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Previsões climáticas sazonais sobre o Brasil: avaliação do RegCM3 aninhado no modelo global CPTEC/COLA; Seasonal climatic forecast over Brazil: evaluation of the RegCM3 model nested to the CPTEC/COLA global model

MACHADO, Rubinei Dorneles; ROCHA, Rosmeri Porfírio da
Fonte: Sociedade Brasileira de Meteorologia Publicador: Sociedade Brasileira de Meteorologia
Tipo: Artigo de Revista Científica
POR
Relevância na Pesquisa
36.2%
Este trabalho avalia o desempenho de previsões sazonais do modelo climático regional RegCM3, aninhado ao modelo global CPTEC/COLA. As previsões com o RegCM3 utilizaram 60 km de resolução horizontal num domínio que inclui grande parte da América do Sul. As previsões do RegCM3 e CPTEC/COLA foram avaliadas utilizando as análises de chuva e temperatura do ar do Climate Prediction Center (CPC) e National Centers for Enviromental Prediction (NCEP), respectivamente. Entre maio de 2005 e julho de 2007, 27 previsões sazonais de chuva e temperatura do ar (exceto a temperatura do CPTEC/COLA, que possui 26 previsões) foram avaliadas em três regiões do Brasil: Nordeste (NDE), Sudeste (SDE) e Sul (SUL). As previsões do RegCM3 também foram comparadas com as climatologias das análises. De acordo com os índices estatísticos (bias, coeficiente de correlação, raiz quadrada do erro médio quadrático e coeficiente de eficiência), nas três regiões (NDE, SDE e SUL) a chuva sazonal prevista pelo RegCM3 é mais próxima da observada do que a prevista pelo CPTEC/COLA. Além disto, o RegCM3 também é melhor previsor da chuva sazonal do que da média das observações nas três regiões. Para temperatura, as previsões do RegCM3 são superiores às do CPTEC/COLA nas áreas NDE e SUL...

Modelos de séries temporais aplicados à análise prospectiva de concessão de crédito bancário; Time series models applied to forecast analysis of banking credit concessions

Abitante, Kleber Giovelli
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 19/03/2007 PT
Relevância na Pesquisa
36.16%
O presente trabalho teve por objetivo modelar as séries de concessão de crédito bancário às pessoas físicas, às pessoas jurídicas e para financiamento de atividades rurais, bem como realizar previsões a cerca dos comportamentos destas séries. A metodologia utilizada foi de Auto- Regressão Vetorial. A propriedade de co-integração entre as variáveis foi considerada no trabalho, sendo que foram estimados modelos de Auto-Regressão Vetorial com Correção de Erro – VEC. Os resultados mostram que o produto, a taxa de juros cobrada nos empréstimos, as exportações e as vendas no varejo podem auxiliar na geração de previsões satisfatórias das concessões de crédito às pessoas jurídicas e às pessoas físicas. Para o modelo de previsão das concessões de crédito para financiamento de atividades rurais, utilizaram-se variáveis referentes à produção de fertilizantes, vendas de tratores e colheitadeiras, produção de leite e produção de carnes bovina, suínas e de aves, sendo que as previsões geradas pelo modelo apresentaram performance adequada, dada a dificuldade da modelagem.; The aim of this study was to model the series of banking credit concessions to individuals, to firms and for rural activities financing...

Prognóstico das variáveis meteorológicas e da evapotranspiração de referência com o modelo de previsão do tempo GFS/NCEP; Prediction of meteorological variables and reference evapotranspiration with GFS/NCEP weather forecast model

Oliveira Filho, Celso Luís de
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 31/07/2007 PT
Relevância na Pesquisa
36.48%
Avaliou-se o desempenho de um modelo numérico de previsão do tempo (GFS - Global Forecast System – antigo AVN – AViatioN model - do Centro Nacional para Previsão Ambiental – NCEP) no prognóstico de variáveis meteorológicas temperatura, déficit de pressão de vapor do ar, saldo de radiação e velocidade do vento, e da evapotranspiração de referência calculada pelos métodos de Thornthwaite (1948) e de Penman-Monteith (Allen et al., 1998). O desempenho foi avaliado por comparação com dados provenientes de uma estação meteorológica, situada em Piracicaba, São Paulo. A temperatura e o déficit de pressão de vapor do ar foram os elementos melhor prognosticados, com desempenho "muito bom" e "bom", de acordo com o índice de desempenho proposto por Camargo e Sentelhas (1997), para no máximo quatro e três dia de antecedência, respectivamente, durante o período seco. Para o período úmido, somente o prognóstico do déficit de pressão de vapor do ar para o primeiro dia mostrou-se "bom". Os prognósticos de saldo de radiação e velocidade do vento foram ruins para ambos os períodos. Em decorrência do bom desempenho do modelo para prognosticar a temperatura, verificou-se que a estimativa de ETo pelo método de Thornthwaite teve boa concordância com o calculado a partir dos dados da estação meteorológica...

Uso de índices fenológicos em modelos de previsão de produtividade do cafeeiro; Use the indexes phenological in models of forecast productivity of coffee tree

Alfonsi, Eduardo Lauriano
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 11/04/2008 PT
Relevância na Pesquisa
36.35%
A estimativa antecipada da produção de café das diversas regiões produtoras é muito importante para o estabelecimento da política cafeeira do país. Apesar disso, não existe no Brasil uma metodologia adequada para previsão antecipada da safra de café que permita uma avaliação segura e precisa. As poucas informações para o estabelecimento de modelos para previsão de safra de café são em conseqüência da complexidade metodológica, ocasionada pela diversidade dos fatores ambientais, culturais e econômicos, envolvidos na produtividade dessa cultura, que devem ser levados em consideração nos modelos de previsão como, por exemplo: cultivares, densidade de plantio, idade da planta, tecnologia empregada, condições edafoclimáticas, etc. Para isso a avaliação das características fenológicas determinantes do desenvolvimento e da produção do cafeeiro é uma ferramenta fundamental no estabelecimento de modelos de previsão de safra. Atualmente as previsões baseiam-se em levantamentos empíricos efetuados visualmente, requerendo, para atingir razoável precisão, técnico ou produtores altamente especializados na cultura. Esta pesquisa teve como objetivo desenvolver uma metodologia para estimar a produtividade do cafeeiro sem utilizar a contagem total de frutos na planta...

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
36.14%
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...

The forecast performance of long memory and Markov switching models

Gabriel, Vasco J.; Martins, Luís F.
Fonte: Universidade do Minho. Núcleo de Investigação em Políticas Económicas Publicador: Universidade do Minho. Núcleo de Investigação em Políticas Económicas
Tipo: Trabalho em Andamento
Publicado em //2000 ENG
Relevância na Pesquisa
46.09%
Recent research has focused on the links between long memory and structural change, stressing the long memory properties that may arise in models with parameter changes. In this paper, we contribute to this research by comparing the forecasting abilities of long memory and Markov switching models. Two approaches are employed: a Monte Carlo study and an empirical comparison, using the quarterly Consumer Price inflation rate in Portugal in the period 1968-1998. Although long memory models may capture some in-sample features of the data, when shifts occur in the series considered, their forecast performance is relatively poor, when compared with simple linear and Markov switching models. Moreover, our findings, in a more general framework, are in accordance with the works of Clements and Hendry (1998) and Clements and Krolzig (1998), reinforcing the idea that simple linear time series models remain useful tools for prediction.; Fundação para a Ciência e Tecnologia (FCT) - PRAXIS XXI/BD/16141/98.

Estudo para o desenvolvimento de um previsor descargas el??tricas atmosf??ricas aplicado ?? regi??o costeira do estado do Rio de Janeiro

Zepka, Gisele dos Santos
Fonte: Universidade Federal do Rio Grande Publicador: Universidade Federal do Rio Grande
Tipo: Dissertação de Mestrado
POR
Relevância na Pesquisa
36.35%
Disserta????o(mestrado) - Universidade Federal do Rio Grande, Programa de P??s-Gradua????o em Engenharia Oce??nica, Escola de Engenharia, 2005.; The atmospheric dynamics evidently is very complex. There are many macro and micron scales processes and meteorological variables involved in the atmospheric physical phenomena. The storms with electrical dischargesare distinguished, among these phenomena, by the damage consequences to the human beings, directly or indirectly. Many researchers have pursued the possibility of forecasting the occurrence of a storm with electrical discharges, principally in the last three decades. However, there are not improvements in forecast performance, mainly due to phenomenon complexity. The main objective of the present dissertation was to accomplish a study to determine the viability or not of constructing a forecast system of atmospheric electrical discharges from artificial intelligence techniques, specifically artificial neural networks (NN). The base of the system was constituted of numerical simulations results of the atmospheric dynamics obtained from the mesoscale model MM5. It was identified meteorological variables (outputs of MM5) that would have some correlation with the electrical discharges. These variables act as input in the NN...

Developing performance measures of mangrove wetlands using simulation models of hydrology, nutrient biogeochemistry, and community dynamics

Twilley, Robert R.; Rivera-Monroy, Victor H.
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
36.24%
The goal of mangrove restoration projects should be to improve community structure and ecosystem function of degraded coastal landscapes. This requires the ability to forecast how mangrove structure and function will respond to prescribed changes in site conditions including hydrology, topography, and geophysical energies. There are global, regional, and local factors that can explain gradients of regulators (e.g., salinity, sulfides), resources (nutrients, light, water), and hydroperiod (frequency, duration of flooding) that collectively account for stressors that result in diverse patterns of mangrove properties across a variety of environmental settings. Simulation models of hydrology, nutrient biogeochemistry, and vegetation dynamics have been developed to forecast patterns in mangroves in the Florida Coastal Everglades. These models provide insight to mangrove response to specific restoration alternatives, testing causal mechanisms of system degradation. We propose that these models can also assist in selecting performance measures for monitoring programs that evaluate project effectiveness. This selection process in turn improves model development and calibration for forecasting mangrove response to restoration alternatives. Hydrologic performance measures include soil regulators...

Global population forecast errors, economic performance and Australian export demand

Shi, Qun; Tyers, Rod
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Working/Technical Paper Formato: 259813 bytes; 350 bytes; application/pdf; application/octet-stream
EN_AU
Relevância na Pesquisa
36.14%
The analysis of global population forecasts of the past 30 years by the US National Academy of Sciences (Bongaarts and Bulatao, 2000) confirms that errors have been considerable and that population forecasts have generally been upward-biased. Recent stochastic population projections also yield wide error bounds. We adapt a standard global economic model to estimate the implications of global and regional population forecast errors for the performance of the global economy and the composition of Australian export demand. The model is GTAP-Dynamic, a recursively dynamic, applied general equilibrium model of the world economy widely used in the analysis of trade policy. The results indicate that the growth rate of population in the rest of the world is important in Australias economic health. Faster population growth benefits Australias producers of energy, minerals and agricultural products while slower population growth benefits its manufacturing and services sectors at the expense of commodities. The net effect appears to be a gain from faster global population growth.; no

Global Population Forecast Errors, Economic Performance and Food Demand: Preliminary Simulations

Graham, Brett; Tyers, Rod
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Working/Technical Paper Formato: 300881 bytes; application/pdf
EN_AU
Relevância na Pesquisa
36.31%
The recent analysis of global population forecasts of the past 30 years by the US National Academy of Sciences (Bongaarts and Bulatao, 2000) confirms that errors have been considerable and that population forecasts have generally been upwardbiased. We adapt a standard global economic model to estimate the implications of the global and regional population forecast errors suggested by this study, via their demographic and income effects, for the performance of the global economy and the composition of global food demand. The model is “GTAP-Dyn”, a recursively dynamic, applied general equilibrium model of the world economy (Ianchovichina and McDougall, 2000). The results indicate that slower than forecast population (and hence labour force) growth causes slower growth in Australia’s overall economy and in its agricultural, food and minerals sectors in particular. When the population growth slowdown is restricted to developing countries, the overall effects on Australia are smaller but there is a substantial reallocation of resources away from agriculture, food production and other natural resource based industries in favour of manufactures.; no

Choice of Sample Split in Out-of-Sample Forecast Evaluation

HANSEN, Peter Reinhard; TIMMERMANN, Allan
Fonte: Instituto Universitário Europeu Publicador: Instituto Universitário Europeu
Tipo: Trabalho em Andamento Formato: application/pdf; digital
EN
Relevância na Pesquisa
46.23%
Out-of-sample tests of forecast performance depend on how a given data set is split into estimation and evaluation periods, yet no guidance exists on how to choose the split point. Empirical forecast evaluation results can therefore be di cult to interpret, particularly when several values of the split point might have been considered. When the sample split is viewed as a choice variable, rather than being fixed ex ante, we show that very large size distortions can occur for conventional tests of predictive accuracy. Spurious rejections are most likely to occur with a short evaluation sample, while conversely the power of forecast evaluation tests is strongest with long out-of-sample periods. To deal with size distortions, we propose a test statistic that is robust to the effect of considering multiple sample split points. Empirical applications to predictability of stock returns and inflation demonstrate that out-of-sample forecast evaluation results can critically depend on how the sample split is determined.

Improving the evaluation of hydrological multi-model forecast performance in the Upper Danube Catchment

BOGNER Konrad; CLOKE Hannah; PAPPENBERGER Florian; DE ROO Arie; THIELEN DEL POZO Jutta
Fonte: Taylor & Francis Publicador: Taylor & Francis
Tipo: Articles in Journals Formato: Printed
ENG
Relevância na Pesquisa
36.24%
Medium range flood forecasting activities, driven by various meteorological forecasts ranging from high resolution deterministic forecasts to low spatial resolution ensemble prediction systems, share a major challenge in the appropriateness and design of performance measures. In this paper possible limitations of some traditional hydrological and meteorological prediction quality and verification measures are identified. Some simple modifications are applied in order to circumvent the problem of the autocorrelation dominating river discharge time-series and in order to create a benchmark model enabling the decision makers to evaluate the forecast quality and the model quality. Although the performance period is quite short the advantage of a simple cost-loss function as a measure of forecast quality can be demonstrated.; JRC.H.7-Land management and natural hazards

Using simulation to assess prediction performance change with simulated annealing on probability arrays

Deines, Jason
Fonte: Universidade Rice Publicador: Universidade Rice
ENG
Relevância na Pesquisa
36.34%
Experimental results suggest that significant improvements in forecast performance can be obtained by applying the simulated annealing on probability arrays (SAPA) algorithm to grouped event probability forecasts. Such forecasts are frequently probabilistically incoherent, even when elicited expert subjects. The algorithm corrects any incoherence within the set of responses from each subject, while at the same time minimizing the sum of the absolute adjustments made to the original probability estimates. These adjusted coherent probability estimates appear to yield improved overall forecast performance, as measured by several different metrics. However, with the only published results consisting of several small experiments, definitive conclusions regarding potential forecast improvements in wider applications are difficult to justify. To address this lack of experimental data, a method for extending the existing published results using simulation is described, and the SAPA algorithm and its effects on forecast performance are examined.

Forecast error metrics for Navy inventory management performance

Jackson, Kenneth J.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Tipo: Tese de Doutorado
Relevância na Pesquisa
36.33%
This research establishes metrics for determining overall Navy secondary inventory forecasting accuracy when compared to actual demands at the Naval Inventory Control Point (NAVICP). Specifically, two performance metrics are introduced: the average performance index (API) and the median absolute deviation performance index (MPI). API measures forecasting accuracy of secondary inventory when compared against demand or forecast performance over a four-quarter period. MPI measures the quarterly variability of forecast errors over the same period. The API and MPI metrics allow for the identification of poorly forecasted NAVICP secondary inventory items. The metrics can be applied to entire inventories or subsets of items based on type, demand, or cost. In addition, the API metric can be used to show overall inventory performance, providing NAVICP with a graphical means to assess forecasting performance improvements (or degradations) over time. The new forecasting accuracy methods developed in this research will allow the Navy to continually gauge the overall health of their inventory management practices and provide a method for improving forecasting accuracy. Additionally, they will assist NAVICP in complying with DoD directives that require NAVICP to monitor and continually develop improvements to inventory management practices.

Projeção de preços de alumínio: modelo ótimo por meio de combinação de previsões; Aluminum price forecasting: optimal forecast combination

Castro, João Bosco Barroso de
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 15/06/2015 PT
Relevância na Pesquisa
36.35%
Commodities primárias, tais como metais, petróleo e agricultura, constituem matérias-primas fundamentais para a economia mundial. Dentre os metais, destaca-se o alumínio, usado em uma ampla gama de indústrias, e que detém o maior volume de contratos na London Metal Exchange (LME). Como o preço não está diretamente relacionado aos custos de produção, em momentos de volatilidade ou choques econômicos, o impacto financeiro na indústria global de alumínio é significativo. Previsão de preços do alumínio é fundamental, portanto, para definição de política industrial, bem como para produtores e consumidores. Este trabalho propõe um modelo ótimo de previsões para preços de alumínio, por meio de combinações de previsões e de seleção de modelos através do Model Confidence Set (MCS), capaz de aumentar o poder preditivo em relação a métodos tradicionais. A abordagem adotada preenche uma lacuna na literatura para previsão de preços de alumínio. Foram ajustados 5 modelos individuais: AR(1), como benchmarking, ARIMA, dois modelos ARIMAX e um modelo estrutural, utilizando a base de dados mensais de janeiro de 1999 a setembro de 2014. Para cada modelo individual, foram geradas 142 previsões fora da amostra, 12 meses à frente...

Demand forecast for short life cycle products

Basallo Triana, Mario José
Fonte: Pontificia Universidad Javeriana; Facultad de Ingenieria; Maestría en Ingeniería con Énfasis en Ingeniería Industrial Publicador: Pontificia Universidad Javeriana; Facultad de Ingenieria; Maestría en Ingeniería con Énfasis en Ingeniería Industrial
Tipo: info:eu-repo/semantics/bachelorThesis; Trabajo de Grado; info:eu-repo/semantics/publishedVersion Formato: application/pdf; 88 p.
SPA
Relevância na Pesquisa
46.23%
Accurate forecast for demand of short life cycle products is a subject of special interest for many companies and researchers. However common forecasting approaches are not appropriate for this type of products due to the characteristics of their demand. This work proposes a method to forecast the demand of short life cycle products. Clustering techniques will be used to obtain natural groups in the time series. This analysis allows to extract relevant information for the forecasting method. The results of the proposed method will be compared to other approaches to forecast the demand of short life cycle products. Several time series datasets of different type of products are considered.

Determinism, Complexity, and Predictability in Computer Performance

Garland, Joshua; James, Ryan; Bradley, Elizabeth
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 23/05/2013
Relevância na Pesquisa
36.14%
Computers are deterministic dynamical systems (CHAOS 19:033124, 2009). Among other things, that implies that one should be able to use deterministic forecast rules to predict their behavior. That statement is sometimes-but not always-true. The memory and processor loads of some simple programs are easy to predict, for example, but those of more-complex programs like compilers are not. The goal of this paper is to determine why that is the case. We conjecture that, in practice, complexity can effectively overwhelm the predictive power of deterministic forecast models. To explore that, we build models of a number of performance traces from different programs running on different Intel-based computers. We then calculate the permutation entropy-a temporal entropy metric that uses ordinal analysis-of those traces and correlate those values against the prediction success

Prevendo o crescimento da produção industrial usando um número limitado de combinações de previsões

Hollauer, Gilberto; Issler, João Victor; Notini, Hilton H.
Fonte: Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de RP Publicador: Universidade de São Paulo. Faculdade de Economia, Administração e Contabilidade de RP
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; ; Formato: application/pdf
Publicado em 01/01/2008 POR
Relevância na Pesquisa
36.17%
O objetivo central deste artigo é o de propor e avaliar modelos econométricos de previsão para o PIB industrial brasileiro. Para tanto, foram utilizados diversos modelos de previsão como também combinações de modelos. Foi realizada uma análise criteriosa das séries a serem utilizadas na previsão. Nós concluímos que a utilização de vetores de cointegração melhora substancialmente a performance da previsão. Além disso, os modelos de combinação de previsão, na maioria dos casos, tiveram uma performance superior aos demais modelos, que já apresentavam boa capacidade preditiva.; The purpose of this article is to propose and evaluate forecasting models for the Brazilian industrial GDP. Most models are based on vector auto-regressions (VARs) or on restricted VARs, but models on the ARMA class are also entertained. We used many forecasting models and also combinations of these models. The use of cointegration vectors improves substantially the forecast performance of industrial GDP. Furthermore, in general, combining models out-performed individual models, even when the performance of the later was acceptable.

Towards improving the framework for probabilistic forecast evaluation

Smith, Leonard A.; Suckling, Emma B.; Thompson, Erica L.; Maynard, Trevor; Du, Hailiang
Fonte: Springer Netherlands Publicador: Springer Netherlands
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em 17/07/2015 EN; EN
Relevância na Pesquisa
36.39%
The evaluation of forecast performance plays a central role both in the interpretation and use of forecast systems and in their development. Different evaluation measures (scores) are available, often quantifying different characteristics of forecast performance. The properties of several proper scores for probabilistic forecast evaluation are contrasted and then used to interpret decadal probability hindcasts of global mean temperature. The Continuous Ranked Probability Score (CRPS), Proper Linear (PL) score, and IJ Good’s logarithmic score (also referred to as Ignorance) are compared; although information from all three may be useful, the logarithmic score has an immediate interpretation and is not insensitive to forecast busts. Neither CRPS nor PL is local; this is shown to produce counter intuitive evaluations by CRPS. Benchmark forecasts from empirical models like Dynamic Climatology place the scores in context. Comparing scores for forecast systems based on physical models (in this case HadCM3, from the CMIP5 decadal archive) against such benchmarks is more informative than internal comparison systems based on similar physical simulation models with each other. It is shown that a forecast system based on HadCM3 out performs Dynamic Climatology in decadal global mean temperature hindcasts; Dynamic Climatology previously outperformed a forecast system based upon HadGEM2 and reasons for these results are suggested. Forecasts of aggregate data (5-year means of global mean temperature) are...

Surface temperature forecast skill comparison for the west coast of Saudi Arabia

ATHAR,HUSSAIN; SARA,ATHAR
Fonte: Centro de Ciencias de la Atmósfera, UNAM Publicador: Centro de Ciencias de la Atmósfera, UNAM
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2014 EN
Relevância na Pesquisa
36.2%
Given the growing interest of the general public in accessing commercial weather forecasts through various media outlets and the available impetuses for promoting tourism in Saudi Arabia (SA), a first attempt is made to present a forecast skill comparison for surface temperature in four cities (Wejh, Yenbo, Jeddah, and Gizan) along the west coast of SA, for the 61-day transitional period (from January 16 to March 16) between the December-January-February (DJF) and the March-April-May (MAM) seasons. A simple skill score comparison method is used to assess the next-day city forecasts for surface temperature from six commercial weather forecast providers based on the operational numerical weather prediction (NWP) model outputs. All the NWP model forecast providers performed better than the respective daily climatology (Clm) for each station. Depending upon the station and the provider, the absolute average maximum daily surface temperature difference between the forecasts and the observations was less than 2 °C. Daily surface temperature forecasts from two versions of an atmospheric-ocean general circulation model are also compared to assess their performance for these coastal locations.