Tropical Mesoscale Convective Systems and Associated Energetics : Observational and Modeling Studies

The main purpose of the thesis is to improve the state of knowledge and understanding of the physical structure of the TMCS and its short range prediction. The present study principally addresses the fine structure, dynamics and microphysics of severe convective storms.The structure and dynamics of the Tropical cloud clusters over Indian region is not well understood. The observational cases discussed in the thesis are limited to the temperature and humidity observations. We propose a mesoscale observational network along with all the available Doppler radars and other conventional and non—conventional observations. Simultaneous observations with DWR, VHF and UHF radars of the same cloud system will provide new insight into the dynamics and microphysics of the clouds. More cases have to be studied in detail to obtain climatology of the storm type passing over tropical Indian region. These observational data sets provide wide variety of information to be assimilated to the mesoscale data assimilation system and can be used to force CSRM.The gravity wave generation and stratosphere troposphere exchange (STE) processes associated with convection gained a great deal of attention to modem science and meteorologist. Round the clock observations using VHF and UHF radars along with supplementary data sets like DWR, satellite, GPS/Radiosondes, meteorological rockets and aircrafl observations is needed to explore the role of convection and associated energetics in detail.

Comparison of stochastic parameterisation approaches in a single-column model

We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stochastic physics schemes that have been proposed for use in general circulation models (GCMs). We argue that although single column tests cannot be definitive in exposing the full behaviour of a stochastic method in the full GCM, and although there are differences between SCM testing of deterministic and stochastic methods, SCM testing remains a useful tool. It is necessary to consider an ensemble of SCM runs produced by the stochastic method. These can be usefully compared to deterministic ensembles describing initial condition uncertainty and also to combinations of these (with structural model changes) into poor man's ensembles. The proposed methodology is demonstrated using an SCM experiment recently developed by the GCSS (GEWEX Cloud System Study) community, simulating transitions between active and suppressed periods of tropical convection.

Departures from convective equilibrium with a rapidly-varying surface forcing

Convective equilibrium is a long-standing and useful concept for understanding many aspects of the behaviour of deep moist convection. For example, it is often invoked in developing parameterizations for large-scale models. However, the equilibrium assumption may begin to break down as models are increasingly used with shorter timesteps and finer resolutions. Here we perform idealized cloud-system resolving model simulations of deep convection with imposed time variations in the surface forcing. A range of rapid forcing timescales from 1 − 36hr are used, in order to induce systematic departures from equilibrium. For the longer forcing timescales, the equilibrium assumption remains valid, in at least the limited sense that cycle-integrated measures of convective activity are very similar from cycle to cycle. For shorter forcing timescales, cycle-integrated convection becomes more variable, with enhanced activity on one cycle being correlated with reduced activity on the next, suggesting a role for convective memory. Further investigation shows that the memory does not appear to be carried by the domain-mean thermodynamic fields but rather by structures on horizontal scales of 5 − 20km. Such structures are produced by the convective clouds and can persist beyond the lifetime of the cloud, even through to the next forcing cycle.

Modelling the diurnal cycle of tropical convection across the "Grey Zone"

We present the results of simulations carried out with the Met Office Unified Model at 12km, 4km and 1.5km resolution for a large region centred on West Africa using several different representations of the convection processes. These span the range of resolutions from much coarser than the size of the convection processes to the cloud-system resolving and thus encompass the intermediate "grey-zone". The diurnal cycle in the extent of convective regions in the models is tested against observations from the Geostationary Earth Radiation Budget instrument on Meteosat-8. By this measure, the two best-performing simulations are a 12km model without convective parametrization, using Smagorinsky style sub-grid scale mixing in all three dimensions and a 1.5km simulations with two-dimensional Smagorinsky mixing. Of these, the 12km model produces a better match to the magnitude of the total cloud fraction but the 1.5km results in better timing for its peak value. The results suggest that the previously-reported improvement in the representation of the diurnal cycle of convective organisation in the 4km model compared to the standard 12km configuration is principally a result of the convection scheme employed rather than the improved resolution per se. The details of and implications for high-resolution model simulations are discussed.

Does convective aggregation need to be represented in cumulus parameterizations?

Tropical deep convection exhibits a variety of levels of aggregation over a wide range of scales. Based on a multisatellite analysis, the present study shows at mesoscale that different levels of aggregation are statistically associated with differing large-scale atmospheric states, despite similar convective intensity and large-scale forcings. The more aggregated the convection, the dryer and less cloudy the atmosphere, the stronger the outgoing longwave radiation, and the lower the planetary albedo. This suggests that mesoscale convective aggregation has the potential to affect couplings between moisture and convection and between convection, radiation, and large-scale ascent. In so doing, aggregation may play a role in phenomena such as “hot spots” or the Madden-Julian Oscillation. These findings support the need for the representation of mesoscale organization in cumulus parameterizations; most parameterizations used in current climate models lack any such representation. The ability of a cloud system-resolving model to reproduce observed relationships suggests that such models may be useful to guide attempts at parameterizations of convective aggregation.

An immunological approach to raising alarms in video surveillance

Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three types of detectors for detecting abnormal activity are developed using negative selection. Tracks gathered by people's movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location.

Big data sensing and service: a tutorial

As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend based on a connected sensor world because of IoT. It brings a strong impact on many sensor-oriented applications, including smart city, disaster control and monitor, healthcare services, and environment protection and climate change study. This paper is written as a tutorial paper by providing the informative concepts and taxonomy on big data sensing and services. The paper not only discusses the motivation, research scope, and features of big data sensing and services, but also exams the required services in big data sensing based on the state-of-the-art research work. Moreover, the paper discusses big data sensing challenges, issues, and needs.

Electronic ceramics based on polycrystalline SnO2, TiO2 and (Sn xTi1-x)O2 solid solution

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Developed and studies on technical and economical viability of an environmental efficient urinal

This work introduces an innovative urinal for public convenience, that promotes at the same time water reuse and personal higiene, in a safe and economical way . Furthermore it demonstrates the latest technology and its technical and economical viabillity of utilization in new and already existing buildings facilities. This new model of personal higiene equipment offers as main benefits the improved economy with subsequent decrease in drinkable water consumption, sanitary safety, low cost and easy installation due to its simplicity and to the fact that it can be installed in already existing facilities. The proposal is constituted by a higienic, ecological and smart system for flushing of public urinals. It is a conjugated system of lavatory and urinal that reuses hands higienization water from the lavatory for flushing purpose. The proposed urinal can be operated manually or automatically by means of a presential sensor. The system promotes drinkable water economy by a rational utilization by avoiding the use of waste water from hand washing in place of clean water for flushing. The proposed equipment increases the economy of clean water in a simple and economical way and it can be installed in any type of public lavatory facilitie such as schools, public buildings, hospitals, commercial buildings, bus terminals, airports, stadiums, parking buildings and shopping centers. Additional benefits of the proposed system is the suggestion of hands washing before and after the use of the urinal without contamination risks from focet handling.and render more attractive the installation for a rational use of clean water in commercial and industrial buildings. Pay-back has shown to be very attractive for a number of internal return rates and also very attractive from the point of view of environmental protection.

Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.

Force sensing for measuring human body movement

The research developed in this thesis explores the sensing and inference of human movement in a dynamic way, as opposed to conventional measurement systems, that are only concerned with discrete evaluations of stimuli in sequential time. Typically, conventional approaches are used to infer the dynamic movement of the body; such as vision and motion tracking devices, with either a human diagnosis or complex image processing algorithm to classify the movement. This research is therefore the first of its kind to attempt and provide a movement classifying algorithm through the use of minimal sensing points, with the application for this novel system, to classify human movement during a golf swing. There are two main categories of force sensing. Firstly, array-type systems consisting of many sensing elements, and are the most commonly researched and commercially available. Secondly, reduced force sensing element systems (RFSES) also known as distributive systems have only been recently exploited in the academic world. The fundamental difference between these systems is that array systems handle the data captured from each sensor as unique outputs and suffer the effects of resolution. The effect of resolution, is the error in the load position measurement between sensing elements, as the output is quantized in terms of position. This can be compared to a reduced sensor element system that maximises that data received through the coupling of data from a distribution of sensing points to describe the output in discrete time. Also this can be extended to a coupling of transients in the time domain to describe an activity or dynamic movement. It is the RFSES that is to be examined and exploited in the commercial sector due to its advantages over array-based approaches such as reduced design, computational complexity and cost.

Gait Measurements and Motor Recovery after Stroke

2000 Mathematics Subject Classification: 62P10, 92C20

Bonnette de test d’optique adaptative pour l'Observatoire du Mont Mégantic

Les télescopes de grande envergure requièrent des nouvelles technologies ayant un haut niveau de maturité technologique. Le projet implique la création d’un banc de test d’optique adaptative pour l’évaluation de la performance sur le ciel de dispositifs connexes. Le banc a été intégré avec succès à l’observatoire du Mont Mégantic, et a été utilisé pour évaluer la performance d’un senseur pyramidal de front d’onde. Le système a permis la réduction effective de la fonction d’étalement du point d’un facteur deux. Plusieurs améliorations sont possibles pour augmenter la performance du système.

Distal limb osteoarthritis in the horse

The aim of this thesis was to study two objective methods of osteoarthritis (OA) diagnosis in horses and use them on the assessment of new intra-articular treatments. The studied methods were a new inertial-sensor based system of lameness detection and cartilage biomarkers in serum. It was found that distal limb flexion is significantly correlated to the presence of metacarpo-phalangeal OA in hind limbs and that inertial-sensors are sensitive in detecting asymmetry in these cases. A positive and significant correlation was observed between Coll2-1 concentration in serum and the presence of joint disease in males and young horses. Fib3-2 measurement has good potential to be used since it is not influenced by sex or age. Using an experimental model of OA, adipose stem cells pre-activated with interferon-gamma decreased joint inflammation and radiographic lesions. In clinical cases, a single injection of high-concentrated and high-molecular weight hyaluronic-acid decreased joint inflammation and biomarkers’ concentration; OSTEOARTRITE DO MEMBRO DISTAL NO CAVALO Resumo: A finalidade desta tese foi estudar dois métodos de diagnóstico objetivo de osteoartrite (OA) em equinos e aplicá-los na avaliação de novas terapias intra-articulares. Utilizou-se um sistema de sensores de movimento e foi avaliada a concentração de biomarcadores de cartilagem no soro. Concluiu-se que a flexão distal positiva está correlacionada com OA na articulação metacarpofalângica nos membros posteriores e que os sensores são sensíveis na detecção de assimetria nestes casos. Existe uma correlação positiva e significativa entre as concentrações de Coll2-1 e a presença de doença articular, sobretudo em machos e jovens. A dosagem de Fib3-2 tem utilidade por não ser influenciada pelo sexo nem idade. Num modelo experimental da doença, a terapia à base de células estaminais reduziu a inflamação articular e as lesões radiográficas. Em casos clínicos, o tratamento com ácido-hialurónico de alta concentração e peso molecular provoca uma diminuição da inflamação articular e dos biomarcadores no soro.

A lightweight balloon-carried cloud charge sensor

Despite the importance of microphysical cloud processes on the climate system, some topics are under-explored. For example, few measurements of droplet charges in nonthunderstorm clouds exist. Balloon carried charge sensors can be used to provide new measurements. A charge sensor is described for use with meteorological balloons, which has been tested over a range of atmospheric temperatures from -60 to 20 degrees C, in cloudy and clear air. The rapid time response of the sensor (to >10 V s(-1)) permits charge densities from 100 fC m(-3) to 1 nC m(-3) to be determined, which is sufficient for it to act as a cloud edge charge detector at weakly charged horizontal cloud boundaries.