Tesi sul tema "Wave forecasting"

Background   By the beginning of the 20th century, the men’s suit entered the menswear market as one the most important fashion garments everdevised. At the same time, fashion became mainly a female engagement, resulting in an under representation of men’s fashion through out the past decade. Relating to the textile and apparel industry, fashion forecasting has become an increasingly important business activity. But the nature of fashion forecasting and the historical neglecting of the men’s suit has created complications when performing this activity. Purpose   The purpose of this thesis is to examine the men’s suit and its development from the given starting point in the 20th century until today, in order to derive a fashion forecasting model suggesting its development by 2029. Design/methodology/approach   This thesis uses an abductive research approach and qualitative multi-methods to answer the research questions. The usage of an intermediate research project answers the first research question. The second research question is answered through the synthesis ofa literature study and semi-structured interviews. The third research question is answered through the derived forecasting model, accomplished through theory matching. Findings   By carrying out a historical investigation of the men’s suit, and then applying this to the derived forecasting model, the men’s suit is expected to be found in both single- and double-breast styles. The suit will have classical features represented through the length, canvas structure, and shoulder construction. Originality/value   This paper carries out a historical investigation of the men’s suit never been done before. It introduces an evaluation framework to categorise and classify the men’s suit, as well as a forecasting model followed by an actual fashion forecast.

In this paper, metal-enhanced fluorescence (MEF) technique is used to lower the detection limit of carcinoembryonic antigen (CEA) which is able to be utilized in forecasting the risk of having certain kinds of cancers, especially colon and rectal cancer. By incubating silver nanocubes (Ag NCs) on the surface of the chips, the detection limit goes down to below 1ng/mL of CEA. Also, when combining MEF with surface acoustic wave (SAW) devices, the incubation time between antigen and antibody will decrease significantly with the fluorescence signal keeping similar or higher level.

The ionosphere is an important factor in high frequency (HF) radio propagation providing an opportunity to study ionospheric variability as well as the space weather conditions under which HF communication can take place. This thesis presents the validation of HF propagation conditions for the Ionospheric Communication Enhanced Profile Analysis and Circuit (ICEPAC) and Advanced Stand Alone Prediction System (ASAPS) models over Africa by comparing predictions with the measured data obtained from the International Beacon Project (IBP). Since these models were not developed using information on the African region, a more accurate HF propagation prediction tool is required. Two IBP transmitter stations are considered, Ruaraka, Kenya (1.24°S, 36.88°E) and Pretoria, South Africa (25.45°S, 28.10°E) with one beacon receiver station located in Hermanus, South Africa (34.27°S, 19.l2°E). The potential of these models in terms of HF propagation conditions is illustrated. An attempt to draw conclusions for future improvement of the models is also presented. Results show a low prediction accuracy for both ICEPAC and ASAPS models, although ICEPAC provided more accurate predictions for daily HF propagation conditions. This thesis suggests that the development of a new HF propagation prediction tool for the African region or the modification of one of the existing models to accommodate the African region, taking into account the importance of the African ionospheric region, should be considered as an option to ensure more accurate HF Propagation predictions over this region.

The main objective of this study is to improve wind wave forecasting in the NW Mediterranean Sea while focusing on the characteristic sharp gradients of the wind and wave conditions. This work was motivated by the limited accuracy of wave models in semi-enclosed-basins and orography-controlled wind conditions, especially during fetch-limited storm events. First, to reduce the commonly observed under-estimation of wave parameters, the mesoscale variability of wind and wave fields was characterized in time (1 h to 1 day) and in space (10 km to 100 km). Second, to better capture the typical sharp gradients, the grid size of the input wind fields was decreased during a characteristic storm event from 18 km to 4 km and the wind input frequency was increased from 6 h to 1 h. Third and last, the rate of wave growth in the numerical model was tuned in order to match the local rate of wave growth. The rate of non-dimensional growth in the region of study, which was calculated using measurements along the fetch, turned out to be faster than simulated using the default physical parameterizations and faster than reported in previous studies. Adjusting the wave growth rate in the model to the observations improved the estimated wave height about 18 % and the peak frequency about 4%. Decreasing the grid size of the numerical models from 12 km to 4 km improved the timing of the wave peaks but not the maximum values of the storm. Increasing the frequency of the wind input (from 6 h to 3 h) improved the estimation of the maximum wave height values (peaks) of the storm about 13%. Summarizing, the results of this work indicated that tackling wind and wave gradients in complex regions such as the study area it is posible to reduce the under-estimation of wave parameters and to improve wave forecasting.<br>L’objectiu principal d’aquest estudi és millorar les prediccions de l’onatge generat pel vent al Mediterrani Noroccidental enfocant-se en els forts gradients de vent i d’onatge característics de la zona. Aquest treball sorgeix de la falta d’exactitud dels models d’onatges en conques semi tancades i en condicions de vent controlades per l’orografia, especialment durant temporals d’onatge limitats pel ‘fetch’. En primer lloc, per tal reduir les sub-estimacions dels parametres de l’onatge, s’ha caracteritzat la variabilitat dels camps de vent i d’onatge tant en temps (entre 1 h i un 1 dia) com en espai (entre 10 i 100 km). En segon lloc, per tal de capturar els forts gradients típics de la zona en els models numèrics d’onatge, durant un temporal característic s’ha reduit el tamany de malla dels vents d’entrada al model de 18 km a 4 km i s’ha augmentat la freqüència d’entrada dels vents de 6 h a 1 h. En tercer i últim lloc, s’ha ajustat la tasa de creixement de l’onatge en els models numèrics d’acord amb la tasa de creixement obtinguda a partir d’observacions locals. La tasa de creixement a la zona d’estudi, que s’ha calculat utilitzant mesures al llag del fetch, ha resultat ser més rápida que la predita utilitzant les parametritzacions incorporades per defecte en els models, i més rápida que les tases obtingudes en experiments anteriors. El fet d’ajustar la tasa de creixement en el model d’onatge ha permès millorar un 18% l’alçada d’ona significant estimada i un 4 % la freqüència de pic de l’onatge. Reduir el tamany de malla dels vents d’entrada de 12 km a 4 km ha permès millorar l’estimació en el temps dels pics d’onatge, però no els valors màxims del temporal. En canvi, augmentar la freqüència dels vents d’entrada (de 6 h a 3 h) ha millorat un 13% l’estimació dels valors màxims d’alçada d’ona durant el temporal. En resum, els resultats d’aquest treball indiquen que abordant els gradients de vent i onatge en regions complexes és posible reduir la sub-estimació dels paràmetres de l’onatge i millorar-ne la seva predicció.<br>El objetivo principal de este estudio es mejorar las predicciones del oleaje generado por el viento en el Mediterráneo Noroccidental enfocando los fuertes gradientes de viento y oleaje característicos de la zona. Este trabajo surge de la falta de exactitud de los modelos de oleaje en cuencas semi-cerradas y en condiciones de viento controladas por la orografía, especialmente durante temporales de oleaje limitados por el ‘fetch’. En primer lugar, para reducir las sub-estimaciones de los parámetros del oleaje, se caracterizó la variabilidad de los campos de viento y oleaje tanto en tiempo (entre 1 h y un 1 día) como en espacio (entre 10 y 100 km). En segundo lugar, para capturar los fuertes gradientes típicos de la zona en los modelos numéricos de oleaje, para un temporal característico, se redujo el tamaño de malla de los vientos de entrada al modelo de 18 km a 4 km y se aumentó la frecuencia de entrada de los vientos de 6 h a 1 h. En tercer y último lugar, se ajustó la tasa de crecimiento del oleaje en los modelos numéricos de acuerdo a la tasa de crecimiento obtenida a partir de observaciones locales. La tasa de crecimiento en la zona de estudio, que se calculó usando medidas de viento y oleaje a lo largo del fetch, resultó ser más rápida que la predicha utilizando las parametrizaciones incorporadas por defecto en los modelos, i más rápida que les tases obtenidas en experimentos anteriores. El hecho de ajustar la tasa de crecimiento en el modelo de oleaje permitió mejorar un 18% la altura de ola significante estimada y un 4 % la frecuencia de pico del oleaje. Reducir el tamaño de malla de los vientos de entrada de 12 km a 4 km permitió mejorar la estimación en el tiempo de los picos de oleaje, pero no los valores máximos del temporal. En cambio, aumentar la frecuencia de los vientos de entrada (de 6 h a 3 h) ha mejorado un 13% la estimación de los valores máximos de altura de ola durante el temporal. En resumen, los resultados de este trabajo indican que abordando los gradientes de viento y oleaje en regiones complejas se reduce la subestimación de los parámetros del oleaje y se mejora su predicción.

The variability of the nearshore wave climate is investigated via the analysis of over 10 years of Acoustic Doppler Current Profiler (ADCP) data from a gauge deployed at Melbourne Beach, FL. Examples of large yearly variability in the significant wave height, peak period, mean direction and energy distribution are found in the data. Estimates of the averaged spectra for the entire record show that the average wave energy is distributed almost symmetrically with the peak being close to shore-normal. It was expected that the peak would be shifted towards the north of shore-normal considering net north to south longshore sediment transport at this location. Further analysis of the directional spectra partitioned into three directional windows reveals that waves from the southeast (avg. Hmo = 0.78 m) are less energetic than those from the northeast (avg. Hmo = 0.87 m), but they arrive from the south 53% more often. Additionally, energy-based significant wave height (Hmo), peak period (Tp) and mean period (Tmean) distributions are studied and modeled with notable success. Radiation stress (Sxy) estimates are computed using both rigorous integration as well as parameter-based approximations. These two estimates are correlated but the parameter-based approximation over predicts Sxy by 42%, because this method assigns all the wave energy into one direction (Ruessink et al., 2001). Finally, it is shown by the Sxy total average that the net longshore forcing at this location is indeed north to south, but yearly and seasonal variability were quite high. The results indicate that short-term wave records may not provide accurate information for planning purposes. For example, if only 3 months of data were collected at this site, there would be a 33% chance that the mean longshore forcing would be erroneously directed from south to north.

Using modern methods of share quotations forecasting is the main goal of this thesis. The special accent is placed on forecasting the trend by means of artificial neural network especially on the optimalization of variables in the training process. Elliot's wave theory is applied in the second part of the thesis, particularly on prediction of future share quotation progress. Buying or selling signal generated by these two methods is consequently compared with ex-post signal yielding a profit. Lastly, successfulness of using these methods for forecasting at stock market is evaluated.

A numerical procedure based upon a boundary integral method for gravity wave making problems is studied in the time domain. The free-surface boundary conditions are combined and expressed in a Lagrangian notation to follow the free-surface particle's motion in time. The corresponding material derivative term is approximated by a finite difference expression, and the velocity terms are extrapolated in time for the completion of the formulations. The fluid-body intersection position at the free surface is predicted by an interpolation function that requires information from both the free surface and the submerged surface conditions. Solutions corresponding to a linear free-surface condition and to a non-linear free-surface condition are obtained at small time increment values. Numerical modelling of surface wave problems is studied in two dimensions and in three dimensions. Comparisons are made to linear analytical solutions as well as to published experimental results. Good agreement between the numerical solutions and measured values is found. For the modelling of a three dimensional wave diffraction problem, results at high wave amplitude are restricted because of the use of quadrilateral elements. The near cylinder region of the free surface is not considered to be well represented because of the coarse element size. Wave forces calculated on the vertical cylinder are found to be affected by the modelled tank length. When the simulated wave length is comparable to the wave tank's dimension, numerical results are found to be less than the experimental measurements. However, when the wave length is shorter than the tank's length, solutions are obtained with very good precision.<br>Applied Science, Faculty of<br>Mechanical Engineering, Department of<br>Graduate

Nonlinear four-wave interactions (Snl) are critical for acquiring realistic spectra needed by operational wave models. High computational demand to calculate these interactions led to an approximation method named the Discrete Interaction Approximation (DIA) to be used broadly in the major operational wave models for a long time. However, the accuracy of the DIA has been controversial since it was first introduced and more precise approximations such as the Two Scale Approximation (TSA in short) are now available. The only issue with the initial TSA`s efficiency is performing an order of a magnitude slower than the DIA in speed. This study questions the exactness of the DIA while trying to increase the competence of the TSA by making improvements on its execution time. Particularly, in this thesis, the main effort is on the local scale term of the TSA since it is the part that consumes the most time while running the code. The findings of this work imply that the TSA can improve its operation speed significantly while maintaining its accuracy with making alterations in the code. By decreasing the number of bands in the local scale it is possible to run the TSA up to 7.5 faster than its initial version.

The dominant natural electromagnetic (EM) radiation in the extremely low frequency (ELF) range is due to global lightning activity. Radio waves of ELF band traveling along the surface of the ground are able to circle the globe and return to the starting point. Schumann Resonances (SR) are the EM phenomena which occur in the cavity formed by the conducting Earth and the ionosphere, with peak frequencies close to 8, 14, 20, 26 Hz, etc. The spectral characteristics of the SR modes are defined by their resonant mode amplitudes, center frequencies and half-widths. The characteristics of the SR became important in aerospace, marine applications, atmospheric studies, in addition to their relevance to global lightning studies due to their frequency band. The objective of this work is two fold: (i) to investigate the characteristics of SR parameters obtained at Sarkoy in Turkey<br>(ii) to model the nonlinear characteristics of the Near Earth Space Processes by forecasting the 1st SR mode intensities different time steps in advance using neural network modeling approach. The results show that the SR amplitudes exhibit the characteristics of Tropical African lightning activity and have maxima around 1400 UT. The neural network results show that the proposed model is able to forecast SR amplitudes from 0,5 to 36 hours in advance within reasonable error limits. Furthermore, a fuzzy neural network model with a non&ndash<br>linear optimization algorithm for the training phase is proposed and tested for the future work.

Thesis (M.E.E.)--University of Delaware, 2006.<br>Principal faculty advisors: Kenneth E. Barner, Dept. of Electrical and Computer Engineering; and Mohsen Badiey, Dept. of Marine and Earth Studies. Includes bibliographical references.

La localisation des seismes enregistres permet de mettre en evidence une fracture crustale majeure, situee a la bordure nord de la haute chaine et qui pourrait correspondre a la suture des plaques europe et iberie. L'etude des mecanismes au foyer et les resultats de la geodesie montrent une elevation de la haute chaine par rapport a l'avant pays nord. L'examen des parametres de la source montre l'heterogeneite de l'etat de contrainte a la surface de la faille sismique. L'etude de l'attenuation des ondes sismiques ne revele pas de variation du facteur de qualite du milieu liee a l'activite sismique. Ces resultats permettraient de progresser dans les domaines de la sismogenese et de la prevision sismique dans les regions de sismicite moyenne

In Folge der Osterweiterung der europäischen Union (EU) und der steigenden Arbeitsmarktintegration zwischen den EU15 und den neuen Mitgliedsstaaten ist die Lohnfindung in Mittel- und Osteuropa zu einem Schwerpunkt der europäischer Wirtschaftspolitik geworden. Zugleich wird das optimale Wechselkursregime für mittel- und osteuropäische Staaten kontrovers diskutiert. Die Dissertation befasst sich mit der Fragestellung, welche Wechselkursstrategie in Mittel- und Osteuropa vorzuziehen ist, um zum einen den Lohnfindungsprozess zu optimieren und zum anderen den Anpassungsprozess (Konvergenzprozess) an europäische Lohnstandards zu beschleunigen. Diese kumulierte Arbeit besteht aus vier unabhängigen Fachaufsätzen. Zuerst wird der Frage nachgegangen, welche Wechselkursstrategie einen optimalen Rahmen für die Lohnsetzung während des Aufholprozesses mittel- und osteuropäischer Staaten ermöglicht (Kapitel zwei). Im Kapitel drei wird die Rolle der Geldpolitik in Bezug auf die Lohnfindung in Staaten mit flexiblen Wechselkursen untersucht. Die Evaluierung der Prognosefähigkeit alternativer Konjunkturindikatoren für die Euro Zone sowie deren Implikationen für den Lohnverhandlungsprozess in Mittel-und Osteuropa ist Gegenstand der Analyse in Kapitel vier. Im fünften Kapitel wird der Rolle der Lohnpolitik auf Leistungsbilanz(un)gleichgewichte in Mittel- und Osteuropa nachgegangen<br>After the Eastern enlargement of the European Union (EU) and increasing participation of labor between the EU15 and the new member states, wage determination in Central and Eastern Europe (CEE) has become a key issue in European economic policy making. At the same time there are controversial discussions regarding the appropriate exchange rate regime for the CEE countries. In this thesis it is examined which exchange rate strategy provides a more favorable framework for wage setting in CEE and leads to faster wage convergence in Europe. This thesis has four parts. First, it is analyzed which exchange rate strategy provides a more favorable framework for wage setting during the economic catch-up process of CEE (section two). Second, the role of monetary policy in wage determination in countries with flexible exchange rate regimes is examined in section three. Third, the predictive power of different euro area business cycle indicators is analyzed in section four. Fourth, the impact of wage determination on the balance of payments in CEE is scrutinized (section five)

The action of sea storms is one of the most complex littoral processes with deep management implications. Along the Catalan shoreline which is about 700 km long, 190 km are subject to erosion and/or flooding. Around one million people live in areas potentially affected. Sea Level Rise could exacerbate this problem in the near future. Reactive interventions have been the norm in coastal engineering and management. This dissertation proposes a pre-storm strategy that foster cost-effective eco-compatible measures, termed Quick Defence Measures (QDM). Pre-storm intervention requires to forecast the future post-storm state. Hence, the main objective of this thesis is to assess present coastal risk through a Coastal Early Warning System (CEWS), termed LIM-COPAS, that forecasts the more relevant episodic coastal hazards at the area. LIM-COPAS consists of four modules: (i) meteorological model; (ii) wave generation/propagation code; (iii) coupled morpho-hydrodynamic model and (iv) risk module via non-stationary multivariate probabilistic models. The performance of this suite of models has been tested with (i) a set of hindcast events and (ii) synthetic storm conditions. The hindcasted events have been: December 2008 (D-08); October-2015 (O-15); November 2015 (N-15); January 2016 (J-16); February 2016 (F-16); December 2016 (D-16) and January 2017 (J-17). In D-08, errors in nearshore spectral wave parameters have been about twice than those in the offshore area. The error was around 20% in hydrodynamics and 50% in morphodynamics. The post-storm response has been acceptably reproduced, with a Brier Skill Score near 0.4. LIM-COPAS has shown good accuracy with high return period events (i.e. Tr,waves > 10 yrs, D-16 and J-17), but lower agreement was found for milder storms (i.e. O-15 and F-16). The meteorological module provided wind fields that were systematically overestimated. The integrated Mean Bias (MB) was -1.52 ± 0.78 m/s. Tarragona (Coefficient of Efficiency, COE = 0.27 ± 0.13) and Begur (COE = 0.29 ± 0.17) had metrics above the average value (COE = 0.24 ± 0.14); but lower agreement was found at Mahón (COE = 0.13 ± 0.16) and Dragonera. Wave metrics were more accurate than for the wind fields. The integrated Hs COE was 0.52±0.12 and Tm02 COE was 0.36±0.14. At the central coast, Hs has presented good metrics: low MB (-0.06 ± 0.08 m) and high COE (0.58 ± 0.11). The northern coast metrics were the most stable. The newly developed risk module has been implemented at 79 beaches. Erosion has been estimated as a bounded cost, whereas flooding as a high upside cost. Dissipative beaches tend to exhibit higher costs than reflective beaches under high sea levels. Tr,waves < 10 yrs events joint with storm-surges can lead to significant damage costs. The estimated losses for the N-15 event (2510·10^3 euros) do not differ excessively from J-17 (3200·10^3 euros). Two types of QDM have been numerically tested: (i) sand dunes and (ii) geotextile detached breakwaters. The benefits from maintaining the sand volumes outperform the flooding cost reduction. In general terms, the detached breakwater can be a suitable option for beaches in an intermediate morphodynamic state against low to moderate sea levels and high wave return periods. At dissipative beaches, dunes are the best option, but they require a minimum beach width (around 30 m) that ensures their lifetime. QDM functionality can be enhanced with compatible long-term actions (nourishments, sand bypasses, submerged vegetation, etc.). A healthy beach state is paramount for the QDM effectiveness. A higher sustainable management under present and future climate can be reached with the joint combination of (i) CEWS as a short-term forecasting tool; (ii) QDM that mitigate storm impacts and (iii) long-term interventions that improves the beach health.<br>La acción de los temporales de mar es uno de los procesos litorales más complejos, con profundas implicaciones en la gestión del litoral. A lo largo de la línea de costa catalana, 190 km están sometidos a erosión y/o inundación. Cerca de un millón de personas viven en áreas potencialmente afectadas. La tradición en ingeniería y gestión costera han sido intervenciones reactivas. Esta tesis propone una estrategia pre-tormenta que fomente una serie de medidas eco-compatibles, denominadas Medidas de Acción Rápida (MAR). Las intervenciones pre-tormenta requieren predecir el estado post-temporal de la costa. Por tanto, el principal objetivo de esta tesis es evaluar el riesgo costero episódico mediante un Sistema de Alarma Temprana Costero (CEWS), denominado LIM-COPAS, que predice las peligrosidades costeras más relevantes en dicha área. LIM-COPAS consiste de cuatro módulos: (i) modelo meteorológico; (ii) código de generación/propagación del oleaje; (iii) modelo acoplado morfo-hidrodinámico y (iv) un módulo de riesgo vía modelos probabilísticos multivariantes y no-estacionarios. El comportamiento de estos módulos ha sido analizado mediante (i) una serie de eventos pasados y (ii) temporales sintéticos. Los eventos pasados han sido: Diciembre 2008 (D-08); Octubre 2015 (O-15); Noviembre 2015 (N-15); Enero 2016 (J-16); Febrero 2016 (F-16); Diciembre 2016 (D-16) y Enero 2017 (J-17). En D-08, los errores en los parámetros espectrales de oleaje costero han sido casi el doble que en mar abierto. El error ha sido del 20% en la hidrodinámica y del 50% en la morfodinámica. La respuesta post-temporal ha sido reproducida aceptablemente, con Brier Skill Score cercanos a 0.4. LIM-COPAS ha demostrado buena precisión con tormentas de alto período de retorno (i.e. Tr,waves _ 10 yrs, D-16 y J-17), pero menor concordancia fue encontrada para las tormentas moderadas (i.e. O-15 y F-16). El módulo meteorológico estimó campos de viento que fueron sistemáticamente sobreestimados. El Sesgo Medio (MB) integrado fue de −1,52 ± 0,78 m/s. Tarragona (Coeficiente de Eficiencia, COE = 0,27±0,13) y Begur (COE = 0,29±0,17) tuvieron métricas por encima de la media (COE = 0,24±0,14); no obstante, peor ajuste se encontró en Mahón (COE = 0,13 ± 0,16) y Dragonera. Las métricas de oleaje fueron más precisas que las del viento. Hs COE integrada fue 0,52±0,12 y Tm02 COE fue 0,36±0,14. En la costa central, Hs presentó buenas métricas: bajo MB (−0,06 ± 0,08 m) y alto COE (0,58 ± 0,11). Las métricas en la costa norte fueron las más estables. El módulo de riesgo ha sido implementado en 79 playas. La erosión se ha estimado como un coste acotado, mientras que la inundación como un coste con alta cota superior. Las playas disipativas tienden a exhibir mayores costes que las playas reflejantes bajo altos niveles del mar. Episodios con Tr,waves _ 10yrs, concomitantes a mareas meteorológicas pueden conllevar costes significantes. Las pérdidas estimadas para N-15 (2510 · 103euros) no difieren en exceso de J-17 (3200 · 103 euros). Dos tipos de MAR han sido testeadas numéricamente: (i) dunas y (ii) diques exentos constituídos por geotextiles llenos de arena. Los beneficios de mantener estables los volúmenes de arena superan la reducción de los costes por inundación. En términos generales, los diques exentos pueden ser una opción adecuada para playas de estado morfodinámico intermedio frente a oleaje de alto período de retorno y niveles del mar bajos a moderados. En playas disipativas, las dunas son la mejor opción, pero requieren un ancho mínimo de playa (cerca de 30 m) que garantice su vida útil. La funcionalidad de las MAR puede mejorarse mediante acciones compatibles a largo-plazo (alimentaciones, bypass de arena, vegetación sumergida, etc.). Un estado de playa saludable es esencial para la efectividad de las MAR. Una gestión más sostenible bajo clima presente y futuro puede ser alcanzada mediante (i) CEWS como herramienta de predicción a corto plazo; (ii) MAR que mitiguen los impactos de los temporales y (iii) intervenciones a largo-plazo que mejoren la salud de la costa.

This thesis examines the measurement, applications and properties of consumer inflation expectations in the context of eight European Union countries: France, Germany, the UK, Spain, Italy, Belgium, the Netherlands and Sweden. The data proceed mainly from the European Commission's Consumer Survey and are qualitative in nature, therefore requiring quantification prior to use. This study first seeks to determine the optimal quantification methodology among a set of approaches spanning three traditions, associated with Carlson-Parkin (1975), Pesaran (1984) and Seitz (1988). The success of a quantification methodology is assessed on the basis of its ability to match quantitative expectations data and on its behaviour in an important economic application, namely the modelling of wages for our sample countries. The wage equation developed here draws on the theoretical background of the staggered contracts and the wage bargaining literature, and controls carefully for inflation expectations and institutional variables. The Carlson-Parkin variation proposed in Curto Millet (2004) was found to be the most satisfactory. This being established, the wage equations are used to test the hypothesis that the advent of EMU generated an increase in labour market flexibility, which would be reflected in structural breaks. The hypothesis is essentially rejected. Finally, the properties of inflation expectations and perceptions themselves are examined, especially in the context of EMU. Both the rational expectations and rational perceptions hypotheses are rejected. Popular expectations mechanisms, such as the "rule-of-thumb" model or Akerlof et al.'s (2000) "near-rationality hypothesis" are similarly unsupported. On the other hand, evidence is found for the transmission of expert forecasts to consumer expectations in the case of the UK, as in Carroll's (2003) model. The distribution of consumer expectations and perceptions is also considered, showing a tendency for gradual (as in Mankiw and Reis, 2002) but non-rational adjustment. Expectations formation is further shown to have important qualitative features.

碩士<br>國立中興大學<br>土木工程學系<br>86<br>Accurate prediction for the wave climate is an essential part in the ocean engineering. This paper reports an application of the artificial neural network for accurate forecast of waves from a time series of the field data. This paper also presents the wave supplementary for a wave record using the neural network model. The back-propagation procedures for minimizing the error of the desired output is used in the learning process of the neural network. The field data measured in three wave stations at Taichung Harbor were used to test theperformance of the neural network model. The wave prediction from the time series of one wave stationor two wave stations is presented. It is found that the neural network model performs well for the waveforecast and wave supplementary when a very short-term wave data is used as a training set. In general, the wave prediction or wave supplementaryfrom the time series of two wave stations has betterperformance than one wave station records used. It is also found that the performance of theprediction of significant wave heights isbetter than that of wave periods.

This thesis contains a manuscript describing the implementation of a high resolution wave forecasting model for the coasts of Washington and Oregon. The purpose of this project was to advance the wave predictive capabilities of the states of Oregon and the southwest part of Washington by including the effects of local bathymetric features in the operational forecasts. A 30 arc-second resolution wave forecasting model was implemented making use of the WAVEWATCH III numerical code covering the coastal region from Klamath, CA to Taholah, WA. The wave forecasts extend to the continental shelf at this resolution. To assess the performance of the model, its output was compared against in situ data, with normalized root-mean-squared errors in significant wave height in the vicinity of 0.20 and linear correlation coefficients greater than 0.80. Making use of the resulting validated regional scale wave forecasting system, an evaluation of the model sensitivity to the inclusion of bottom friction and wind input at the shelf level was performed. Results suggest that neither dissipation due to bottom friction or wind generation are significant for long term forecasting/hindcasting in the region. Results from a series of hindcasts suggest that several significant offshore features may affect the nearshore wave field. To evaluate it, a shelf scale SWAN model was implemented and a series of numerical experiments performed. Results suggest that the Astoria and McArthur Canyons; the Stonewall, Perpetua, and Heceta Banks; and Cape Blanco are significant bathymetric features that are capable of producing significant alongshore variability in wave heights nearshore.<br>Graduation date: 2013

碩士<br>國立成功大學<br>水利及海洋工程學系專班<br>96<br>Wave is one of the natural forces and will affect human’s activities in the ocean such as sailing, leisurely movements, offshore engineering, disaster rescuing and military training. Reasonable accuracy wave forecasting data should do great help for all kind of marine activities. The hydrological data of wave height as well as period, wind speed and direction collected by the data buoy in Dapeng Bay and Little-Liouciou are used to be input variables to set up the GMDH wave height forecasting model. Trail and error procedure provided first to determine input variables and sums for the best model fitting. The SGMDH process then introduced to improve the ill condition of high rank nonlinear terms which is derived through the self-organizing multilayer algorithm of GMDH structure. The optimum wave height forecasting model could be constructed after the calibrate step to revised the time lag between simulated and measured results. In addition, model parameters could be modified by the stepwise regression algorithm using the update data and threshold to achieve the purpose of self-regulating, long term and time variable wave height accurate forecasting. The trend of forecasting wave height series were in agreement with measuring materials of the data buoy in this research. The maximum and minimum error between forecasting and measuring data of Dapeng Bay data buoy are 21.66~3.89cm and 0.19~0.01cm respectively and have an average error of 4.96~1.22cm. As to Little-Liouciou data buoy, its maximum and minimum error are 12.46~1.23cm and 0.10~0.01cm respectively and get an average error of 3.13~0.74cm. So, the GMDH forecasting model proposed by this paper is in conformity with the requirement of forecasting and could be applied in practical usage for wave height prediction at the specified location.

碩士<br>國立成功大學<br>國際管理碩士在職專班<br>97<br>Two theories are compared, Efficient Market Hypothesis (EMH) and Elliot Wave Theory (EWT), using qualitative analysis in the form of a direct comparison and technical analysis in the form of chart analysis. Classical economic theory and its leading proponent Efficient Market Hypothesis EMH represent the status quo and the idea of rational decision making in financial markets, while Elliot Wave Theory represents the idea of mass irrational behavior which is somewhat predictable. These two theoretical extremes represent contrasting views of how finance markets work. Crude oil is the chosen medium through which these two theories are compared. The comparison is made within the framework of gleaning useful trading and investing advice for an amateur with limited resources. The results do not indicate a clear cut winner, but offers insight into the strengths and weaknesses of either theory, and how an amateur could benefit.

碩士<br>國立雲林科技大學<br>資訊管理系碩士班<br>95<br>In stock markets, investors forecast the future price trend based on open data such as past trading data, market news and financial reports. What they care about most is to make accurate predictions to bring profit for them. Therefore, they are absorbed in lifting forecasting accuracy for stock markets. Fuzzy time-series models have been utilized to forecast the number of enrollment, the height of temperature and stock price patterns since they are first induced by Song and Chissom in 1993. However, from literature, there are two major drawbacks of traditional methods such as the lack of consideration in determining reasonable universe of discourse and the length of intervals. Besides, it is clear to see that the past researchers lacked stock technical analysis theories for supporting their models. Hence, we provide the Elliot’s Wave Principle as the theory base for our forecast model. Furthermore, we consider the relation between price and volume in the proposed model to forecast stock price because it is usually ignored in past researchers. Therefore, we survey the technical indicators of volume and choose the volume ratio, VR, to modify the forecasting values. In order to solve these problems above, an objective and reasonable approach is then proposed. Traditional forecasting models forecast stock price based on singular price indicator, lacking other factors such as volume indicators, so it is not thoughtful enough to forecast stock price. We propose a wave principle based fuzzy bi-time series model to improve the forecast accuracy, and apply three parameters, alpha, beta and gamma, to refine our forecast model. And set some criteria in order to make trading possible. Using the TAIEX (Taiwan stock index) and NASDAQ (a worldwide famous high-tech industries integrated index in America) as the forecasting datasets, the empirical results show that the proposed model outperforms other conventional models.

碩士<br>國立成功大學<br>水利及海洋工程學系碩博士班<br>91<br>The Objective Analysis, which is widely implemented in routine weather forecsting, is utilized in present study to predict typhoon waves around Taiwan. In order to establish the statistical model, large amount information of historical typhoon waves, which were obtained by observations and numerical model simulations, have been adopted. Due to the following facts that the typhoon wind fields features the nature of highly temporal and spatial variation, and that the typhoon wave filed is largely influenced by the evolution of typhoon swells, the Hybrid Wave Model proposed by Wen(1999) is utilized in present study to simulate the typhoon waves. Concerning to the input of the wave model, the predicted wind field is calculated using Lee(1993)’s formula, which were derived based on Ekman theory. The predicted wind direction and wind speed at the elevation of 10 m could thus be estimated from the forecasting barometric field, which is provided by Central Weather Bureau every twelve hours. As the barometric data issued with time interval of 12 hours, details of the fast moving typhoon might not be conserved. For the sake to obtain accurate interpolation of barometric for single hour estimation, an new interpolation method is proposed in present study. The method entitled as Shift Linear Interpolation, is proved to be capable of eliminating the unreasonable results of using tradictional linear interpolation, such as the appearance of two typhoon eyes. Finally, the statistical model established using objective analysis is validated by observed typhoon wave. The results demonstrate the effective of present model. The present typhoon wave forecasting model is easy to be implemented. It is useful for engineering applications when there is no numerical wind field available and providing typhoon wave forecast for a specific site in the offshore or coastal regions is necessary.

碩士<br>國立屏東科技大學<br>土木工程系碩士班<br>91<br>Variation of tidal levels has a significant influence on the living pattern and construction development along the costal region, and thus the prediction of tidal levels varied with time may become very useful in the design and an engineering project. The main purpose of this study, at first, was by using Visual Basic language to arrange the time history (1971-2002) tidal recorded data at Kaohsiung harbor, the largest harbor in Taiwan. From visualized software design, the variation of tidal levels can be seen more clearly and regarding the completeness of recording data can be detected more easily. In the next, the present study was focused on the training of a completed observation data set in the year 2000, with the use of harmonic tidal equations, to predict short-term and long-term tidal levels by back-propagation neural networks and genetic algorithm, which could be found popularly in artificial intelligence applications. The comparison results showed that the neural networks have a better performance than that of genetic algorithm in this type of problem. Meanwhile, from various combinations of input layer, hidden layer and output layer in neural networks, a relatively better model was obtained for further analysis including monthly and seasonly predictions. The analyzed results exhibited that the neural networks model did have the ability to predict the tidal levels varied with time with a moderately accuracy. The obtained information might provide a good reference for the relatively engineering design in the investigation area.

碩士<br>國立成功大學<br>高階管理碩士在職專班(EMBA)<br>100<br>Trends and forecasts of a variety of parameters in the ocean are very important to marine management. This study gathers data of wave heights of Suao buoy which is located in the coastal area of Ilan Long De Lize Industrial Park from 2000 to 2011. This study converts data into information for marine management by utilizing the methodology of time series analysis and forecasting of statistics. The ADF test is utilized to analyze stationary and trends. ARMA(1,1), ARMA(2,2), ARIMA(2,1,1), ARIMA(2,1,2) and ARIMA(1,2,1) models are established and tested. Series of wave heights are transformed by Napierian logarithm before fitting ARMA(2,2) and ARIMA(2,1,2) models. Data are sampled by different ways and used to validate hypotheses of this study. Based on results of the ADF test, it shows that: First, both series of maxima of month and of typhoon are stationary. Secondly, series of annual maxima and averages of significant wave heights are non-stationary. There is no deterministic trend for the non-stationary series. The non-stationary is due to the stochastic trend. In addition, according to results of different ways of sampling, whether the series is stationary or not is also infected by the sampling ways. Based on analytical results of forecasting models, it shows that: First, the series of daily maxima of significant wave heights is stationary. Transformed series of annual maxima and averages are stationary too. Secondly, Both ARMA(1,1) and ARMA(2,2) models are not so suitable for untransformed and transformed series of daily maxima of significant wave heights of 2009. ARIMA(2,1,1) and ARIMA(2,1,2) model are suitable for untransformed and transformed series of annual averages of wave heights of 2000-2011. ARIMA(2,1,1) model is better than ARIMA(2,1,2) model. ARIMA(1,2,1) and ARMA(2,2) model are suitable for untransformed and transformed series of annual maxima of wave heights of 2000-2011. ARMA(2,2) model is better than ARIMA(1,2,1) model. In addition, series sampled by different ways is fitted by different model. Sampled wave heights data do not fit ARMA(1,1) well which is utilized by Agrawal ＆ Deo(2002). Transformed annual maximum wave heights fit ARMA(2,2) well which is used by Stefanakos(1999). Trend and forecast of waves is helpful to oil and electricity industries directly. These information may minify loss. It’s necessary for managers of industries located in coastal industrial parks to be aware of risk from natural hazards and to prevent them as more as possible. Managers have to minify loss from these hazards in order to increase profit.

碩士<br>國立成功大學<br>水利及海洋工程學系<br>103<br>A forecasting model of near shore typhoon wave height developed as a alternative is proposed in this paper by the self-organizing GMDH (Group Method of Data Handling) algorithm with 4 parameters of wave height(H), wind speed(V), distance(L) and azimuth (θ) between the target location and typhoon center. Data of these 4 parameters/ variables observed at Hsin Chu and Long Dong data buoys as well as obtained from CWB could be used to calibrated, verified and construct the prior 1~ 6hrs near shore typhoon wave height forecasting model with 15 typhoon events data during 2006 to 2009 to provide the necessity of typhoon warning facility. A recursive GMDH model could be reorganized by using the update data to match the time variant properties in forecasting steps to improve the forecasting accuracy. Data supplementation model could be set up by the OTE(Ocean Tide Efficiency) concept and EMD(Empirical Mode Decomposition) technique and tested by the measured and acquired ADCP data of Taoyuan Yon An/Hsinchu Long Fung and Hsin Chu data buoy for lost its total 1/3,1/4 and 1/6 of monsoon wave height data. Typhoon wave height lost data supplementation is tested also with Hsin Chu and Long Dong data buoy’s data of 6 typhoon events for missed its total 1/3,1/2 and 2/3 of typhoon wave data by the same method. Prior 1~6hr typhoon wave height forecasting results show that the average RMSE, CC and error scale ratio are in between 20.0~47.8cm, 79.4~93.6% and 11.5~23.4%. Monsoon wave height missed data supplement results reveal that the average RMSE, CC and error scale ratio are in between 10.5~20.2cm, 78.1~ 87.7%, and 15.6~20.1% respectively, and typhoon wave height lost data supplement results reveal that the average RMSE, CC and error scale ratio are 53.4cm, 70.2%, and 23.6% by the EMD technique.

碩士<br>國立中興大學<br>土木工程學系<br>90<br>Due to the complexity and randomness of the wind waves, the prediction of waves based on the simplified relationship may obtain substantial error. This study attempts to predict the wind waves by applying the technique of an artificial neural network (ANN), in which the supervised learning models with back-propagation scheme is adopted. The ANN estimates the interconnection weights between the waves and the corresponding wind speeds by training the past records. The topology of the selection of the neurons of input, outputs and the hidden layers is discussed in detail in the study. Using long-term wind and wave data from one of the National Data Buoy Center (NDBC) buoy stations in the Pacific Ocean, this study examined the validity and accuracy of the ANN model. It is found that the six-hourly average significant wave height and the six-hourly maximum significant wave height can be predicted from training the previous eighteen hours data of waves and wind speeds. The results show that the neural network model can well predict a five-days to fifteen-days of waves using a previous 20-days’ records.

<div><br></div><div>Extreme heat is one of the deadliest health hazards that is projected to increase in intensity and persistence in the near future. Temperatures are further exacerbated in the urban areas due to the Urban Heat Island (UHI) effect resulting in increased heat-related mortality and morbidity. However, the spatial distribution of urban temperatures is highly heterogeneous. As a result, metrics such as UHI Intensity that quantify the difference between the average urban and non-urban air temperatures, often fail to characterize this spatial and temporal heterogeneity. My objective in this thesis is to understand and characterize the spatio-temporal dynamics of UHI for cities across the world. This has several applications, such as targeted heat mitigation, energy load estimation, and neighborhood-level vulnerability estimation.</div><div><br></div><div>Towards this end, I have developed a novel multi-scale framework of identifying emerging heat clusters at various percentile-based thermal thresholds T_thr and refer to them collectively as <i>intra-Urban Heat Islets</i>. Using the Land Surface Temperatures from Landsat for 78 cities representative of the global diversity, I have showed that the heat islets have a fractal spatial structure. They display properties analogous to that of a percolating system as T_thr varies. At the percolation threshold, the size distribution of these islets in all cities follows a power-law, with a scaling exponent = 1.88 and an aggregated Area-Perimeter Fractal Dimension =1.33. This commonality indicates that despite the diversity in urban form and function across the world, the urban temperature patterns are different realizations with the same aggregated statistical properties. In addition, analogous to the UHI Intensity, the mean islet intensity, i.e., the difference between mean islet temperature and thermal threshold, is estimated for each islet, and their distribution follows an exponential curve. This allows for a single metric (exponential rate parameter) to serve as a comprehensive measure of thermal heterogeneity and improve upon the traditional UHI Intensity as a bulk metric.</div><div><br></div><div><br></div><div>To study the impact of urban form on the heat islet characteristics, I have introduced a novel lacunarity-based metric, which quantifies the degree of compactness of the heat islets. I have shown that while the UHIs have similar fractal structure at their respective percolation threshold, differences across cities emerge when we shift the focus to the hottest islets (T_thr = 90^th percentile). Analysis of heat islets' size distribution demonstrates the emergence of two classes where the dense cities maintain a power law, whereas the sprawling cities show an exponential deviation at higher thresholds. This indicates a significantly reduced probability of encountering large heat islets for sprawling cities. In contrast, analysis of heat islet intensity distributions indicates that while a sprawling configuration is favorable for reducing the mean Surface UHI Intensity of a city, for the same mean, it also results in higher local thermal extremes. </div><div><br></div><div>Lastly, I have examined the impact of external forcings such as heatwaves (HW) on the heat islet characteristics. As a case study, the European heatwave of 2018 is simulated using the Weather Research Forecast model with a focus on Paris. My results indicate that the UHI Intensity under this HW reduces during night time by 1^oC on average. A surface energy budget analysis reveals that this is due to drier and hotter rural background temperatures during the HW period.</div><div>To analyze the response of heat islets at every spatial scale, power spectral density analysis is done. The results show that large contiguous heat islets (city-scale) persist throughout the day during a HW, whereas the smaller islets (neighborhood-scale) display a diurnal variability that is the same as non-HW conditions. </div><div><br></div><div>In conclusion, I have presented a new viewpoint of the UHI as an archipelago of intra-urban heat islets. Along the way, I have introduced several properties that enable a seamless comparison of thermal heterogeneity across diverse cities as well as under diverse climatic conditions. This thesis is a step towards a comprehensive characterization of heat from the spatial scales of an urban block to a megalopolis.</div><div><br></div>

碩士<br>國立成功大學<br>水利及海洋工程學系碩博士班<br>100<br>Swell and wind wave, as well as the southwest air current, induced by typhoons moving around Taiwan in summer influence severely the near shore structures and marine environment. Therefore, it is important to discuss the mechanism of typhoon wave’s deforming process while typhoon is moving on surroundings and to develop the typhoon wave height forecasting model to meet the requirement of disaster prevention during the typhoon season. A forecasting model of typhoon wave height developed by the GMDH (Group Method of Data Handling) structure of Self-Organization Algorithm with four parameters of wave height (H), wind speed (V), distance (L) and azimuth (θ) between the target location and typhoon center is proposed in this paper. Data of these 4 parameters observed at Hsin Chu data buoy and obtained from CWB were be used to construct the prior 6hrs typhoon wave height forecasting model first to provide the necessity of warning facility with fifteen typhoon events data during 2006 to 2009. Then, a recursive GMDH model could be organized by using the update data to match the time variant properties in forecasting steps to improve the predict accuracy. In addition, a prior 1hr typhoon wave height forecasting model could be set up by cooperate prior 6hrs predict results with the log-logarithm correlation between progressive every 6hr’s and every hour’s measured wave height data to enhance the model advanced applications. The modeling approach shows that the Stepwise regression GMDH (SGMDH) algorithm is better than GMDH on typhoon wave height forecasting in typhoon events modeling, and the Jangmi typhoon event modeling with the RMSE 22.67cm and CC 97.16％ result the best simulation. Hence, taking this optimum model to forecast wave height of other 14 typhoon events and results show that the average RMSE, CC and error scale ratio (RMSE/H(1/3)) are 20.37cm, 90.55% and 17.32% respectively. Due to the necessity of disaster prevention, a prior 6hrs wave height forecasting model was build up by taking the data of 11 typhoon events and the predicted results reveal that the average RMSE, CC and error scale ratio are 41.34 cm, 80.09% and 26.41% respectively. A prior 1hr wave height forecasting model base on the log-log relation as mentioned above was then applied to calculate the progressive every 1hr’s wave height by using the predicted values of every 6hrs step. Simulation tests show that the average RMSE, CC and error scale ratio are 29.53 cm, 90.76% and 18.42% respectively. In consequence of typhoon wave height forecasting with the data of 8~14 typhoon events, both prior 6hrs and 1hr typhoon wave height forecasting appear the trend of forecasting results in agreement with measuring materials of the data buoy and result reasonable predicting accuracy in this research with the average RMSE, CC and error scale ratio in between 20.37cm~41.34cm, 80.09%~90.76% and 17.32%~26.41% respectively. So, the GMDH forecasting model possesses the practical usage of typhoon wave height forecasting at the specific surroundings.

Thesis (M.S.)--Florida State University, 2004.<br>Advisor: Dr. Philip Cunningham, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Sept. 22, 2004). Includes bibliographical references.

A thesis submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, Johannesburg, in fullment of the requirements for the Doctor of Philosophy in Economics Degree, June 2017<br>This thesis contains three main chapters. The rst chapter employs wageprice spirals to generate ination forecasts for Australia, Canada, France, South Korea, South Africa, United Kingdom and the United States. We use three competing specications of the wage-price spirals, and test which specication provides the best forecasts of price ination. For each specication we provide one quarter, four quarter and eight quarter ahead dynamic forecasts of price ination. The rst two wage-price spirals in the rst chapter are from the Keynesian tradition from te standpoint of expectations formation. The chapter also considers the New Keynesian wage-price spiral. We use the Root Means Square Error and the Clark and West statistic to compare the performance of ination forecasts from the three competing wage-price spirals that we consider in the rst chapter of the thesis. We nd that the New Keynesian wage and price specication su⁄ers from the wrong sign problem, and its forecasts of price ination generally outperform those from the old Keynesian wage price spiral for the eight quarter ahead time horizon. The usefulness of this nding to the conduct of monetary policy is limited due to the wrong sign problem of the forcing variable in the New Keynesian wageprice spiral. We also nd that the Flaschel type specication of price and wage ination produce four and eight quarter head ination forecasts that are better than those from the Fair type specication. We further nd that the Fair type specication price and wage equation produce the best forecasts of ination for the one quarter ahead time horizon. In the second chapter, we estimate natural variables and test their ability to explain the ination process for the eight countries that we consider. We use the traditional Keynesian wage-price spiral and the triangle system approaches to estimate the NAIRU and potential output. In the case of the traditional Keynesian wage-price spiral, the price Phillips curve, which can be specied as a triangle Phillips curve, features backward looking ination expectations and nominal wage ination, the output gap and supply shocks. The nominal wage Phillips curve features ination expectations and price ination and the unemployment gap. The presence of price ination in the nominal wage Phillips curve and the presence of nominal wage ination in the price Phillips curve leads to the interaction between the two Phillips curves. The separate demand pressure terms allows for their identication since, as someauthorsintheliteraturearguethatthegoodsandlabourmarketsdonot move in line with each other. To compute the NAIRU and potential output using the Keynesian approach, we rstly exploit the information contained in vector of unobservable by estimating the wage-price spiral in di⁄erence form using the Seemingly Unrelated Regression method. We use this regression method in order to control for any correlation that may exist between errors in the price and wage Phillips curves. This allows us to solve for the vector of potential output and the NAIRU. We then the moving average technique in order to avoid problems associated with the HP lter for smoothing. Due to data availability, use the MA (20) approximation of the low pass lter after padding the endpoints with forecasts from an AR(4) process. We follow a similar procedure in the estimation of the estimation of the NAIRU and potential output for the triangle system approach. To test which method produces the best natural variables, we t the gaps that are computed from the NAIRU and potential output in a simple single equation price Phillips curve. To test which specication produces the best natural varibles we use a simple single equation triangle price Phillips curve. We nd that the output gaps computed from the two competing approaches are signicantly correlated, the same applies to the unemployment gaps computed from the two approaches. We nd that the quality of unemployment rate gaps computed from the Keynesian and triangle system approach to produce similar quality of results when tted to a single equation triangle price Phillips curve. The Keynesian approach slightly outperforms the triangle systems approach in the when considering the output gap as a proxy for the demand pressure. These results indicate that the wage-price spiral still remains an important tool in the determination of the dynamics ination. In the third chapter, we analyze the relationship between monetary policy and natural variables for Australia, Canada, France, South Korea, South Africa, United Kingdom and the United States. We do this by specifying a relationship between natural rates and the real interest rate. The theoretical relationship between the two variables is positive in the case of the NAIRU and negative through Okuns law in the case of potential output. We regress the natural variable against a constant and the MA(8) of the real interest rate. We nd that the parameter of the real interest rate generally has a correct sign when considering the Keynesian approach computed NAIRUs, with only four being signicant. In the case of the triangle system approach NAIRU, we nd that the real interest rate parameter has a correct sign and signicant four countries. We nd that NAIRUs computed using di⁄erent methodologies can produce a di⁄erent reference point for policy makers. We then introduce hysteresis in the relationship between monetary policy and the NAIRU. We then nd that the interest rate parameter generally has a incorrect sign across the three approaches. The HP ltering approach which we include in our study for comparison purposes produces incorrect correlation for all the countries, while the Keynesian approach negative correlation for seven countries, and the triangle system approach in six countries. In the case of the relationship between monetary policy and potential output, we nd that the real interest rate parameter has an incorrect sign. When introducing hysteresis in the relationship between monetary policy and potential we nd that, unlike in the case of the NAIRU this plays signicant role in the relationship.<br>XL2018

Two post processing methods for quantifying the shadow effect of the offshore wind farm Princes Amalia (PA) onto Egmond aan Zee (OWEZ) wind farm are analyzed and benchmarked. The first method is the author’s proposed shadow effect determination method (SEDM), which quantifies an offshore wind farm’s shadow effect based on mesoscale WRF (Weather Research Forecast) idealized modeling and the observed frequency of the analyzed site’s wind conditions. The Fitch turbine parametrization scheme and Mellor-Yamada-Nakanishi-Niino (MYNN) surface layer and planetary boundary layer (PBL) schemes were used to simulate the wind farm’s interactions, based on site conditions. The proposed physical downscaling method (SEDM) uses filtered simulated atmospheric stability and wind speed conditions, in order to calculate the percent wind speed deficit downstream of PA, with regard, first, to observed wind speed frequency and, secondly, to wind speed and corresponding atmospheric stability regimes. Then a statistical downscaling method, based on the established Analog Ensemble (AnEn) technique, developed by Luca Delle Monache et al. (2011) was employed to verify the results from the first method. This method runs a post processing algorithm using the weighted average of the observations that were verified when the 15 best analogs were valid. Observed wind speed data at 10 m and 50 m height was used as Numerical Weather Prediction (NWP) input data and fit to observed time series data. From this, wind speeds at 116 m were extrapolated, in order to estimate the reconstructed atmospheric stability. The two methods were benchmarked and shadow effects were quantified in the range of 7.53% - 22.92% for the SEDM and within an 80% confidence interval of 0.23% -1.83% for the statistical downscaling method. Given the physical method’s exceedance of this confidence interval, WRF idealized modeling proves itself as a consistent means of quantifying an offshore wind farm’s wake, as demonstrated by comparable studies, however inaccurate when benchmarked to statistical modelling methods that use observed wind speed data to recreate atmospheric conditions.<br>Wake Research Group