910 resultados para forecasts
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◾PICES Science in 2007 (pdf, 0.1 Mb) ◾2007 Wooster Award (pdf, 0.1 Mb) ◾FUTURE - A milestone reached but our task is not done (pdf, < 0.1 Mb) ◾International symposium on "Reproductive and Recruitment Processes of Exploited Marine Fish Stocks" (pdf, 0.1 Mb) ◾Recent results of the micronekton sampling inter-calibration experiment (pdf, 0.1 Mb) ◾2007 PICES workshop on "Measuring and monitoring primary productivity in the North Pacific" (pdf, 0.1 Mb) ◾2007 Harmful Algal Bloom Section annual workshop events (pdf, 0.1 Mb) ◾A global approach for recovery and sustainability of marine resources in Large Marine Ecosystems (pdf, 0.3 Mb) ◾Highlights of the PICES Sixteenth Annual Meeting (pdf, 0.4 Mb) ◾Ocean acidification of the North Pacific Ocean (pdf, 0.3 Mb) ◾Workshop on NE Pacific Coastal Ecosystems (2008 Call for Salmon Survival Forecasts) (pdf, 0.1 Mb) ◾The state of the western North Pacific in the first half of 2007 (pdf, 0.4 Mb) ◾PICES Calendar (pdf, 0.4 Mb) ◾The Bering Sea: Current status and recent events (pdf, 0.3 Mb) ◾PICES Interns (pdf, 0.3 Mb) ◾Recent trends in waters of the subarctic NE Pacific (pdf, 0.3 Mb) ◾Election results at PICES (pdf, 0.2 Mb) ◾A new PICES award for monitoring and data management activities (pdf, < 0.1 Mb)
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Esta dissertação apresenta resultados da aplicação de filtros adaptativos, utilizando os algoritmos NLMS (Normalized Least Mean Square) e RLS (Recursive Least Square), para a redução de desvios em previsões climáticas. As discrepâncias existentes entre o estado real da atmosfera e o previsto por um modelo numérico tendem a aumentar ao longo do período de integração. O modelo atmosférico Eta é utilizado operacionalmente para previsão numérica no CPTEC/INPE e como outros modelos atmosféricos, apresenta imprecisão nas previsões climáticas. Existem pesquisas que visam introduzir melhorias no modelo atmosférico Eta e outras que avaliam as previsões e identificam os erros do modelo para que seus produtos sejam utilizados de forma adequada. Dessa forma, neste trabalho pretende-se filtrar os dados provenientes do modelo Eta e ajustá-los, de modo a minimizar os erros entre os resultados fornecidos pelo modelo Eta e as reanálises do NCEP. Assim, empregamos técnicas de processamento digital de sinais e imagens com o intuito de reduzir os erros das previsões climáticas do modelo Eta. Os filtros adaptativos nesta dissertação ajustarão as séries ao longo do tempo de previsão. Para treinar os filtros foram utilizadas técnicas de agrupamento de regiões, como por exemplo o algoritmo de clusterização k-means, de modo a selecionar séries climáticas que apresentem comportamentos semelhantes entre si. As variáveis climáticas estudadas são o vento meridional e a altura geopotencial na região coberta pelo modelo de previsão atmosférica Eta com resolução de 40 km, a um nível de pressão de 250 hPa. Por fim, os resultados obtidos mostram que o filtro com 4 coeficientes, adaptado pelo algoritmo RLS em conjunto com o critério de seleção de regiões por meio do algoritmo k-means apresenta o melhor desempenho ao reduzir o erro médio e a dispersão do erro, tanto para a variável vento meridional quanto para a variável altura geopotencial.
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Este artigo compara a habilidade preditiva foradaamostra de um modelo DSGE (DynamicStochastic General EquilibriumModel)Novo-Keynesiano, especificado e estimado para o Brasil, com a de um modelo Autorregressivo Vetorial (VAR) e com a de um modelo AutorregressivoVetorial Bayesiano (BVAR). O artigo inova em relação a outros trabalhos similares feitos para o Brasil (Castro et al. (2011) e Caetano e Moura (2013)), ao escolher uma especificação para o modelo DSGE que, ao permitir o uso de um conjunto de informação mais rico, tornou possível computar-se a habilidade preditiva do DSGE a partir de previsões que são,verdadeiramente,previsõesfora da amostra. Ademais, diferentemente de outros artigos que utilizaram dados brasileiros, avalia-se em que medida as respostas das variáveis aos choques na política monetária e no câmbio, obtidas pelo modelo DSGE, se assemelham àquelas de um BVAR estimado através de procedimentos bayesianos desenvolvidos de forma consistente. O modelo DSGE estimado é similar ao utilizado por Justiniano e Preston (2010) e Alpanda (2010). O modelo BVAR foi estimado utilizando uma metodologia semelhante à desenvolvida por Sims e Zha (1998), Waggoner e Zha (2003) e Ramírez, Waggoner e Zha (2007).Os resultados obtidos mostram que o modelo DSGE é capaz de gerar, para algumas variáveis, previsões competitivas em relação às dos outros modelos rivais VAR e BVAR. Além disso, as respostas das variáveis aos choques nas políticas monetária e cambial, nos modelos DSGE e BVAR, são bastante similares.
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Moving ecosystem modeling from research to applications and operations has direct management relevance and will be integral to achieving the water quality and living resource goals of the 2010 Chesapeake Bay Executive Order. Yet despite decades of ecosystem modeling efforts of linking climate to water quality, plankton and fish, ecological models are rarely taken to the operational phase. In an effort to promote operational ecosystem modeling and ecological forecasting in Chesapeake Bay, a meeting was convened on this topic at the 2010 Chesapeake Modeling Symposium (May, 10-11). These presentations show that tremendous progress has been made over the last five years toward the development of operational ecological forecasting models, and that efforts in Chesapeake Bay are leading the way nationally. Ecological forecasts predict the impacts of chemical, biological, and physical changes on ecosystems, ecosystem components, and people. They have great potential to educate and inform not only ecosystem management, but also the outlook and opinion of the general public, for whom we manage coastal ecosystems. In the context of the Chesapeake Bay Executive Order, ecological forecasting can be used to identify favorable restoration sites, predict which sites and species will be viable under various climate scenarios, and predict the impact of a restoration project on water quality.
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This report presents the results of a two-year investigation and summary of oceanographic satellite data obtained from multiple operational data providers and sources, spanning years of operational data collection. Long-term summaries of Sea Surface Temperature (SST) and SST fronts, Sea Surface Height Anomalies (SSHA), surface currents, ocean color chlorophyll and turbidity, and winds are provided. Merged satellite oceanographic data revealed information on: (1) seasonal cycles and timing of transition periods; (2) linkages between seasonal effects (warming and cooling), upwelling processes and transport; and (3) nutrient/sediment sources, sinks, and physical limiting factors controlling surface response for Olympic Coast marine environments. These data and information can be used for building relevant hind cast models, ecological forecasts, and regional environmental indices (e.g. upwelling, climate, “hot spot”) on biological distribution and/or response in the PNW.
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EXTRACT (SEE PDF FOR FULL ABSTRACT): Since 1986, the U.S. Geological Survey and National Weather Service have operated a warning system for debris flows triggered by severe rainstorms in the San Francisco Bay region. The NWS tracks storm systems as they approach the region, forecasts precipitation, and observes rainfall with a network of radiotelemetered rain gauges (ALERT). The USGS also monitors ALERT data and compares the observed and forecast rainfall to thresholds for debris-flow initiation. Both groups jointly assess debris-flow hazards and issue public advisories when rainfall conditions reach or approach critical levels.
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The study based on time series marine fish production data during the period of 1983-1984 to 2007-2008 in Bangladesh. For this growth analysis six deterministic time series models are considered. The estimated best fitting models are the cubic, quadratic and quadratic model is appropriate for industrial marine fish production, artisanal marine fish production and total marine fish production in Bangladesh respectively. The study attempts to provide forecasts of marine fish production in Bangladesh for the year of 2008-09 to 2012-13. The magnitude of instability in marine fish production was attempted by computing the coefficient of variation (CV) and the percentage deviation from three years moving average values. The study revealed that the total marine fish production was observed to be relatively stable (CV being 31.85%) compared to the artisanal marine fish production (CV being 32.04%) and industrial marine fish (CV being 47.20%). For the three components of marine fish production the growth rates were different over different time points. The variation of the growth rates in industrial marine fish production was -21.6% to 13.12%, in artisanal marine fish production was 2.39% to 5.29% and in total marine fish production was 11.23% to 24.85% during the study period.
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Steel production accounts for 25% of industrial carbon emissions. Long-term forecasts of steel demand and scrap supply are needed to develop strategies for how the steel industry could respond to industrialization and urbanization in the developing world while simultaneously reducing its environmental impact, and in particular, its carbon footprint. We developed a dynamic stock model to estimate future final demand for steel and the available scrap for 10 world regions. Based on evidence from developed countries, we assumed that per capita in-use stocks will saturate eventually. We determined the response of the entire steel cycle to stock saturation, in particular the future split between primary and secondary steel production. During the 21st century, steel demand may peak in the developed world, China, the Middle East, Latin America, and India. As China completes its industrialization, global primary steel production may peak between 2020 and 2030 and decline thereafter. We developed a capacity model to show how extensive trade of finished steel could prolong the lifetime of the Chinese steelmaking assets. Secondary steel production will more than double by 2050, and it may surpass primary production between 2050 and 2060: the late 21st century can become the steel scrap age.
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Demand for aluminum in final products has increased 30-fold since 1950 to 45 million tonnes per year, with forecasts predicting this exceptional growth to continue so that demand will reach 2-3 times today's levels by 2050. Aluminum production uses 3.5% of global electricity and causes 1% of global CO2 emissions, while meeting a 50% cut in emissions by 2050 against growing demand would require at least a 75% reduction in CO2 emissions per tonne of aluminum produced--a challenging prospect. In this paper we trace the global flows of aluminum from liquid metal to final products, revealing for the first time a complete map of the aluminum system and providing a basis for future study of the emissions abatement potential of material efficiency. The resulting Sankey diagram also draws attention to two key issues. First, around half of all liquid aluminum (~39 Mt) produced each year never reaches a final product, and a detailed discussion of these high yield losses shows significant opportunities for improvement. Second, aluminum recycling, which avoids the high energy costs and emissions of electrolysis, requires signification "dilution" (~ 8 Mt) and "cascade" (~ 6 Mt) flows of higher aluminum grades to make up for the shortfall in scrap supply and to obtain the desired alloy mix, increasing the energy required for recycling.
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Identifying strategies for reducing greenhouse gas emissions from steel production requires a comprehensive model of the sector but previous work has either failed to consider the whole supply chain or considered only a subset of possible abatement options. In this work, a global mass flow analysis is combined with process emissions intensities to allow forecasts of future steel sector emissions under all abatement options. Scenario analysis shows that global capacity for primary steel production is already near to a peak and that if sectoral emissions are to be reduced by 50% by 2050, the last required blast furnace will be built by 2020. Emissions reduction targets cannot be met by energy and emissions efficiency alone, but deploying material efficiency provides sufficient extra abatement potential.
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Using energy more efficiently is essential if carbon emissions are to be reduced. According to the International Energy Agency (IEA), energy efficiency improvements represent the largest and least costly savings in carbon emissions, even when compared with renewables, nuclear power and carbon capture and storage. Yet, how should future priorities be directed? Should efforts be focused on light bulbs or diesel engines, insulating houses or improving coal-fired power stations? Previous attempts to assess energy efficiency options provide a useful snapshot for directing short-term responses, but are limited to only known technologies developed under current economic conditions. Tomorrow's economic drivers are not easy to forecast, and new technical solutions often present in a disruptive manner. Fortunately, the theoretical and practical efficiency limits do not vary with time, allowing the uncertainty of economic forecasts to be avoided and the potential of yet to be discovered efficient designs to be captured. This research aims to provide a rational basis for assessing all future developments in energy efficiency. The global fow of energy through technical devices is traced from fuels to final services, and presented as an energy map to convey visually the scale of energy use. An important distinction is made between conversion devices, which upgrade energy into more useable forms, and passive systems, from which energy is lost as low temperature heat, in exchange for final services. Theoretical efficiency limits are calculated for conversion devices using exergy analysis, and show a 89% potential reduction in energy use. Efforts should be focused on improving the efficiency of, in relative order: biomass burners, refrigeration systems, gas burners and petrol engines. For passive systems, practical utilisation limits are calculated based on engineering models, and demonstrate energy savings of 73% are achievable. Significant gains are found in technical solutions that increase the thermal insulation of building fabrics and reduce the mass of vehicles. The result of this work is a consistent basis for comparing efficiency options, that can enable future technical research and energy policy to be directed towards the actions that will make the most difference.
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As a kind of novel green solvent, Room Temperature Ionic Liquids (RTILs) have been paid ever-increasing attentions in RTIL-based extraction for metal separation, since they have many unique proper-ties, such as non-volatile and non-flammable. The progress of that is mainly composed of the partition properties, mechanisms, defects, overcome methods and forecasts of the processes on the environmental analytical chemistry, has been reviewed.
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Long-wave dynamics of the interannual variations of the equatorial Indian Ocean circulation are studied using an ocean general circulation model forced by the assimilated surface winds and heat flux of the European Centre for Medium-Range Weather Forecasts. The simulation has reproduced the sea level anomalies of the Ocean Topography Experiment (TOPEX)/Poseidon altimeter observations well. The equatorial Kelvin and Rossby waves decomposed from the model simulation show that western boundary reflections provide important negative feedbacks to the evolution of the upwelling currents off the Java coast during Indian Ocean dipole (IOD) events. Two downwelling Kelvin wave pulses are generated at the western boundary during IOD events: the first is reflected from the equatorial Rossby waves and the second from the off-equatorial Rossby waves in the southern Indian Ocean. The upwelling in the eastern basin during the 1997-98 IOD event is weakened by the first Kelvin wave pulse and terminated by the second. In comparison, the upwelling during the 1994 IOD event is terminated by the first Kelvin wave pulse because the southeasterly winds off the Java coast are weak at the end of 1994. The atmospheric intraseasonal forcing, which plays an important role in inducing Java upwelling during the early stage of an IOD event, is found to play a minor role in terminating the upwelling off the Java coast because the intraseasonal winds are either weak or absent during the IOD mature phase. The equatorial wave analyses suggest that the upwelling off the Java coast during IOD events is terminated primarily by western boundary reflections.
Impact of spatial resolution and spatial difference accuracy on the performance of Arakawa A-D grids
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This paper alms at illustrating the impact of spatial difference scheme and spatial resolution on the performance of Arakawa A-D grids in physical space. Linear shallow water equations are discretized and forecasted on Arakawa A-D grids for 120-minute using the ordinary second-order (M and fourth-order (C4) finite difference schemes with the grid spacing being 100 km, 10 km and I km, respectively. Then the forecasted results are compared with the exact solution, the result indicates that when the grid spacing is I kin, the inertial gravity wave can be simulated on any grid with the same results from C2 scheme or C4 scheme, namely the impact of variable configuration is neglectable; while the inertial gravity wave is simulated with lengthened grid spacing, the effects of different variable configurations are different. However, whether for C2 scheme or for C4 scheme, the RMS is minimal (maximal) on C (D) grid. At the same time it is also shown that when the difference accuracy increases from C2 scheme to C4 scheme, the resulted forecasts do not uniformly decrease, which is validated by the change of the group A velocity relative error from C2 scheme to C4 scheme. Therefore, the impact of the grid spacing is more important than that of the difference accuracy on the performance of Arakawa A-D grid.
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A hybrid coupled ocean-atmosphere model is designed, which consists of a global AGCM and a simple anomaly ocean model in the tropical Pacific. Retroactive experimental predictions initiated in each season from 1979 to 1994 are performed. Analyses indicate that: (1) The overall predictive capability of this model for SSTA over the central-eastern tropical Pacific can reach one year, and the error is not larger than 0.8 degrees C. (2) The prediction skill depends greatly on the season when forecasts start. However, the phenomenon of SPB (spring prediction barrier) is not found in the model. (3) The ensemble forecast method can effectively improve prediction results. A new initialization scheme is discussed.