Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

COVID-19 pandemic: impacts on bees,beekeeping, and potential role of bee products as antiviral agents and immune enhancers

Environmental Science and Pollution Research - COVID-19 pandemic has passed to the front all the contradictions of the beekeeping sector: the valuable role of bee products as immune enhancers and...     

Transport of chlorinated dioxins and furans in soil columns: modeling pentachlorophenol pole-treating oil influence

Column experiments were conducted to validate a screening model predicting the influence of pentachlorophenol (PCP) pole-treating oil on the vertical migration of its impurities, chlorinated dioxins and furans (PCDD/Fs). PCP pole-treating oil (15 mL d⁻¹) and water (20 mL d⁻¹) were added daily to the top of sand and organic soil columns during 35 d. Column soil samples were analyzed to determine concentrations of hydrocarbons and PCDD/Fs at several depths in the columns (0-30 cm) and their evolution in time (7, 14, 21 and 35 d).The model predicted a significant vertical migration of PCDD/Fs due to the presence of oil as a free phase and PCDD/Fs were found in the different column layers at concentrations consistent with model predictions (same order of magnitude). Measured PCDD/Fs concentrations are in total disagreement with literature data and with model prediction in the absence of oil free phase, which implies PCDD/F properties alone cannot be used to predict their fate in the current context: the influence of PCP pole-treating oil must be accounted for to properly explain their migration.