Determination of Cloud Motion Applying the Lucas-Kanade Method to Sky Cam Imagery

The atmospheric conditions existing where concentrated solar power plants (CSP) are installed need to be carefully studied. A very important reason for this is because the presence of clouds causes drops in electricity generated from solar energy. Therefore, forecasting the cloud displacement trajectory in real time is one of the functions and tools that CSP operators must develop for plant optimization, and to anticipate drops in solar irradiance. For short forecast of cloud movement (10 min) is enough with describe the cloud advection while for longer forecast (over 15 min), it is necessary to predict both advection and cloud changes. In this paper, we present a model that predict only the cloud advection displacement trajectory for different sky conditions and cloud types at the pixel level, using images obtained from a sky camera, as well as mathematical methods and the Lucas-Kanade method to measure optical flow. In the short term, up to 10 min the future position of the cloud front is predicted with 92% certainty while for 25–30 min, the best predicted precision was 82%

The state-of-the-art progress in cloud detection, identification, and tracking approaches: a systematic review

A cloud is a mass of water vapor floating in the atmosphere. It is visible from the ground and can remain at a variable height for some time. Clouds are very important because their interaction with the rest of the atmosphere has a decisive influence on weather, for instance by sunlight occlusion or by bringing rain. Weather denotes atmosphere behavior and is determinant in several human activities, such as agriculture or energy capture. Therefore, cloud detection is an important process about which several methods have been investigated and published in the literature. The aim of this paper is to review some of such proposals and the papers that have been analyzed and discussed can be, in general, classified into three types. The first one is devoted to the analysis and explanation of clouds and their types, and about existing imaging systems. Regarding cloud detection, dealt with in a second part, diverse methods have been analyzed, i.e., those based on the analysis of satellite images and those based on the analysis of images from cameras located on Earth. The last part is devoted to cloud forecast and tracking. Cloud detection from both systems rely on thresholding techniques and a few machine-learning algorithms. To compute the cloud motion vectors for cloud tracking, correlation-based methods are commonly used. A few machine-learning methods are also available in the literature for cloud tracking, and have been discussed in this paper too

Can geoengineering be optimised?

Geoengineering is the intentional, large-scale manipulation of Earth’s climate. It has been suggested that this could be done to counteract or ameliorate the effects of anthropogenic climate change, to reduce its negative impacts or buy time for global greenhouse gas emissions to be reduced. Stratospheric aerosol injection, where aerosols in the stratosphere are used to reflect sunlight and so cool climate, has been widely studied. Altering the altitude, latitude, or timing of aerosol injections could result in different radiative forcing patterns, which suggests there may be potential to “optimise” stratospheric aerosol injection geoengineering to achieve particular climate goals. The extent to which geoengineering could be optimised, beyond idealised studies that counteract the global mean temperature increase of greenhouse gases, has only relatively recently begun to be explored. Chapter 1 discusses the background of geoengineering as a concept and includes a literature review and discussion of robust results that have emerged from modelling studies of geoengineering. Chapter 2 uses a combination of analytical techniques and the simple climate model, FaIR, to examine different scenarios for “peak-shaving” – temporarily using geoengineering to hold global mean temperatures below a certain threshold – and examines trade-offs between the amount of warming avoided and the implied duration of commitment to geoengineering. Chapters 3-5 analyse simulations from the HadCM3 climate model, simulated using climateprediction.net, which uses thousands of volunteer computers to generate large ensembles of simulations with differing distributions of stratospheric aerosol optical depth counteracting an abrupt quadrupling of carbon dioxide to represent different attempts at tailoring geoengineering. Chapter 3 details initial calibration and characterisation of the response to simple patterns of radiative forcing, and establishes that the temperature response to different patterns of forcing is, to a good approximation, linear and additive. Chapter 4 expands on this and discusses various methods for optimising for temperature and precipitation, including analysis of trade-offs for attempting to optimise temperature in different regions, and analysis of whether there are a limited number of fundamental modes of response in the HadCM3 climate model to a range of imposed radiative forcing patterns. Chapter 5 examines the impact of geoengineering on climate and weather extremes, using metrics that represent heatwaves, flooding, and dry periods, and analysing any differences in the distribution of extreme events between simulations of the preindustrial and geoengineered climates. In the final chapter, results and conclusions are summarised, and possible future work is outlined

The characterisation and simulation of 3D vision sensors for measurement optimisation

The use of 3D Vision is becoming increasingly common in a range of industrial applications including part identification, reverse engineering, quality control and inspection. To facilitate this increased usage, especially in autonomous applications such as free-form assembly and robotic metrology, the capability to deploy a sensor to the optimum pose for a measurement task is essential to reduce cycle times and increase measurement quality. Doing so requires knowledge of the 3D sensor capabilities on a material specific basis, as the optical properties of a surface, object shape, pose and even the measurement itself have severe implications for the data quality. This need is not reflected in the current state of sensor haracterisation standards which commonly utilise optically compliant artefacts and therefore can not inform the user of a 3D sensor the realistic expected performance on non-ideal objects.This thesis presents a method of scoring candidate viewpoints for their ability to perform geometric measurements on an object of arbitrary surface finish. This is achieved by first defining a technology independent, empirical sensor characterisation method which implements a novel variant of the commonly used point density point cloud quality metric, which is normalised to isolate the effect of surface finish on sensor performance, as well as the more conventional assessment of point standard deviation. The characterisation method generates a set of performance maps for a sensor per material which are a function of distance and surface orientation. A sensor simulation incorporates these performance maps to estimate the statistical properties of a point cloud on objects with arbitrary shape and surface finish, providing the sensor has been characterised on the material in question.A framework for scoring measurement specific candidate viewpoints is presented in the context of the geometric inspection of four artefacts with different surface finish but identical geometry. Views are scored on their ability to perform each measurement based on a novel view score metric, which incorporates the expected point density, noise and occlusion of measurement dependent model features. The simulation is able to score the views reliably on all four surface finishes tested, which range from ideal matt white to highly polished aluminium. In 93% of measurements, a set of optimal or nearly optimal views is correctly selected.</div

The spatial distribution of haze over the Bojanala District

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science. Johannesburg, 2015.The air quality over the Bojanala District has been identified as an area of concern. The Bojanala Platinum District falls within the Waterberg Priority Area, which was declared as a priority area for air quality in 2012. This study was conducted in the southern part of the Bojanala district to identify the spatial and temporal distribution of aerosols over the district. Aerosol optical thickness and Ångstrom exponent were derived using data retrieved from direct solar radiation measurements using hazemeters during winter 2008, early winter 2009 and late winter 2010. Results of the study reveal that aerosol loadings differ significantly as winter progresses. AOT levels are found to be considerably higher during winter and late winter, compared with the early winter campaign. Diurnal variation during the late winter campaign is found to be very similar to that of the early winter campaign, with little variation in aerosol loadings and characteristics during the day; while the winter 2008 campaign reveals a significant decreasing trend in AOT and Ångstrom exponent as the day progresses. The AOT and Ångstrom exponent levels for the different campaigns, local sources and the diurnal trends identified assist in the attribution of domestic fuel burning practices; and the concentration of pollutants emitted in the area by inversion layers to the characteristics of the aerosol loadings during winter. The high AOT and contribution of fine mode particles during late winter is attributed to the onset of the biomass burning season. The importance of industrial sources to the aerosol loadings is clear during all three campaigns; however, it is clear that aerosols at different levels in the atmosphere have a significant impact on AOT over the district. The vertical distribution of aerosols is explored through the use of trajectories and associated surface wind roses which indicate that foreign airmasses from the Mpumalanga Highveld and the Atlantic Ocean clearly have a significant impact on the aerosol loadings over the Bojanala District and are associated with extremes in AOT levels. Further, spatial analysis reveals that the highest concentrations of aerosols (associated with larger particles) are identified toward the eastern side of the district except during late winter. It is probable that the aerosols in the Bojanala District may have a significant regional climatic impact which requires further investigation

Gas in engine cooling systems: occurrence, effects and mitigation

The presence of gas in engine liquid cooling systems can have severe consequences for engine efficiency and life. The presence of stagnant, trapped gases will result in cooling system hotspots, causing gallery wall degradation through thermal stresses, fatigue and eventual cracking. The presence of entrained, transient gases in the coolant flow will act to reduce its bulk thermal properties and the performance of the system s coolant pump; critically the liquid flow rate, which will severely affect heat transfer throughout the engine and its ancillaries. The hold-up of gas in the pump s impeller may cause the dynamic seal to run dry, without lubrication or cooling. This poses both an immediate failure threat should the seal overheat and rubber components melt and a long term failure threat from intermittent quench cooling, which causes deposit formation on sealing faces acting to abrade and reduce seal quality. Bubbles in the coolant flow will also act as nucleation sites for cavitation growth. This will reduce the Net Positive Suction Head available (NPSHA) in the coolant flow, exacerbating cavitation and its damaging effects in locations such as the cylinder cooling liners and the pump s impeller. This thesis has analysed the occurrence of trapped gas (air) during the coolant filling process, its behaviour and break-up at engine start, the two-phase character of the coolant flow these processes generate and the effects it has on coolant pump performance. Optical and parametric data has been acquired in each of these studies, providing an understanding of the physical processes occurring, key variables and a means of validating numerical (CFD) code of integral processes. From the fundamental understanding each study has provided design rules, guidelines and validated tools have been developed, helping cooling system designers minimise the occurrence of trapped air during coolant filling, promote its breakup at engine start and to minimise its negative effects in the centrifugal coolant pump. It was concluded that whilst ideally the prevention of cooling system gases should be achieved at source, they are often unavoidable. This is due to the cost implications of finding a cylinder head gasket capable of completely sealing in-cylinder combustion pressures, the regular use of nucleate boiling regimes for engine cooling and the need to design cooling channel geometries to cool engine components and not necessarily to avoid fill entrapped air. Using the provided rules and models, it may be ensured stagnant air is minimised at source and avoided whilst an engine is running. However, to abate the effects of entrained gases in the coolant pump through redesign is undesirable due to the negative effects such changes have on a pump s efficiency and cavitation characteristics. It was concluded that the best solution to entrained gases, unavoidable at source, is to remove them from the coolant flow entirely using phase separation device(s)

Understanding Structure and Function in Semiarid Ecosystems: Implications for Terrestrial Carbon Dynamics in Drylands

This study advances understanding of how the changes in ecosystem structure and function associated with woody shrub encroachment in semi-arid grasslands alter ecosystem carbon (C) dynamics. In terms of both magnitude and dynamism, dryland ecosystems represent a major component of the global C cycle. Woody shrub encroachment is a widespread phenomenon globally, which is known to substantially alter ecosystem structure and function, with resultant impacts on C dynamics. A series of focal sites were studied at the Sevilleta National Wildlife Refuge in central New Mexico, USA. A space-for-time analogue was used to identify how landscape structure and function change at four stages over a grassland to shrubland transition. The research had three key threads: 1. Soil-associated carbon: Stocks of organic and inorganic C in the near-surface soil, and the redistribution of these C stocks by erosion during high-intensity rainfall events were quantified using hillslope-scale monitoring plots. Coarse (>2 mm) clasts were found to account for a substantial proportion of the organic and inorganic C in these calcareous soils, and the erosional effluxes of both inorganic and organic C increased substantially across the vegetation ecotone. Eroded sediment was found to be significantly enriched in organic C relative to the contributing soil with systematic changes in OC enrichment across the vegetation transition. The OC enrichment dynamics observed were inconsistent with existing understanding (derived largely from reductionist, laboratory-based experiments) that OC enrichment is largely insignificant in the erosional redistribution of C. 2. Plant biomass: Cutting-edge proximal remote sensing approaches, using a remotely piloted lightweight multirotor drone combined with structure-from-motion (SfM) photogrammetry were developed and used to quantify biomass carbon stocks at the focal field sites. In such spatially heterogeneous and temporally dynamic ecosystems existing measurement techniques (e.g. on-the-ground observations or satellite- or aircraft-based remote sensing) struggle to capture the complexity of fine-grained vegetation structure, which is crucial for accurately estimating biomass. The data products available from the novel SfM approach developed for this research quantified plants just 15 mm high, achieving a fidelity nearly two orders of magnitude finer than previous implementations of the method. The approach developed here will revolutionise the study of biomass dynamics in short-sward ecogeomorphic systems. 3. Ecohydrological modelling: Understanding the effects of water-mediated degradation processes on ecosystem carbon dynamics over greater than observable spatio-temporal scales is complicated by significant scale-dependencies and thus requires detailed mechanistic understanding. A process-based, spatially-explicit ecohydrological modelling approach (MAHLERAN - Model for Assessing Hillslope to Landscape Erosion, Runoff and Nutrients) was therefore comprehensively evaluated against a large assemblage of rainfall runoff events. This evaluation highlighted both areas of strength in the current model structure, and also areas of weakness for further development. The research has improved understanding of ecosystem degradation processes in semi-arid rangelands, and demonstrates that woody shrub encroachment may lead to a long-term reduction in ecosystem C storage, which is contrary to the widely promulgated view that woody shrub encroachment increases C storage in terrestrial ecosystems.NERC Doctoral Training Grant (NE/K500902/1)NSF Long Term Ecological Research Program at the Sevilleta National Wildlife Refuge (DEB-1232294

Spatio-temporal and structural analysis of vegetation dynamics of Lowveld Savanna in South Africa

Savanna vegetation structure parameters are important for assessing the biomes status under various disturbance scenarios. Despite free availability remote sensing data, the use of optical remote sensing data for savanna vegetation structure mapping is limited by sparse and heterogeneous distribution of vegetation canopy. Cloud and aerosol contamination lead to inconsistency in the availability of time series data necessary for continuous vegetation monitoring, especially in the tropics. Long- and medium wavelength microwave data such as synthetic aperture radar (SAR), with their low sensitivity to clouds and atmospheric aerosols, and high temporal and spatial resolution solves these problems. Studies utilising remote sensing data for vegetation monitoring on the other hand, lack quality reference data. This study explores the potential of high-resolution TLS-derived vegetation structure variables as reference to multi-temporal SAR datasets in savanna vegetation monitoring. The overall objectives of this study are: (i) to evaluate the potential of high-resolution TLS-data in extraction of savanna vegetation structure variables; (ii) to estimate landscape-wide aboveground biomass (AGB) and assess changes over four years using multi-temporal L-band SAR within a Lowveld savanna in Kruger National Park; and (iii) to assess interactions between C-band SAR with various savanna vegetation structure variables. Field inventories and TLS campaign were carried out in the wet and dry seasons of 2015 respectively, and provided reference data upon which AGB, CC and cover classes were modelled. L-band SAR modelled AGB was used for change analysis over 4 years, while multitemporal C-band SAR data was used to assess backscatter response to seasonal changes in CC and AGB abundant classes and cover classes. From the AGB change analysis, on average 36 ha of the study area (91 ha) experienced a loss in AGB above 5 t/ha over 4 years. A high backscatter intensity is observed on high abundance AGB, CC classes and large trees as opposed to low CC and AGB abundance classes and small trees. There is high response to all structure variables, with C-band VV showing best polarization in savanna vegetation mapping. Moisture availability in the wet season increases backscatter response from both canopy and background classes

Entropy production and the climate

The entropy production rate of the climate is a topic of active study but ongoing confusion, spurred by the yet-unproven hypothesis that the climate system might be organising itself to maximise its entropy production rate and, more broadly, the potential of probing our climate from unorthodox simplifying perspectives. In this thesis, a re-examination of some fundamentals in this topic is offered. Two main suggestions for a climate-relevant global entropy production rate have been established in the literature: one which focuses on non-radiative processes only (labelled 'material') and one which includes all radiative and non-radiative processes (labelled 'planetary'). Another physically-motivated entropy production rate is introduced and investigated here -- the transfer entropy production rate -- which distinguishes radiation according to the role it plays within the system, considering only entropy production due to those transfers of energy which occur within the climate. Various lines of reasoning and evidence point towards the new rate being physically meaningful, which is significant especially as it offers a re-interpretation of the entropy production optimisation hypothesis. Next, the response of entropy production rates to changing climate conditions is investigated and the results used to verify a simple conceptual model capable of predicting the direction of the changes. The transfer and material entropy production rates are found to be significantly more responsive than the planetary rate to the climate's state and they both are able to resolve changes which surface temperature cannot: a simple solar radiation management scenario is found to be able to restore global average surface temperature but not the entropy production rates. Finally, the measurement of the entropy production budget via radiation information in observational and GCM datasets is explored. A new method for accounting for entropy storage in the recently published CERES SYN1deg entropy flux dataset is demonstrated, which makes it possible to estimate the material and transfer entropy production rates from that dataset. This reveals that the transfer and material entropy production rates have increased in line with temperature over the past 20 years and that entropy production rates are higher in years with higher solar absorption. Furthermore, there is a hemispheric asymmetry of entropy production, with more occurring in the Northern hemisphere. The global mean material entropy production rate is 55.3 mW/m^2K and the transfer entropy production rate, 82.0 mW/m^2K in that dataset between March 2000 and February 2018. As a whole, this investigation deepens our understanding of entropy production in the climate and offers new definitions, frameworks and observed patterns to stimulate further research.Open Acces