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Thesis (Ph. D.)--University of Sydney, 2000. / Title from title screen (viewed February 12, 2009). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Biological Sciences, Faculty of Science. Degree awarded 2000; thesis submitted 1999. The 2 in the title is in subscript. Includes bibliographical references. Also available in print form.

Thesis (Ed.D.)--Teachers College, Columbia University, 1995. / Typescript; issued also on microfilm. Sponsor: Warren E. Yasso. Dissertation Committee: O. Roger Anderson. Includes bibliographical references (leaves 95-109).

The attribution of recent global warming to anthropogenic emissions is now well established. However, the relation of recent changes in other properties of the climate system to human activities is not as clearly understood. The aim of this thesis is to improve our understanding of this relation in the case of two of these properties, namely the diurnal temperature range (DTR) and modes of tropospheric variability. The DTR, the difference between daily maximum and minimum temperatures, has decreased over global land areas at a rate comparable to the mean warming. Model simulations including the effects of human emissions produce a comparable change, albeit of smaller magnitude. This decrease results from increased reflection of solar radiation by clouds moderated by decreasing soil moisture, mostly through its effect on the ground heat capacity. Recent trends in indices of some modes of atmospheric variability suggest the possibility that forced climate change may manifest itself through a projection onto these pre-existing modes. Model simulations indicate that this is plausible in the case of sea level pressure, but only partly so in the case of surface air temperature. On the interannual time scale examined in this thesis, these projections are consistent with a linear interpretation, rather than a nonlinear one. These results are, however, sensitive to the representation of small scale processes in the models. For instance, the DTR response depends strongly on the representation of cloud and land surface processes. Further examination of the response of one of the tropospheric modes, namely the Southern Annular Mode which represents the meridional shift of the mid latitude jet in the Southern Hemisphere, indicates that it is sensitive to the parametrisation of sub-grid scale mixing in the ocean. Nevertheless, these results suggest that the recent changes are consistent with enhanced greenhouse warming, and indicate that they are likely to continue into the foreseeable future. / Graduate

A 0.24 degrees C jump of record warm global mean surface temperature (GMST) over the past three consecutive record-breaking years (2014-2016) was highly unusual and largely a consequence of an El Nino that released unusually large amounts of ocean heat from the subsurface layer of the northwestern tropical Pacific. This heat had built up since the 1990s mainly due to greenhouse-gas (GHG) forcing and possible remote oceanic effects. Model simulations and projections suggest that the fundamental cause, and robust predictor of large record-breaking events of GMST in the 21st century, is GHG forcing rather than internal climate variability alone. Such events will increase in frequency, magnitude, and duration, as well as impact, in the future unless GHG forcing is reduced.

The Community Earth System Model (CESM) is a coupling of five different models which are combined to simulate the dynamic interactions between and within the Earth's atmosphere, ocean, land, land-ice, and sea-ice. In this work, the installation and testing of CESM on Portland State University's Cluster for Climate Change and Aerosol Research (CsAR) is described and documented, and two research applications of the model are performed. First, the improved treatment of cloud microphysics within recent versions of CESM's atmospheric module is applied to an examination of changes in shortwave cloud forcing (SWCF) and results are compared to output from older versions of the model. Second, the CESM model is applied to an examination of the effect that increased methane (CH4) concentrations have had on the catalytic destruction of stratospheric ozone (O3) by ozone depleting compounds (ODCs) such as chlorofluorocarbons (CFCs) and nitrous oxide (N2O).

Water is a primary driver of the physical, geochemical and biological evolution of the Earth. The near-surface hydrosphere (exosphere) includes the atmosphere, cryosphere (glacial and polar ice), the biosphere, surface water, groundwater, and the oceans. The amounts of water in these various reservoirs of the hydrologic cycle have likely varied significantly over the past 700 Ma, with the cryosphere and continental biosphere reservoirs likely showing the most dramatic variations relative to the modern. For example, 700 Ma, during snowball-Earth conditions, the planet may have been almost entirely enveloped in ice, whereas throughout much of the Phanerozoic, greenhouse conditions predominately prevailed and the Earth had a much smaller cryosphere. Similarly, before about 444 Ma and the proliferation of land plants, the continental biosphere reservoir would have effectively non-existent. However, today, plants play a critical role in storage and transfer of water within the hydrologic cycle. Because the amount of water in the exosphere is thought to have remained relatively constant during the past 700 Ma, variations in the amounts of water held by the in the various exogenic reservoirs exert concomitant effects on other reservoirs in the exosphere. We present a conceptual and numerical model that examines variations in the amount of water in the various reservoirs of the near-surface hydrologic cycle (exosphere) during the past 700 Ma and quantify variations in the rates of exchange of water between these reservoirs in deep time. Variations in the sizes of major reservoirs are primarily controlled by changes in global average temperature, and the movement of water between the atmosphere, surface water, and ocean reservoirs varies in concert with the waxing and waning of the cryosphere. We find that variations in the sizes of major reservoirs are primarily controlled by changes in global average temperature, and the flux of water between the atmosphere, surface water, and ocean reservoirs varies in concert with the waxing and waning of the cryosphere, with some fluxes decreasing to 0.0 kg/yr during snowball-Earth conditions. We find that the amount of water precipitated from the atmosphere to the cryosphere increases from greenhouse conditions to -10.5°C and decreases from -10.5°C to snowball-earth conditions, highlighting "tipping-point" behavior due to changes in temperature and cryosphere surface area. The amount of surface runoff to the oceans varies in proportion to the amount of water removed from the surface water reservoir and transferred into the continental biosphere. Variations in the movement of water between near-surface reservoirs that are driven by the waxing and waning of the cryosphere and emergence and growth of plant life thus have significant implications for the transfer of weathering products to the oceans and could contribute to short-term (<1 Ma) variations in seawater composition and isotopic signatures. / Ph. D.

This study focuses on two main broad areas of active research on climate: climate variability and climate change and their implications on regional precipitation characteristics. All the analysis is carried out for a climate change-sensitive region, the state of Florida, USA. The focus of the climate variability analysis is to evaluate the influence of individual and coupled phases (cool and warm) of Atlantic multidecadal oscillation (AMO) and El Niäno southern oscillation (ENSO) on regional precipitation characteristics. The two oscillations in cool and warm phases modulate each other which have implications on flood control and water supply in the region. Extreme precipitation indices, temporal distribution of rainfall within extreme storm events, dry and wet spell transitions and antecedent conditions preceding extremes are evaluated. Kernel density estimates using Gaussian kernel for distribution-free comparative analysis and bootstrap sampling-based confidence intervals are used to compare warm and cool phases of different lengths. Depth-duration-frequency (DDF) curves are also developed using generalized extreme value (GEV) distributions characterizing the extremes. ... This study also introduces new approaches to optimally select the predictor variables which help in modeling regional precipitation and further provides a mechanism to select an optimum spatial resolution to downscale the precipitation projections. New methods for correcting the biases in monthly downscaled precipitation projections are proposed, developed and evaluated in this study. The methods include bias corrections in an optimization framework using various objective functions, hybrid methods based on universal function approximation and new variants. / by Aneesh Goly. / Thesis (Ph.D.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Orientador: Irenilza de Alencar Naas / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-12T04:44:51Z (GMT). No. of bitstreams: 1 Salgado_DouglasD'Alessandro_D.pdf: 3167854 bytes, checksum: 2a149c44af5c26b803e75f1f15eb8ca3 (MD5) Previous issue date: 2006 / Resumo: O agronegócio e responsável por 33% do Produto Interno Bruto (PIB), 42% das exportações totais e 37% dos empregos brasileiros. O Brasil e hoje o segundo maior produtor e maior exportador de carne de frango do mundo, com exportações de 2,4 milhões de toneladas por ano e receitas cambiais de US$ 2,6 bilhões. Devido a importância que o setor agrícola tem para a economia nacional, torna-se fundamental a analise de todo e qualquer fator que possa afetar seu desempenho de maneira efetiva nas próximas décadas. O clima, como um dos principais fatores limitantes e determinantes da produção agrícola, enquadra-se nesse cenário e, como tal, deve ser cada vez mais estudado e conhecido, tendo em vista a tendência de sua alteração em um futuro próximo. As perdas de desempenho na produção avícola, decorrentes de situações extremas de tempo estão associadas a maior incidência de patologias, condenação de carcaças, morte pré-abate e ao menor tempo de vida de prateleira dos produtos alimentícios de origem animal. Entre tais situações extremas, pode ser destacada a onda de calor, definida como sendo um evento relativamente raro, em que as temperaturas diárias alcançam patamares muito acima dos padrões da região afetada, podendo permanecer por um período mínimo de três dias consecutivos. Esta pesquisa teve como objetivo desenvolver uma metodologia para estimar o risco de ocorrências de fenômenos meteorológicos de alta temperatura (temperatura diária extrema e onda de calor) em diferentes municípios do estado de São Paulo, com base em dados meteorológicos diários e, através de uma analise exploratória, fornecer a distribuição de risco desses fenômenos, gerando subsídios para o produtor avícola prevenir perdas decorrentes desses fenômenos. Os dados históricos meteorológicos fornecidos pelo CEPAGRI-UNICAMP foram adaptados as analises estatísticas, sendo realizadas as analises descritivas e exploratórias com as temperaturas. Os dados de temperaturas diárias foram categorizados em forma binária, estimando-se probabilidades condicionais (riscos), através das freqüências relativas obtidas em tabelas de contingência. Usando o software Minitab15® e de um programa elaborado em linguagem Delphi® foram realizadas as analises de risco, a partir das quais foram confeccionados os mapas com o auxilio do software ArcGis 9.2 - ESRI.® A pesquisa apresentou uma metodologia para quantificar os riscos de fenômenos meteorológicos de alta temperatura, identificou os fatores climáticos e sua influencia sobre os riscos. Esse trabalho apontou que os municípios da região oeste do estado de São Paulo são os mais suscetíveis a apresentarem perda na produção avícola devido as temperaturas ambiente, sendo recomendado maior cuidado com o excesso de calor nos alojamentos nas granjas, por parte do produtor. Também foi constatado que os valores médios e medianos das temperaturas mínimas sao bons preditores do risco, devido a alta associação entre o risco e essas variáveis. / Abstract: The agribusiness is responsible for 33% of Brazilian Gross National Product (GNP), 42% of the total export and 37% of Brazilian job offers. Nowadays, Brazil is the second largest producer of poultry meat and the largest export, exporting as much as 2,4 million tons per year . Due to the sector's importance, it becomes essential to analyze each and every issue that may effectively affect its performance in the next decades. Climate, as one of the determinant factors of the agricultural production, fits to this scenario and should be studied, considering the changes that are possibly taking place in a near future. Performance losses in poultry production due to extreme weather conditions are related to higher incidence of pathologies, carcass condemnation, pre-slaughter death and shorter shelf-time for animal origin food products. Among such extreme situations, it is possible to highlight the heat wave, which is defined as a quite rare event, when the daily temperatures are higher than the affected region's pattern and which may last at least 3 days. The present work aimed at developing a methodology to estimate the risk of high temperatures (extreme daily temperatures and heat waves) in different cities in the state of Sao Paulo, based on meteorological data. Also, through an exploratory analysis, this work aimed at offering these phenomena's risk distribution and providing bird producers with subsidies that will allow prevention of losses due to the occurrence of these phenomena. The meteorological data, collected throughout history, were provided by CEPAGRI-UNICAMP and were adapted to the statistical descriptive and exploratory analysis. The daily temperature data were binarily categorized and the conditional probabilities (risk) were estimated through the relative frequencies obtained from contingency tables. Risk analysis was performed using the software Minitab 15® and a software elaborated in Delphi® language. Based on this analysis, it was possible to elaborate maps using the software ArcGis 9.2 - ESRI® The research provided a methodology to quantify the risks of high temperatures phenomena and identified the climatic factors and their influence over those risks. This work showed that the cities in the west of the state of Sao Paulo are highly exposed to performance losses in poultry production due to high ambient temperatures and it is strongly recommended that measures are taken to ease the excessive heat inside the livestock in poultry houses. It was also clear that the average and median values of the minimum temperatures are good means of predicting the risk due to its association to those variables. / Doutorado / Construções Rurais e Ambiencia / Engenharia Agricola