Comparison of Measured and Numerically Simulated Turbulence Statistics in a Convective Boundary Layer Over Complex Terrain

The Weather Research and Forecasting (WRF) model can be used to simulate atmospheric processes ranging from quasi-global to tens of m in scale. Here we employ large-eddy simulation (LES) using the WRF model, with the LES-domain nested within a mesoscale WRF model domain with grid spacing decreasing from 12.15 km (mesoscale) to 0.03 km (LES). We simulate real-world conditions in the convective planetary boundary layer over an area of complex terrain. The WRF-LES model results are evaluated against observations collected during the US Department of Energy-supported Columbia Basin Wind Energy Study. Comparison of the first- and second-order moments, turbulence spectrum, and probability density function of wind speed shows good agreement between the simulations and observations. One key result is to demonstrate that a systematic methodology needs to be applied to select the grid spacing and refinement ratio used between domains, to avoid having a grid resolution that falls in the grey zone and to minimize artefacts in the WRF-LES model solutions. Furthermore, the WRF-LES model variables show large variability in space and time caused by the complex topography in the LES domain. Analyses of WRF-LES model results show that the flow structures, such as roll vortices and convective cells, vary depending on both the location and time of day as well as the distance from the inflow boundaries.     

Tropical atmospheric stability and wind structures as inferred from the Indian MST radar observations

Summary The MST (Mesosphere-Stratosphere-Tropospher) Radar Facility at Gadanki (13.47° N, 79.18° E), near Tirupati, Andhra Pradesh, India has been operated over seven diurnal cycles—three in November 1994, one in September 1995 and three in January–February 1996 with an objective to study the wind and stability characteristics in the troposphere and lower-stratosphere. The radar-measured height profiles of both zonal (EW) and meridional (NS) wind components and near-simultaneous radiosonde measurements from Madras (13.04° N, 80.7° E) and Bangalore (12.85° N, 77.58° E), the two stations close to either side of the radar site, have been compared and they are found to be in gross agreement within the limitations of the sensing techniques.The results of the study also indicated multiple stable and turbulent structures/stratification throughout the height region from about 4 to 30 km. It is noticed that the stable layers are well marked around the altitudes 4 km, 12 km and the tropopause while the turbulent layers exist a few kilometers below the tropopause. These stable and turbulent layer structures showed good correspondence with the radar-measured wind gradients and also with the radiosonde-derived temperature and wind distributions over Madras. The maximum positive gradient in the signal-tonoise ratio (SNR) which corresponds to radar tropopause is found to coincide with the greater potential temperature gradient and smaller wind gradient. The time evolution of atmospheric stability structure, derived from the SNR, spectral width and vertical wind revealed a diffused tropopause or tropopause weakening which is found to be associated with broader spectral width and larger gradients of winds. This feature is considered to be due either to the instability associated with large vertical gradients in horizontal winds (dynamical instability) or to the instability generated by the convection (convective instability).With 6 Figures     

Distribution and enrichment of trace metals in marine sediments of Bay of Bengal,off Ennore,south-east coast of India

In order to avoid the pollution of trace metals in marine environment, it is necessary to establish the data and understand the mechanisms influencing the distribution of trace metals in marine environment. The concentration of heavy metals (Fe, Mn, Cr, Cu, Ni, Pb, Zn, Co and Cd) were studied in sediments of Ennore shelf, to understand the metal contamination due to heavily industrialized area of Ennore, south-east coast of India. Concentration of metals shows significant variability and range from 1.7 to 3.7% for Fe, 284–460 μg g⁻¹ for Mn, 148.6–243.2 μg g⁻¹ for Cr, 385–657 μg g⁻¹ for Cu, 19.8–53.4 μg g⁻¹ for Ni, 5.8–11.8 μg g⁻¹ for Co, 24.9–40 μg g⁻¹ for Pb, 71.3–201 μg g⁻¹ for Zn and 4.6–7.5 μg g⁻¹ for Cd. For various metals the contamination factor (CF) and geoaccumulation index (I _geo) has been calculated to assess the degree of pollution in sediments. The geoaccumulation index shows that Cd, Cr and Cu moderately to extremely pollute the sediments. This study shows that the major sources of metal contamination in the Ennore shelf are land-based anthropogenic ones, such as discharge of industrial wastewater, municipal sewage and run-off through the Ennore estuary. The intermetallic relationship revealed the identical behavior of metals during its transport in the marine environment.     

L.R.S. Bianchi Type I string dust magnetized cosmological models

L.R.S. Bianchi Type I string dust cosmological models with and without magnetic field following the techniques used by Letelier and Stachel, is investigated. To get a determinate solution, we assume a conditionσ is proportional to scalar of expansion θ where σ is shear and θ is scalar of expansion and which leads to A=ℓ B ⁿwhere n is a constant and ℓ is proportionality constant. Some special models are also investigated by introducing the transformation, , which leads to Riccati type differential equation. The physical and geometrical aspects of the models are also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

The assessment of aerosol optical properties over Mohal in the northwestern Indian Himalayas using satellite and ground-based measurements and an influence of aerosol transport on aerosol radiative forcing

The present study deals with the aerosol optical properties which are assessed during the period 2007 to 2009 over Mohal (31.9oN, 77.12oE) in the northwestern Indian Himalaya, using ground-based measurements and multi-satellite data. The daily average value of aerosol optical depth (AOD) at 500?nm, ?ngstr?m exponent and turbidity coefficient are 0.24?±?0.08, 1.02?±?0.34 and 0.13?±?0.05, respectively. The comparative study of satellite and ground-based measurements reveals that the percentage retrieval for daily AOD at 550?nm over Mohal within the expected accuracy (???? _p?? ?=?±0.05?±?0.15?? _p?? ) is around 87%, with a significant correlation coefficient of 0.76. The present study suggests that the retrieval of AOD through satellite data is able to characterise the distribution of AOD over Mohal. However, further efforts are needed in order to eliminate systematic errors in the existing Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm. The transport of desert dust and anthropogenic aerosol during high aerosol loading days caused a significant reduction in surface-reaching solar radiation by 149 and 117%, respectively. This large reduction in surface-reaching solar radiation increased the atmospheric heating rate by 0.93 and 0.72?K?day^?1, respectively. This study indicates significant climatic implications due to the transport of aerosols in the northwestern Indian Himalaya.     

A novel and generalized approach in the inversion of geoelectrical resistivity data using Artificial Neural Networks (ANN)

The non-linear apparent resistivity problem in the subsurface study of the earth takes into account the model parameters in terms of resistivity and thickness of individual subsurface layers using the trained synthetic data by means of Artificial Neural Networks (ANN). Here we used a single layer feed-forward neural network with fast back propagation learning algorithm. So on proper training of back propagation networks it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data with reference to the synthetic data trained in the appropriate network. During training, the weights and biases of the network are iteratively adjusted to make network performance function level more efficient. On adequate training, errors are minimized and the best result is obtained using the artificial neural networks. The network is trained with more number of VES data and this trained network is demonstrated by the field data. The accuracy of inversion depends upon the number of data trained. In this novel and specially designed algorithm, the interpretation of the vertical electrical sounding has been done successfully with the more accurate layer model.     

Distribution, classification, petrological and related gochemical (SRA) characteristics of a tropical lowland peat dome in the Kota Samarahan-Asajaya area, West Sarawak, Malaysia

Petrographic studies indicate that lateral variations in the decomposition levels of peat are associated with the predominantly occurring peat macerals. Source Rock Analyzer (SRA) results indicate lateral variation in peat organic matter types from type II to III and back again to type II, occurring laterally within the top 0-m to 0.5-m layer at the basin margin to the midsection and further towards the near-center areas of the peat dome. This variation is most likely caused by a combination of factors: (a) Horizontal zonation and lateral variation of the dominant species of plant assemblages (b) Fibric (marginal) peats and hemic to sapric peats associated with type II organic matter (kerogen). Sample organic matter (coal-equivalent kerogen) typing indicates that the relative abundance of phytoclasts and palynomorphs generally supports the organic matter classification obtained by the SRA method. Lateral variations in the peat organic matter types may support the lateral vegetation variation concept. The classification of peat organic matter types (interpreted from visual analyses of palynological slides) occurring from the basin periphery to the mid-section and further towards the basin center yields organic matter of type II to type III and mixed types II to III (coal kerogen-equivalent), respectively.     

Analysis of SARAL/AltiKa Wind and Wave over Indian Ocean and its Real-time Application in Wave Forecasting System at ISRO

The current study aims to analyze the wind and wave parameters over Indian Ocean region obtained from first Ka –band altimeter AltiKa onboard SARAL, a collaborative mission of Indian Space Research Organization (ISRO) and Centre National d'Etudes Spatiales (CNES), France. It also demonstrates a real time application of SARAL data by assimilating the wave height in a wave model operational at the Space Applications Centre, ISRO. State-of–the art coastal wave model Simulating Wave Near shore (SWAN) is used for this purpose. The well-tested optimal interpolation technique is adopted for assimilation. Before proceeding to the assimilation per se, SARAL/AltiKa Wind and Significant Wave Height (SWH) have been validated using in- situ observations and WAVEWATCH III model. Apart from assessment of wind and wave data quality, this also served the purpose of providing error covariance to be used in assimilation. Supremacy of the assimilation run over parallel control run without assimilation has been judged by comparing the results with buoy observations at Indian National Centre for Ocean Information System (INCOIS). The statistics of validation of the assimilation run has been found to be extremely encouraging and interesting.