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Tiwari, Pushp Raj. "Dynamical downscaling for wintertime seasonal prediction of precipitation over northwest India." Thesis, IIT Delhi, 2016. http://localhost:8080/xmlui/handle/12345678/7091.
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Wahl, Sabrina [Verfasser]. "Uncertainty in mesoscale numerical weather prediction: probabilistic forecasting of precipitation / Sabrina Wahl." Bonn : Universitäts- und Landesbibliothek Bonn, 2015. http://d-nb.info/1080561099/34.
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Surcel, Madalina. "A comparison study of precipitation forecasts from three numerical weather prediction systems." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66848.
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Precipitation forecasts over the Continental US from three numerical weather prediction systems, the 4-km resolution, Storm Scale Ensemble Prediction System (SSEF), the 15-km resolution Global Environmental Multiscale (GEM) model and the 28-km resolution Weather Research and Forecasting (WRF) model, are compared and validated against radar observations for 24 precipitation cases between 16 April and 06 June 2008. The diversity of these systems allows the discussion of several issues: the representation of the diurnal cycle of precipitation in Numerical Weather Prediction (NWP) models, the importance of horizontal resolution for forecast accuracy, the effect of radar data assimilation and the advantage of performing ensemble forecasts rather than less costly, deterministic forecasts. The investigation is carried out through the analysis of statistical measures, skill scores and time-longitude diagrams of precipitation fields. An interesting finding of this study is that, during the study period, the diurnal variability of precipitation was influenced by a combination of weak thermal forcing and strong synoptic forcing, resulting in large scale precipitation systems consistent in terms of initiation timing and propagation characteristics. In addition, the radar observations showed much more consistency than the model forecasts. It is likely that timing and positioning errors led to larger spread of forecasted precipitation coverage and intensity throughout the time-longitude domain. None of the analysis presented here proved the superiority of the 4-km resolution models over the 15-km resolution GEM. It was however determined that radar data assimilation and ensemble prediction added value to the forecasts, mainly through the reduction of positional errors.<br>L'objectif de cette étude est l'évaluation des prévisions de précipitations aux États-Unis effectuées par trois systèmes de prévision numérique par rapport aux observations radars pour 24 jours entre le 16 avril et le 6 juin 2008. L'intérêt principal est de déterminer l'habileté des systèmes de prévision de reproduire le cycle diurne de précipitations. Les différences entre ces systèmes nous permettent d'apprécier l'importance de la résolution horizontale du modèle, de la prévision probabiliste et de l'assimilation des données radar. L'étude est effectuée par l'analyse des mesures statistiques et des diagrammes temps-longitude des champs de précipitations. Un résultat intéressant de ce travail est que, lors de la période d'étude, la variabilité diurne de précipitations a été influencée par une certaine combinaison des forçages synoptiques et thermiques. Donc, la plupart des systèmes observés ont les mêmes propriétés au niveau de l'initiation et de la propagation. D'ailleurs, les prévisions numériques n'ont pas réussi à reproduire ces propriétés. La variabilité observée dans les systèmes de précipitations générés par les modèles est possiblement causée par des erreurs de phase.L'analyse présentée dans ce mémoire ne démontre pas la supériorité des prévisions de précipitations à petite échelle. Cependant, l'assimilation des données radars et la prévision d'ensemble contribuent à l'amélioration des prévisions de précipitations.
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Hossain, Md Monowar. "CMIP5 Decadal Precipitation at Catchment Level and Its Implication to Future Prediction." Thesis, Curtin University, 2022. http://hdl.handle.net/20.500.11937/89149.
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This study assesses the monthly precipitation of CMIP5 decadal experiment over Brisbane River catchment for a spatial resolution of 0.050 and then predicts the monthly precipitation for decadal timescale through a Bidirectional LSTM and Machine Learning Algorithms using GCMs and observed data. To use GCM data in this future prediction, investigations were carried out for a suitable spatial interpolation method, a better simulation period, model drifts, and drift correction alternatives based on different skill tests.
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Gnanasekar, Nithyakumaran. "Temperature and Hourly Precipitation Prediction System for Road Bridge using Artificial Neural Networks." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873819.
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Binder, Peter. "Aspects of precipitation simulation in numerical weather prediction : towards an operational mesoscale NWP model /." Zürich : Schweizerische Meteorologische Anstalt, 1992. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=9908.
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Mbali, Siphumelelo. "Improving estimation of precipitation and prediction of river flows in the Jonkershoek mountain catchment." University of the Western Cape, 2016. http://hdl.handle.net/11394/5878.
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Magister Scientiae - MSc (Earth Science)<br>Rainfall is the main input into the land phase of the hydrological cycle which greatly determines
the available water resources. Accurate precipitation information is critical for mountain
catchments as they are the main suppliers of usable water to the human population. Rainfall
received in mountain catchments usually varies with altitude due to the orographic influence on
the formation of rainfall. The Langrivier mountain catchment, a sub-catchment of the
Jonkershoek research catchment, was found to have a network of rain gauges that does not
accurately represent the catchment rainfall. As a result, this study aimed to improve the
estimation of catchment precipitation and evaluate how improving estimation catchment
precipitation affects the prediction of streamflows.
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Ganguly, Auroop Ratan. "Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8374.
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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2002.<br>Includes bibliographical references (p. 205-218).<br>Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. Recent advances in precipitation physics, Numerical Weather Prediction (NWP) models, availability of high quality remotely sensed measurements, and data dictated forecasting tools, offer the opportunity of improvements in this area. Investigative studies were performed to quantify the value of available tools and data, which indicated the promise and the pitfalls of emerging ideas. Our studies suggested that an intelligent combination of NWP model outputs and remotely sensed radar measurements, that uses process physics and data dictated tools, could improve distributed QPF. Radar measurements have distributed structure, while NWP-QPF incorporate large scale physics. Localized precipitation processes are not well handled by NWP models, and grid average NWP-QPF are not too useful for distributed QPF owing to the spatial variability of rainfall. However, forecasts for atmospheric variables from NWP have information relevant for modeling localized processes and improving distributed QPF, especially in the Summer. Certain precipitation processes like advection and large scale processes could be modeled using physically based algorithms. The physics for other processes like localized convection or residual structures are not too well understood, and data dictated tools like traditional statistical models or Artificial Neural Networks (ANN) are often more applicable.<br>(cont.) A new strategy for distributed QPF has been proposed that utilizes information from radar and NWP. This strategy decomposes the QPF problem into component processes, and models these processes using precipitation physics and data dictated tools, as appropriate and applicable. The proposed strategy improves distributed QPF over existing techniques like radar extrapolation alone, NWP-QPF with or without statistical error correction, hybrid models that combine radar extrapolation with NWP-QPF, parameterized physically based methods, and data dictated tools alone. New insights are obtained on the component processes of distributed precipitation, the information content in radar and NWP, and the achievable precipitation predictability.<br>by Auroop R. Ganguly.<br>Ph.D.
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Surussavadee, Chinnawat. "Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38537.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2007.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 229-234).<br>This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for icy hydrometeors (F([lambda])), to be used as a global precipitation ground-truth for evaluating alternative millimeter-wave satellite designs and for developing methods for millimeter-wave precipitation retrieval and assimilation. The model's predicted millimeter-wave atmospheric radiances were found to statistically agree with those observed by satellite instruments [Advanced Microwave Sounding Unit-A/B (AMSU-A/B)] on the United States National Ocean and Atmospheric Administration NOAA-15, -16, and -17 satellites over 122 global representative storms. Whereas such radiance agreement was found to be sensitive to assumptions in MM5 and the radiative transfer model, precipitation retrieval accuracies predicted using the MM5/TBSCAT/F([lambda]) model were found to be robust to the assumptions.<br>(cont.) Appropriate specifications for geostationary microwave sounders and their precipitation retrieval accuracies were studied. It was found that a 1.2-m micro-scanned filled-aperture antenna operating at 118/166/183/380/425 GHz, which is relatively inexpensive, simple to build, technologically mature, and readily installed on a geostationary satellite, could provide useful observation of important global precipitation with ~20-km resolution every 15 minutes. AMSU global precipitation retrieval algorithms for retrieving surface precipitation rate, peak vertical wind, and water-paths for rainwater, snow, graupel, cloud water, cloud ice, and the sum of rainwater, snow, and graupel, over non-icy surfaces were developed separately using a statistical ensemble of global precipitation predicted by the MM5/TBSCAT/F([lambda]) model. Different algorithms were used for land and sea, where principal component analysis was used to attenuate unwanted noises, such as surface effects and angle dependence. The algorithms were found to perform reasonably well for all types of precipitation as evaluated against MM5 ground-truth. The algorithms also work over land with snow and sea ice, but with a strong risk of false detections. AMSU surface precipitation rates retrieved using the algorithm developed in this thesis reasonably agree with those retrieved for the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) aboard the Aqua satellite over both land and sea.<br>(cont.) Surface precipitation rates retrieved using the Advanced Microwave Sounding Unit (AMSU) aboard NOAA-15 and -16 satellites were further compared with four similar products derived from other systems that also observed the United States Great Plains (USGP) during the summer of 2004. These systems include AMSR-E aboard the Aqua satellite, the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites, the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) aboard the TRMM satellite, and a surface precipitation rate product (NOWRAD), produced and marketed by Weather Services International Corporation (WSI) using observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) systems of the Next-Generation Weather Radar (NEXRAD) program. The results show the reasonable agreement among these surface precipitation rate products where the difference is mostly in the retrieval resolution, which depends on instruments' characteristics. A technique for assimilating precipitation information from observed millimeter-wave radiances to MM5 model was proposed. Preliminary study shows that wind and other correction techniques could help align observations at different times so that information from observed radiances is used at appropriate locations.<br>by Chinnawat Surussavadee.<br>Ph.D.
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Pieper, Patrick [Verfasser]. "Meteorological Drought - Universal Monitoring and reliable seasonal Prediction with the Standardized Precipitation Index / Patrick Pieper." Hamburg : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020. http://d-nb.info/1227582404/34.
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Garcia, José Roberto Motta. "Neural networks input-based models to calibrate the mean precipitation of an ensemble prediction system." Instituto Nacional de Pesquisas Espaciais (INPE), 2016. http://urlib.net/sid.inpe.br/mtc-m21b/2016/08.05.13.14.
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Although ensemble forecasting systems provide richer forecasts by adding probabilistic concepts to single deterministic forecasts, they have intrinsic shortcomings caused by the lack of full comprehension of the relationship between meteorological variables. It is especially noticed in medium and large-scale forecasts, whose effects of chaotic behavior of the atmosphere drastically increase as the target forecasting date is lengthened. Improvements on weather forecasting systems can be done either by the meteorology staff concerning physical aspects of weather behavior as well as by implementing computational statistical methods in order to tune the weather forecasting model output. The purpose of this work is to compute, along the forecast horizon, a more accurate precipitation value than the ensemble mean precipitation by post-processing INPE/CPTEC's ensemble prediction output. To achieve the goal, some prognostic fields and derived data are combined and submitted as explanatory variables to an artificial neural network system. Experiments were guided in an exploratory way such that several computational models were generated and thereafter assessed. The study was individually performed at some grid points located within the boundaries of La Plata Basin. Results indicate that the application of this methodology presented values closer to actual values when compared to the ensemble mean precipitation. It also shows that the inclusion of the ensemble mean precipitation itself, as well as data from adjacent grid points, improve the calibration process of the target grid point. In addition, the exploratory approach detects different artificial network models to fit specific location and lead-time. Although this input-driven system computes less than ideal forecasting values, it performs better than the mean output of the ensemble model, which is widely used in various weather forecasting products.<br>Embora os sistemas de previsão por conjuntos forneçam previsões mais ricas, acrescentando conceitos probabilísticos às previsões determinísticas simples, eles têm deficiências intrínsecas causadas pela falta de plena compreensão da relação entre variáveis meteorológicas. Isto é especialmente notado nas previsões de média e grande escala, cujos efeitos de comportamento caótico da atmosfera aumentam drasticamente à medida que a data alvo de previsão é estendida. Melhorias nos sistemas de previsão do tempo podem ser feitas tanto pela equipe de meteorologia em relação aos aspectos físicos do comportamento do tempo, bem como através da aplicação de métodos computacionais estatísticos, visando ajustar a saída do modelo de previsão. O objetivo deste trabalho é calcular, ao longo do horizonte de previsão, um valor de precipitação mais preciso do que a precipitação média do sistema de previsão por conjunto através do pós-processamento das saídas do modelo do INPE/CPTEC. Para atingir esta meta, alguns campos de prognóstico e dados derivados são combinados e apresentados como variáveis explanatórias a um sistema de rede neural artificial. Os experimentos foram orientados de forma exploratória onde vários modelos computacionais foram gerados e posteriormente avaliados. O estudo foi realizado individualmente em alguns pontos de grade localizados dentro dos limites da Bacia da Prata. Os resultados indicam que a aplicação desta metodologia apresentou valores mais próximos da realidade do que a média de precipitação do sistema de previsão por conjuntos. Mostra também que ao incluir a própria precipitação média, bem como dados de pontos de grade adjacentes o processo de calibração melhora no ponto de grade alvo. Além disso, a abordagem exploratória traz uma melhora ainda maior pois detecta diferentes modelos de redes neurais para locais e dias de previsão específicos. Embora este sistema baseado em entrada calcule valores de previsão inferiores aos ideais, ele tem um desempenho melhor do que a média do modelo de previsão por conjunto, que é amplamente usado em vários produtos de previsão de tempo.
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Silva, Duarte Jorge Alves de Carvalho e. "Mineral scale prediction modelling : precipitation of CaCO3 scale in CO2-water alternating gas production systems." Thesis, Heriot-Watt University, 2017. http://hdl.handle.net/10399/3301.
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The injection of CO2 in oil reservoirs for tertiary oil recovery is one of the main Enhanced Oil Recovery (EOR) processes and it is widely used in the oil and gas industry. To prevent early gas breakthrough, CO2 is commonly injected in alternated slugs with water, in a process known as CO2 Water Alternating Gas (CO2 WAG). When such processes are carried out in carbonate reservoirs, there is the potential for calcite (CaCO3) dissolution in the reservoir and its subsequent re-precipitation in production systems, thus posing a flow assurance risk that must be carefully managed. A new thermodynamic model that addresses all of the major steps involved in the precipitation of CaCO3 scale in CO2 WAG production systems is proposed, including: i) the dissolution of injected CO2 into the reservoir brine; ii) the rock-brine interactions and the dissolution of CaCO3 rock; iii) the reactive flow and transport of aqueous components in the reservoir; iv) the partition of components between the liquid, vapour, and water phases; and v) the precipitation of CaCO3 scale as a function of decreasing pressure (and temperature) in CO2 WAG production systems (i.e. in the well and in topside equipment). Thus, an aqueous electrolyte model has been implemented and coupled with a Vapour-Liquid Equilibrium (VLE) model, a multiphase flash model, and a reactive transport model. The non-ideal behaviour of the aqueous and hydrocarbon phases (vapour and liquid) has been modelled by using respectively the Pitzer equations and an Equation of State (EOS) (Soave-Redlich-Kwong, SRK, and Peng-Robinson, PR, EOS, have been used, among others). The implementation of these models has been validated by comparing results with experimental data and/or with results obtained by using industry standard software. In addition, the impact of VLE, multiphase flash, and reactive transport calculations on the precipitation of CaCO3 scale has been investigated, by considering commonly available production data. Also, a procedure had been devised to address each step involved in the precipitation of CaCO3 scale in CO2 WAG production wells individually, and together in an integrated approach. In fact, this work focuses on building the boundaries for the CaCO3 scaling system, thus allowing to define, and work on, worst case scenarios. This gives the required information – both qualitatively and quantitatively – to manage CaCO3 scale in CO2 WAG production wells.
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MASCARO, GIUSEPPE. "Assessing uncertainty propagation of precipitation input in hydrometeorological ensemble forecasting systems." Doctoral thesis, Università degli Studi di Cagliari, 2008. http://hdl.handle.net/11584/265979.
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The aim of the thesis is the assessment of precipitation input uncertainty into hydrological response in hydrometeorological ensemble systems for flood prediction.
The study has been preliminary focused on the development of a hydrometeorological system that couples a statistical precipitation downscaling model, known as STRAIN, with a fully-distributed hydrological model, known as tRIBS.
In a subsequent part of the research, a rigorous method has been designed to test the consistency hypothesis (i.e. ensemble and observations are drawn from the same distribution) of the ensemble precipitation fields generated by downscaling models. The verification procedure has been tested by means of numerical experiments. Results permit us to conclude that: (i) ensemble members generated using model parameters estimated on the observed event are overdispersed; (ii) the adoption of a single calibration relation linking model parameters and coarse meteorological observable can lead to the generation of consistent ensemble members; (iii) when a single calibration relation is not able to explain observed events variability, storm-specific calibration relation should be adopted to return consistent forecasts.
Finally, in the last part of the work, a rigorous method has been developed to assess consistency of ensemble streamflows produced by hydrometeorological systems. The method has been tested with numerical experiments using the prediction system designed in the preliminary phase of the study with the purpose of evaluating the propagation of uncertainty of downscaled precipitation input into hydrological response.
The innovative aspects of the thesis rely on (i) the development of rigorous verification methods for ensemble outputs of hydrometeorological systems; and (ii) the application of these procedure on a great number of events in order to draw statistically significant conclusions.
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Hill, Andrew D. "Improving diameter growth prediction of Douglas-fir in eastern Washington State, U.S.A. by incorporating precipitation and temperature /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/5458.
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Xiao, Ying. "A Two-dimensional Stochastic Model for Prediction of Localized Corrosion." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1108481091.
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Zahiri, Saden H. (Saden Heshmatollah) 1966. "Prediction of the processing window and austemperability for austempered ductile iron." Monash University, School of Physics and Materials Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8408.
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Lv, Duchao. "A Multi-Scale Simulation Approach to Deformation Mechanism Prediction in Superalloys." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1469009668.
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Vich, Ramis Maria del Mar. "Design of ensemble prediction systems based on potential vorticity perturbations and multiphysics. Test for western Mediterranean heavy precipitation events." Doctoral thesis, Universitat de les Illes Balears, 2012. http://hdl.handle.net/10803/84075.
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L'objectiu principal d'aquesta tesi és millorar l'actual capacitat de predicció de fenòmens meteorològics de pluja intensa potencialment perillosos a la Mediterrània occidental. Es desenvolupen i verifiquen tres sistemes de predicció per conjunts (SPC) que tenen en compte incerteses presents en els models numèrics i en les condicions inicials. Per generar els SPC s'utilitza la connexió entre les estructures de vorticitat potencial (VP) i els ciclons, a més de diferents esquemes de parametrització física. Es mostra que els SPC proporcionen una predicció més hàbil que la determinista. Els SPC generats pertorbant les condicions inicials han obtingut millor puntuació en verificacions estadístiques. Els resultats d'aquesta tesi mostren la utilitat i la idoneïtat dels mètodes de predicció basats en la pertorbació d'estructures de VP de nivells alts, precursors de les situacions ciclòniques. Els resultats i estratègies presentats pretenen ser un punt de partida per a futurs estudis que facin ús d'aquests mètodes.<br>The main goal of this thesis is to improve the current prediction skill of potentially hazardous heavy precipitation weather events in the western Mediterranean region. We develop and test three different ensemble prediction systems (EPSs) that account for uncertainties present in both the numerical models and the initial conditions. To generate the EPSs we take advantage of the connection between potential vorticity (PV) structures and cyclones, and use different physical parameterization schemes. We obtain an improvement in forecast skill when using an EPS compared to a determinist forecast. The EPSs generated perturbing the initial conditions perform better in the statistical verification scores. The results of this Thesis show the utility and suitability of forecasting methods based on perturbing the upper-level precursor PV structures present in cyclonic situations. The results and strategies here discussed aim to be a basis for future studies making use of these methods.
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Akanegbu, J. O. (Justice Orazulukwe). "Development of a precipitation index-based conceptual model to overcome sparse data barriers in runoff prediction in cold climate." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526221281.
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Abstract This thesis describes the development of a new precipitation index-based conceptual water balance model with parameters easily regionalized through the functional relationship with catchment and climate attributes. It also presents a simple method for improving model dynamics for streamflow simulations in a non-stationary climate. The model was developed for streamflow modelling and prediction in high-latitude catchments, where model parameter regionalization is difficult due to limited availability of hydrological data for the region. The model couples a snow accumulation and melt formulation with a current precipitation index (CPI) formulation to simulate daily precipitation in runoff hydrograph pattern from catchments with seasonal snow cover. Using new runoff conversion factors CT and Lf, and a threshold flow factor ThQ, the simulated CPI hydrograph is converted into daily runoff and routed using the transformation function Maxbas. The model was developed in Microsoft Excel workbook and tested in 32 catchments in Finland, a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and reproduce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. In addition, incorporating temperature conditions influencing inter-annual variability in streamflow into the model structure improved its structural dynamics, thereby improving its performance in a non-stationary climate. Most model parameters showed strong relationships with observable catchment characteristics, climate characteristics, or both. The parameter functional relationships derived from the model parameter-catchment relationships produced equally good model results when applied to independent test catchments used as mock-ungauged catchments. Inclusion of snow-water equivalent records and use of multiple objective functions for snow-water equivalent and runoff simulations during model optimization helped reduce the effect of parameter equifinality, making it easier to determine optimal parameter values. The current precipitation index (CPIsnow) model is a parsimonious tool for predicting streamflow in data-limited high-latitude regions<br>Tiivistelmä Tämä väitöskirja käsittelee yksinkertaisen sadantaan perustuvan konseptuaalisen vesitasemallin kehitystä ja soveltamista boreaalisille valuma-alueille sekä malliin liittyvää alueellista parametrisointia valuma-alueominaisuuksien ja ilmastoaineiston perusteella. Hydrologinen malli on luotu laskemaan ja ennustamaan valuntaa pohjoisille valuma-alueille, joilta on vähän hydrologista tietoa. Malli yhdistää lumen kertymisen ja sulannan tunnettuun sadantaindeksiin perustuvaan malliin (CPI) ja edelleen simuloi päivittäisen hydrografin valuma-alueille, joilla on selkeä lumipeitteinen ajanjakso. Malli laskee MaxBas funktion avulla CPI:llä muodostetun hydrografin päivittäiseksi valunnaksi valuntaan liittyvien malliparametrien CT ja Lf sekä virtaaman kynnysarvon ThQ avulla. Malli kehitettiin Excel-ympäristössä ja sitä testattiin 32 valuma-alueella Suomessa. Valuma-alueet edustivat maantieteellisesti kattavasti alueita, joilla esiintyy tyypillisesti kausittainen lumipeite. Saadut tulokset osoittivat, että kehitetty malli simuloi ja tuottaa päivittäisen valunnan riittävällä tarkkuudella valuma-alueille, vaikka hydrologista ja fysikaalista tietoa alueilta olisi niukasti. Useimmat malliparametrit olivat vahvasti riippuvaisia joko valuma-alue ominaisuuksista tai ilmastollisista parametreista tai molemmista. Parametrien funktionaalinen yhteys muodostettiin valuma-alueiden ominaisuuksien perusteella ja testattiin riippumattomalla valuma-aluejoukolla hyvin tuloksin. Malliparametrien samatavoitteellisuutta eli ekvifinaliteettiä voitiin vähentää huomioimalla mallissa lumen vesiarvomittaukset sekä hyödyntämällä useita parametrisia funktioita. Tällöin myös optimaalisten parametrien löytyminen nopeutui ja helpottui. Tämän väitöstyön pohjalta syntynyt uusi sadannan indeksiin pohjautuva laskentamalli (CPIsnow) mahdollistaa valunnan arvioinnin pieniltä valuma-alueilta, joilta on niukasti aineistoa saatavilla ja joissa lumen sulanta ja kertyminen ovat keskeisiä hydrologisia prosesseja
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Dean, John R. "Improving summer drought prediction in the Apalachicola-Chattahoochee-Flint river basin with empirical downscaling." unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-07152008-200815/.
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Thesis (M.A.)--Georgia State University, 2008.<br>Title from file title page. Jeremy E. Diem, committee chair; Jeremy W. Crampton, John W. Matthews, committee members. Electronic text (84 p. : ill. (some col., maps (some col.)) : digital, PDF file. Description based on contents viewed Oct. 1, 2008. Includes bibliographical references (p. 77-84).
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Carlert, Sara. "Investigation and Prediction of Small Intestinal Precipitation of Poorly Soluble Drugs : a Study Involving in silico, in vitro and in vivo Assessment." Doctoral thesis, Uppsala universitet, Institutionen för farmaci, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-178053.
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The main objectives of the present project were to increase the understanding of small intestinal precipitation of poorly soluble pharmaceutical drugs, investigate occurrence of crystalline small intestinal precipitation and effects of precipitation on absorption. The aim was to create and evaluate methods of predicting crystalline small intestinal drug precipitation using in vivo, in vitro and in silico models. In vivo small intestinal precipitation from highly supersaturated solutions of two weakly basic model drugs, AZD0865 and mebendazole, was investigated in humans and canine models. Potential precipitation of AZD0865 was investigated by examining dose dependent increases in human maximum plasma concentration and total exposure, which turned out to be dose linear over the range investigated, indicating no significant in vivo precipitation. The small intestinal precipitation of mebendazole was investigated from drug concentrations and amount of solid drug present in dog jejunum as well as through the bioavailability after direct duodenal administration in dogs. It was concluded that mebendazole small intestinal precipitation was limited, and that intestinal supersaturation was measurable for up to 90 minutes. In vitro precipitation methods utilizing simulated or real fasted gastric and intestinal fluids were developed in order to simulate the in vivo precipitation rate. The methods overpredicted in vivo precipitation when absorption of drug was not simulated. An in vitro-in silico approach was therefore developed, where the in vitro method was used for determining the interfacial tension (γ), necessary for describing crystallization in Classical Nucleation Theory (CNT). CNT was evaluated using a third model drug, bicalutamide, and could successfully describe different parts of the crystallization process of the drug. CNT was then integrated into an in silico absorption model. The in vivo precipitation results of AZD0865 and mebendazole were well predicted by the model, but only by allowing the fundamental constant γ to vary with concentration. Thus, the in vitro-in silico approach could be used for small intestinal precipitation prediction if the in vitro concentration closely matched in vivo small intestinal concentrations.
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Marx, Hester Gerbrecht. "The use of artificial neural networks to enhance numerical weather prediction model forecasts of temperature and rainfall." Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-02102009-161401/.
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Vasconi, Matteo. "Sensitivity of forecast skill to the parameterisation of moist convection in the COSMO model." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14566/.
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The parameterisation of convection in limited-area models is an important source of uncertainty as regards the spatio-temporal forecast of precipitation.
The development and implementation of ensemble systems in which different convection schemes are used provides an opportunity to upgrade state-of-the-art probabilistic systems at the convection-parameterised scale. As for the limited-area model COSMO, the sensitivity of the forecast skill to the use of different convection schemes is assessed by performing different sets of experiments.
For one case of heavy precipitation over Italy, the performance of COSMO model run with the Bechtold scheme or with the Tiedtke scheme is investigated in both deterministic and ensemble modes with particular attention to the types of forecast errors (e.g. location, timing, intensity) provided by the different convection schemes in terms of total precipitation.
In addition to this, a 10-member ensemble has been run for approximately 2 months with the Bechtold scheme, using the same initial and boundary conditions as members 1-10 of the operational COSMO-LEPS ensemble system (which has 20 members, all run with the Tiedtke scheme). The performance of these members is assessed and compared to that of the system made of members 1-10 of COSMO-LEPS; in particular the spread/skill relation of the two 10-member ensembles in terms of total precipitation is evaluated. Finally, the performance of an experimental 20-member ensemble system (which has 10 members run with the Bechtold plus 10 members run with the Tiedtke scheme) is compared to that of operational COSMO-LEPS over the 2-month period. The new system turned out to have higher skill in terms of precipitation forecast with respect to COSMO-LEPS over the period. In this approach the use of the Bechtold scheme is proposed as a perturbation for the COSMO-LEPS ensemble, relatively to how uncertainties in the model representation of the cumulus convection can be described and quantified.
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Chardon, Jérémy. "Intérêts de la méthode des analogues pour la génération de scénarios de précipitations à l'échelle de la France métropolitaine : Cohérence spatiale et adaptabilité du lien d'échelle." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENU044/document.
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Les scénarios hydrologiques requis pour les études d'impacts hydrologiques nécessitent de disposer de scénarios météorologiques non biaisés et qui soient de surcroît adaptés aux échelles spatiales et temporelles des hydro-systèmes considérés. Les scénarios météorologiques obtenus en sortie brute des modèles de climat et/ou des modèles de prévision numérique du temps sont de ce fait non appropriées. Les sorties de ces modèles sont par suite souvent adaptées à l'aide de Méthodes de Descente d'Echelle Statistique (MDES). Depuis les années 2000, les MDES ont beaucoup été utilisées pour la génération de scénarios météorologiques en un site. En revanche, la génération de scénarios spatiaux couvrant de larges territoires est une tâche plus difficile, en particulier lorsque l'on souhaite respecter la cohérence spatiale des précipitations à prédire. Parmi les MDES usuelles, les approches basées sur la recherche de situations analogues passées permettent de satisfaire cette contrainte. Dans cette thèse, nous évaluons la capacité d'un Modèle Analog (MA) – où l'analogie porte sur les géopotentiels 1 000 et 500 hPa – pour la génération de scénarios de précipitation spatialement cohérents pour le territoire Français métropolitain. Dans un premier temps, la transposition spatiale du modèle MA est évaluée : le modèle s'avère utilisable pour la génération de scénarios spatiaux cohérents sur des territoires couvrant plusieurs dizaines de milliers de kilomètres carrés dès lors qu'aucune barrière climatique n'est rencontrée. Dans un second temps, nous évaluons la sensibilité des performances de prédiction à l'agrégation spatiale de la variable à prédire. L'augmentation de performance avec l'agrégation s'explique alors par la diminution de la variabilité du prédictand, pour autant que les variables de grande échelle considérées soient de bons prédicteurs pour la région considérée. Dans une dernière étude, nous explorons la possibilité d'améliorer la performance locale du modèle analogue par l'ajout de prédicteurs locaux. Le modèle combiné qui en résulte permet d'accroître sensiblement les performances de prédiction par l'adaptation du lien d'échelle sur la base d'un jeu de prédicteurs additionnels. Il apparaît de plus que la pertinence de ces prédicteurs dépend de la situation de grande échelle rencontrée ainsi que de la région considérée<br>Hydrological scenarios required for the impact studies need to have unbiased meteorological scenarios adapted to the space and time scales of the considered hydro-systems. Hence, meteorological scenarios obtained from global climate models and/or numerical weather prediction models are not really appropriated. Outputs of these models have to be post-processed, which is often carried out thanks to Statistical Downscaling Methods (SDMs). Since the 2000's, SDMs are widely used for the generation of scenarios at a single site. The generation of relevant precipitation fields over large regions or hydro-systems is conversely not straightforward, in particular when the spatial consistency has to be satisfied. One strategy to fulfill this constraint is to use a SDM based on the search of past analog situations. In this PhD, we evaluate the ability of an Analog Model (AM) – where the analogy is applied to the geopotential heights 1000 and 500 hPa – for the generation of spatially coherent precipitation scenarios over the French metropolitan territory. In a first part, the spatial transferability of an AM is evaluated: the model appears to be usable for the generation of spatial coherent scenarios over territories covering several tens of thousands squared kilometers if no climatological barrier is met in between. In a second part, we evaluate the sensitivity of the prediction performance to the spatial aggregation of the predictand. The performance increases with the aggregation level as long as the large scale variables are good predictors of precipitation for the region under consideration. This performance increase has to be related to the decrease of the predictand variability. We finally explore the possibility of improving the local performance of the AM using additional local scale predictors. For each prediction day, the prediction is obtained from a parametric regression model, for which predictors and parameters are estimated from the analog dates. The resulting combined model noticeably allows increasing the prediction performance by adapting the downscaling link for each prediction day. The selected predictors for a given prediction depend on the large scale situation and on the considered region
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Evans, Daniel Christopher. "Predicting Injection Site Drug Precipitation." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/312666.
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Administering drug therapy through the intravenous route ensures rapid, and complete, bioavailability, which can be critical in an emergency situation. However, bypassing all of its protective barriers leaves the body vulnerable to harm if the parenteral formulation becomes unstable when mixed with the blood. An example of this formulation instability is the precipitation of poorly water-soluble drugs after mixing with the blood's aqueous environment. This happens when parenteral formulations rely too heavily upon the solution pH, and excipients, to increase the drug solubility. This precipitation in the blood can damage venous cell membranes producing symptoms ranging from mild skin irritation to death. To screen potential drug formulations for problems such as injection site drug precipitation, pharmaceutical companies have traditionally used costly and time consuming animal studies. To reduce the amount of pre-clinical animal studies necessary to find an optimal IV formulation, an in vitro device to detect injection site drug precipitation is introduced. In addition to the device, software that simulates the dilution of a parenteral drug formulation with blood upon administration has been developed and is introduced. Both the device and software were tested on commercially available formulations plus one formulation currently in clinical trials. The results and capabilities of the new device were compared to those obtained using an earlier in vitro device. Finally, a robust model for early screening of injection site precipitation is developed using both the in vitro device and software.
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Kaabi, Abdenacer. "Régionalisation des étiages dans le Nord Ouest de l'Algérie : premiers tests." Grenoble 1, 1994. http://www.theses.fr/1994GRE10165.
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La presente recherche a consiste en l'elaboration de tests de modelisation synthetique et previsionnelle des etiages dans le nord-ouest de l'algerie. Ces tests concernent des methodes d'evaluation des ressources estivales par le biais de la predetermination des etiages a l'aide des concepts qdf (debit-duree-frequence), et de la prevision par l'analyse des tarissements. Le choix de la region se justifie par le fait que, ces dernieres annees, la secheresse a sevi beaucoup plus sur les regions situees a l'ouest de l'algerie. Le choix du lot des stations a ete fait par l'agence nationale des ressources hydrauliques (anrh). Le premier test propose un modele descriptif definissant les debits (volumes) minimaux vcnd(t), pour une assez large plage de durees continues d (en jours) et de periode moyenne de retour t (en annees). Le calage de ce modele a ete fait sur 24 stations choisies sur l'ensemble des 32 stations disponibles en donnees, par une simple methode de regression lineaire, aboutissant a un modele ayant un seul parametre optimise et un parametre hydrologique egalement externe. Ce dernier represente le debit minimal a d = 30 jours et t = 2 ans, c'est a dire le vcn(30,2). Il est reliable aux debits mensuels minimaux de l'annee qmna(2) et aux debits mensuels d'etiage qme(2). Dans le cas de periodes a debits nuls, un troisieme parametre (a calculer ou a estimer de maniere externe) est introduit. Des cartes representant ces parametres ont ete etablies, et ont montre une possible regionalisation des etiages sur l'ensemble des bassins versants, pour peu qu'il y ait une densite suffisante dans l'information (donnees suffisantes par rapport a la variabilite locale). L'exploitation des observations locales (sites ou stations a courtes durees) est possible par l'etablissement d'un lien entre ces dernieres et celles issues des stations suffisamment jaugees. Le deuxieme test propose un modele exponentiel classique, cale sur un lot de 21 stations extraites du meme ensemble. Ce modele permet d'evaluer un volume theorique de nappes mobilisables pour soutenir les etiages et l'etablissement d'une liaison entre ce volume et les debits charnieres. Ces derniers coincident avec la periode de debut des etiages (tc = 150 ou 175 jours de l'annee civile). Des liaisons entre les coefficients de tarissement et ces debits charnieres ont ete etablies, pour estimer ces volumes theoriques specifiques utiles
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Moupfouma, Fidèle. "Etude des précipitations et de leurs effets sur les liaisons hertziennes en visibilité et par satellite dans les régions tropicales." Paris 13, 1987. http://www.theses.fr/1987PA132007.
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Modèle mathématique semi empirique décrivant la distribution cumulative des intensités de pluie quelle que soit la région du monde. Etude de l'influence des affaiblissements dus à la place sur la qualité de fonctionnement des systèmes et modèle de prévision des affaiblissements. Adaptation d'un des paramétres à chacune des regions du globe
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Chen, Chia-Jeng. "Hydro-climatic forecasting using sea surface temperatures." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/48974.
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A key determinant of atmospheric circulation patterns and regional climatic conditions is sea surface temperature (SST). This has been the motivation for the development of various teleconnection methods aiming to forecast hydro-climatic variables. Among such methods are linear projections based on teleconnection gross indices (such as the ENSO, IOD, and NAO) or leading empirical orthogonal functions (EOFs). However, these methods deteriorate drastically if the predefined indices or EOFs cannot account for climatic variability in the region of interest. This study introduces a new hydro-climatic forecasting method that identifies SST predictors in the form of dipole structures. An SST dipole that mimics major teleconnection patterns is defined as a function of average SST anomalies over two oceanic areas of appropriate sizes and geographic locations. The screening process of SST-dipole predictors is based on an optimization algorithm that sifts through all possible dipole configurations (with progressively refined data resolutions) and identifies dipoles with the strongest teleconnection to the external hydro-climatic series. The strength of the teleconnection is measured by the Gerrity Skill Score. The significant dipoles are cross-validated and used to generate ensemble hydro-climatic forecasts. The dipole teleconnection method is applied to the forecasting of seasonal precipitation over the southeastern US and East Africa, and the forecasting of streamflow-related variables in the Yangtze and Congo Rivers. These studies show that the new method is indeed able to identify dipoles related to well-known patterns (e.g., ENSO and IOD) as well as to quantify more prominent predictor-predictand relationships at different lead times. Furthermore, the dipole method compares favorably with existing statistical forecasting schemes. An operational forecasting framework to support better water resources management through coupling with detailed hydrologic and water resources models is also demonstrated.
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Roulin, Emmannuel. "Medium-range probabilistic river streamflow predictions." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209270.
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River streamflow forecasting is traditionally based on real-time measurements of rainfall over catchments and discharge at the outlet and upstream. These data are processed in mathematical models of varying complexity and allow to obtain accurate predictions for short times. In order to extend the forecast horizon to a few days - to be able to issue early warning - it is necessary to take into account the weather forecasts. However, the latter display the property of sensitivity to initial conditions, and for appropriate risk management, forecasts should therefore be considered in probabilistic terms. Currently, ensemble predictions are made using a numerical weather prediction model with perturbed initial conditions and allow to assess uncertainty. <p><p>The research began by analyzing the meteorological predictions at the medium-range (up to 10-15 days) and their use in hydrological forecasting. Precipitation from the ensemble prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used. A semi-distributed hydrological model was used to transform these precipitation forecasts into ensemble streamflow predictions. The performance of these forecasts was analyzed in probabilistic terms. A simple decision model also allowed to compare the relative economic value of hydrological ensemble predictions and some deterministic alternatives. <p><p>Numerical weather prediction models are imperfect. The ensemble forecasts are therefore affected by errors implying the presence of biases and the unreliability of probabilities derived from the ensembles. By comparing the results of these predictions to the corresponding observed data, a statistical model for the correction of forecasts, known as post-processing, has been adapted and shown to improve the performance of probabilistic forecasts of precipitation. This approach is based on retrospective forecasts made by the ECMWF for the past twenty years, providing a sufficient statistical sample. <p><p>Besides the errors related to meteorological forcing, hydrological forecasts also display errors related to initial conditions and to modeling errors (errors in the structure of the hydrological model and in the parameter values). The last stage of the research was therefore to investigate, using simple models, the impact of these different sources of error on the quality of hydrological predictions and to explore the possibility of using hydrological reforecasts for post-processing, themselves based on retrospective precipitation forecasts. <p>/<p>La prévision des débits des rivières se fait traditionnellement sur la base de mesures en temps réel des précipitations sur les bassins-versant et des débits à l'exutoire et en amont. Ces données sont traitées dans des modèles mathématiques de complexité variée et permettent d'obtenir des prévisions précises pour des temps courts. Pour prolonger l'horizon de prévision à quelques jours – afin d'être en mesure d'émettre des alertes précoces – il est nécessaire de prendre en compte les prévisions météorologiques. Cependant celles-ci présentent par nature une dynamique sensible aux erreurs sur les conditions initiales et, par conséquent, pour une gestion appropriée des risques, il faut considérer les prévisions en termes probabilistes. Actuellement, les prévisions d'ensemble sont effectuées à l'aide d'un modèle numérique de prévision du temps avec des conditions initiales perturbées et permettent d'évaluer l'incertitude.<p><p>La recherche a commencé par l'analyse des prévisions météorologiques à moyen-terme (10-15 jours) et leur utilisation pour des prévisions hydrologiques. Les précipitations issues du système de prévisions d'ensemble du Centre Européen pour les Prévisions Météorologiques à Moyen-Terme ont été utilisées. Un modèle hydrologique semi-distribué a permis de traduire ces prévisions de précipitations en prévisions d'ensemble de débits. Les performances de ces prévisions ont été analysées en termes probabilistes. Un modèle de décision simple a également permis de comparer la valeur économique relative des prévisions hydrologiques d'ensemble et d'alternatives déterministes.<p><p>Les modèles numériques de prévision du temps sont imparfaits. Les prévisions d'ensemble sont donc entachées d'erreurs impliquant la présence de biais et un manque de fiabilité des probabilités déduites des ensembles. En comparant les résultats de ces prévisions aux données observées correspondantes, un modèle statistique pour la correction des prévisions, connue sous le nom de post-processing, a été adapté et a permis d'améliorer les performances des prévisions probabilistes des précipitations. Cette approche se base sur des prévisions rétrospectives effectuées par le Centre Européen sur les vingt dernières années, fournissant un échantillon statistique suffisant.<p><p>A côté des erreurs liées au forçage météorologique, les prévisions hydrologiques sont également entachées d'erreurs liées aux conditions initiales et aux erreurs de modélisation (structure du modèle hydrologique et valeur des paramètres). La dernière étape de la recherche a donc consisté à étudier, à l'aide de modèles simples, l'impact de ces différentes sources d'erreur sur la qualité des prévisions hydrologiques et à explorer la possibilité d'utiliser des prévisions hydrologiques rétrospectives pour le post-processing, elles-même basées sur les prévisions rétrospectives des précipitations.<br>Doctorat en Sciences<br>info:eu-repo/semantics/nonPublished
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Quéno, Louis. "Apport de prévisions météorologiques à échelle kilométrique pour la modélisation du manteau neigeux en montagne." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30360/document.
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Le suivi et la représentation de la variabilité du manteau neigeux en montagne sont des enjeux écologiques et sociétaux majeurs. Le récent développement de modèles météorologiques à échelle kilométrique offre un potentiel nouveau pour améliorer les simulations d'enneigement en montagne. Dans cette thèse, nous avons évalué l'apport des prévisions météorologiques du modèle de prévision numérique du temps AROME à 2.5 km de résolution horizontale pour alimenter le modèle détaillé de manteau neigeux Crocus. Les simulations AROME-Crocus distribuées ont d'abord été évaluées sur les Pyrénées de 2010 à 2014, montrant un apport en termes de représentation de la variabilité spatio-temporelle du manteau neigeux par rapport à l'approche par massif du système opérationnel actuel SAFRAN-Crocus, malgré une surestimation des hauteurs de neige. Par la suite, la valeur ajoutée de produits satellitaires de rayonnements incidents a été étudiée pour des simulations d'enneigement dans les massifs alpins et pyrénéens, soulignant leur bonne qualité en montagne mais un impact mitigé sur le couvert neigeux simulé. Enfin, on a montré comment le schéma de microphysique nuageuse d'AROME associé à Crocus permet de mieux prévoir la formation de glace en surface du manteau neigeux par précipitations verglaçantes dans les Pyrénées. Ces travaux ouvrent la voie à une prévision nivologique distribuée à haute résolution en montagne<br>Monitoring and representing the snowpack variability in mountains are crucial ecological and societal issues. The recent development of meteorological models at kilometric scale offers a new potential to improve snowpack simulations in mountains. In this thesis, we assessed the potential of forecasts from the numerical weather prediction model AROME at 2.5 km horizontal resolution to drive the detailed snowpack model Crocus. AROME-Crocus distributed simulations were first evaluated over the Pyrenees from 2010 to 2014. They showed benefits in representing the snowpack spatio-temporal variability as compared to the massif-based approach of the current operational system SAFRAN-Crocus, despite an overestimation of snow depth. Then, we studied the potential added value of satellite-derived products of incoming radiations for simulating the snow cover in the French Alps and Pyrenees. These products were found of good quality in mountains but their impact on the simulated snow cover is questionable. Finally, we showed how the cloud microphysics scheme of AROME associated with Crocus enables to better predict ice formation on top of the snowpack due to freezing precipitation in the Pyrenees. These works pave the way for high-resolution distributed snowpack forecasting in mountains
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Risley, John. "Predicting runoff and salinity intrusion using stochastic precipitation inputs." Diss., The University of Arizona, 1989. http://ezproxy.library.arizona.edu/login?url=.
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McKechnie, Nicole R., and University of Lethbridge Faculty of Arts and Science. "Predicting climate change impacts on precipitation for western North America." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2005, 2005. http://hdl.handle.net/10133/269.
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Global Circulation Models (GCMs) are used to create projections of possible future climate characteristics under global climate change scenarios. Future local and regional precipitation scenarios can be developed by downscaling synoptic CGM data. Daily 500-mb geopotential heights from the Canadian Centre for Climate Modeling and Analysis's CGCM2 are used to represent future (2020-2050) synoptics and are compared to daily historical (1960-1990) 500-mb geopotential height reanalysis data. The comparisons are made based on manually classified synoptic patterns identified by Changnon et al. (1993.Mon. Weather Rev. 121:633-647). Multiple linear regression models are used to link the historical synoptic pattern frequencies and precipitation amounts for 372 weather stations across western North America,. The station-specific models are then used to forecast future precipitation amounts per weather station based on synoptic pattern frequencies forecast by the CGCM2 climate change forcing scenario. Spatial and temporal variations in precipitation are explored to determine monthly, seasonal and annual trends in climate change impacts on precipitation in western North America. The resulting precipitation scenarios demonstrate a decrease in precipitation from 10 to 30% on an annual basis for much of the south and western regions of the study area. Seasonal forecasts show variations of the same regions with decreases in precipitation and select regions with increases in future precipitation. A major advancement of this analysis was the application of synoptic pattern downscaling to summer precipitation scenarios for western North America.<br>ix, 209 leaves : col. maps ; 29 cm.
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Zelelew, Mulugeta. "Improving Runoff Estimation at Ungauged Catchments." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for vann- og miljøteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19675.
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Water infrastructures have been implemented to support the vital activities of human society. The infrastructure developments at the same time have interrupted the natural catchment response characteristics, challenging society to implement effective water resources planning and management strategies. The Telemark area in southern Norway has seen a large number of water infrastructure developments, particularly hydropower, over more than a century. Recent developments in decision support tools for flood control and reservoir operation has raised the need to compute inflows from local catchments, most of which are regulated or have no observed data. This has contributed for the motivation of this PhD thesis work, with an aim of improving runoff estimation at ungauged catchments, and the research results are presented in four manuscript scientific papers. The inverse distance weighting, inverse distance squared weighting, ordinary kriging, universal kriging and kriging with external drift were applied to analyse precipitation variability and estimate daily precipitation in the study area. The geostatistical based univariate and multivariate map-correlation concepts were applied to analyse and physically understand regional hydrological response patterns. The Sobol variance based sensitivity analysis (VBSA) method was used to investigate the HBV hydrological model parameterization significances on the model response variations and evaluate the model’s reliability as a prediction tool. The HBV hydrological model space transferability into ungauged catchments was also studied. The analyses results showed that the inverse distance weighting variants are the preferred spatial data interpolation methods in areas where relatively dense precipitation station network can be found. In mountainous areas and in areas where the precipitation station network is relatively sparse, the kriging variants are the preferred methods. The regional hydrological response correlation analyses suggested that geographic proximity alone cannot explain the entire hydrological response correlations in the study area. Besides, when the multivariate map-correlation analysis was applied, two distinct regional hydrological response patterns - the radial and elliptical-types were identified. The presence of these hydrological response patterns influenced the location of the best-correlated reference streamgauges to the ungauged catchments. As a result, the nearest streamgauge was found the best-correlated in areas where the radial-type hydrological response pattern is the dominant. In area where the elliptical-type hydrological response pattern is the dominant, the nearest reference streamgauge was not necessarily the best-correlated. The VBSA verified that varying up to a minimum of four to six influential HBV model parameters can sufficiently simulate the catchments' responses characteristics when emphasis is given to fit the high flows. Varying up to a minimum of six influential model parameters is necessary to sufficiently simulate the catchments’ responses and maintain the model performance when emphasis is given to fit the low flows. However, varying more than nine out of the fifteen HBV model parameters will not make any significant change on the model performance. The hydrological model space transfer study indicated that estimation of representative runoff at ungauged catchments cannot be guaranteed by transferring model parameter sets from a single donor catchment. On the other hand, applying the ensemble based model space transferring approach and utilizing model parameter sets from multiple donor catchments improved the model performance at the ungauged catchments. The result also suggested that high model performance can be achieved by integrating model parameter sets from two to six donor catchments. Objectively minimizing the HBV model parametric dimensionality and only sampling the sensitive model parameters, maintained the model performance and limited the model prediction uncertainty.
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Dildine, Garrett. "Equilibrium-Based Predictions OF Phosphorus Recovery From Different Wastewater Streams via Chemical Precipitation." Ohio University Honors Tutorial College / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1619196791599087.
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Boers, Niklas. "Complex network analysis of extreme rainfall in South America." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17237.
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Basierend auf der Theorie von Netzwerken wird ein allgemeines Rahmenwerk entwickelt, um kollektive Synchronisationsphänome von Extremereignissen in komplexen Systemen zu studieren. Die Methode vergleicht die Variabilität der einzelnen Teile des Systems auf Grundlage von Beobachtungszeitreihen mit dem Ziel, emergente Synchronisationsmuster von Extremereignissen auf makroskopischer Ebene aufzudecken. Zu diesem Zweck werden die einzelnen Zeitreihen eines interaktiven Systems mit den Knoten eines Netzwerks identifiziert und die Abhängigkeiten zwischen diesen durch die Kanten des Netzwerks dargestellt. Die komplexe interne Synchronisationsstruktur des Systems wird so in Form der Netzwerktopologie mathematisch zugänglich gemacht und kann durch die Einführung geeigneter Netzwerkmaße analysiert werden. Die Methode wird im Folgenden auf räumlich und zeitlich hochaufgelöste Regendaten aus Satellitenmessungen angewendet, um die kollektive Dynamik extremer Regenereignisse in Südamerika zu untersuchen. Diese Anwendung verfolgt drei Ziele: Erstens wird gezeigt, wie die hier entwickelte Methode zur klimatologischen Analyse verwendet werden kann. Zweitens können Quellen und Senken von Extremereignissen durch die Einführung des Konzeptes der Netzwerkdivergenz identifiziert werden. Dies erlaubt es, die gerichteten Netzwerkpfade, entlang derer Extremereignisse synchronisieren, nachzuverfolgen. Auf dieser Grundlage wird eine statistische Regel gewonnen, die beträchtliche Anteile der extremen Regenereignisse in den Zentralanden vorhersagt. Drittens werden die bis dahin entwickelten Methoden und gewonnenen Einsichten dazu verwendet, die Darstellung extre- mer Regenereignisse in verschiedenen Datensätzen zu vergleichen. Insbesondere wird in diesem Kontext die Implementierung solcher Ereignisse in drei gängigen Klimamodellen evaluiert.<br>Based on the theory of networks, a general framework is developed to study collective synchronization phenomena of extreme events in complex systems. The method relies on observational time series encoding the variability of the single parts of the system, and is intended to reveal emerging patterns of extreme event synchronization on the macroscopic level. For this purpose, the time series obtained from an interactive system under consideration are identified with network nodes, and the possibly delayed and non-linear interdependence of extreme events in different time series is represented by network links connecting the nodes. In this way, the complex internal synchronization structure of the system becomes accessible in terms of the topology of the network, which can be analyzed by introducing suitable network measures. The methodology is applied to satellite-derived rainfall time series of high spatiotemporal resolution in order to investigate the collective dynamics of extreme rainfall events in South America. The purpose of this application is threefold: First, it is shown how the methodology can be used for climatic analysis by revealing climatological mechanism from the spatial patterns exhibited by different network measures. Second, by introducing the concept of network divergence, sink and source regions of extreme events can be identified, allowing to track their directed synchronization pathways through the network. A simple statistical forecast rule is derived on this basis, predicting substantial fractions of extreme rainfall events in the Central Andes. Third, the methodology and the insights developed in the first two steps are used to evaluate the dynamical representation of extreme events in different datasets, and in particular their dynamical implementation in three state of the art climate models.
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Smith, Tyler Jon. "A conceptual precipitation-runoff modeling suite model selection, calibration and predictive uncertainty assessment /." Thesis, Montana State University, 2008. http://etd.lib.montana.edu/etd/2008/smith/SmithT1208.pdf.
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In Montana and much of the Rocky Mountain West, the single most important parameter in forecasting the controls on regional water resources is snowpack. Despite the heightened importance of snowpack, few studies have considered the representation of uncertainty in coupled snowmelt/hydrologic conceptual models. Uncertainty estimation provides a direct interpretation of the risk associated with predictive modeling results. Bayesian inference, through the application of Markov chain Monte Carlo methods, provides a statistical means of approximating uncertainty associated with both the parameters and the model structure. This thesis addresses the complexities of predictive modeling in hydrology through the development, implementation and analysis of a suite of conceptual hydrologic models under a Bayesian inference framework. The research is presented in four main sections. First, a comparative assessment of three recently developed Markov chain Monte Carlo algorithms, based on their performance across two case studies, is performed. This study has revealed that the extreme complexity of the parameter space associated with simple, conceptual models is best explored by the Delayed Rejection Adaptive Metropolis algorithm. Second, a complete description of the models and study site incorporated in the study are presented, building on established theories of model development. Third, an investigation of the value of each model structure, considering predictive performance, uncertainty and physical realism is presented. This section builds on results of the first section, through the application of the Delayed Rejection Adaptive Metropolis algorithm for model calibration and uncertainty quantification under Bayesian principles. Finally, a discussion of the Simulation and Prediction Lab for Analysis of Snowmelt Hydrology, developed to incorporate the tasks of model selection, calibration and uncertainty analysis into a simple graphical user interface is explained. The application of a complete modeling framework from model selection to calibration and assessment presented in this thesis represents a holistic approach to the development of improved understanding of snow-dominated watersheds through prediction by coupled snowmelt/hydrologic modeling strategies.
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Choux, Mathieu. "Development of new predictor climate variables for statistical downscaling of daily precipitation process." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98951.
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Statistical downscaling (SD) procedures have been frequently used for assessing the potential impacts of climate change and variability on hydrological regime. These procedures are based on the empirical relationships between large-scale atmospheric variables (predictors) and surface environment parameters (e.g., precipitation and temperature). The present research work is hence concerned with the development of new predictor climate variables that could be used for improving the accuracy of downscaling of daily precipitation process at a local site. The new predictors should be able to provide a more accurate simulation of the local variable since they could describe more accurately the physical characteristics of the precipitation process. In particular, a better reproduction of summer rainfall event is expected through an improved inclusion of main thermodynamic forcings from humidity and stability parameters.<br>The first part of this study focuses on the re-computation of the geostrophic circulation predictor variables developed by Wilby and Wigley (2000), reconstructed from mean sea level pressure or geopotential heights. The same circulation variables are re-computed from prognostic winds of the National Centre for Environmental Prediction (NCEP) re-analysis data set (Kalnay et al., 1996). Assessment of the performance of the re-computed predictors is carried out using the Statistical DownScaling Model (SDSM), developed by Wilby et al. (2002), and based on a number of climate indices characterizing the frequency, intensity and extremes of daily precipitation process. Two different predictor sets are considered, the first consisting of circulation-only variables, the second including a raw specific humidity predictor. For each predictor set, results obtained from the two computation techniques are compared. Daily precipitation data available at Montreal-Dorval Airport station for the 1961-1990 period were used in this assessment. Results indicated that the re-computation of geostrophic variables for both sets could yield significant improvements in the reproduction of local precipitation characteristics for the validation 1976-1990 period. The most striking improvement can be achieved for winter, as expected from the greater influence of large-scale circulation forcings on precipitation in this season. In the second part, new advection variables are developed based on a generalized omega equation. It is found that the Laplacian of temperature advection and the differential vorticity advection appear as direct forcings of the vertical velocity, strongly correlated with the precipitation process. Precipitable water and atmospheric instability indices are also included in the predictor range, mainly to reach a better simulation of convective precipitation. Next, a new statistical downscaling scheme is developed, combining a Principal Component Analysis (PCA) of the new predictors and the SDSM model. Analysis of the different computed principal components confirms the major role of the two identified advection terms and the humidity/instability predictors. Assessment of the new PCA+SDSM scheme shows significant improvements of the simulation of precipitation intensity, although results are less conclusive regarding the precipitation occurrence.<br>Finally, the influence of the calibration period length on the new downscaling scheme performance was carried out by comparing the simulation results obtained from two calibration runs of 15 and 30 years of length: for the 1961-1975 period and for the 1961-1990 one. It was found that doubling the calibration period length could lead to significant improvements in the reproduction of the local precipitation characteristics.
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Alexander, Cindy-Ann Patricia. "A Fuzzy Rule-Based Model for Predicting Precipitation in the Marion, Illinois Station Area." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/881.
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The purpose of this paper is present the results of a developed, and implemented a Fuzzy rule based model to determine the probability of precipitation in the Marion Illinois area during the summer months. The model employs fuzzy logic and the results are compared to actual data to measure how reliable and viable this method is as an option in the precipitation prediction. Researchers, over the years, have been developing models for simulating, predicting and analyzing atmospheric phenomena, in order to accurately determine their immediate and long term effects on the environment and the quality of human life, such as in agriculture, ecosystem evolution, biodiversity, and disaster preparedness (decision support systems: drought/ warning or flash floods). To simulate global climate changes, researchers use General Circulation Models (GCMs). These have been developed using numerical weather predictions. These models are very useful for global impact studies such as global warming, but they are limited if applied to regional scenarios. This is because they are not able to neither simulate the local effects nor accurately present spatial and temporal resolutions. Continued work to improve the efficiency of these systems has led to the development of various models. Improvements have come in the form of Regional Climate Models; they have higher resolution and take into account orographic effects. These models use downscaling techniques, which bridge the gap between the global climate simulations and regional climate impact assessment. This paper presents the implementation of a fuzzy rule-based downscaling technique with specific application to the Marion, Illinois area. It shows that this method has the distinct advantage of being both computation and resource inexpensive while producing accurate information in a timely manner.
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Das, Tapash. "The impact of spatial variability of precipitation on the predictive uncertainty of hydrological models." [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-28827.
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Kauffeldt, Anna. "Disinformative and Uncertain Data in Global Hydrology : Challenges for Modelling and Regionalisation." Doctoral thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-236864.
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Water is essential for human well-being and healthy ecosystems, but population growth and changes in climate and land-use are putting increased stress on water resources in many regions. To ensure water security, knowledge about the spatiotemporal distribution of these resources is of great importance. However, estimates of global water resources are constrained by limitations in availability and quality of data. This thesis explores the quality of both observational and modelled data, gives an overview of models used for large-scale hydrological modelling, and explores the possibilities to deal with the scarcity of data by prediction of flow-duration curves. The evaluation of the quality of observational data for large-scale hydrological modelling was based on both hydrographic data, and model forcing and evaluation data for basins worldwide. The results showed that a GIS polygon dataset outperformed all gridded hydrographic products analysed in terms of representation of basin areas. Through a screening methodology based on the long-term water-balance equation it was shown that as many as 8–43% of the basins analysed displayed inconsistencies between forcing (precipitation and potential evaporation) and evaluation (discharge) data depending on how datasets were combined. These data could prove disinformative in hydrological model inference and analysis. The quality of key hydrological variables from a numerical weather prediction model was assessed by benchmarking against observational datasets and by analysis of the internal land-surface water budgets of several different model setups. Long-term imbalances were found between precipitation and evaporation on the global scale and between precipitation, evaporation and runoff on both cell and basin scales. These imbalances were mainly attributed to the data assimilation system in which soil moisture is used as a nudge factor to improve weather forecasts. Regionalisation, i.e. transfer of information from data-rich areas to data-sparse areas, is a necessity in hydrology because of a lack of observed data in many areas. In this thesis, the possibility to predict flow-duration curves in ungauged basins was explored by testing several different methodologies including machine learning. The results were mixed, with some well predicted curves, but many predicted curves exhibited large biases and several methods resulted in unrealistic curves.<br>Vatten är en förutsättning för människors och ekosystems hälsa, men befolkningsökning och förändringar av klimat och markanvändning förväntas öka trycket på vattenresurserna i många regioner i världen. För att kunna säkerställa en god tillgång till vatten krävs kunskap om hur dessa resurser varierar i tid och rum. Tillförlitligheten hos skattningar av globala vattenresurser begränsas dock både av begränsad tillgänglighet av och kvalitet hos observerade data. Denna avhandling utforskar kvaliteten av såväl observations- som modellbaserade data, ger en överblick över modeller som används för storskalig hydrologisk modellering och utforskar möjligheterna att förutsäga varaktighetskurvor som ett sätt att hantera bristen på data i många områden. Utvärderingen av observationsbaserade datas kvalitet baserades på hydrografiska data och driv- och utvärderingsdata för storskaliga hydrologiska modeller. Resultaten visade att en uppsättning data över hydrografin baserad på GIS-polygoner representerade avrinningsområdesareorna bättre än alla de som byggde på rutor. En metod baserad på långtidsvattenbalansen identifierade att kombinationen av drivdata (nederbörd och potentiell avdunstning) och utvärderingsdata (vattenföring) var fysiskt orimlig för så många som 8–43 % av de analyserade avrinningsområdena beroende på hur olika datauppsättningar kombinerades. Sådana data kan vara desinformativa för slutsatser som dras av resultat från hydrologiska modeller och analyser. Kvaliteten hos hydrologiskt viktiga variabler från en numerisk väderprognosmodell utvärderades dels genom jämförelser med observationsdata och dels genom analys av landytans vattenbudget för ett flertal olika modellvarianter. Resultaten visade obalanser mellan långtidsvärden av nederbörd och avdunstning i global skala och mellan långtidsvärden av nederbörd, avdunstning och avrinning i både modellrute- och avrinningsområdesskala. Dessa obalanser skulle till stor del kunna förklaras av den data assimilering som görs, i vilken markvattenlagret används som en justeringsfaktor för att förbättra väderprognoserna. Regionalisering, som innebär en överföring av information från områden med god tillgång på mätdata till områden med otillräcklig tillgång, är i många fall nödvändig för hydrologisk analys på grund av att mätdata saknas i många områden. I denna avhandling utforskades möjligheten att förutsäga varaktighetskurvor för avrinningsområden utan vattenföringsdata genom flera metoder inklusive maskininlärning. Resultaten var blandade med en del kurvor som förutsas väl, och andra kurvor som visade stora systematiska avvikelser. Flera metoder resulterade i orealistiska kurvor (ickemonotona eller med negativa värden).
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Das, Tapash [Verfasser]. "The impact of spatial variability of precipitation on the predictive uncertainty of hydrological models / von Tapash Das." Stuttgart : Inst. für Wasserbau, 2006. http://d-nb.info/996777660/34.
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Zamboni, Laura. "Seasonal variability of precipitation over South Eastern South America: its relationship with upper level circulation as physical base for predictions." Doctoral thesis, Università degli studi di Trieste, 2009. http://hdl.handle.net/10077/3212.
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2007/2008<br>At the interannual timescale Sea Surface Temperature (SST) associated with El Niño Southern Oscillation (ENSO) have been identified as modulators of rainfall over South America. The proposed mechanism responsible for anomalies over northern South America involves the modification of the Walker circulation, while the generation (or excitement) of the Pacific-South American (PSA) modes would represent the teleconnection to the subtropics. However, the latter is present even in seasons in which ENSO is not at its peak.
In this study our aim is to investigate the interannual variability of seasonal precipitation over South Eastern South America (SESA), which comprises southern Brazil, Uruguay, Paraguay and northeastern Argentina, and its dynamical dependence from ENSO and the PSA modes.
We have shown the existence of a pervasive mode of upper level atmospheric variability which dominates the circulation over South America in all seasons. The mode consists of a continental scale vortex and resembles the eastern end of the leading Pacific-South American mode (PSA1). Differences in the structure and intensity of the vortex and the effects of orography affect the transport and convergence of moisture into SESA thus creating rainfall anomalies there.
Motivated by and to test further the reported relationship between the upper level wind and precipitation anomalies, we developed a method to predict precipitation over SESA in which the upper level wind is the predictor. The method has a high potential in all seasons, but limited skill in forecast mode due to limitations of Coupled General Circulation Model performances.
In exploring the predictability of the vortex, we assessed to what extent each connection of the schematic chain ENSO->PSA1->vortex->rainfall holds. The latter relationship between the vortex over SA and rainfall in SESA holds in spring, summer and fall.
The vortex is, at least partially, an internal mode of variability in all seasons.
In spring the whole chain of elements is observed: the vortex appears as a mode forced by ENSO via excitement of the leading PSA mode.
In summer the vortex is uncoupled from the circulation over the Pacific Ocean, supporting the interpretation that regional effects dominate during the monsoon season. No connection with SSTs, and thus predictability, is found for this season.
In fall the PSA1 pattern and the vortex are partially linked as for the spring season. However, the connection with SSTs is more puzzling and further analysis is required to clarify the nature of the leading PSA mode and its predictability.
In view of our results, we underline that the leading Pacific-South American pattern properly comprehends centers of anomalies over the Southern Pacific Ocean only but not those over the South American sector.<br>XXI Ciclo<br>1979
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Albergel, Jean. "Genèse et prédétermination des crues au Burkina Faso : du m² au km² : étude des paramètres hydrologiques et de leur évolution." Paris 6, 1987. http://www.theses.fr/1987PA066139.
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Vavae, Hilia. "A simple forecasting scheme for predicting low rainfalls in Funafuti, Tuvalu." The University of Waikato, 2008. http://hdl.handle.net/10289/2435.
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The development of some ability for forecasting low rainfalls would be helpful in Tuvalu as rainwater is the only source of fresh water in the country. The subsurface water is brackish and saline so the entire country depends totally on rainwater for daily domestic supplies, agricultural and farming activities. More importantly, these atolls are often influenced by droughts which consequently make inadequate drinking water an issue. A simple graph-based forecasting scheme is developed and presented in this thesis for forecasting below average mean rainfall in Funafuti over the next n-month period. The approach uses precursor ocean surface temperature data to make predictions of below average rainfall for n = 1, 2 12. The simplicity of the approach makes it a suitable method for the country and thus for the Tuvalu Meteorological Service to use as an operational forecasting tool in the climate forecasting desk. The graphical method was derived from standardised monthly rainfalls from the Funafuti manual raingauge for the period January 1945 to July 2007. The method uses lag-1 and-lag 2 NINO4 sea surface temperatures to define whether prediction conditions hold. The persistence of predictability tends to be maintained when the observed NINO4 ocean surface temperatures fall below 26.0oC. Although the developed method has a high success probability of up to 80 percent, this can only be achieved when conditions are within the predictable field. A considerable number of below average rainfall periods are not within the predictable field and therefore cannot be forecast by this method. However, the graphical approach has particular value in warning when an existing drought is likely to continue.
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Vogel, Peter [Verfasser], and T. [Akademischer Betreuer] Gneiting. "Assessing Predictive Performance: From Precipitation Forecasts over the Tropics to Receiver Operating Characteristic Curves and Back / Peter Vogel ; Betreuer: T. Gneiting." Karlsruhe : KIT-Bibliothek, 2019. http://d-nb.info/1179964055/34.
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Frischbier, Nico. "Untersuchungen zur einzelbaumverursachten kleinräumigen Variabilität und regenhöhenbasierten Dynamik des Bestandesniederschlages am Beispiel zweier Buchen-Fichten-Mischbestände." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-94870.
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Trifft herabfallender Regen auf Waldflächen, so wird dieser Niederschlag umverteilt zu Interzeption, Stammabfluss, durchfallenden und abtropfenden Niederschlag. Besonders hohe Stammablaufmengen im Kronenzentrum und markante Abtropfstellen am Kronenrand einzelner Baumarten lassen sich zudem nur erklären, wenn am jeweiligen Messplatz unter Baumkronen eine weitere Niederschlagskomponente zugelassen wird, mit der laterale Wasserbewegungen innerhalb der expliziten Einzelbaumkrone beschrieben und bilanziert werden (lateraler [Zu- oder Ab-]Fluss). Ziel dieser Arbeit war es deshalb, der niederschlagsabhängigen und kleinräumigen Dynamik dieser Umverteilung im Wald am Beispiel der Baumarten Buche (Fagus sylvatica L.) und Fichte (Picea abies (L.) Karst.) durch Aufnahmen und Auswertungen in zwei Mischbeständen beider Baumarten nachzugehen. Wiederholende Niederschlagsaufzeichnungen einzelner Regenereignisse wurden hierzu in Relation zur jeweiligen Freilandniederschlagsmenge, zur Art der Messplatzüberschirmung im Kronendach und zur Distanz des Messplatzes zum ihn dominierenden Baum varianz- und regressionsanalytisch untersucht und um Ergebnisse aus Stammablaufanalysen und Streumodellen ergänzt. Auf dieser Basis konnten Kausalmodelle zur Schätzung des Unterkronenniederschlages mit hoher Güte hergeleitet werden, die im Detail ein baumartspezifisches räumliches Verhalten der einzelnen Niederschlagskomponenten beim Passieren der Baumkrone belegen. Neben den Besonderheiten, die sich bei Messungen in Bestandeslücken einstellen, ergeben sich so z.B. in der Vegetationsperiode je nach Messplatzposition und Freilandniederschlagsmenge Unterschiede im Niederschlag unter beiden Baumartenkronen von bis zu 35 % des Freilandniederschlages je Einzelereignis und zwar stets zugunsten der Buchenüberschirmung. Am Stammfuss von Buchen kann darüber hinaus zusätzliches Wasser durch den Stammabfluss eingetragen werden. Hierfür notwenige Wassermengen können plausibel aus dem nachgewiesenen lateralen Wasserabfluss im inneren Kronendrittel von Buchen gedeckt werden. Über ein räumlich konkretes Interzeptionsmodell, kombiniert mit Blattflächenschätzungen für Einzelbäume konkreter Dimension, konnte ein räumliches LAI-Modell für Buchen abgeleitet werden, dass höchste LAI-Werte im Kronenzentrum annimmt. Da der Bestandesniederschlag hinsichtlich Niederschlagsmenge, Bestockung, Belaubungszustand und zum räumlich konkreten Messplatz unter der einzelnen Baumkrone veränderlich ist, wird die gewissenhaftere Berücksichtigung dieser Einflussvariablen angeregt und der bisher häufig praktizierten pauschalen Aufteilung des Niederschlages in einzelne Niederschlagskomponenten auf Basis von Flächen- und Messphasendurchschnittswerten widersprochen<br>Forests redistribute the precipitation falling on their canopy into interception, stemflow, drip or direct throughfall. Extremely high amounts of stemflow in the centre of the crown and distinct drip points along the crown edge of certain tree species can only be explained by admitting an additional precipitation component at these measurement locations that describes and captures the lateral movement of water within the individual tree crown (lateral in- or outflow). The aim of this study was therefore to analyse these precipitation-dependent, small-scale dynamics of precipitation redistribution in forests using field-measurements from two mixed stands of European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) Karst.). Periodic measurements of individual precipitation events were examined in relation to the respective gross precipitation, the type of canopy above a plot and the distance of a plot to its dominant sheltering canopy tree using variance and regression analysis, and complemented with stemflow analyses and litterfall models. Using this dataset, causal models for the high-precision estimation of throughfall were derived, showing tree species-specific pathways of the individual precipitation components through the tree crown. Apart from the particularities of measurements in canopy gaps, differences in throughfall between spruce and beech during the vegetation period amount to up to 35 % of gross precipitation per event, in favour of the beech canopy and depending on plot location. At the stem base of beech trees additional water can reach the forest floor via stemflow. The amount of water required to generate this stemflow can plausibly be explained by means of the verified lateral water flow in the inner third of beech crowns. Using a spatially explicit interception model combined with LAI estimates for specific individual trees, a spatial LAI model was developed for beech, showing maximal LAI values in the crown centre. As the net forest precipitation is sensitive with respect to precipitation amount, stand type, foliage status and the spatially explicit plot location below an individual tree crown, this study recommends the consideration of these influential factors and contradicts the commonly practiced blanket partitioning of precipitation into individual components based on spatial and temporal averages
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Amey, Katherine Springer. "Hydrology And Predictive Model Of Headwater Streams And The Groundwater/Surface Water Interactions Supporting Brook Trout Habitat In Northeast Ohio." Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1301618586.
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Luciani, Riccardo. "Study of Europe-ENSO teleconnection in an El Niño index phase analysis framework." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18807/.
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El Niño/Southern Oscillation (ENSO) is the most important coupled ocean-atmosphere phenomenon to cause global climate variability on seasonal to interannual time scales. Therefore understanding some of its most important features may help to shed light on the field of climate predictions. Here the focus is put on the seasonal precipitation patterns which respond to persistent thermal forcing happening thousands of kilometers far away.
The first objective of this work is to look for and describe the correlation patterns between seasonal rainfall anomalies over Northern Italy and global seasonal Sea Surface Temperature anomalies (SSTA). Tri-monthly means of precipitation and tri-monthly means of SSTA from observational datasets are used in an anomaly correlation study in order to explore this teleconnection. The study is developed in the Nino Index Phase Analysis (NIPA) framework, as presented by Zimmerman et al., which consists in separating the positive and negative ENSO phase years in the computation of the anomaly correlation.
The second objective of the work is to check if the correlations found are consistent with the shift of the circulation pattern which is due to a non-weak ENSO state. The anomaly means of the main ocean-atmospheric variables are examined in order to characterise the way in which the circulation works when the system is under El Niño or La Niña conditions and when the precipitation over the basins is higher or lower.
Then, a Rossby waves simulation software is used to show that the propagation of a Rossby wave train, in a basic state with zonally varying middle latitude or low latitude jet, may be the cause of the correlations in the area under exam and for the seasons chosen, and how. This is an indication of the fact that the ENSO state and its spatial features can influence the tropospheric pathways through which planetary waves can propagate and this, in turn, could have an effect on midlatitudes large-scale circulation.
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Chkir, Najiba. "Mise au point d'un modèle hydrologique conceptuel intégrant l'état hydrique du sol dans la modélisation pluie-débit." Phd thesis, Marne-la-vallée, ENPC, 1994. http://www.theses.fr/1994ENPC9410.
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L’importance de l’état initial des bassins versants, et surtout de l’état hydrique du sol, dans la formation des débits est reconnue depuis longtemps. La connaissance précise de cet état hydrique et de sa prise en compte dans la modélisation Pluie-Débit reste cependant un des problèmes actuels de l’hydrologie. Aux mesures « in situ », trop ponctuelles et difficilement généralisables, viennent s’ajouter de nouvelles techniques de télédétection pouvant fournir une information « tout temps » et spatialisée de l’état de surface des bassins versants. L’objectif de cette thèse est de mettre au point un modèle hydrologique conceptuel Pluie-Débit, capable de prendre en compte l’état hydrique des sols. Deux outils de base ont été utilisés : le modèle conceptuel GR3J (puis GR4J) pour la simulation des débits et le modèle physique bi-couches inspiré du « Schéma de Deardorff » pour le suivi de l’humidité des deux couches de sol, superficielle et racinaire. De nombreux schémas de couplage ont été testés en s’appuyant sur les données du BVRE de l’Orgeval, où existent des séries de données de pluie, de débit et d’humidité du sol. Le modèle retenu, « GRHUM », a une fonction de production dérivée du schéma de Deardorff et a conservé la fonction de transfert de GR4J. C’est un modèle à six paramètres, simulant le débits journaliers et l’humidité de deux couches de sol. Le modèle a été validé sur le BVRE de Naisin et sur 35 autres bassins versants situés en Bretagne. Les résultats obtenus montrent les bonnes aptitudes du modèle à simuler les débits et l’humidité de la couche de sol racinaire. La prise en compte de l’occupation réelle du sol, à partir de cartes de cultures et accessible par télédétection, améliore la simulation des humidités de surface. Le fonctionnement de ce modèle peut être réalisé en deux modes : « simulation » lorsque les données d’humidité du sol ne sont pas disponibles et « assimilation » lorsque ces données sont présentes. Le modèle « GRHUM » ouvre des perspectives nouvelles pour l’utilisation de l’état hydrique du sol déterminé à partir de données satellitaires (radar, IRT) dans la prévision des débits<br>Conceptual hydrological modelling fails in describing the temporal evolution of soil hydric state by the use of classic methods of soil moisture measurement. It is well known that soil hydrodynamic behaviour is highly heterogeneous in the catchment. New remote sensed techniques of measurements can provide information about the spatial variability of this date. Actuel conceptual models use an index that represents the soil water content. This approach is not adapted to the use of remotely sensed data. The aim of this research is to develop a software which can estimate the soil hydric state evolution and simulate basin outflows. Thus, we will be able to use the remotely sensed data. This study is based on two existing tools. The first is the hydrologic conceptual model GR3J which is used to simulate the runoff. The second is the physically based two layers model, issued from de « Deardorff’s schema », and which is used to estimate the moisture evolution o f the two soil layers. These models were calibrated apart using date from basins of different hydrodynamic and morphological characteristics. He final model is obtained by a combination of the two previous models and can provide the capacity of each of them. This study have been done on the Orgeval’s catchment. The final model have been successfully validated on the Brittany region (France) where the ERS-1 project is situated. The model can run with two functional modes depending on the soil moisture data availability (simulation and assimilation)
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Crowell, Kevin L. "Precipitation prediction using artificial neural networks." 2008. http://purl.galileo.usg.edu/uga%5Fetd/crowell%5Fkevin%5Fl%5F200812%5Fms.
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