The distribution of model-based estimates of equilibrium climate sensitivity has not changed substantially in more than 30 years. Efforts to narrow this distribution by weighting projections according to measures of model fidelity have so far failed, largely because climate sensitivity is independent of current measures of skill in current ensembles of models. This work presents a cautionary example showing that measures of model fidelity that are effective at narrowing the distribution of future projections (because they are systematically related to climate sensitivity in an ensemble of models) may be poor measures of the likelihood that a model will provide an accurate estimate of climate sensitivity (and thus degrade distributions of projections if they are used as weights). Furthermore, it appears unlikely that statistical tests alone can identify robust measures of likelihood. The conclusions are drawn from two ensembles: one obtained by perturbing parameters in a single climate model and a second containing the majority of the world’s climate models. The simple ensemble reproduces many aspects of the multimodel ensemble, including the distributions of skill in reproducing the present-day climatology of clouds and radiation, the distribution of climate sensitivity, and the dependence of climate sensitivity on certain cloud regimes. Weighting by error measures targeted on those regimes permits the development of tighter relationships between climate sensitivity and model error and, hence, narrower distributions of climate sensitivity in the simple ensemble. These relationships, however, do not carry into the multimodel ensemble. This suggests that model weighting based on statistical relationships alone is unfounded and perhaps that climate model errors are still large enough that model weighting is not sensible.

Thesis (M.S.)--University of Nevada, Reno, 2006. / "December, 2006." Includes bibliographical references (leaves 104-108). Online version available on the World Wide Web.

The Southeast United States during summer and fall is often affected by droughts and tropical cyclones. Both phenomena rank among the most expensive of natural hazards, although droughts are not as feared by the public as hurricanes. When a tropical cyclone causes a pendulum swing from drought to wet conditions, it is known as a “drought-busting tropical cyclone.” The majority of the research related to drought busting tropical cyclones investigates only the storms during their tropical cyclone phase, which covers the southeastern states that have boundaries adjacent to the Atlantic Ocean. An unanswered question from this literature is whether or not these findings apply to the interior southeastern states that have no ocean boundaries, where there is an increase in the probability of a drought-busting tropical cyclone transitioning to an extra-tropical cyclone. This thesis research attempts to determine the impact of drought-busting cyclones on the states of Kentucky and Tennessee. Research findings in this thesis revealed that droughts occur more frequently in the eastern climate divisions of the study area, 2-3 tropical cyclones affect the study area each year, and 6% of warm-season precipitation comes from tropical cyclones or their remnants. Chi-Square analysis and Kruskal-Wallis tests suggest that the Atlantic Multidecadal Oscillation (AMO) has statistically significant relationships with drought frequency, tropical cyclone precipitation, and extra-tropical cyclone precipitation in several climate divisions. While the literature argues that drought-busting tropical cyclones are common in coastal locations, they were found to be rare in Kentucky and Tennessee.

Note:

This thesis focuses on evaluation of joint occurrence of extreme precipitation and streamflow events at several hydrologic structures in South Florida. An analysis of twelve years storm events and their corresponding peak streamflow events during wet and dry season including annual peaks considering two seasons was performed first. Dependence analysis using time series data of precipitation and streamflow was carried out next. The analysis included use of storm events with different temporal lags from the time of occurrence of peak streamflow events. Bi-variate joint probability was found to be appropriate to analyze the joint occurrence of events. Evaluation of joint exceedence probabilities under two phases of Atlantic multidecadal oscillation (AMO) influencing south Florida was also evaluated. All methodologies are evaluated for application using observations at several structures in the case study region to provide advances and valuable insights on joint extremes of precipitation and streamflows. / by Chia-hung Lin. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

The influence of anthropogenic emissions on aerosol distributions and the hydrological cycle are examined with a focus on monsoon precipitation over the Indian subcontinent, during January 2001 to December 2005, using the European Centre for Medium-Range Weather Forecasts-Hamburg (ECHAM5.5) general circulation model extended by the Hamburg Aerosol Module (HAM). The seasonal variability of aerosol optical depth (AOD) retrieved from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellite is broadly well simulated (R 0.6–0.85) by the model. The spatial distribution and seasonal cycle of the precipitation observed over the Indian region are reasonably well simulated (R 0.5 to 0.8) by the model, while in terms of absolute magnitude, the model underestimates precipitation, in particular in the south-west (SW) monsoon season. The model simulates significant anthropogenic aerosol-induced changes in clear-sky net surface solar radiation (dimming greater than -7 W m-2), which agrees well with the observed trends over the Indian region. A statistically significant decreasing precipitation trend is simulated only for the SWmonsoon season over the central-north Indian region, which is consistent with the observed seasonal trend over the Indian region. In the model, this decrease results from a reduction in convective precipitation, where there is an increase in stratiform cloud droplet number concentration (CDNC) and solar dimming that resulted from increased stability and reduced evaporation. Similarities in spatial patterns suggest that surface cooling, mainly by the aerosol indirect effect, is responsible for this reduction in convective activity. When changes in large-scale dynamics are allowed by slightly disturbing the initial state of the atmosphere, aerosol absorption in addition leads to a further stabilization of the lower troposphere, further reducing convective precipitation.

The distribution of model-based estimates of equilibrium climate sensitivity has not changed substantially in more than 30 years. Efforts to narrow this distribution by weighting projections according to measures of model fidelity have so far failed, largely because climate sensitivity is independent of current measures of skill in current ensembles of models. This work presents a cautionary example showing that measures of model fidelity that are effective at narrowing the distribution of future projections (because they are systematically related to climate sensitivity in an ensemble of models) may be poor measures of the likelihood that a model will provide an accurate estimate of climate sensitivity (and thus degrade distributions of projections if they are used as weights). Furthermore, it appears unlikely that statistical tests alone can identify robust measures of likelihood. The conclusions are drawn from two ensembles: one obtained by perturbing parameters in a single climate model and a second containing the majority of the world’s climate models. The simple ensemble reproduces many aspects of the multimodel ensemble, including the distributions of skill in reproducing the present-day climatology of clouds and radiation, the distribution of climate sensitivity, and the dependence of climate sensitivity on certain cloud regimes. Weighting by error measures targeted on those regimes permits the development of tighter relationships between climate sensitivity and model error and, hence, narrower distributions of climate sensitivity in the simple ensemble. These relationships, however, do not carry into the multimodel ensemble. This suggests that model weighting based on statistical relationships alone is unfounded and perhaps that climate model errors are still large enough that model weighting is not sensible.

The influence of anthropogenic emissions on aerosol distributions and the hydrological cycle are examined with a focus on monsoon precipitation over the Indian subcontinent, during January 2001 to December 2005, using the European Centre for Medium-Range Weather Forecasts-Hamburg (ECHAM5.5) general circulation model extended by the Hamburg Aerosol Module (HAM). The seasonal variability of aerosol optical depth (AOD) retrieved from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellite is broadly well simulated (R 0.6–0.85) by the model. The spatial distribution and seasonal cycle of the precipitation observed over the Indian region are reasonably well simulated (R 0.5 to 0.8) by the model, while in terms of absolute magnitude, the model underestimates precipitation, in particular in the south-west (SW) monsoon season. The model simulates significant anthropogenic aerosol-induced changes in clear-sky net surface solar radiation (dimming greater than -7 W m-2), which agrees well with the observed trends over the Indian region. A statistically significant decreasing precipitation trend is simulated only for the SWmonsoon season over the central-north Indian region, which is consistent with the observed seasonal trend over the Indian region. In the model, this decrease results from a reduction in convective precipitation, where there is an increase in stratiform cloud droplet number concentration (CDNC) and solar dimming that resulted from increased stability and reduced evaporation. Similarities in spatial patterns suggest that surface cooling, mainly by the aerosol indirect effect, is responsible for this reduction in convective activity. When changes in large-scale dynamics are allowed by slightly disturbing the initial state of the atmosphere, aerosol absorption in addition leads to a further stabilization of the lower troposphere, further reducing convective precipitation.

Submitted by Maria Beatriz Vieira (mbeatriz.vieira@gmail.com) on 2017-05-08T15:56:08Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_patricia_nunes_tuchtenhagen.pdf: 4953358 bytes, checksum: 7c840b0ed102c32fdb89c11af7167972 (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-05-09T10:52:57Z (GMT) No. of bitstreams: 2 dissertacao_patricia_nunes_tuchtenhagen.pdf: 4953358 bytes, checksum: 7c840b0ed102c32fdb89c11af7167972 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-05-09T10:52:57Z (GMT). No. of bitstreams: 2 dissertacao_patricia_nunes_tuchtenhagen.pdf: 4953358 bytes, checksum: 7c840b0ed102c32fdb89c11af7167972 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2013-11-01 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / A crescente demanda e consumo de energia elétrica, tanto pela sociedade econômica como social; em adição à política mundial para a implementação de sistemas de geração empregando fontes renováveis, tem sido fator determinante na expansão de fazendas eólicas em diferentes países. Para a determinação do local para a instalação de fazendas eólicas é de importância fundamental proceder a estudos, realizar análises e avaliar a disponibilidade da fonte que permite gerar a energia, ou seja, do vento, em níveis de altura compatíveis com a dos geradores eólicos. Tendo em vista que, raramente se dispõe de dados de medições do vento necessários para consolidar os requisitos básicos e fundamentais, particularmente sobre o Brasil, é proposta, desenvolvida e aplicada uma metodologia que permite avaliar o potencial eólico sobre o país para um ano. Os dados necessários para elaborar o mapeamento e a avaliação do potencial eólico, durante o ano de 2011, foram produzidos, de hora em hora, com o processamento do modelo de mesoescala WRF (Weather Research and Forecasting). A avaliação dos resultados foi realizada em termos de médias diárias, número de horas sequenciais com ventos, vento médio acima de valores pré-estabelecidos de vento e período de rampa, análises sazonal e anual, frequência dos ventos e densidade da probabilidade de Weibull. Como conclusão geral da análise realizada, foram caracterizadas algumas regiões do país, localizadas próximas do litoral do Nordeste e Sul do país, que se apresentam como locais marcadamente favoráveis à instalação de fazendas eólicas. Entretanto, aponta-se, também, que há diversas outras áreas esparsas sobre o país que podem ser indicadas como locais com grande potencialidade energética. / The increasing demand and electric energy consumption, by both economic and social society, in addition to the worldwide politics for the implementation of generation systems employing renewable sources, has been determinant factors of the expansion of wind farms in different countries. To find out an installation local of wind power farms, it is of fundamental importance to proceed studies, perform analysis and evaluate the availability of the source to generate energy – that is, the wind at vertical levels which are consistent with the wind turbine height. Given that, scarcely the wind measurement data needed are available to consolidate the basic and fundamental requirements, particularly over Brazil, it is proposed, developed and a methodology is applied, for the assessment of wind energy potential over the country for a year. The required data for the mapping and assessment of wind energy potential, during the year 2011 were produced, for every hour, throughout the mesoscale model WRF (Weather Research and Forecasting) forecasting. The result evaluation has been performed in terms of daily mean wind average, number of sequential hours with wind, wind above pre-established values and ramp period, seasonal and annual analysis, wind frequency analysis and Weibull probability density. The general conclusion of the performed analysis has been the characterization of some region of the country, located nearby the shoreline of the Northeast and South of the county, as remarkable locals favorable for the installation of wind farms. However, it has been also pointed out that there are several other areas, scattered over the country, which can be suitable places with great energy potentiality.

Submitted by Maria Beatriz Vieira (mbeatriz.vieira@gmail.com) on 2017-05-08T16:23:16Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-05-09T10:54:02Z (GMT) No. of bitstreams: 2 dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-05-09T10:54:02Z (GMT). No. of bitstreams: 2 dissertacao_rodrigo_da_silva_pereira.pdf: 1723922 bytes, checksum: 18533319b08c17041a8e5681e41087ff (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-02-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Esta dissertação tem como propósito geral a análise do clima presente e o comportamento futuro dos eventos extremos de precipitação local de curta duração com potencial para causar alagamento nas principais cidades do Rio Grande do Sul abrangendo diferentes regiões do Estado: Porto Alegre, Caxias do Sul, Santa Maria e Pelotas. Baseado no histórico de alagamentos de cada cidade e nos dados diários de precipitação obtidos das estações meteorológicas do INMET (Instituto Nacional de Meteorologia) obteve-se o limiar que identificou a taxa de precipitação que representa um evento com potencial para causar alagamento na cidade, sendo os eventos divididos em caso de atenção (percentil 25) ou de alerta (percentil 75) nas 48h precedentes à ocorrência do alagamento. Os resultados revelaram um crescimento sutil dos casos, tanto atenção quanto alerta, nos últimos 53 anos. A cidade de Porto Alegre foi a que apresentou os menores limiares para condição de alagamento, o que era esperado devido sua maior urbanização. Ao avaliar o comportamento sazonal dos casos constatou-se que no clima presente (1961-2013), o trimestre julho-agosto-setembro foi a época do ano mais propícia a casos de alagamentos. Posteriormente, os casos foram correlacionados com três índices climáticos que medem as anomalias de TSM (Temperatura da Superfície do Mar) do Atlântico Sul e do Pacífico, no intuito de avaliar se suas ocorrências estão associadas a fenômenos climáticos de grande escala. As correlações encontradas variaram de fracas a moderadas, mas com alto nível de confiança estatística para o IME (Índice Multivariado do ENOS). O uso de modelagem climática regional (modelo ETA-HadCM3) denotou que num cenário futuro (A1B de acordo com o Painel Intergovernamental sobre Mudanças Climáticas) para o período de 2021-2070 haverá no geral, um pequeno acréscimo no número de casos de atenção para todas as cidades, quando comparado aos valores observados no clima presente (1961-2013). Em Pelotas, haverá uma mudança na climatologia dos eventos com deslocamento da estação com maior número de casos do trimestre JAS (clima presente) para o OND (cenário futuro). / This work has as general purpose the analysis of present climate and future behavior of short duration extreme local rainfall events with potential for causing flooding in major cities in Rio Grande do Sul State covering different regions: Porto Alegre, Caxias do Sul, Santa Maria and Pelotas. Based on history of floods of each city and on the rainfall data obtained from meteorological stations of INMET (National Institute of Meteorology), the thresholds that have identified which precipitation rate is an event with the potential to cause flooding in the city were obtained, being such events divided in case of attention (25th percentile) or case of alert (75th percentile) in 48 hours before the occurrence of flooding. The results showed a subtle increase of cases, both as alert and attention in the last 53 years. The city of Porto Alegre was presented the least thresholds for flooding condition, which was expected due to its increased urbanization. In assessing the seasonal behavior of the cases it was found that in this climate, the July-August-September was the time of year most facilitates cases of flooding. Later, cases were correlated with three climate indices that measure the SST (Sea Surface Temperature) anomalies in order to assess whether their occurrences are associate to large-scale climatic phenomena. It was found weak to moderate correlations, but with a high level of statistical confidence for the EMI (ENSO Multivariate Index). The use of regional climate model (ETA-HadCM3) denotes that in a future scenario (A1B following International Panel on Climate Change) for the period 2021-2070 will be in general an increase number of cases of attention for all cities, when compared to those observed in the present climate (1961-2013). In Pelotas there will be a climatological change due to a displacement of the season with more cases: from JAS quarter (present) to OND quarter (future scenario).