Dissertations / Theses: 'Weather Mathematical models'

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Melton, Roy Wayne. "Parallelizing the spectral method in climate and weather modeling." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04062004-164733/unrestricted/melton%5Froy%5Fw%5F200312%5Fphd.pdf.

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Nyulu, Thandekile. "Weather neutral models for short-term electricity demand forecasting." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1018751.

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Energy demand forecasting, and specifically electricity demand forecasting, is a fun-damental feature in both industry and research. Forecasting techniques assist all electricity market participants in accurate planning, selling and purchasing decisions and strategies. Generation and distribution of electricity require appropriate, precise and accurate forecasting methods. Also accurate forecasting models assist producers, researchers and economists to make proper and beneficial future decisions. There are several research papers, which investigate this fundamental aspect and attempt var-ious statistical techniques. Although weather and economic effects have significant influences on electricity demand, in this study they are purposely eliminated from investigation. This research considers calendar-related effects such as months of the year, weekdays and holidays (that is, public holidays, the day before a public holiday, the day after a public holiday, school holidays, university holidays, Easter holidays and major religious holidays) and includes university exams, general election days, day after elections, and municipal elections in the analysis. Regression analysis, cate-gorical regression and auto-regression are used to illustrate the relationships between response variable and explanatory variables. The main objective of the investigation was to build forecasting models based on this calendar data only and to observe how accurate the models can be without taking into account weather effects and economic effects, hence weather neutral models. Weather and economic factors have to be forecasted, and these forecasts are not so accurate and calendar events are known for sure (error-free). Collecting data for weather and economic factors is costly and time consuming, while obtaining calendar data is relatively easy.

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Yan, Hanjun. "Numerical methods for data assimilation in weather forecasting." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/555.

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Data assimilation plays an important role in weather forecasting. The purpose of data assimilation is try to provide a more accurate atmospheric state for future forecast. Several existed methods currently used in this field fall into two categories: statistical data assimilation and variational data assimilation. This thesis focuses mainly on variational data assimilation. The original objective function of three dimensional data assimilation (3D-VAR) consists of two terms: the difference between the pervious forecast and analysis and the difference between the observations and analysis in observation space. Considering the inaccuracy of previous forecasting results, we replace the first term by the difference between the previous forecast gradients and analysis gradients. The associated data fitting term can be interpreted using the second-order finite difference matrix as the inverse of the background error covariance matrix in the 3D-VAR setting. In our approach, it is not necessary to estimate the background error covariance matrix and to deal with its inverse in the 3D-VAR algorithm. Indeed, the existence and uniqueness of the analysis solution of the proposed objective function are already established. Instead, the solution can be calculated using the conjugate gradient method iteratively. We present the experimental results based on WRF simulations. We show that the performance of this forecast gradient based DA model is better than that of 3D-VAR. Next, we propose another optimization method of variational data assimilation. Using the tensor completion in the cost function for the analysis, we replace the second term in the 3D-VAR cost function. This model is motivated by a small number of observations compared with the large portion of the grids. Applying the alternating direction method of multipliers to solve this optimization problem, we conduct numerical experiments on real data. The results show that this tensor completion based DA model is competitive in terms of prediction accuracy with 3D-VAR and the forecast gradient based DA model. Then, 3D-VAR and the two model proposed above lack temporal information, we construct a third model in four-dimensional space. To include temporal information, this model is based on the second proposed model, in which introduce the total variation to describe the change of atmospheric state. To this end, we use the alternating direction method of multipliers. One set of experimental results generates a positive performance. In fact, the prediction accuracy of our third model is better than that of 3D-VAR, the forecast gradient based DA model, and the tensor completion based DA model. Nevertheless, although the other sets of experimental results show that this model has a better performance than 3D-VAR and the forecast gradient based DA model, its prediction accuracy is slightly lower than the tensor completion based model.

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Schiefelbein, Jon M. "Prototype development of machine-to-machine operational nephanalysis." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FSchiefelbein.pdf.

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Schroder, Ulf P. "Development of a weather radar signal simulator to examine sampling rates and scanning schemes." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Sep%5FSchroder.pdf.

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Wahl, Douglas Timothy. "Increasing range and lethality of Extended -Range Munitions (ERMS) using Numerical Weather Prediction (NWP) and the AUV workbench to compute a Ballistic Correction (BALCOR)." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FWahl.pdf.

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Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Wendell Nuss, Don Brutzmann. "December 2006." Includes bibliographical references (p. 107-116). Also available in print.

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Sanabia, Elizabeth R. "Objective identification of environmental patterns related to tropical cyclone track forecast errors." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FSanabia.pdf.

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Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2006.
Thesis Advisor(s): Patrick A. Harr, Russell L. Elsberry. "September 2006." Includes bibliographical references (p. 43). Also available in print.

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Nakakita, Kunio. "Toward real-time aero-icing simulation using reduced order models." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99781.

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Even though the power of supercomputers has increased extraordinarily, there is still an insatiable need for more advanced multi-disciplinary CFD simulations in the aircraft analysis and design fields. A particular current interest is in the realistic three-dimensional fully viscous turbulent flow simulation of the highly non-linear aspects of aero-icing. This highly complex simulation is still computationally too demanding in industry, especially when several runs, such as parametric studies, are needed. In order to make such compute-intensive simulations more affordable, this work presents a reduced order modeling approach, based on the "Proper Orthogonal Decomposition", (POD), method to predict a wider swath of flow fields and ice shapes based on a limited number of "snapshots" obtained from complete high-fidelity CFD computations. The procedure of the POD approach is to first decompose the fields into modes, using a limited number of full-calculations snapshots, and then to reconstruct the field and/or ice shapes using those decomposed modes for other conditions, leading to reduced order calculations. The use of the POD technique drastically reduces the computational cost and can provide a more complete map of the performance degradation of an iced aircraft over a wide range of flight and weather conditions.

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Shorts, Vincient F. "A mathematical analysis of the Janus combat simulation weather effects models and sensitivity analysis of sky-to-ground brightness ratio on target detection." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA289629.

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Thesis (M.S. in Applied Mathematics) Naval Postgraduate School, September 1994.
Thesis advisor(s): Bard K. Mansager, Maurice D. Weir. "September 1994." Bibliography: p. 63-64. Also available online.

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Khajehei, Sepideh. "A Multivariate Modeling Approach for Generating Ensemble Climatology Forcing for Hydrologic Applications." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2403.

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Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. Currently, Numerical Weather Prediction (NWP) models are developing ensemble forecasts for various temporal and spatial scales. However, it is proven that the raw products of the NWP models may be biased at the basin scale; unlike model grid scale, depending on the size of the catchment. Due to the large space-time variability of precipitation, bias-correcting the ensemble forecasts has proven to be a challenging task. In recent years, Ensemble Pre-Processing (EPP), a statistical approach, has proven to be helpful in reduction of bias and generation of reliable forecast. The procedure is based on the bivariate probability distribution between observation and single-value precipitation forecasts. In the current work, we have applied and evaluated a Bayesian approach, based on the Copula density functions, to develop an ensemble precipitation forecasts from the conditional distribution of the single-value precipitation. Copula functions are the multivariate joint distribution of univariate marginal distributions and are capable of modeling the joint distribution of two variables with any level of correlation and dependency. The advantage of using Copulas, amongst others, includes its capability of modeling the joint distribution independent of the type of marginal distribution. In the present study, we have evaluated the capability of copula-based functions in EPP and comparison is made against an existing and commonly used procedure for same i.e. meta-Gaussian distribution. Monthly precipitation forecast from Climate Forecast System (CFS) and gridded observation from Parameter-elevation Relationships on Independent Slopes Model (PRISM) have been utilized to create ensemble pre-processed precipitation over three sub-basins in the western USA at 0.5-degree spatial resolution. The comparison has been made using both deterministic and probabilistic frameworks of evaluation. Across all the sub-basins and evaluation techniques, copula-based technique shows more reliability and robustness as compared to the meta-Gaussian approach.

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Aliaga, Rivera Cristhian Neil. "An unsteady multiphase approach to in-flight icing /." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112552.

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Ice accretion is a purely unsteady phenomenon that is presently approximated by most icing codes using quasi-steady modeling. The accuracy of ice prediction is thus directly related to the arbitrarily prescribed time span during which the impact of ice growth on both flow and droplets is neglected. The objective of this work is to remove this limitation by implementing a cost-effective unsteady approach. This is done by fully coupling, in time, a diphasic flow (interacting air and droplet particles) with the ice accretion model. The two-phase flow is solved using the Navier-Stokes and Eulerian droplet equations with dual-time stepping in order to improve computational time. The ice shape is either obtained from the conservation of mass and energy within a thin film layer for glaze and mixed icing conditions, or from a mass balance between water droplets impingement and mass flux of ice for rime icing conditions. The iced surface being constantly displaced in time, Arbitrary Lagrangian-Eulerian terms are added to the governing equations to account for mesh movement. Moreover, surface smoothing techniques are developed to prevent degradation of the iced-surface geometric discretization. For rime ice, the numerical results clearly show that the new full unsteady modeling improves the accuracy of ice prediction, compared to the quasi-steady approach, while in addition ensuring time span independence. The applicability of the unsteady icing model for predicting glaze ice accretion is also demonstrated by coupling the diphasic model to the Shallow Water Icing Model. A more rigorous analysis reveals that this model requires the implementation of local surface roughness and that previous quasi-steady validations cannot be carried out using a small number of shots, therefore the need for unsteady simulation.

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Evangelista, Raquel Couto. "Impacto das mudanças climáticas na produtividade de eucalipto em duas regiões do Brasil." Universidade Federal de Viçosa, 2006. http://locus.ufv.br/handle/123456789/5272.

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Made available in DSpace on 2015-03-26T13:50:16Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1916552 bytes, checksum: c18d32a0eda19b2b7b6680811092f773 (MD5) Previous issue date: 2006-08-11
Conselho Nacional de Desenvolvimento Científico e Tecnológico
The planted eucalyptus forests are the bigger and the most productive in Brazil. The high growth rate and the short cycle are intrinsic to this wood production system, making essential the development of management and operational practices that guarantee the economic feed-back and the sustainability of these crops. Attempt to estimate the productive potential of an area, by using growth models based on physiologic methods, permits the risk evaluation of climate changes and identification of new areas capable to grow forests. Climate changes scenarios associated to growth models based on processes can be useful to identify the risks of negative consequences on the future yield of planted forests, and consequently, reduce the impacts of climate changes and evaluate adaptation ways. Thereby, this study had the goal to evaluate climate changes on the forest production of eucalyptus through the growth model 3-PG in two productive areas: Area I - north Espirito Santo and south Bahia; and Area II – mid-east Minas Gerais. Two climate change scenarios (A2 and B2) from the global climatic model CCSR/NIES, for three future periods (2011-2040, 2041-2070 e 2071- 2100) were used to feed the model 3-PG with climate data. To evaluate the simulated results of the future yield, was used as a base period the data bank climatology of the CRU, obtaining by that, the current yield. According to the anomalies generated, by the difference between the future scenarios values and the climatology, was observed the rising on the maximum and minimum temperature values on the two studied areas and the decrease of rainfall values in both areas. Has been proved in this study also that, the future variations on temperature and rainfall have caused a reduction on the eucalyptus yield in both analyzed areas, being the reduction on north Espirito Santo and south Bahia of 39,1% in 2071 – 2100 on A2 scenario, and on mid-east Minas Gerais 36,9% in 2071-2100 also on A2 scenario. Through the results was concluded that the eucalyptus crops can suffer impacts on their yields due to climate changes, mainly referring to temperature and rainfall variations.
As florestas plantadas de eucalipto são as maiores e mais produtivas do Brasil, a alta taxa de crescimento e o ciclo curto são típicos destes sistemas de produção de madeira, portanto torna-se essencial que práticas operacionais e de manejo sejam desenvolvidas para garantir retorno econômico e assegurar a longo-prazo a sustentabilidade destas plantações. A tentativa de estimar o potencial produtivo de uma região, por meio de modelos de crescimento baseados em processos fisiológicos, permite a avaliação dos riscos da variação climática e a identificação de novas áreas aptas ao plantio florestal. Cenários de mudanças climáticas associados a modelos de crescimento baseados em processos, podem ser úteis para identificar os riscos de conseqüências negativas na produtividade futura de florestas plantadas, podendo assim, mitigar os impactos das mudanças climáticas e avaliar meios de adaptação. Desta forma, este trabalho teve como objetivo avaliar os impactos das mudanças climáticas na produção florestal de eucalipto, por meio do modelo de crescimento 3-PG, em duas regiões produtoras: Região I - norte do Espírito Santo e sul da Bahia; e Região II - centro-leste de Minas Gerais. Foram utilizados como dados de entrada de clima no modelo 3-PG, dois cenários de mudanças climáticas (A2 e B2) do modelo climático global CCSR/NIES, para três períodos futuros: 2011-2040, 2041-2070 e 2071-2100. Para avaliar os resultados simulados da produtividade futura, utilizou-se como período base a climatologia do banco de dados do CRU, obtendo assim, a produtividade “atual”. Conforme as anomalias geradas, pela diferença entre os valores dos cenários futuros e da climatologia, observou-se aumento nos valores de temperatura máxima e mínima nas duas regiões estudadas e decréscimo nos valores de precipitação em ambas as regiões. Comprovou-se neste estudo, que as variações futuras na temperatura e precipitação provocaram redução na produtividade de eucalipto nas duas regiões analisadas, sendo que na região do norte do Espírito Santo e sul da Bahia essa redução chegou a 39,7% em 2071-2100 no cenário A2, e no centro-leste de Minas Gerais a redução chegou a 41,7% em 2071-2100 também no cenário A2. Diante dos resultados, concluiu-se que as plantações de eucalipto podem sofrer impactos em sua produtividade, devido às mudanças climáticas, principalmente no que diz respeito às variações na temperatura e na precipitação.

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Sanz, Rodrigo Javier. "On antarctic wind engineering." Doctoral thesis, Universite Libre de Bruxelles, 2011. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209953.

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Antarctic Wind Engineering deals with the effects of wind on the built environment. The assessment of wind induced forces, wind resource and wind driven snowdrifts are the main tasks for a wind engineer when participating on the design of an Antarctic building. While conventional Wind Engineering techniques are generally applicable to the Antarctic environment, there are some aspects that require further analysis due to the special characteristics of the Antarctic wind climate and its boundary layer meteorology.

The first issue in remote places like Antarctica is the lack of site wind measurements and meteorological information in general. In order to complement this shortage of information various meteorological databases have been surveyed. Global Reanalyses, produced by the European Met Office ECMWF, and RACMO/ANT mesoscale model simulations, produced by the Institute for Marine and Atmospheric Research of Utrecht University (IMAU), have been validated versus independent observations from a network of 115 automatic weather stations. The resolution of these models, of some tens of kilometers, is sufficient to characterize the wind climate in areas of smooth topography like the interior plateaus or the coastal ice shelves. In contrast, in escarpment and coastal areas, where the terrain gets rugged and katabatic winds are further intensified in confluence zones, the models lack resolution and underestimate the wind velocity.

The Antarctic atmospheric boundary layer (ABL) is characterized by the presence of strong katabatic winds that are generated by the presence of surface temperature inversions in sloping terrain. This inversion is persistent in Antarctica due to an almost continuous cooling by longwave radiation, especially during the winter night. As a result, the ABL is stably stratified most of the time and, only when the wind speed is high it becomes near neutrally stratified. This thesis also aims at making a critical review of the hypothesis underlying wind engineering models when extreme boundary layer situations are faced. It will be shown that the classical approach of assuming a neutral log-law in the surface layer can hold for studies of wind loading under strong winds but can be of limited use when detailed assessments are pursued.

The Antarctic landscape, mostly composed of very long fetches of ice covered terrain, makes it an optimum natural laboratory for the development of homogeneous boundary layers, which are a basic need for the formulation of ABL theories. Flux-profile measurements, made at Halley Research Station in the Brunt Ice Shelf by the British Antarctic Survery (BAS), have been used to analyze boundary layer similarity in view of formulating a one-dimensional ABL model. A 1D model of the neutral and stable boundary layer with a transport model for blowing snow has been implemented and verified versus test cases of the literature. A validation of quasi-stationary homogeneous profiles at different levels of stability confirms that such 1D models can be used to classify wind profiles to be used as boundary conditions for detailed 3D computational wind engineering studies.

A summary of the wind engineering activities carried out during the design of the Antarctic Research Station is provided as contextual reference and point of departure of this thesis. An elevated building on top of sloping terrain and connected to an under-snow garage constitutes a challenging environment for building design. Building aerodynamics and snowdrift management were tested in the von Karman Institute L1B wind tunnel for different building geometries and ridge integrations. Not only for safety and cost reduction but also for the integration of renewable energies, important benefits in the design of a building can be achieved if wind engineering is considered since the conceptual phase of the integrated building design process.

Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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Halmstad, Andrew Jason. "Investigating Future Variation of Extreme Precipitation Events over the Willamette River Basin Using Dynamically Downscaled Climate Scenarios." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/327.

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One important aspect related to the management of water resources under future climate variation is the occurrence of extreme precipitation events. In order to prepare for extreme events, namely floods and droughts, it is important to understand how future climate variability will influence the occurrence of such events. Recent advancements in regional climate modeling efforts provide additional resources for investigating the occurrence of extreme events at scales that are appropriate for regional hydrologic modeling. This study utilizes data from three Regional Climate Models (RCMs), each driven by the same General Circulation Model (GCM) as well as a reanalysis dataset, all of which was made available by the North American Regional Climate Change Assessment Program (NARCCAP). A comparison between observed historical precipitation events and NARCCAP modeled historical conditions over Oregon's Willamette River basin was performed. This comparison is required in order to investigate the reliability of regional climate modeling efforts. Datasets representing future climate signal scenarios, also provided by NARCCAP, were then compared to historical data to provide an estimate of the variability in extreme event occurrence and severity within the basin. Analysis determining magnitudes of two, five, ten and twenty-five year return level estimates, as well as parameters corresponding to a representative Generalized Extreme Value (GEV) distribution, were determined. The results demonstrate the importance of the applied initial/boundary driving conditions, the need for multi-model ensemble analysis due to RCM variability, and the need for further downscaling and bias correction methods to RCM datasets when investigating watershed scale phenomena.

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Kane, Aniruddha V. "Cost-Benefit Analysis Model for Advanced Weather Forecasting Installations in Airport Terminal Areas." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/34870.

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Better utilization of the airport system capacities can significantly decrease delays, as well as number of cancelled flights. An efficient Air Traffic Control system equipped with advanced technology installations in the terminal area can help reduce flight delays and cancellations. The same technology could also help reduce accidents in the terminal area, thereby increasing the safety of the system. Due to the expense of fielding advanced technology in the terminal area, it is important to conduct realistic cost-benefit analysis to predict the life-cycle cost of the system. A computer simulation and optimization model to estimate the costs and benefits of fielding advanced technologies at airport terminal areas is introduced in this paper. The model developed is called the Cost-Benefit Analysis Terminal Investment Model (COTIM). This model considers costs and benefits to both service providers (Federal Aviation Administration and airport authorities) and users (Airlines). The model combines a simulation-optimization based approach to predict benefits and costs accrued in one day or throughout the life-cycle of the facility.

We present an example to demonstrate the functionality of the model using Chicago O'Hare International Airport (ORD) equipped with the Integrated Terminal Weather System (ITWS). The Integrated Terminal Weather System (ITWS) is a relatively new technology that forecasts convective weather movements thus allowing Air Traffic Control (ATC) personnel to re-direct flights inside the terminal area efficiently.

COTIM estimates flight delays and cancellations at an airport, when the airport is equipped with advanced technologies such as ITWS. The model performs cost-benefit analysis by comparing a baseline scenario without terminal area technologies against a scenario with technology. The difference between the two scenarios help decision makers justify whether technology investments are warranted of not.

Master of Science

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Yarker, Morgan Brown. "Teacher Challenges, Perceptions, and Use of Science Models in Middle School Classrooms about Climate, Weather, and Energy Concepts." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4929.

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Research suggests that scientific models and modeling should be topics covered in K-12 classrooms as part of a comprehensive science curriculum. It is especially important when talking about topics in weather and climate, where computer and forecast models are the center of attention. There are several approaches to model based inquiry, but it can be argued, theoretically, that science models can be effectively implemented into any approach to inquiry if they are utilized appropriately. Yet, it remains to be explored how science models are actually implemented in classrooms. This study qualitatively looks at three middle school science teachers' use of science models with various approaches to inquiry during their weather and climate units. Results indicate that the teacher who used the most elements of inquiry used models in a way that aligned best with the theoretical framework than the teachers who used fewer elements of inquiry. The theoretical framework compares an approach to argument-based inquiry to model-based inquiry, which argues that the approaches are essentially identical, so teachers who use inquiry should be able to apply model-based inquiry using the same approach. However, none of the teachers in this study had a complete understanding of the role models play in authentic science inquiry, therefore students were not explicitly exposed to the ideas that models can be used to make predictions about, and are representations of, a natural phenomenon. Rather, models were explicitly used to explain concepts to students or have students explain concepts to the teacher or to each other. Additionally, models were used as a focal point for conversation between students, usually as they were creating, modifying, or using models. Teachers were not observed asking students to evaluate models. Since science models are an important aspect of understanding science, it is important that teachers not only know how to implement models into an inquiry environment, but also understand the characteristics of science models so that they can explicitly teach the concept of modeling to students. This study suggests that better pre-service and in-service teacher education is needed to prepare students to teach about science models effectively.

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Granlöf, Markus. "A study of the effects of winterclimate and atmospheric icing onhigh-speed passenger trains." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171868.

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Harsh winter climate causes various problems for both the public andprivate sector in Sweden, especially in the northern part and the railway industryis no exception. This master thesis project covers an investigation of the eects ofthe winter climate and a phenomena called atmospheric icing on the performance ofthe train in a region called the Botnia-Atlantica region. The investigation was donewith data over a short period January-February 2017 with simulated weather datafrom the Weather research and forecast model that was compared with the periodOctober - December 2016. The investigation only included high speed trains.The trains have been analysed based on two dierent performance measurements.The cumulative delay which is the increment in delay over a section and the currentdelay which is the current delay compared to the schedule. Cumulative delaysare investigated with survival analysis and the current delay is investigated with aMulti-state Markov model.The results show that the weather could have an eect on the trains performancewhere the survival analysis detected connection between the weather and cumulativedelays. The Markov model also showed a connection between the weather anddelayed trains including that the presence of atmospheric icing had a negative eecton remaining in a state of non-delay.

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Al-Ogaili, Farah F. "Incorporating Environmental Factors into Trip Planning." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1508196014262712.

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Trémolet, Yannick. "Parallélisation d'algorithmes variationnels d'assimilation de données en météorologie." Grenoble 1, 1995. http://www.theses.fr/1995GRE10211.

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Le probleme de l'assimilation de donnees sous sa forme generale peut se formuler: comment utiliser simultanement un modele theorique et des observations pour obtenir la meilleure prevision meteorologique ou oceanographique ?, sa resolution est tres couteuse, pour la prochaine generation de modeles elle necessitera une puissance de calcul de l'ordre de 10 tflops. A l'heure actuelle, aucun calculateur n'est capable de fournir de telles performances mais cela devrait etre possible dans quelques annees, en particulier grace aux ordinateurs paralleles a memoire distribuee. Mais, la programmation de ces machines reste un processus complique et on ne connait pas de methode generale pour paralleliser de maniere optimale un algorithme donne. Nous tenterons, de repondre au probleme de la parallelisation de l'assimilation de donnees variationnelle, ce qui nous conduira a etudier la parallelisation d'algorithmes numeriques d'optimisation assez generaux. Pour cela, nous etendrons la methodologie de l'ecriture des modeles adjoints au cas ou le modele direct est parallele avec echanges de messages explicites. Nous etudierons les differentes approches possibles pour paralleliser la resolution du probleme de l'assimilation de donnees: au niveau des modeles meteorologiques direct et adjoints, au niveau de l'algorithme d'optimisation ou enfin au niveau du probleme lui-meme. Cela nous conduira a transformer un probleme sequentiel d'optimisation sans contraintes en un ensemble de problemes d'optimisation relativement independants qui pourront etre resolus en parallele. Nous etudierons plusieurs variantes de ces trois approches tres generales et leur utilite dans le cadre du probleme de l'assimilation de donnees. Nous terminerons par l'application des methodes de parallelisation precedentes au modele de shallow water et comparerons leurs performances. Nous presenterons egalement une parallelisation du modele meteorologique arps (advanced regional prediction system)

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Shaevitz, Daniel Albert. "Extreme weather: subtropical floods and tropical cyclones." Thesis, 2016. https://doi.org/10.7916/D8BC3ZTD.

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Extreme weather events have a large effect on society. As such, it is important to understand these events and to project how they may change in a future, warmer climate. The aim of this thesis is to develop a deeper understanding of two types of extreme weather events: subtropical floods and tropical cyclones (TCs). In the subtropics, the latitude is high enough that quasi-geostrophic dynamics are at least qualitatively relevant, while low enough that moisture may be abundant and convection strong. Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. In the first part of this thesis, I examine the possible triggering of convection by the large-scale dynamics and investigate the coupling between the two. Specifically two examples of extreme precipitation events in the subtropics are analyzed, the 2010 and 2014 floods of India and Pakistan and the 2015 flood of Texas and Oklahoma. I invert the quasi-geostrophic omega equation to decompose the large-scale vertical motion profile to components due to synoptic forcing and diabatic heating. Additionally, I present model results from within the Column Quasi-Geostrophic framework. A single column model and cloud-revolving model are forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. It is found that convection was triggered primarily by mechanically forced orographic ascent over the Himalayas during the India/Pakistan flood and by upper-level Potential Vorticity disturbances during the Texas/Oklahoma flood. Furthermore, a climate attribution analysis was conducted for the Texas/Oklahoma flood and it is found that anthropogenic climate change was responsible for a small amount of rainfall during the event but the intensity of this event may be greatly increased if it occurs in a future climate. In the second part of this thesis, I examine the ability of high-resolution global atmospheric models to simulate TCs. Specifically, I present an intercomparison of several models' ability to simulate the global characteristics of TCs in the current climate. This is a necessary first step before using these models to project future changes in TCs. Overall, the models were able to reproduce the geographic distribution of TCs reasonably well, with some of the models performing remarkably well. The intensity of TCs varied widely between the models, with some of this difference being due to model resolution.

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21

Guerra, Larry C. "Predicting evapotranspiration and soil moisture distribution from terrain attributes and weather." Phd thesis, 1995. http://hdl.handle.net/1885/138808.

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22

"Inventory models with weather derivatives and weather-conditional rebates for seasonal products." Thesis, 2007. http://library.cuhk.edu.hk/record=b6074501.

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Key words. Newsvendor Model, Inventory Model, Seasonal Product, Weather Risk, Weather Option, Weather Derivative, Weather-Conditional Rebate, CVaR, Mean-CVaR.
The first model considers the problem of hedging inventory risk for a newsvendor who sells a seasonal product. The newsvendor not only decides the order quantity, but also adopts a weather hedging strategy. A typical hedging strategy is to use an option that is constructed on a weather index before the season begins, which will compensate the buyer of the option if the actual seasonal weather index is above (or below) a given strike level. We explore the joint decision problem in mean-variance, expected utility, conditional value-at-risk (CVaR), and mean-CVaR frameworks. We analyze the impact of weather hedging on optimal order quantity. It is proven that the newsvendor may order more than in the absence of weather options. Numerical analysis on the sensitivity of the optimal order quantity, the risk premium of the option, the portfolio selection and the comparison between the weather option hedging and a particular operational hedging are presented as well.
The second model investigates the advantages of early sales of a seasonal product. To induce early sales, the newsvendor adopts a weather-conditional rebate program, which will pay rebates to the customers who buy the product in the preselling period if a specified weather condition for normal selling season is realized. For an example, a certain amount of refund will be paid to early buyer if the seasonal average temperature falls below the past-three-year seasonal average. Two conditional rebate programs with early booking and early purchasing are investigated and compared. Both of them can price differentiate within a customer among his/her post valuation on the seasonal product, and thus increase the sales. For the early purchasing program, it can further save inventory holding cost and ordering cost. The expected profit can be improved by the programs. Moreover, combined with weather derivatives, the conditional rebate program can manage the financial risk with the expected profit being still improved.
To investigate the means that firms may adopt in managing the adverse impacts of weather on their businesses, this dissertation proposes and analyzes two inventory models for seasonal products when the demand is sensitive to the weather in the season. Both models are formulated under the newsvendor context.
Gao, Fei.
"October 2007."
Adviser: Youhua Frank Chen.
Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 5002.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references (p. 108-119).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.

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23

Nguyen, Hiep Van. "Numerical simulations of airflow and weather during the summer over the island of Oahu." Thesis, 2006. http://hdl.handle.net/10125/20707.

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"Joint optimal ordering and weather hedging contract decisions: a newsvendor model." 2005. http://library.cuhk.edu.hk/record=b5892499.

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Yeung Yun Sing Samson.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 64-67).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Background --- p.5
Chapter 2.1 --- Applicability of Weather Derivative in Hong Kong: The Recre- ation Industry --- p.7
Chapter 2.2 --- Types of Weather Risk --- p.9
Chapter 3 --- Literature Review --- p.12
Chapter 4 --- Basic Model --- p.17
Chapter 4.1 --- Notations --- p.18
Chapter 4.2 --- Assumptions --- p.21
Chapter 4.3 --- The Profit Model --- p.22
Chapter 5 --- Fundamental Analysis --- p.25
Chapter 5.1 --- Sales Profit Analysis --- p.25
Chapter 5.2 --- Option Analysis --- p.27
Chapter 5.3 --- Profit Function Reformulation --- p.30
Chapter 6 --- Objectivel: Lexicographic Optimization --- p.35
Chapter 6.1 --- Equivalence between Lexicographic Optimization and Expected Utility Maximization --- p.38
Chapter 6.2 --- Minimizing the Conditional Profit Variance given Q* --- p.39
Chapter 6.3 --- Numerical Examples --- p.42
Chapter 6.3.1 --- Convexity of conditional profit variance --- p.42
Chapter 6.3.2 --- Correlation between Q* & N* --- p.47
Chapter 7 --- Objective2: Mean-Variance Optimization --- p.52
Chapter 7.1 --- Numerical Examples --- p.59
Chapter 8 --- Conclusion and Future Work --- p.61
Bibliography --- p.64
Chapter A --- Weather Option Pricing --- p.68
Chapter B --- Infeasibility of Perfect Hedge --- p.70

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Donaldson, William S. "Integrating real-time weather data with dynamic crop development models." Thesis, 1991. http://hdl.handle.net/1957/36712.

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Crop development models are commonly used in research. However, their use as crop management tools for growers is rare. Decision support systems (DSS), which combine crop models with expert systems, are being developed to provide management assistance to growers. Researchers at Oregon State University are in the process of developing a DSS. Research was conducted to develop a computer program to provide current and generated weather data for use by the DSS. The objectives of this research were to obtain a weather station, develop a set of quality control procedures to check data from the station, obtain a weather generator program, and create a weather data manager program to implement the above objectives. A weather station was obtained and was placed near two existing weather stations for ten months. Data from the weather station was compared with the other two stations for values of monthly average maximum temperature, minimum temperature, and daily total solar radiation and monthly total precipitation. The weather station performed well. Only measurements of total daily solar radiation were consistently different from the other stations. Based on a comparison of the weather station with an Eppley pyranometer, a factor was calculated to correct the solar radiation readings. The quality control procedures used on the weather data were adapted from automated procedures given in the literature. When tested, the procedures performed as desired. When used on actual data from the weather station, values that failed the procedures were apparently legitimate values. Options were added to the data manager program that allow the user to quickly decide what to do with failed values. For a weather data generator, WGEN was chosen from the generators presented in the literature. An input parameter file was created for the Corvallis, Oregon area and thirty years of data were generated. Monthly means from this data were compared with thirty-year historical monthly means for Corvallis. Precipitation data from WGEN compared well with the historical data. The generated data for maximum and minimum temperature and daily total solar radiation had great differences from the historical data. It is believed that the input parameters for the Corvallis area suggested by the authors of WGEN are not appropriate. The weather data manager program was written in the C programming language, and occupies approximately 98 kilobytes of disk space, not including the eleven files created directly and indirectly by the program. The main functions of the program are: 1) retrieving data from the weather station and performing quality control procedures on the data (allowing the user to decide what to do with values that failed QC); 2) viewing and editing of files by the user; 3) weather data generation (creating a file of only generated data or appending generated data to the file of current data from the weather station to create a file containing a full year of weather data); and 4) miscellaneous functions (monitoring the weather station, setting the calendar in the station's datalogger, and changing information used by the data manager program). It is hoped that this program will be a significant contribution towards the development of a decision support system.
Graduation date: 1992

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26

"A rebate scheme that can improve the performance of a supply chain with weather-sensitive demand." 2006. http://library.cuhk.edu.hk/record=b5893070.

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Zhu Jing.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2006.
Includes bibliographical references (leaves 54-58).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Literature Review --- p.6
Chapter 2.1 --- Supply Chain Contracts --- p.6
Chapter 2.2 --- Risk Aversion --- p.10
Chapter 3 --- Rebate Scheme in a Risk-Neutral Supply Chain --- p.12
Chapter 3.1 --- Market Demand is Perfectly Correlated with Temperature --- p.13
Chapter 3.1.1 --- The Integrated Supply Chain: the Benchmark --- p.13
Chapter 3.1.2 --- The Decentralized Supply Chain --- p.14
Chapter 3.1.3 --- Supply Chain Coordination with a Rebate --- p.15
Chapter 3.2 --- Market Demand is Partially Correlated with Temperature --- p.18
Chapter 3.2.1 --- Additive Random Variable --- p.18
Chapter 3.2.2 --- Multiplicative Random Variable --- p.21
Chapter 3.3 --- Discussion and Conclusion --- p.22
Chapter 4 --- Rebate Scheme in a Risk-Averse Supply Chain --- p.24
Chapter 4.1 --- Case of Perfectly Correlated Demand --- p.26
Chapter 4.1.1 --- Without a Shortage Cost --- p.26
Chapter 4.1.2 --- Shortage Cost s > 0 --- p.32
Chapter 4.2 --- Case of Demand with an Additive Random Variable --- p.33
Chapter 4.3 --- Discussion and Conclusion --- p.37
Chapter 5 --- Numerical Analysis --- p.38
Chapter 5.1 --- Risk-Neutral Supply Chain --- p.39
Chapter 5.1.1 --- Perfectly Correlated Demand Model --- p.39
Chapter 5.1.2 --- Partially Correlated Demand Model --- p.39
Chapter 5.2 --- Risk-Averse Supply Chain --- p.45
Chapter 5.3 --- Brief Summary --- p.47
Chapter 6 --- Conclusion --- p.49
Chapter A --- Matlab Source Code --- p.51
Bibliography --- p.54

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27

Chia, Eng-Hock. "Stochastic modelling of the weather : selected aspects." Phd thesis, 1991. http://hdl.handle.net/1885/138820.

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28

Ziauddin, Abutaher Md. "Simulation of weather effect minimization investment : an application to grain drying system design and management in a developing region." Thesis, 1985. http://hdl.handle.net/10125/9208.

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29

Farnham, David J. "Identifying and Modeling Spatio-temporal Structures in High Dimensional Climate and Weather Datasets with Applications to Water and Energy Resource Management." Thesis, 2018. https://doi.org/10.7916/D8321CTB.

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Weather and climate events are costly to society both financially and in terms of human health and well being. The costs associated with extreme climate events have motivated governments, NGOs, private investors, and insurance companies to use the data and tools at their disposal to estimate the past, present, and future hazards associated with a wide range of natural phenomena in an effort to develop mitigation and/or adaptation strategies. The nonstationary nature of climate risks requires the use of numerical climate models, often general circulation models (GCMs), to project future risk. The climate risk field, however, currently finds itself in a predicament because GCMs can be biased and do not provide a clear way to credibly estimate their uncertainty with respect to simulations of future surface climate conditions. In response to this predicament, I lay the groundwork for a set of GCM credibility assessments by identifying the large-scale drivers of surface climate events that evolve over a range of timescales ranging from daily to multi-decadal. I specifically focus on three types of climate events relevant to the water and energy sectors: 1) seasonal precipitation, which impacts drinking water supplies and agricultural productivity; 2) extreme precipitation and the costly associated riverine flooding; and 3) temperature, wind, and solar radiation fields that modulate both electricity demand and potential renewable electricity supply. In chapter I, I derive a set of atmospheric indices and investigate their efficacy to predict distributed seasonal precipitation throughout the conterminous United States. These indices can also be used to diagnose the impact of tropical sea surface temperature heating patterns on conterminous United States precipitation. This is particularly of interest in the aftermath of the unexpected precipitation patterns in the conterminous United States during the 2015-2016 El Niño event. I show that the set of atmospheric indices, which I derive from zonal winds over the conterminous United States and portions of the North Atlantic and Pacific oceans, can skillfully predict precipitation over most regions of the conterminous United States better than previously recognized mid-latitude atmospheric and tropical oceanic indices. This work contributes a set of intermediate atmospheric indices that can be used to assess the efficacy of forecasting and simulation climate models to capture signal that exists between tropical heating, mid-latitude circulation, and mid-latitude precipitation. In chapter II, I first show that the frequency of regional extreme precipitation events, which are predictive of riverine flooding, in the Ohio River Basin are poorly simulated by a GCM relative to historical precipitation observations. I then illustrate that the same GCM is much better able to simulate the statistical characteristics of a set of atmospheric field-derived indices that I show to be strongly related to the precipitation events of interest. Thus, I develop a statistical model that allows for the simulation of the precipitation events based on the GCM's atmospheric fields, which allows me to estimate future hazard based on credibly simulated GCM fields. Lastly, I validate the fully Bayesian statistical model against historical observations and use the statistical model to project the future frequency of the regional extreme precipitation events. I conclude that there is evidence of increasing regional riverine flood hazard in the Central US river basin out to the year 2100, but that there is high uncertainty regarding the magnitude of the trend. This work suggests that the identification of atmospheric circulation patterns that modulate the probability of extreme precipitation and riverine flood risk may improve flood hazard projections by allowing risk analysts to assess GCMs with respect to their ability to simulate relevant atmospheric patterns. In chapter III, I present the first comprehensive assessment of quasi-periodic decadal variations in wind and solar electricity potential and of covariability between heating and cooling electricity demand and potential wind and solar electricity production. I focus on six locations/regions in the conterminous United States that represent different climate zones and contain major load centers. The decadal variations are linked to quasi-oscillatory variations of the global climate system and lead to time-varying risks of meeting heating + cooling demand using wind/solar power. The quasi-cyclical patterns in renewable energy availability have significant ramifications for energy systems planning as we continue to increase our reliance on renewable, weather- and climate-dependent energy generation. This work suggests that certain modes of low frequency climate variability influence potential wind and solar energy supplies and are thus especially important for GCMs to credibly simulate. All of the investigations are designed to be broadly applicable throughout the mid-latitudes and are demonstrated with specific case studies in the conterminous United States. The dissertation sections represent three cases where statistical techniques can be used to understand surface climate and climate hazards. This understanding can ultimately help to mitigate and adapt to climate variabilities and secular changes, which impact society, by assisting in the development, improvement, and credibility assessment of GCMs capable of reliably projecting future climate hazards.

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Wilks, Daniel S. "Specification of local surface weather elements from large-scale general circulation model information, with application to agricultural impact assessment." Thesis, 1986. http://hdl.handle.net/1957/29136.

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A procedure for model-assisted climate impact assessment is developed. The approach combines data from observations and atmospheric general circulation models (GCNs), and provides the basis for a potentially valuable means of using information derived from GCMs for climate impact assessments on local scales. The first component of this procedure is an extension of the 'climate inverse' method of Kim al. (1984). Daily mesoscale temperature and precipitation values are stochastically specifed on the basis of observational data representing the average over an area corresponding to a GCN grid element. Synthetic local data sets generated in this manner resemble the corresponding observations with respect to various spatial and temporal statistical measures. A method for extrapolation to grid-scale 'scenarios' of a changed climate on the basis of control and experimental integrations of a GCM, in conjunction with observational data, is also presented. The statistical characteristics of daily time series from each of these data sources are portrayed in terms of the parameters of a multivariate time-domain stochastic model. Significant differences between the model data sets are applied to the corresponding parameters derived from the observations, and synthetic data Bets representing the inferred changed climate are generated using Monte-Carlo simulations. The use of the procedure is illustrated in a case study. The potential climatic impacts of a doubling of atmospheric carbon dioxide concentrations on three important North American grain cropping regions is investigated using two 'physiological' crop models. Although the specific results must be interpreted with caution, they are moderately optimistic and demonstrate possible means by which agricultural production may adapt to climatic changes.
Graduation date: 1987

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Martin, Zane Karas. "The Interaction of the Madden-Julian Oscillation and the Quasi-Biennial Oscillation in Observations and a Hierarchy of Models." Thesis, 2020. https://doi.org/10.7916/d8-8993-fc60.

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The Madden-Julian oscillation (MJO) and the quasi-biennial oscillation (QBO) are two key modes of variability in the tropical atmosphere. The MJO, characterized by propagating, planetary-scale signals in convection and winds, is the main source of subseasonal variability and predictability in the tropics. The QBO is a ~28-month cycle in which the tropical stratospheric zonal winds alternate between easterly and westerly regimes. Via thermal wind balance these winds induce temperature anomalies, and both wind and temperature signals reach the tropopause. Recent observational results show a remarkably strong link between the MJO and the QBO during boreal winter: the MJO is stronger and more predictable when QBO winds in the lower stratosphere are easterly than when winds are westerly. Despite its important implications for MJO theory and prediction, the physical processes driving the MJO-QBO interaction are not well-understood. In this thesis, we use a hierarchy of models – including a cloud-resolving model, a forecast model, and a global climate model – to examine whether models can reproduce the MJO-QBO link, and better understand the possible mechanisms driving the connection. Based in part on our modeling findings, we further explore observed QBO temperature signals thought to be important for the MJO-QBO link. After providing necessary background and context in the first two chapters, the third chapter looks at the MJO-QBO link in a small-domain, cloud-resolving model. The model successfully simulates convection associated with two MJO events that occurred during the DYNAMO field campaign. To examine the effect of QBO, we add various QBO temperature and wind anomalies into the model. We find that QBO temperature anomalies alone, without wind anomalies, qualitatively affect the model MJO similarly to the observed MJO-QBO connection. QBO wind anomalies have no clear effect on the modeled MJO. We note however that the MJO response is quite sensitive to the vertical structure of the QBO temperature anomalies, and for realistic temperature signals the model response is very small. In the fourth chapter, we look at the MJO-QBO link in a state-of-the-art global forecast model with a good representation of the MJO. We conduct 84 hind-cast experiments initialized on dates across winters from 1989-2017. For each of these dates, we artificially impose an easterly and a westerly QBO in the stratospheric initial conditions, and examine the resulting changes to the simulated MJO under different stratospheric states. We find that the effect of the QBO on the model MJO is of the same sign as observations, but is much smaller. A large sample size is required to capture any QBO signal, and tropospheric initial conditions seem more important than the stratosphere in determining the behavior of the simulated MJO. Despite the weak signal, we find that simulations with stronger QBO temperature anomalies have a stronger MJO response. In the fifth chapter, we conduct experiments in recent versions of a NASA general circulation model. We find that a version with a high vertical resolution generates a reasonable QBO and MJO, but has no MJO-QBO link. However, this model has weaker-than-observed QBO temperature anomalies, which may explain the lack of an MJO impact. To explore this potential bias, we impose the QBO by nudging the model stratospheric winds towards reanalysis, leading to more realistic simulation of QBO temperature anomalies. Despite this, the model still fails to show a strong MJO-QBO link across several ensemble experiments and sensitivity tests. We conclude with discussion of possible reasons why the model fails to capture the MJO-QBO connection. The sixth chapter examines QBO temperature signals in a range of observational and reanalysis datasets. In particular, we are motivated by two elements of the MJO-QBO relationship which are especially puzzling: the seasonality (i.e. that the MJO-QBO link is only significant in boreal winter) and long-term trend (i.e. that the MJO-QBO link seems to have only emerged since the 1980s). By examining QBO temperature signals around the tropopause, we highlight changes to the strength and structure of QBO temperature anomalies both in boreal winter and in recent decades. Whether these changes are linked to the MJO-QBO relationship, and what more generally might explain them, is not presently clear. Overall, we demonstrate that capturing the MJO-QBO relationship in a variety of models is a difficult task. The majority of evidence indicates that QBO-induced temperature anomalies are a plausible pathway through which the QBO might modulate the MJO, but the theoretical description of precisely how these temperature anomalies may impact convection is lacking and likely more nuanced than the literature to date suggests. Most models show only a weak modulation of the MJO associated with changes in upper-tropospheric temperatures, and even when those temperature signals are artificially enhanced, comprehensive GCMs still fail to show a significant MJO-QBO connection. Our observational study indicates that temperature anomalies associated with the QBO show striking modulations on various timescales of relevance to the MJO-QBO link, but do not conclusively demonstrate a clear connection to the MJO. This difficulty simulating a strong MJO-QBO connection suggests that models may lack a key process in driving the MJO and coupling the tropical stratosphere and troposphere. It is further possible that the observed link may be in some regards different than is currently theorized -- for example statistically not robust, due to non-stratospheric processes, or driven by some mechanism that has not been suitably explored.

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Dissertations / Theses on the topic 'Weather Mathematical models'

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