.1 µg/m3 respectively. Weather parameters along with low mixing height played significant role in the occurrence of high concentration of these chemical species. NH4+ was the prime neutralizer of the acidic components and mostly occurred in (NH4)2SO4/NH4HSO4, NH4NO3 and NH4Cl molecular forms. Major sources of these chemical species were fossil fuel combustion in aviation activity and transportation, coal burning in thermal power plants, industrial processes and emissions from biomass burning and agro-based activity. The quality of air with respect to PM2.5 always remained deteriorated. It became alarming during low visibility period mainly due to high concentration of Cl-, NO3-, SO42- and NH4+. Both meteorological and chemical processes interactively fed each other which occasionally resulted in fog development and visibility degradation. The knowledge gained by this study will help in simulation of atmospheric processes which lead to fog development and dispersal in the Delhi region.