996 resultados para weather systems


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The South Shetland Islands are located at the northern tip of the AP which is among the fastest warming regions on Earth. The islands are especially vulnerable to climate change due to their exposure to transient low-pressure systems and their maritime climate. Surface air temperature increases (2.5K in 50 years) are concurrent with retreating glacier fronts, an increase in melt areas, ice surface lowering and rapid break-up and disintegration of ice shelves. We have compiled a unique meteorological data set for the King George Island (KGI)/Isla 25 de Mayo, the largest of the South Shetland Islands. It comprises high-temporal resolution and spatially distributed observations of surface air temperature, wind directions and wind velocities, as well as glacier ice temperatures in profile with a fully equipped automatic weather station on the Warszawa Icefield, from November 2010 and ongoing. In combination with two long-term synoptic datasets (40 and 10 years, respectively) and NCEP/NCAR reanalysis data, we have looked at changes in the climatological drivers of the glacial melt processes, and the sensitivity of the inland ice cap with regard to winter melting periods and pressure anomalies. The analysis has revealed, a positive trend of 5K over four decades in minimum surface air temperatures for winter months, clearly exceeding the published annual mean statistics, associated to a decrease in mean monthly winter sea level pressure. This concurs with a positive trend in the Southern Annular Mode (SAM) index, which gives a measure for the strength and extension of the Antarctic vortex. We connect this trend with a higher frequency of low-pressure systems hitting the South Shetland Islands during austral winter, bringing warm and moist air masses from lower latitudes. Due to its exposure to the impact of transient synoptic weather systems, the ice cap of KGI is especially vulnerable to changes during winter glacial mass accumulation period. A revision of seasonal changes in adiabatic air temperature lapse rates and their dependency on exposure and elevation has shown a clear decoupling of atmospheric surface layers between coastal areas and the higher-elevation ice cap, showing the higher sensitivity to free atmospheric flow and synoptic changes. Observed surface air temperature lapse rates show a high variability during winter months (standard deviations up to ±1.0K/100 m), and a distinct spatial variability reflecting the impact of synoptic weather patterns. The observed advective conditions bringing warm, moist air with high temperatures and rain, lead to melt conditions on the ice cap, fixating surface air temperatures to the melting point. This paper assesses the impact of large-scale atmospheric circulation variability and climatic changes on the atmospheric surface layer and glacier mass accumulation of the upper ice cap during winter season for the Warszawa Icefield on KGI.

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We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems.

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The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the ‘Year Without a Summer’ of 1816 in Europe and North America. Although a tragic event — tens of thousands of people lost their lives — the eruption also was an ‘experiment of nature’ from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora’s effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO₂. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged.

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In this thesis used four different methods in order to diagnose the precipitation extremes on Northeastern Brazil (NEB): Generalized Linear Model s via logistic regression and Poisson, extreme value theory analysis via generalized extre me value (GEV) and generalized Pareto (GPD) distributions and Vectorial Generalized Linea r Models via GEV (MVLG GEV). The logistic regression and Poisson models were used to identify the interactions between the precipitation extremes and other variables based on the odds ratios and relative risks. It was found that the outgoing longwave radiation was the indicator variable for the occurrence of extreme precipitation on eastern, northern and semi arid NEB, and the relative humidity was verified on southern NEB. The GEV and GPD distribut ions (based on the 95th percentile) showed that the location and scale parameters were presented the maximum on the eastern and northern coast NEB, the GEV verified a maximum core on western of Pernambuco influenced by weather systems and topography. The GEV and GPD shape parameter, for most regions the data fitted by Weibull negative an d Beta distributions (ξ < 0) , respectively. The levels and return periods of GEV (GPD) on north ern Maranhão (centerrn of Bahia) may occur at least an extreme precipitation event excee ding over of 160.9 mm /day (192.3 mm / day) on next 30 years. The MVLG GEV model found tha t the zonal and meridional wind components, evaporation and Atlantic and Pacific se a surface temperature boost the precipitation extremes. The GEV parameters show the following results: a) location ( ), the highest value was 88.26 ± 6.42 mm on northern Maran hão; b) scale ( σ ), most regions showed positive values, except on southern of Maranhão; an d c) shape ( ξ ), most of the selected regions were adjusted by the Weibull negative distr ibution ( ξ < 0 ). The southern Maranhão and southern Bahia have greater accuracy. The level period, it was estimated that the centern of Bahia may occur at least an extreme precipitatio n event equal to or exceeding over 571.2 mm/day on next 30 years.

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The study aims to improve the understanding about different atmospheric environments leading to the development of storms associated with heavy precipitation in Madeira Island. For this purpose, four main goals have been considered: 1) To document the synoptic and mesoscale environments associated with heavy precipitation. 2) To characterize surface precipitation patterns that affected the island during some periods of significant accumulated precipitation using numerical modelling. 3) To study the relationship between surface precipitation patterns and mesoscale environments. 4) To highlight how the PhD findings obtained in the first three goals can be translated into an operational forecast context. Concerning the large scale environment, precipitation over the island was favoured by weather systems (e.g, mesoscale convective systems and low pressure systems), as well as by the meridional transport of high amount of moisture from a structure denominated as “Atmospheric River”. The tropical origin of this moisture is underscored, however, their impact on the precipitation in Madeira was not so high during the 10 winter seasons [2002 – 2012] studied. The main factor triggering heavy precipitation events over the island is related to the local orography. The steep terrain favours orographically-induced stationary precipitation over the highlands, although maximum of precipitation at coastal region may be produced by localized blocking effect. These orographic precipitating systems presented different structures, associated with shallow and deep convection. Essentially, the study shows that the combination of airflow dynamics, moist content, and orography is the major mechanism that produces precipitation over the island. These factors together with the event duration act to define the regions of excessive precipitation. Finally, the study highlights two useful points for the operational sector, regarding the meridional water vapour transport and local effects causing significant precipitation over the Island; RESUMO: O estudo procura melhorar o entendimento sobre os diferentes ambientes atmosféricos que favorecem o desenvolvimento de tempestades associadas com precipitação intensa na ilha da Madeira. Nesse sentido foram definidos quatro objetivos: 1) Documentar os ambientes sinópticos e de mesoescala associados com precipitação intensa; 2) Caracterizar padrões de precipitação na superfície, em eventos de elevada precipitação acumulada, utilizando modelação numérica; 3) Estudar as relações entre os padrões de precipitação e ambientes de mesoescala; 4) Mostrar como tais resultados podem ser utilizados num contexto operacional de previsão do tempo. Em relação a ambientes de larga escala, verificou-se que a ocorrência de eventos de precipitação intensa sobre a ilha foi favorecida por sistemas meteorológicos, assim como pelo transporte meridional de humidade por meio de estruturas atualmente denominadas Rios atmosféricos. Neste último caso é de destacar a origem tropical de humidade, no entanto, o seu impacto na precipitação sobre a Madeira durante os 10 invernos estudados [2002-2012] não foi tão elevada. O principal fator que favorece os eventos de precipitação intensa está relacionado com a orografia local. O terreno complexo da ilha favorece a ocorrência de precipitação estacionária induzida orograficamente sobre as terras mais altas, embora a precipitação nas zonas costeiras possa ser produzida por um efeito localizado de bloqueio. Estes sistemas orográficos precipitantes apresentaram diferentes estruturas, associados a convecção pouco profunda e profunda. O estudo mostra que a combinação entre as características do escoamento, a quantidade de humidade, e a orografia são os condimentos essenciais para o desenvolvimento da precipitação sobre a ilha, atuando de maneira a definir as regiões de precipitação excessiva. Por fim, o estudo destaca dois pontos que podem ser úteis na previsão do tempo operacional, ligados a larga escala e aos efeitos locais, os quais podem levar ao desenvolvimento de tempestades e precipitação intensa sobre a ilha.

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This paper shows preliminary results of research into the occurrence of strong anticyclonic systems that influenced the weather in Poland during the period 1971–2000. The study was based on NCEP/NCAR reanalysis data, including daily values of the 1000 and 500 hPa geopotential heights, maps of mentioned geopotential heights and maps of sea-level field pressure. With the use of these data a number of exceptionally strong high-pressure systems were identified, together with their areas of origin and subsequent development patterns. They were then broken down into five groups with similar dynamics. The numbers of systems in each group were not found to follow any significant change trends in the long term. The greatest differences between groups were identified in terms of their annual occurrence rates and centre pressure values.

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Mode of access: Internet.

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The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

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The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of global warming on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since all building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. Based on a review of the existing weather data generation models, this paper presents an effective method to generate approximate future hourly weather data suitable for the study of the impact of global warming. Depending on the level of information available for the prediction of future weather condition, it is shown that either the method of retaining to current level, constant offset method or diurnal modelling method may be used to generate the future hourly variation of an individual weather parameter. An example of the application of this method to the different global warming scenarios in Australia is presented. Since there is no reliable projection of possible change in air humidity, solar radiation or wind characters, as a first approximation, these parameters have been assumed to remain at the current level. A sensitivity test of their impact on the building energy performance shows that there is generally a good linear relationship between building cooling load and the changes of weather variables of solar radiation, relative humidity or wind speed.

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The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of climate change on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since most of building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. In this paper, the methods used to prepare future weather data for the study of the impact of climate change are reviewed. The advantages and disadvantages of each method are discussed. The inherent relationship between these methods is also illustrated. Based on these discussions and the analysis of Australian historic climatic data, an effective framework and procedure to generate future hourly weather data is presented. It is shown that this method is not only able to deal with different levels of available information regarding the climate change, but also can retain the key characters of a “typical” year weather data for a desired period.