C. V. Srinivas

Formulation of stability-dependent empirical relations for turbulent intensities from surface layer turbulence measurements for dispersion parameterization in a lagrangian particle dispersion model

Season- and stability-dependent turbulence intensity (σu/u*, σv/u*, σw/u*) relationships are derived from experimental turbulence measurements following surface layer scaling and local stability at the tropical coastal site Kalpakkam, India for atmospheric dispersion parameterization. Turbulence wind components (u′, v′, w′) measured with fast response UltraSonic Anemometers during an intense observation campaign for wind field modeling called Round Robin Exercise are used to formulate the flux–profile relationships using surface layer similarity theory and Fast Fourier Transform technique. The new relationships (modified Hanna scheme) are incorporated in a Lagrangian Particle Dispersion model FLEXPART-WRF and tested by conducting simulations for a field tracer dispersion experiment at Kalpakkam. Plume dispersion analysis of a ground level hypothetical release indicated that the new turbulent intensity formulations provide slightly higher diffusivity across the plume relative to the original Hanna scheme. The new formulations for σu, σv, σw are found to give better agreement with observed turbulent intensities during both stable and unstable conditions under various seasonal meteorological conditions. The simulated concentrations using the two methods are compared with those obtained from a classical Gaussian model and the observed SF6 concentration. It has been found that the new relationships provide comparatively higher diffusion across the plume relative to the model default Hanna scheme and provide downwind concentration results in better agreement with observations.

Numerical simulation of tropical cyclone thane: role of boundary layer and surface drag parameterization schemes

In the recent times, several advanced numerical models are utilized for the prediction of the intensity, track and landfall time of a cyclone. Still there are number of issues concerning their prediction and the limitation of numerical models in addressing those issues. The most pertinent question is how intensive a cyclone can become before it makes a landfall and where the cyclone moves under the ambient large-scale flow. In this paper, detailed study has been carried out using Weather Research Forecast model with two boundary schemes to address the above question by considering a recent tropical cyclone in Bay of Bengal region of North Indian Ocean. In addition, the impact of the surface drag effect on the low-level winds and the intensity of the cyclone are also studied. The result reveals that large differences are noted in the ocean surface fluxes between YSU and MYJ with MYJ producing relatively higher fluxes than YSU. It is found that the YSU scheme produced a better simulation for the THANE cyclone in terms of winds, pressure distribution and cloud fractions. Comparison with available observations indicated the characteristics of horizontal divergence, vorticity and vector track positions produced by YSU experiment are more realistic than with MYJ and other experiments. However, when the drag coefficient is changed as 0.5 or 2.0 from the default values, appreciable changes in the surface fluxes are not noticed. A maximum precipitation is reported in YSU as compared to the MYJ PBL scheme for the tropical cyclone THANE.

Land Surface Processes Simulation Over Thar Desert in Northwest India

Land surface processes in data scarce arid northwestern India and their influence on the regional climate including monsoon are now gaining enhanced scientific attention. In this work the seasonal variation of land surface parameters and surface-energy flux components over Lasiurus sindicus grassland system in Thar Desert, western India were simulated using the mesoscale WRF model. The data on surface fluxes from a micrometeorological station, and basic surface level weather data from the Central Arid Zone Research Institute’s experimental field station (26o59′41″N; 71o29′10″E), Jaisalmer, were used for comparison. Simulations were made for typical fair weather days in three seasons [12–14 January (peak winter); 29–31 May (peak summer), 19–21 August (monsoon)] during 2012. Sensitivity experiments conducted using a 5-layer soil thermal diffusion (5TD) scheme and a comprehensive land surface physics scheme (Noah) revealed the 5TD scheme gives large biases in surface fluxes and other land surface parameters. Simulations show large variations in surface fluxes and meteorological parameters in different seasons with high friction velocities, sensible heat fluxes, deep boundary layers in summer and monsoon season as compared to winter. The shortwave radiation is underestimated during the monsoon season, and is overestimated in winter and summer. In general, the model simulated a cold bias in soil temperature in summer and monsoon season and a warm bias in winter; the simulated surface fluxes and air temperature followed these trends. These biases could be due to a negative bias in net radiation resulting from a high bias in downward shortwave radiation in various seasons. The Noah LSM simulated various parameters more realistically in all seasons than the 5TD soil scheme due to inclusion of explicit vegetation processes in the former. The differences in the simulated fluxes with the two LSMs are small in winter and large in summer. The deep mixed layers are distributed in the northeastern parts in summer, northern areas in southwest monsoon and in southwestern parts during winter seasons and associated with the land-cover and vegetation dynamics. Our results present a baseline simulation study in this data scarce arid region.