Volatile organic compounds (VOCs) are crucial in driving ozone concentration; particularly in urban areas where VOC limited regimes are prominent. The limited measurements of VOCs, however, hinder assessing the VOC-ozone relationship. The application of machine learning (ML) models for surface ozone prediction using meteorology and pollutant data has been explored in this work for 2014–16 over a metropolitan region in India. Simulations with different inputs were conducted to weigh the relative importance of different parameters from an ozone prediction perspective. While isoprene was identified as a prominent parameter for predicting ozone peaks at this location, CO was also featured important. Season-wise comparison of ozone prediction results shows low accuracy for summer.
Kalbande R., Kumar Bipin, Maji S., Yadav R., Atey K., Rathore D.S., Beig G., Chemosphere, 326: 138474, June 2023, DOI:10.1016/j.chemosphere.2023.138474, 1-8
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Predicting Indian Summer Monsoon (ISM) is a challenging task due to its complexity and nonlinear interactions. Three sets of hindcast experiments are carried out for 9 months each, for the period 1993-2019, NCEP-CFSv2. The experiments differ from each other in the way they are initialized: one is initialized in February (FebIC), and the second in May (MayIC), whereas in the third one (Exp), ocean is initialized in February and allowed to evolve but the atmosphere reinitialized every month up to May. The representation of mean tropical Indo-Pacific Sea surface temperature (SST), Walker circulation, mean monsoon circulation and moisture transport to Indian landmass are better represented in Exp. The ISM rainfall prediction (interannual) skill improved in Exp as compared to FebIC and MayIC over central India, Indian land mass and extended monsoon region. The initialization strategy adopted in Exp reduces the model initial shocks especially in the upper ocean heat content and SST over the Indo-Pacific region, thereby offering a cost-effective alternative approach for reduction of the initial shock. The well-known cold tongue SST bias over the equatorial Pacific in MayIC is reduced significantly in Exp with improved monsoon teleconnections and the overdependence of ISM rainfall on El Niño Southern Oscillation in MayIC is also reduced in Exp.
Fousiya T.S., Gnanaseelan C., Halder S., Kakatkar R., Chowdary J.S., Patekar D., Parekh A., International Journal of Climatology, Online, May 2023, DOI:10.1002/joc.8126, 1-21
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The presence of persistent heavy fog in northern India during winter creates hazardous situations for transportation systems and disrupts the lives of about 400 million people.
WiFEX is a first-of-its-kind multi-institutional initiative dealing with intensive ground-based measurement campaigns for developing a suitable fog forecasting capability under the aegis of the smart cities mission of India. An operational modeling framework, the WRF Model, was set up to provide fog predictions during the measurement campaign. These field observations helped to interpret the strengths and deficiencies in the numerical modeling framework. Results have shown that micrometeorological, thermodynamic, surface dynamical processes, microphysical properties, and synoptic-scale systems are alone not governing the fog genesis and evolution, but the detailed chemical processes also play a crucial role in the fog life cycle and should necessarily be considered in fog modelling efforts over polluted regions.
Ghude S.D., Jenamani R.K., Kulkarni R., Wagh S., Dhangar N.G., Parde A.N., Acharja P., Lonkar P., Govardhan G., Yadav P., Vispute A., Debnath S., Lal D. M., Bisht D.S., Jena C., Pawar P.V., Dhankhar S.S., Sinha V., Chate D.M., Safai P.D., Nigam N., Konwar M., Hazra A., Dharmaraj T., Gopalkrishnan V., Padmakumari B., Gultepe I., Biswas M., Karipot A.K., Prabhakaran Thara, Nanjundiah R.S., Rajeevan M., Bulletin of the American Meteorological Society, 104, May 2023, DOI:10.1175/BAMS-D-21-0197.1, E980–E1005
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Effect of horizontal electric field (EH) = 0, 100, and 300 kVm−1 on the characteristics of binary collisions of small water drops (dS = 0.4–1.8 mm diameter) with large drops (dL = 3–3.5 mm diameter) has been investigated in a small vertical wind tunnel using a high-speed digital camera. The increase in the electric field reduces the probability of coalescence when a non-dimensional parameter, Weber number (We) < 1. However, an increase in We restricts the probability of coalescence when We ≥ 1. After a binary collision, the relaxation time for coalescence is higher than that for the breakup and increases from the filament to sheet to disk mode of breakup in all-electric field values. Fragment size distributions after the filament and sheet types of breakups differ. More violent collisions have a tendency to increase the number of fragments of the sizes between dL and dS. It is concluded therefore that, the effect of the electric field needs to be included in the estimation of drop growth and precipitation in clouds.
Bhalwankar R., Pawar V., Kamra A.K., Journal of Geophysical Research: Atmospheres, 128: e2022JD037543, April 2023, DOI:10.1029/2022JD037543, 1-18
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