Nudging of vertical profiles of meteorological parameters in one-dimensional atmospheric model: A step towards improvements in numerical simulations

In this article, we describe a simple yet effective method for insertion of observational datasets in a mesoscale atmospheric model used in one-dimensional configuration through Nudging. To demonstrate the effectiveness of this technique, vertical profiles of meteorological parameters obtained from GLASS Sonde launches from a tiny island of Kaashidhoo in the Republic of Maldives are injected in a mesoscale atmospheric model — Advanced Regional Prediction System (ARPS), and model simulated parameters are compared with the available observational datasets. Analysis of one-time nudging in the model simulations over Kaashidhoo show that incorporation of this technique reasonably improves the model simulations within a time domain of +6 to +12 Hrs, while its impact on +18 Hrs simulations and beyond becomes literally null.     

Subfilter-Scale Modelling Using Transport Equations: Large-Eddy Simulation of the Moderately Convective Atmospheric Boundary Layer

We perform large-eddy simulation (LES) of a moderately convective atmospheric boundary layer (ABL) using a prognostic subfilter-scale (SFS) model obtained by truncating the full conservation equations for the SFS stresses and fluxes. The truncated conservation equations contain production mechanisms that are absent in eddy-diffusivity closures and, thus, have the potential to better parametrize the SFS stresses and fluxes. To study the performance of the conservation-equation-based SFS closure, we compare LES results from the surface layer with observations from the Horizontal Array Turbulence Study (HATS) experiment. For comparison, we also show LES results obtained using an eddy-diffusivity closure. Following past studies, we plot various statistics versus the non-dimensional parameter, Λ _w /Δ, where Λ _w is the wavelength corresponding to the peak in the vertical velocity spectrum and Δ is the filter width. The LES runs are designed using different domain sizes, filter widths and surface fluxes, in order to replicate partly the conditions in the HATS experiment. Our results show that statistics from the different LES runs collapse reasonably and exhibit clear trends when plotted against Λ _w /Δ. The trends exhibited by the production terms in the modelled SFS conservation equations are qualitatively similar to those seen in the HATS data with the exception of SFS buoyant production, which is underpredicted. The dominant production terms in the modelled SFS stress and flux budgets obtained from LES are found to approach asymptotically constant values at low Λ _w /Δ. For the SFS stress budgets, we show that several of these asymptotes are in good agreement with their corresponding theoretical values in the limit Λ _w /Δ → 0. The modelled SFS conservation equations yield trends in the mean values and fluctuations of the SFS stresses and fluxes that agree better with the HATS data than do those obtained using an eddy-diffusivity closure. They, however, underpredict considerably the level of SFS anisotropy near the wall when compared to observations, which could be a consequence of the shortcomings in the model used for the pressure destruction terms. Finally, we address the computational cost incurred due to the use of additional prognostic equations.     

Fast matched field processing

It is shown how the computational burden of source localization by matched field processing (MFP) can be significantly reduced (20 to 30 times) by expressing the correlation in terms of a discrete Fourier transform and using the fast Fourier transform (FFT) algorithm. The price paid to achieve increased speed is in the form of quantization phase errors. It is shown through analysis and computer simulation that the quantization errors reduce the source peak height, depending upon the size of DFT. The proposed fast MFP works for range localization only. However, the depth estimation is possible by repeated application of the above algorithm for different depths     

Spatio-temporal variation and sensitivity analysis of aerosol particulate matter during the COVID-19 phase-wise lockdowns in Indian cities

Journal of Atmospheric Chemistry - At the pandemic of COVID-19, the movement of business and other non-essential activities were majorly restricted at the end of March 2020 in India and continued...     

Degradation of Textile Dyeing Wastewater by a Modified Solar Photo‐Fenton Process Using Steel Scrap/H2O2

This experimental research deals with using steel scrap as a heterogeneous catalyst. This catalyzes the oxidation reaction of real textile dye wastewater based on a modified solar photo‐Fenton oxidation process. Morphologic analysis and mapping of the elementary composition of the steel scrap have been carried out by scanning electron microscopy. The effects of concentration of H₂O₂, the pH of the solution and the catalyst loading on the degradation of textile dye wastewater are elucidated. Kinetic studies have been performed for the decolorization of wastewater under optimum conditions. It could be concluded that the steel scrap is a potential substitute for ferrous salts as a catalyst for the solar photo‐Fenton reaction.     

Climate change projections over India by a downscaling approach using PRECIS

This study presents a comprehensive assessment of the possible regional climate change over India by using Providing REgional Climates for Impacts Studies (PRECIS), a regional climate model (RCM) developed by Met Office Hadley Centre in the United Kingdom. The lateral boundary data for the simulations were taken from a sub-set of six members sampled from the Hadley Centre’s 17- member Quantified Uncertainty in Model Projections (QUMP) perturbed physics ensemble. The model was run with 25 km × 25 km resolution from the global climate model (GCM) - HadCM3Q at the emission rate of special report on emission scenarios (SRES) A1B scenarios. Based on the model performance, six member ensembles running over a period of 1970-2100 in each experiment were utilized to predict possible range of variations in the future projections for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095) with respect to the baseline period (1975-2005). The analyses concentrated on maximum temperature, minimum temperature and rainfall over the region. For the whole India, the projections of maximum temperature from all the six models showed an increase within the range 2.5°C to 4.4°C by end of the century with respect to the present day climate simulations. The annual rainfall projections from all the six models indicated a general increase in rainfall being within the range 15-24%. Mann-Kendall trend test was run on time series data of temperatures and rainfall for the whole India and the results from some of the ensemble members indicated significant increasing trends. Such high resolution climate change information may be useful for the researchers to study the future impacts of climate change in terms of extreme events like floods and droughts and formulate various adaptation strategies for the society to cope with future climate change.     

Improving pulsar distances by modelling interstellar scattering

In this paper we propose a scenario for the formation of a population of baryon-rich, dark-matter-deficient dwarf galaxies at high redshift from the mass swept out in the intergalactic medium (IGM) by energetic outflows from luminous quasars. We predict the intrinsic properties of these galaxies, and examine the prospects for their observational detection in the optical, X-ray and radio wavebands. Detectable thermal Sunyaev–Zel'dovich decrements on arcminute scales in the cosmic microwave background radiation maps are expected during the shock-heated expanding phase from these hot bubbles. We conclude that the optimal detection strategy for these dwarfs is via narrow-band Lyman-α imaging of regions around high-redshift quasars. A scaled-down (in the energetics) version of the same model is speculated upon as a possible mechanism for forming pre-galactic globular clusters.