Computational models for the prediction of severe thunderstorms over east indian region

Thunderstorm is one of the most spectacular weather phenomena in the atmosphere. Many parts over the Indian region experience thunderstorms at higher frequency during pre-monsoon months (March- May), when the atmosphere is highly unstable because of high temperatures prevailing at lower levels. Most dominant feature of the weather during the pre-monsoon season over the eastern Indo-Gangetic plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’wester’ or ‘Kalbaishakhi’. The severe thunderstorms associated with thunder, squall line, lightning and hail cause extensive losses in agriculture, damage to structure and also loss of life. The casualty due to lightning associated with thunderstorms in this region is the highest in the world. The highest numbers of aviation hazards are reported during occurrence of these thunderstorms. In India, 72% of tornadoes are associated with this thunderstorm.

Characteristics of ABL during active and weak phases of monsoon

Understanding of the Atmospheric Boundary Layer (ABL) is imperative in the arena of the monsoon field. Here, the features of the ABL are studied employing Conserved Variable Analysis (CVA) using equivalent potential temperature and humidity. In addition, virtual potential temperature and wind are used during active and weak phases of monsoon. The analysis is carried out utilising the radiosonde observations during the monsoon months for two stations situated in the west coast of India. All these parameters show considerable variations during active and weak monsoon phases in both the stations. The core speed and core height vary with these epochs. The core speed is found to be more than 38 knots in the active monsoon phase around 1.2 km over Trivandrum and around 2 km over Mangalore. But during weak monsoon phase the core wind speed is decreased and core height is elevated over both stations. The wind direction shows an additional along shore component during weak monsoon period. The Convective Boundary Layer (CBL) height shows increase during weak monsoon phase over both stations due to less cloudiness and subsequent insolation. The CBL height during the southwest monsoon is more over Mangalore and is attributed by the orographic lifting in the windward side of the Western Ghats while the influence of the Ghats is less over Trivandrum.

SST–convection relation over tropical oceans

According to current knowledge, convection over the tropical oceans increases with sea surface temperature (SST) from 26 to 29 °C, and at SSTs above 29 °C, it sharply decreases. Our research shows that it is only over the summer warm pool areas of Indian and west Pacific Oceans (monsoon areas) where the zone of maximum SST is away from the equator that this kind of SST-convection relationship exists. In these areas (1) convection is related to the SST gradient that generates low-level moisture convergence and upward vertical motion in the atmosphere. This has modelling support. Regions of SST maxima have low SST gradients and therefore feeble convection. (2) Convection initiated by SST gradient produces strong wind fields particularly cross-equatorial low-level jetstreams (LLJs) on the equator-ward side of the warm pool and both the convection and LLJ grow through a positive feedback process. Thus, large values of convection are associated with the cyclonic vorticity of the LLJ in the atmospheric boundary layer. In the inter-tropical convergence zone (ITCZ) over the east Pacific Ocean and the south Pacific convergence zone (SPCZ) over the west Pacific Ocean, low-level winds from north and south hemisphere converge in the zone of maximum SST, which lies close to the equator producing there elongated bands of deep convection, where we find that convection increases with SST for the full range of SSTs unlike in the warm pool regions. The low-level wind divergence computed using QuikSCAT winds has large and significant linear correlation with convection in both the warm pool and ITCZ/SPCZ areas. But the linear correlation between SST and convection is large only for the ITCZ/SPCZ. These findings have important implications for the modelling of largescale atmospheric circulations and the associated convective rainfall over the tropical oceans

The diagnosis of severe thunderstorms with high-resolution WRF model

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’westers’(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region

Connected digit speech recognition system for Malayalam language

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

Microphytoplankton community structure in the North Eastern Arabian Sea during Winter Monsoon

The overall attempt of the study was aimed to understand the microphytoplankton community composition and its variations along a highly complex and dynamic marine ecosystem, the northern Arabian Sea. The data generated provides a first of its kind knowledge on the major primary producers of the region. There appears significant response among the microphytoplankton community structure towards the variations in the hydrographic conditions during the winter monsoon period. Interannually, variations were observed within the microphytoplankton community associated with the variability in temperature patterns and the intensity of convective mixing. Changing bloom pattern and dominating species among the phytoplankton community open new frontiers and vistas towards more intense study on the biological responses towards physical processes. The production of large amount of organic matter as a result of intense blooming of Noctiluca as well as diatoms aggregations augment the particulate organic substances in these ecosystem. This definitely influences the carbon dynamics of the northern Arabian Sea. Detailed investigations based on time series as well as trophodynamic studies are necessary to elucidate the carbon flux and associated impacts of winter-spring blooms in NEAS. Arabian sea is considered as one among the hotspot for carbon dynamics and the pioneering records on the major primary producers fuels carbon based export production studies and provides a platform for future research. Moreover upcoming researches based on satellite based remote sensing on productivity patterns utilizes these insitu observations and taxonomic data sets of phytoplankton for validation of bloom specific algorithm development and its implementation. Furthermore Saurashtra coast is considered as a major fishing zone of Indian EEZ. The studies on the phytoplankton in these regions provide valuable raw data for fishery prediction models and identifying fishing zones. With the Summary and Conclusion 177 baseline data obtained further trophodynamic studies can be initiated in the complex productive North Eastern Arabian Seas (NEAS) ecosystem that is still remaining unexplored.

Einfluss der Führung des Trocknungsprozesses auf den Trocknungsverlauf und die Produkteigenschaften empfindlicher biologischer Güter

Die Konvektionstrocknung ist eine der ältesten Methoden zur Konservierung von Lebensmitteln. Es ist bekannt, dass Agrarprodukte temperaturempfindlich sind. Bei Überhitzung erleiden sie chemische und physikalische Veränderungen, die ihre Qualität vermindern. In der industriellen Praxis wird die Konvektionstrocknung in der Regel auf Grundlage empirisch ermittelter Werte durchgeführt, welche die Produkttemperatur nicht berücksichtigen. Es ist deshalb nicht sichergestellt, ob der Prozess optimal oder auch nur gut betrieben wird. Inhalt dieser Arbeit ist ein Vergleich der klassischen einstufigen Konvektionstrocknung mit einer Prozessführungsstrategie bei der die Produkttemperatur als Regelgröße eingeführt wird. Anhand der Untersuchung des Trocknungsverhaltens von Äpfeln werden die beiden Verfahren analysiert, die erhaltenen Ergebnisse miteinander verglichen und daraus optimierte Trocknungsbedingungen abgeleitet. Die für dieses Projekt entwickelte Prozessanlage erlaubt die simultane Untersuchung sämtlicher wesentlicher Temperaturen, der Gewichtsveränderung und der optischen Qualitätskriterien. Gleichzeitig ist es möglich, entweder die Lufttemperatur oder die Temperatur des Produktes zur regeln, während die jeweils andere Größe als Messwert erfasst wird. Es kann weiterhin zwischen Durch- und Überströmung gewählt werden.

Connecting the Water and Carbon Cycles for the Generation of Food Security and Ecosystem Services

Water scarcity and food insecurity are pervasive issues in the developing world and are also intrinsically linked to one another. Through the connection of the water cycle and the carbon cycle this study illustrates that synergistic benefits can be realized by small scale farmers through the implementation of waste water irrigated agroforestry. The WaNuLCAS model is employed using La Huerta agroforestry site in Texcoco, South Central Mexico, as the basis for parameterization. The results of model simulations depicting scenarios of water scarcity and waste water irrigation clearly show that the addition of waste water greatly increases the agroforestry system’s generation of crop yields, above- and below-ground biomass, soil organic matter and carbon storage potential. This increase in carbon sequestration by the system translates into better local food security, diversified household income through payments for ecosystem services and contributes to the mitigation of global climate change.

Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts

This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.

Face Detection in Still Gray Images

We present a trainable system for detecting frontal and near-frontal views of faces in still gray images using Support Vector Machines (SVMs). We first consider the problem of detecting the whole face pattern by a single SVM classifer. In this context we compare different types of image features, present and evaluate a new method for reducing the number of features and discuss practical issues concerning the parameterization of SVMs and the selection of training data. The second part of the paper describes a component-based method for face detection consisting of a two-level hierarchy of SVM classifers. On the first level, component classifers independently detect components of a face, such as the eyes, the nose, and the mouth. On the second level, a single classifer checks if the geometrical configuration of the detected components in the image matches a geometrical model of a face.

Defects in Self Assembled Colloidal Crystals

Colloidal self assembly is an efficient method for making 3-D ordered nanostructures suitable for materials such as photonic crystals and macroscopic solids for catalysis and sensor applications. Colloidal crystals grown by convective methods exhibit defects on two different scales. Macro defects such as cracks and void bands originate from the dynamics of meniscus motion during colloidal crystal growth while micro defects like vacancies, dislocation and stacking faults are indigenous to the colloidal crystalline structure. This paper analyses the crystallography and energetics of the microscopic defects from the point of view of classical thermodynamics and discusses the strategy for the control of the macroscopic defects through optimization of the liquid-vapor interface.

Transport of Sub-micron Aerosols in Bifurcations

The convective-diffusive transport of sub-micron aerosols in an oscillatory laminar flow within a 2-D single bifurcation is studied, using order-of-magnitude analysis and numerical simulation using a commercial software (FEMLAB®). Based on the similarity between momentum and mass transfer equations, various transient mass transport regimes are classified and scaled according to Strouhal and beta numbers. Results show that the mass transfer rate is highest at the carinal ridge and there is a phase-shift in diffusive transport time if the beta number is greater than one. It is also shown that diffusive mass transfer becomes independent of the oscillating outer flow if the Strouhal number is greater than one.

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

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