The objectives of the Winter Fog Experiment (WIFEX) over the Indo-Gangetic Plains of India are to develop better now-casting and forecasting of winter fog on various time-and spatial scales. Maximum fog occurrence over northwest India is about 48 days (visibility <1000 m) per year, and it occurs mostly during the December-February time-period. The physical and chemical characteristics of fog, meteorological factors responsible for its genesis, sustenance, intensity and dissipation are poorly understood. Improved understanding on the above aspects is required to develop reliable forecasting models and observational techniques for accurate prediction of the fog events. Extensive sets of comprehensive groundbased instrumentation were deployed at the Indira Gandhi International Airport, New Delhi. Major in situ sensors were deployed to measure surface micrometeorological conditions, radiation balance, turbulence, thermodynamical structure of the surface layer, fog droplet and aerosol microphysics, aerosol optical properties, and aerosol and fog water chemistry to describe the complete environmental conditions under which fog develops. In addition, Weather Forecasting Model coupled with chemistry is planned for fog prediction at a spatial resolution of 2 km. The present study provides an introductory overview of the winter fog field campaign with its unique instrumentation.
A direct numerical simulation (DNS) with the decaying turbulence setup has been carried out to study cloud‐edge mixing and its impact on the droplet size distribution (DSD) applying thermodynamic conditions observed in monsoon convective clouds over Indian subcontinent during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). Evaporation at the cloud‐edges initiates mixing at small scale and gradually introduces larger‐scale fluctuations of the temperature, moisture, and vertical velocity due to droplet evaporation. Our focus is on early evolution of simulated fields that show intriguing similarities to the CAIPEEX cloud observations. A strong dilution at the cloud edge, accompanied by significant spatial variations of the droplet concentration, mean radius, and spectral width, are found in both the DNS and in observations. In DNS, fluctuations of the mean radius and spectral width come from the impact of small‐scale turbulence on the motion and evaporation of inertial droplets. These fluctuations decrease with the increase of the volume over which DNS data are averaged, as one might expect. In cloud observations, these fluctuations also come from other processes, such as entrainment/mixing below the observation level, secondary CCN activation, or variations of CCN activation at the cloud base. Despite large differences in the spatial and temporal scales, the mixing diagram often used in entrainment/mixing studies with aircraft data is remarkably similar for both DNS and cloud observations. We argue that the similarity questions applicability of heuristic ideas based on mixing between two air parcels (that the mixing diagram is designed to properly represent) to the evolution of microphysical properties during turbulent mixing between a cloud and its environment.
Microphysical characteristics of premonsoon and monsoon deep cumuli over India observed by an instrumented aircraft are contrasted focusing on influences of environmental conditions and entrainment‐mixing processes. Differences in the lower tropospheric temperature and moisture profiles lead to contrasting undiluted cloud buoyancy profiles around the cloud base, larger in the premonsoon case. It is argued that this affects the variation of the mean and maximum cloud droplet number concentrations and the droplet radius within the lowest several hundred meters above the cloud base. The conserved‐variable thermodynamic diagram analysis suggests that entrained parcels originate from levels close to the observational level. Mixing processes and their impact on the droplet size distribution (DSD) are investigated contrasting 1 Hz and 10 Hz observations. Inhomogeneous‐type mixing, likely because of unresolved small‐scale structures associated with active turbulent stirring, is noted at cloud edge volumes where dilution is significant and DSDs shift toward smaller sizes with reduced droplet number concentrations due to complete evaporation of smaller droplets and partial evaporation of larger droplets. DSDs within cloud core volumes suggest that the largest droplets are formed in the least diluted volumes where raindrops can form at higher levels; no superadiabatic droplet growth is observed. The typical diluted parcel size is approximately 100–200 m for cloud edge volumes, and it is much smaller, 10–20 m, for cloud core volumes. Time scale analysis indicates the possibility of inhomogeneous type mixing within the diluted cloud edge volumes at spatial scales of a 100 m or more.
Large eddy simulation with contrasting environmental humidity is used to study entrainment and detrainment rates and convective mass flux during the development stages of continental deep cumulus clouds. The cumulus clouds studied here are deeper than marine shallow cumulus or stratocumulus in the published literature. The main objective of the study is to parameterize the entrainment and detrainment rates in monsoon clouds during the break monsoon periods over land, useful for the large‐scale atmospheric models. A systematic decrease in cloud liquid water path is noted in drier environments as clouds become shallower due to the reduction of positive buoyancy in the cloud core. Updraft and downdraft velocities in the subcloud layers are strengthened in the drier environments, which are found to affect in‐cloud updraft strength. A most important finding of the present study is the effect of environmental humidity on the entrainment (and detrainment) rates and the convective mass flux. Many previous studies on this topic reported opposite results. The present study found that decreasing environmental humidity leads to a decrease in both the entrainment rate and the convective mass flux but an increase in the detrainment rate. The relationship of the entrainment parameters with the environmental relative humidity can be used for parameterization in the large‐scale models. The physical mechanism responsible for such response is identified as the strengthening of the subcloud updrafts compensated by the enhanced downdraft into the boundary layer in the drier environments, and this mechanism subsequently led to higher in‐cloud updraft velocity, resulting in lower entrainment rate.
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