933 resultados para condition monitoring system
Conditioning of incremental variational data assimilation, with application to the Met Office system
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Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.
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A two-dimensional X-ray scattering system developed around a CCD-based area detector is presented, both in terms of hardware employed and software designed and developed. An essential feature is the integration of hardware and software, detection and sample environment control which enables time-resolving in-situ wide-angle X-ray scattering measurements of global structural and orientational parameters of polymeric systems subjected to a variety of controlled external fields. The development and operation of a number of rheometers purpose-built for the application of such fields are described. Examples of the use of this system in monitoring degrees of shear-induced orientation in liquid-crystalline systems and crystallization of linear polymers subsequent to shear flow are presented.
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This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames – one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.
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This study evaluates the use of European Centre for Medium-Range Weather Forecasts (ECMWF) products in monitoring and forecasting drought conditions during the recent 2010–2011 drought in the Horn of Africa (HoA). The region was affected by a precipitation deficit in both the October–December 2010 and March–May 2011 rainy seasons. These anomalies were captured by the ERA-Interim reanalysis (ERAI), despite its limitations in representing the March–May interannual variability. Soil moisture anomalies of ERAI also identified the onset of the drought condition early in October 2010 with a persistent drought still present in September 2011. This signal was also evident in normalized difference vegetation index (NDVI) remote sensing data. The precipitation deficit in October–December 2010 was associated with a strong La Niña event. The ECMWF seasonal forecasts for the October–December 2010 season predicted the La Niña event from June 2010 onwards. The forecasts also predicted a below-average October–December rainfall, from July 2010 onwards. The subsequent March–May rainfall anomaly was only captured by the new ECWMF seasonal forecast system in the forecasts starting in March 2011. Our analysis shows that a recent (since 1999) drying in the region during the March–May season is captured by the new ECMWF seasonal forecast system and is consistent with recently published results. The HoA region and its population are highly vulnerable to future droughts, thus global monitoring and forecasting of drought, such as that presented here, will become increasingly important in the future. Copyright © 2012 Royal Meteorological Society
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Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.
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Considerable efforts are currently invested into the setup of a Global Climate Observing System (GCOS) for monitoring climate change over the coming decades, which is of high relevance given concerns on increasing human influences. A promising potential contribution to the GCOS is a suite of spaceborne Global Navigation Satellite System (GNSS) occultation sensors for global long-term monitoring of atmospheric change in temperature and other variables with high vertical resolution and accuracy. Besides the great importance with respect to climate change, the provision of high quality data is essential for the improvement of numerical weather prediction and for reanalysis efforts. We review the significance of GNSS radio occultation sounding in the climate observations context. In order to investigate the climate change detection capability of GNSS occultation sensors, we are currently performing an end-to-end GNSS occultation observing system simulation experiment over the 25-year period 2001 to 2025. We report on this integrated analysis, which involves in a realistic manner all aspects from modeling the atmosphere via generating a significant set of stimulated measurements to an objective statistical analysis and assessment of 2001–2025 temporal trends.
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In any wide-area distributed system there is a need to communicate and interact with a range of networked devices and services ranging from computer-based ones (CPU, memory and disk), to network components (hubs, routers, gateways) and specialised data sources (embedded devices, sensors, data-feeds). In order for the ensemble of underlying technologies to provide an environment suitable for virtual organisations to flourish, the resources that comprise the fabric of the Grid must be monitored in a seamless manner that abstracts away from the underlying complexity. Furthermore, as various competing Grid middleware offerings are released and evolve, an independent overarching monitoring service should act as a corner stone that ties these systems together. GridRM is a standards-based approach that is independent of any given middleware and that can utilise legacy and emerging resource-monitoring technologies. The main objective of the project is to produce a standardised and extensible architecture that provides seamless mechanisms to interact with native monitoring agents across heterogeneous resources.
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Monitoring resources is an important aspect of the overall efficient usage and control of any distributed system. In this paper, we describe a generic open-source resource monitoring architecture that has been specifically designed for the Grid. The paper consists of three main sections. In the first section, we outline our motivation and briefly detail similar work in the area. In the second section, we describe the general monitoring architecture and its components. In the final section of the paper, we summarise the experiences so far and outline our future work.
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In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.
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Large changes in the extent of northern subtropical arid regions during the Holocene are attributed to orbitally forced variations in monsoon strength and have been implicated in the regulation of atmospheric trace gas concentrations on millenial timescales. Models that omit biogeophysical feedback, however, are unable to account for the full magnitude of African monsoon amplification and extension during the early to middle Holocene (˜9500–5000 years B.P.). A data set describing land-surface conditions 6000 years B.P. on a 1° × 1° grid across northern Africa and the Arabian Peninsula has been prepared from published maps and other sources of palaeoenvironmental data, with the primary aim of providing a realistic lower boundary condition for atmospheric general circulation model experiments similar to those performed in the Palaeoclimate Modelling Intercomparison Project. The data set includes information on the percentage of each grid cell occupied by specific vegetation types (steppe, savanna, xerophytic woods/scrub, tropical deciduous forest, and tropical montane evergreen forest), open water (lakes), and wetlands, plus information on the flow direction of major drainage channels for use in large-scale palaeohydrological modeling.
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The present study investigated whether developmental changes in cognitive control may underlie improvements of time-based prospective memory. Five-, 7-, 9-, and 11-year-olds (N = 166) completed a driving simulation task (ongoing task) in which they had to refuel their vehicle at specific points in time (PM task). The availability of cognitive control resources was experimentally manipulated by imposing a secondary task that required divided attention. Children completed the driving simulation task both in a full attention condition and a divided attention condition where they had to carry out a secondary task. Results revealed that older children performed better than younger children on the ongoing task and PM task. Children performed worse on the ongoing and PM tasks in the divided attention condition compared to the full attention condition. With respect to time monitoring in the final interval prior to the PM target, divided attention interacted with age such that older children’s time monitoring was more negatively affected by the secondary task compared to younger children. Results are discussed in terms of developmental shifts from reactive to proactive monitoring strategies.
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In this paper we investigate the equilibrium properties of magnetic dipolar (ferro-) fluids and discuss finite-size effects originating from the use of different boundary conditions in computer simulations. Both periodic boundary conditions and a finite spherical box are studied. We demonstrate that periodic boundary conditions and subsequent use of Ewald sum to account for the long-range dipolar interactions lead to a much faster convergence (in terms of the number of investigated dipolar particles) of the magnetization curve and the initial susceptibility to their thermodynamic limits. Another unwanted effect of the simulations in a finite spherical box geometry is a considerable sensitivity to the container size. We further investigate the influence of the surface term in the Ewald sum-that is, due to the surrounding continuum with magnetic permeability mu(BC)-on the convergence properties of our observables and on the final results. The two different ways of evaluating the initial susceptibility, i.e., (1) by the magnetization response of the system to an applied field and (2) by the zero-field fluctuation of the mean-square dipole moment of the system, are compared in terms of speed and accuracy.
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In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.
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This paper describes the hydrochemistry of a lowland, urbanised river-system, The Cut in England, using in situ sub-daily sampling. The Cut receives effluent discharges from four major sewage treatment works serving around 190,000 people. These discharges consist largely of treated water, originally abstracted from the River Thames and returned via the water supply network, substantially increasing the natural flow. The hourly water quality data were supplemented by weekly manual sampling with laboratory analysis to check the hourly data and measure further determinands. Mean phosphorus and nitrate concentrations were very high, breaching standards set by EU legislation. Though 56% of the catchment area is agricultural, the hydrochemical dynamics were significantly impacted by effluent discharges which accounted for approximately 50% of the annual P catchment input loads and, on average, 59% of river flow at the monitoring point. Diurnal dissolved oxygen data demonstrated high in-stream productivity. From a comparison of high frequency and conventional monitoring data, it is inferred that much of the primary production was dominated by benthic algae, largely diatoms. Despite the high productivity and nutrient concentrations, the river water did not become anoxic and major phytoplankton blooms were not observed. The strong diurnal and annual variation observed showed that assessments of water quality made under the Water Framework Directive (WFD) are sensitive to the time and season of sampling. It is recommended that specific sampling time windows be specified for each determinand, and that WFD targets should be applied in combination to help identify periods of greatest ecological risk. This article is protected by copyright. All rights reserved.
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The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.