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PREDPOL: Um modelo de previsão da maturação da cana-de-açúcar visando planejamento otimizado; PREDPOL: A forecast model of sugarcane maturation seeking optimized planning

Scarpari, Maximiliano Salles
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 25/04/2007 PT
Relevância na Pesquisa
36.2%
A cultura da cana-de-açúcar é submetida durante o seu desenvolvimento a diferentes condições ambientais e de manejo sendo a maturação afetada diretamente por estas condições. Destas condições, surge a necessidade de se quantificar as respostas da cultura aos diferentes estímulos para fins de planejamento. Modelos de previsão da qualidade da matéria-prima tornamse ferramentas importantes na lavoura canavieira, em especial a previsão da curva de acúmulo de sacarose nos colmos, objetivando suprir estimativas de rendimento ao longo da safra, visando à caracterização das alternativas de manejo, aumentando a eficácia das decisões gerenciais e estratégicas. Os objetivos deste trabalho foram desenvolver modelos empíricos capazes de obter estimativas de ATR - Açúcar Total Recuperável nas variedades RB 72 454, RB 85 5156, RB 85 5536, SP 81-3250 e SP 80-1842 ao longo da safra, utilizando dados referentes aos fatores de produção, gerando uma ferramenta que auxilie a tomada de decisão e o planejamento estratégico; medir a variação espaço-temporal do IAF - índice de área foliar e o ATR das variedades RB 85 5156 e SP 80-3280 ao longo de um ciclo para calibração do modelo, simulando os demais; confirmar e relacionar a influência do armazenamento disponível...

Previsão de chuva com auxílio de radar de tempo visando a um sistema de alerta antecipado de cheias em áreas urbanas; Precipitation forecast aided by weather radar for early warning system of urban floods

Gonçalves, Micheli Fernandes
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 19/06/2009 PT
Relevância na Pesquisa
46.37%
Para reduzir as perdas humanas e materiais durante as inundações, é possível realizar estudo conciso da previsão de chuva, etapa principal de um sistema de alerta antecipado de inundação. O uso de informações de radar de tempo, quando acopladas a modelos de previsão de precipitação baseados fisicamente, pode contribuir para o monitoramento e previsão de episódios de chuva intensa. Desta forma, a previsão de chuva, baseada no uso de informações de radar, juntamente com um modelo conceitual de previsão hidrometeorológica, foi descrita neste trabalho. Teve-se por objetivo aperfeiçoar as previsões de chuva de curtíssimo prazo (poucos minutos), que acopladas a um modelo chuva-vazão, podem ser usadas em sistemas de alerta antecipado. O modelo hidrometeorológico adotado, que considera uma nuvem hipotética unidimensional vertical, foi inicialmente desenvolvido por Georgakakos e Bras (1984a) e ampliado, neste trabalho. Para tal, adotou-se o uso das informações de Topo dos Ecos para determinação da altura das nuvens e considerou-se que a componente do modelo relativa à massa de água líquida no interior da nuvem corresponde à estimativa do conteúdo de água líquida integrado verticalmente (VIL) efetuada por radar. Para eventos de natureza frontal quente e convectiva...

Verificação da previsão do tempo em São Paulo com o modelo operacional WRF; Review of weather in São Paulo with the WRF Operational Model.

Bender, Fabiani Denise
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 01/11/2012 PT
Relevância na Pesquisa
36.45%
Este estudo tem como objetivo a verificação das previsões diárias, das temperaturas máxima e mínima e precipitação acumulada, realizadas pelo modelo operacional de previsão numérica do tempo WRF (Weather Research Forecasting) para o estado de São Paulo. As condições iniciais e de fronteira fornecidas pela análise e previsão das 00UTC do modelo Global Forecast System (GFS), são usados no processamento do WRF, para previsões de 72 horas, em duas grades aninhadas (espaçamentos horizontais de grade de 50 km, D1, e 16,6 km, D2). O período avaliado foi de abril de 2010 a março de 2011. As comparações diárias das temperaturas máxima e mínima foram realizadas entre os valores preditos e observados nas estações de superfície de Registro, São Paulo, Paranapanema, Campinas, Presidente Prudente e Votuporanga (dados da CIIAGRO); através do erro médio (EM) e raiz do erro médio quadrático (REQM), para os prognósticos das 36, 60 e 72 horas. A precipitação acumulada diária é avaliada com relação ao produto MERGE, pela aplicação da ferramenta MODE, na previsão das 36 horas, para um limiar de 0,3 mm, no domínio espacial abrangendo o Estado de São Paulo e vizinhanças. Primeiramente, fez-se uma análise, comparando os pares de grade dos campos previsto e observado...

Subsídios à operação de reservatórios baseada na previsão de variáveis hidrológicas

Bravo, Juan Martín
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Tese de Doutorado Formato: application/pdf
POR
Relevância na Pesquisa
36.48%
Diversas atividades humanas são fortemente dependentes do clima e da sua variabilidade, especialmente aquelas relacionadas ao uso da água. A operação integrada de reservatórios com múltiplos usos requer uma série de decisões que definem quanta água deve ser alocada, ao longo do tempo para cada um dos usos, e quais os volumes dos reservatórios a serem mantidos. O conhecimento antecipado das condições climáticas resulta de vital importância para os operadores de reservatórios, pois o insumo dos reservatórios é a vazão dos rios, que por sua vez é dependente de condições atmosféricas e hidrológicas em diferentes escalas de tempo e espaço. A pesquisa trata sobre três importantes elementos de subsídio à tomada de decisão na operação de reservatórios baseada na previsão de variáveis hidrológicas: (a) as previsões de vazão de curto prazo; (b) as previsões de precipitação de longo prazo e (c) as medidas de desempenho das previsões. O reservatório de Furnas, localizado na bacia do Rio Grande, em Minas Gerais, foi selecionado como estudo de caso devido, principalmente, à disponibilidade de previsões quantitativas de chuva e pela importância desse reservatório na região analisada. A previsão de curto prazo de vazão com base na precipitação foi estimada com um modelo empírico (rede neural artificial) e a previsão de precipitação foi obtida pelo modelo regional ETA. Uma metodologia de treinamento e validação da rede neural artificial foi desenvolvida utilizando previsões perfeitas de chuva (considerando a chuva observada como previsão) e utilizando o maior número de dados disponíveis...

Dynamic load-balancing : a new strategy for weather forecast models

Rodrigues, Eduardo Rocha
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Tese de Doutorado Formato: application/pdf
ENG
Relevância na Pesquisa
86.4%
Weather forecasting models are computationally intensive applications and traditionally they are executed in parallel machines. However, some issues prevent these models from fully exploiting the available computing power. One of such issues is load imbalance, i.e., the uneven distribution of load across the processors of the parallel machine. Since weather models are typically synchronous applications, that is, all tasks synchronize at every time-step, the execution time is determined by the slowest task. The causes of such imbalance are either static (e.g. topography) or dynamic (e.g. shortwave radiation, moving thunderstorms). Various techniques, often embedded in the application’s source code, have been used to address both sources. However, these techniques are inflexible and hard to use in legacy codes. In this thesis, we explore the concept of processor virtualization for dynamically balancing the load in weather models. This means that the domain is over-decomposed in more tasks than the available processors. Assuming that many tasks can be safely executed in a single processor, each processor is put in charge of a set of tasks. In addition, the system can migrate some of them from overloaded processors to underloaded ones when it detects load imbalance. This approach has the advantage of decoupling the application from the load balancing strategy. Our objective is to show that processor virtualization can be applied to weather models as long as an appropriate strategy for migrations is used. Our proposal takes into account the communication pattern of the application in addition to the load of each processor. In this text...

Avaliação dos dados decendiais de precipitação e temperatura máxima e mínima do ar simulados pelo modelo ECMWF para o estado de São Paulo

Moraes, Rafael Aldighieri; Rocha, Jansle Vieira; de Souza Rolim, Glauco; Lamparelli, Rubens Augusto Camargo; Martins, Marcel Motta
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 397-407
ENG; POR
Relevância na Pesquisa
36.27%
The weather and climate has a direct influence in agriculture, it affects all stages of farming, since soil preparation to harvest. Meteorological data derived from automatic or conventional weather stations are used to monitor these effects. These meteorological data has problems like difficulty of data access and low density of meteorological stations in Brazil. Meteorological data from atmospheric models, such as ECMWF (European Center for Medium-Range Weather Forecast) can be an alternative. Thus, the aim of this study was to compare 10-day period precipitation, maximum and minimum air temperature data from the ECMWF model with interpolated maps from 33 weather stations in Sao Paulo state between 2005 and 2010 and generate statistical maps pixel by pixel. Statistical index showed spatially satisfactory (most of the results with R 2 > 0.60, d > 0.7, RMSE < 5°C and < 50 mm; Es < 5°C and < 24 mm) in period and ECMWF model can be recommended for use in the Sao Paulo state.; A agricultura possui dependência direta das condições do tempo e do clima. Estas afetam todas as etapas das atividades agrícolas, desde o preparo do solo até a colheita. De modo a acompanhar estes efeitos, são utilizados dados meteorológicos, que são provenientes de estações automáticas ou convencionais. Devido à dificuldade de acesso aos dados em tempo quase-real...

Sistemática das estimativas da água precipitável e modelos de mesoescala

Yamasaki, Yoshihiro
Fonte: Universidade de Aveiro Publicador: Universidade de Aveiro
Tipo: Tese de Doutorado
POR
Relevância na Pesquisa
36.22%
O estado da arte dos modelos de previsão numérica e o continuamente crescente aumento da performance dos computadores permitem processar modelos de previsão do tempo em escalas espaciais e temporais muito altas. Em um futuro próximo espera-se, até mesmo, que permitam processa-los com a simulação numérica explícita da convecção da umidade. Entretanto, ressalta-se que a convecção é um processo dinâmico intrinsecamente caótico, com predictabilidade limitada, que impõe severas limitações devidas, entre outras que ainda são desconhecidas, a natureza dos espalhamentos e ocorrências imprevisíveis das células convectivas. Inúmeros são os parâmetros meteorológicos que podem ser produzidos com o processamento de modelos de previsão de tempo. Eles podem ser obtidos como resultados diretos do modelo ou serem determinados mediante o emprego de equações diagnósticas apropriadas. Além disso, são igualmente vários os meios disponíveis para análise para fins de emissão de uma previsão de tempo, pois estas têm grande dependência da escala espacial e temporal do modelo. Os modelos de previsão de tempo com grande resolução espacial, que vêm sendo crescentemente utilizados, são os modelos desenvolvidos com tecnologias que permitem prever precipitação de escala meso-beta e tempo superior até mesmo de 48 horas de antecedência. Entretanto...

Application of statistical correction in extended weather forecasting in the southern region of Brazil

Avila,Ana Maria Heuminski de; Cardoso,Andrea de Oliveira
Fonte: Sociedade Brasileira de Meteorologia Publicador: Sociedade Brasileira de Meteorologia
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2012 EN
Relevância na Pesquisa
46.3%
Adverse weather conditions in critical periods of vegetative plant growth affect crop productivity, being a fundamental parameter for yield forecast. An increase in weather forecasting accuracy may be obtained by applying statistical correction to remove model bias. This study used statistical correction of ensemble forecasting with the atmospheric general circulation model (Center for Weather Forecasting and Climate Studies/Center for Ocean - Land - Atmosphere Studies - CPTEC/COLA) by mean error removal for three cities in the South of Brazil. Comparisons were made between corrected and original precipitation forecasts, and between these and data observed at their respective meteorological stations. Results showed that the applied statistical correction method may improve forecasting performance in some situations and that the term of forecast present high accuracy, indicating the importance of ensemble forecasting as an auxiliary tool in agricultural crop monitoring.

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Publicado em 02/01/2014 EN
Relevância na Pesquisa
46.34%
The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China...

Human-Centered Systems Analysis of Aircraft Separation from Adverse Weather

Vigeant-Langlois, Laurence; Hansman, R. John
Fonte: MIT - Massachusetts Institute of Technology Publicador: MIT - Massachusetts Institute of Technology
Tipo: Relatório Formato: 5924237 bytes; application/pdf
Relevância na Pesquisa
36.44%
Adverse weather significantly impacts the safety and efficiency of flight operations. Weather information plays a key role in mitigating the impact of adverse weather on flight operations by supporting air transportation decision-makers’ awareness of operational and mission risks. The emergence of new technologies for the surveillance, modeling, dissemination and presentation of information provides opportunities for improving both weather information and user decision-making. In order to support the development of new weather information systems, it is important to understand this complex problem thoroughly. This thesis applies a human-centered systems engineering approach to study the problem of separating aircraft from adverse weather. The approach explicitly considers the role of the human operator as part of the larger operational system. A series of models describing the interaction of the key elements of the adverse aircraft-weather encounter problem and a framework that characterizes users’ temporal decisionmaking were developed. Another framework that better matches pilots’ perspectives compared to traditional forecast verification methods articulated the value of forecast valid time according to a spacetime reference frame. The models and frameworks were validated using focused interviews with ten national subject matter experts in aviation meteorology or flight operations. The experts unanimously supported the general structure of the models and made suggestions on clarifications and refinements which were integrated in the final models. In addition...

Dowscaling estocástico para extremos climáticos via interpolação espacial

Carvalho, Daniel Matos de
Fonte: Universidade Federal do Rio Grande do Norte; BR; UFRN; Programa de Pós-Graduação em Matemática Aplicada e Estatística; Probabilidade e Estatística; Modelagem Matemática Publicador: Universidade Federal do Rio Grande do Norte; BR; UFRN; Programa de Pós-Graduação em Matemática Aplicada e Estatística; Probabilidade e Estatística; Modelagem Matemática
Tipo: Dissertação Formato: application/pdf
POR
Relevância na Pesquisa
36.23%
Present day weather forecast models usually cannot provide realistic descriptions of local and particulary extreme weather conditions. However, for lead times of about a small number of days, they provide reliable forecast of the atmospheric circulation that encompasses the subscale processes leading to extremes. Hence, forecasts of extreme events can only be achieved through a combination of dynamical and statistical analysis methods, where a stable and significant statistical model based on prior physical reasoning establishes posterior statistical-dynamical model between the local extremes and the large scale circulation. Here we present the development and application of such a statistical model calibration on the besis of extreme value theory, in order to derive probabilistic forecast for extreme local temperature. The dowscaling applies to NCEP/NCAR re-analysis, in order to derive estimates of daily temperature at Brazilian northeastern region weather stations; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Os dados de reanálise de temperatura do ar e precipitação do NCEP National Centers for Environmental Predictions serão refinados para a produção dos níveis de retorno para eventos extremos nas 8 capitais do Nordeste Brasileiro - NB: São Luis...

A Space weather information service based upon remote and in-situ measurements of coronal mass ejections heading for Earth: A concept mission consisting of six spacecraft in a heliocentric orbit at 0.72 AU

Ritter, Birgit; Meskers, Arjan J. H.; Miles, Oscar; Ru??wurm, Michael; Scully, Stephen; Rold??n Aranda, Andr??s; Hartkorn, Oliver; J??stel, Peter; R??ville, Victor; Lupu, Sorina; Ruffenach, Alexis
Fonte: EDP Sciences Publicador: EDP Sciences
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
46.27%
The Earth???s magnetosphere is formed as a consequence of interaction between the planet???s magnetic field and the solar wind, a continuous plasma stream from the Sun. A number of different solar wind phenomena have been studied over the past 40 years with the intention of understanding and forecasting solar behavior. One of these phenomena in particular, Earth-bound interplanetary coronal mass ejections (CMEs), can significantly disturb the Earth???s magnetosphere for a short time and cause geomagnetic storms. This publication presents a mission concept consisting of six spacecraft that are equally spaced in a heliocentric orbit at 0.72 AU. These spacecraft will monitor the plasma properties, the magnetic field???s orientation and magnitude, and the 3D-propagation trajectory of CMEs heading for Earth. The primary objective of this mission is to increase space weather forecasting time by means of a near real-time information service, that is based upon in-situ and remote measurements of the aforementioned CME properties. The obtained data can additionally be used for updating scientific models. This update is the mission???s secondary objective. In-situ measurements are performed using a Solar Wind Analyzer instrumentation package and fluxgate magnetometers...

A Study of Machine Learning Techniques for Daily Solar Energy Forecasting using Numerical Weather Models

Aler, Ricardo; Martín, Ricardo; Valls, José M.; Galván, Inés M.
Fonte: Springer International Publishing Publicador: Springer International Publishing
Tipo: info:eu-repo/semantics/acceptedVersion; info:eu-repo/semantics/conferenceObject; info:eu-repo/semantics/bookPart
Publicado em //2015 ENG
Relevância na Pesquisa
46.09%
Forecasting solar energy is becoming an important issue in the context of renewable energy sources and Machine Learning Algorithms play an important rule in this field. The prediction of solar energy can be addressed as a time series prediction problem using historical data. Also, solar energy forecasting can be derived from numerical weather prediction models (NWP). Our interest is focused on the latter approach.We focus on the problem of predicting solar energy from NWP computed from GEFS, the Global Ensemble Forecast System, which predicts meteorological variables for points in a grid. In this context, it can be useful to know how prediction accuracy improves depending on the number of grid nodes used as input for the machine learning techniques. However, using the variables from a large number of grid nodes can result in many attributes which might degrade the generalization performance of the learning algorithms. In this paper both issues are studied using data supplied by Kaggle for the State of Oklahoma comparing Support Vector Machines and Gradient Boosted Regression. Also, three different feature selection methods have been tested: Linear Correlation, the ReliefF algorithm and, a new method based on local information analysis.; Proceedings of: 8th International Symposium on Intelligent Distributed Computing (IDC'2014). Madrid...

Verification of the AFWA 3-Element Severe Weather Forecast Algorithm

Pagliaro, Daniel E.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Tipo: Tese de Doutorado Formato: xvi, 87 p. : maps ;
Relevância na Pesquisa
56.39%
Accurate severe thunderstorm forecasts are critical to providing sufficient leadtime to protect lives and property. The Air Force Weather Agency has developed a 3-Element Severe Weather Forecast Algorithm that when applied to model forecasts gives and outlook region for severe thunderstorms. Improvements were made in this study to enhance the algorithm's forecast skill, reduce its "false alarm" rate, and thereby increase the amount of lead-time for installation commanders to take decisive action to protect personnel and resources. This paper discusses the performance of the 3-Element Algorithm in its original form, and the adjustments made to overcome some of its limitations. The 3-Element Algorithm techniques and results of a performance evaluation are presented. Based on the amount of forecast improvement, eight configurations were retained for analysis across the entire dataset containing six severe weather cases. A new stability proxy, the Elevated Total-Totals Index, was developed and integrated into the algorithm to improve severe weather forecasts over high-elevation regions where some traditional severe weather indices cannot be accurately computed. Additionally, the horizontal gradient of convective available potential energy was studied as a new indicator to the presence of dynamic forcing. It is hoped that improvements discussed in this paper will make the 3-Element Algorithm an effective tool in the early forecasting of severe weather...

Prediction of flu epidemic activity with dynamical model based on weather forecast

Postnikov, Eugene B.; Tatarenkov, Dmitry V.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 25/04/2014
Relevância na Pesquisa
46.16%
The seasonality of respiratory diseases (common cold, influenza, etc.) is a well-known phenomenon studied from ancient times. The development of predictive models is still not only an actual unsolved problem of mathematical epidemiology but also is very important for the safety of public health. Here we show that SIRS (Susceptible-Infected-Recovered-Susceptible) model accurately enough reproduces real curves of flu activity. It contains variable reaction rate, which is a function of mean daily temperature. The proposed alternation of variables represents SIRS equations as the second-order ODE with an outer excitation. It reveals an origin of such predictive efficiency and explains analytically the 1:1 dynamical resonance, which is known as a crucial property of epidemic behavior. Our work opens the perspectives for the development of instant short-time prediction of a normal level of flu activity based on the weather forecast, and allow to estimate a current epidemic level more precisely. The latter fact is based on the explicit difference between the expected weather-based activity and instant anomalies.; Comment: 12 pages, 2 figures

Similarity-based semi-local estimation of EMOS models

Lerch, Sebastian; Baran, Sandor
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 11/09/2015
Relevância na Pesquisa
36.32%
Weather forecasts are typically given in the form of forecast ensembles obtained from multiple runs of numerical weather prediction models with varying initial conditions and physics parameterizations. Such ensemble predictions tend to be biased and underdispersive and thus require statistical postprocessing. In the ensemble model output statistics (EMOS) approach, a probabilistic forecast is given by a single parametric distribution with parameters depending on the ensemble members. This article proposes two semi-local methods for estimating the EMOS coefficients where the training data for a specific observation station are augmented with corresponding forecast cases from stations with similar characteristics. Similarities between stations are determined using either distance functions or clustering based on various features of the climatology, forecast errors, ensemble predictions and locations of the observation stations. In a case study on wind speed over Europe with forecasts from the Grand Limited Area Model Ensemble Prediction System, the proposed similarity-based semi-local models show significant improvement in predictive performance compared to standard regional and local estimation methods. They further allow for estimating complex models without numerical stability issues and are computationally more efficient than local parameter estimation.

Sensitivity of tropical deep convection in global models: effects of horizontal resolution, surface constraints and 3D atmospheric nudging

Chemel, Charles; Russo, Maria; Hosking, Scott; Telford, Paul; Pyle, John
Fonte: Wiley Publicador: Wiley
Tipo: Article; accepted version
Relevância na Pesquisa
45.97%
This is the accepted version of the following article: 'Sensitivity of tropical deep convection in global models: effects of horizontal resolution, surface constraints and 3D atmospheric nudging', which will be published in Atmospheric Science Letters. This record will be updated with citation and DOI after publication.; This Author Accepted Manuscript version will be embargoed until 12 months after publication date to meet the publisher requirements. However the Gold Open Access version will be made available on publication.; We investigate the ability of global models to capture the spatial patterns of tropical deep convection. Their sensitivity is assessed through changing horizontal resolution, surface flux constraints, and constraining background atmospheric conditions. We assess two models at typical climate and weather forecast resolutions. Comparison with observations indicates that increasing resolution generally improves the pattern of tropical convection. When the models are constrained with realistic surface fluxes and atmospheric structure, the location of convection improves dramatically and is very similar irrespective of resolution and parameterisations used in the models.; RCUK, Other

Using information processing techniques to forecast, schedule, and deliver sustainable energy to electric vehicles

Pulusani, Praneeth
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
56.38%
As the number of electric vehicles on the road increases, current power grid infrastructure will not be able to handle the additional load. Some approaches in the area of Smart Grid research attempt to mitigate this, but those approaches alone will not be sufficient. Those approaches and traditional solution of increased power production can result in an insufficient and imbalanced power grid. It can lead to transformer blowouts, blackouts and blown fuses, etc. The proposed solution will supplement the ``Smart Grid'' to create a more sustainable power grid. To solve or mitigate the magnitude of the problem, measures can be taken that depend on weather forecast models. For instance, wind and solar forecasts can be used to create first order Markov chain models that will help predict the availability of additional power at certain times. These models will be used in conjunction with the information processing layer and bidirectional signal processing components of electric vehicle charging systems, to schedule the amount of energy transferred per time interval at various times. The research was divided into three distinct components: (1) Renewable Energy Supply Forecast Model, (2) Energy Demand Forecast from PEVs, and (3) Renewable Energy Resource Estimation. For the first component...

Atmospheric observations and numerical weather prediction

Schulze,G.C.
Fonte: South African Journal of Science Publicador: South African Journal of Science
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/08/2007 EN
Relevância na Pesquisa
36.25%
Today's 72-hour weather forecast is as accurate, globally, as the 24-hour forecast of the 1980s. The recent improvement in accuracy, for the southern hemisphere in particular, is remarkable. This achievement came about through scientific understanding of dynamical and physical processes in the atmosphere coupled with new and enhanced modelling techniques, increased availability of remote-sensing data from weather satellites, and progress in data assimilation techniques that incorporate weather observations into numerical prediction models. The great advances in computing power have also contributed significantly to the forecaster's performance. Further improvements in the accuracy and reliability of climate and weather forecasts are to be expected as a result of superior data observation and assimilation techniques and modelling. The challenge to the forecaster is to provide user-specific risk-management information on various time scales, so that the users of this information can realize the social and economic value of advanced weather and environmental predictions more fully.

Development of a framework for an integrated time-varying agrohydrological forecast system for Southern Africa: Initial results for seasonal forecasts

Ghile,YB; Schulze,RE
Fonte: Water SA Publicador: Water SA
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2008 EN
Relevância na Pesquisa
36.44%
Uncertainty about hydro-climatic conditions in the immediate future (today), as well as the near (up to one week) and more distant futures (up to one season) remains a fundamental problem challenging decision makers in the fields such as water resources, agriculture, and many other water-sensitive sectors in Southern Africa. Currently many institutions, such as the SA Weather Service, provide weather and climate forecasts with lead times ranging from 1 d to one season. However, disconnects exist between the weather/climate forecasts and their links to agrohydrological models, and in the applications of forecast information for targeted agricultural and water-related decision-making. The skills level of the current weather and climate forecasts, and the mismatch in scales between the output from weather/climate models and the spatial scales at which hydrological models are applied, as well as the format of seasonal forecasts in that they cannot be used directly in agrohydrological models, are some of the problems identified in this study and are being addressed. This has necessitated the development of a GIS-based framework in which the 'translation' of weather and climate forecasts into more tangible agrohydrological forecasts such as streamflows...