scholarly journals AUTOMATIC CALIBRATION OF A WAVE MODEL WITH AN EVOLUTIONARY BAYESIAN METHOD

2017 ◽  
pp. 26
Author(s):  
Rodrigo Alonso ◽  
Sebastián Solari
Keyword(s):  
Atlantic Coast ◽  
Target Function ◽  
Wave Model ◽  
Reanalysis Data ◽  
Measure Data ◽  
Data Series ◽  
Model Parameters ◽  
Engineering Project ◽  
Wave Reanalysis ◽  
Two Parameters

Bayesian Inference has been widely applied with success in science and engineering. One of its main uses is the inference of model parameters in order to reconcile model outputs with evidence provided by measures. In this article we propose this application for coastal engineering problems. Specifically, it is proposed to infer the parameters of a numerical wave model used to downscale wave reanalysis data to a coastal site. The proposed method is applied to a case study on the Uruguayan Atlantic coast, where a few month wave measure data series is available and needs to be extended in order to be used on an engineering project. The wave model used is SWAN and the data in deep waters and the wind data were obtained from the ERA-Interim reanalysis. At first, the method was tested with one and two parameters, since in these cases it is possible to compare the obtained results with a plot of the target function. Finally it was used to calibrate four parameters of the wave model and assess the uncertainty introduced by the selection of a set of parameters.

scholarly journals Bayesian trend analysis of extreme wind using observed and hindcast series off the Catalan coast, NW Mediterranean Sea

2014 ◽  
Vol 14 (9) ◽  
pp. 2387-2397 ◽  
Author(s):  
M. I. Ortego ◽  
J. J. Egozcue ◽  
R. Tolosana-Delgado
Keyword(s):  
Generalized Pareto Distribution ◽  
Western Mediterranean ◽  
Quality Data ◽  
Occurrence Rate ◽  
Data Series ◽  
Model Parameters ◽  
Storm Events ◽  
Average Wind Speed ◽  
Magnitude Distribution ◽  
Catalan Coast

Abstract. It has been suggested that climate change might modify the occurrence rate and magnitude of large ocean-wave and wind storms. The hypothesised reason is the increase of available energy in the atmosphere–ocean system. Forecasting models are commonly used to assess these effects, given that good-quality data series are often too short. However, forecasting systems are often tuned to reproduce the average behaviour, and there are concerns on their relevance for extremal regimes. We present a methodology of simultaneous analysis of observed and hindcast data with the aim of extracting potential time drifts as well as systematic regime discrepancies between the two data sources. The method is based on the peak-over-threshold (POT) approach and the generalized Pareto distribution (GPD) within a Bayesian estimation framework. In this context, storm events are considered points in time, and modelled as a Poisson process. Storm magnitude over a reference threshold is modelled with a GPD, a flexible model that captures the tail behaviour of the magnitude distribution. All model parameters, i.e. shape and location of the magnitude GPD and the Poisson occurrence rate, are affected by a trend in time. Moreover, a systematic difference between parameters of hindcast and observed series is considered. Finally, the posterior joint distribution of all these trend parameters is studied using a conventional Gibbs sampler. This method is applied to compare hindcast and observed series of average wind speed at a deep buoy location off the Catalan coast (NE Spain, western Mediterranean; buoy data from 2001; REMO wind hindcasting from 1958 on). Appropriate scale and domain of attraction are discussed, and the reliability of trends in time is addressed.

scholarly journals COMPARATIVE ANALYSIS OF DIFFERENT CAD METHODS FOR EXTRACTION OF THE HEMT NOISE WAVE MODEL PARAMETERS

2017 ◽  
Vol 16 (2) ◽  
pp. 117
Author(s):  
Vladica Đorđević ◽  
Zlatica Marinković ◽  
Olivera Pronić-Rančić
Keyword(s):  
Comparative Analysis ◽  
Electron Mobility ◽  
Computer Aided Design ◽  
Wave Model ◽  
High Electron Mobility Transistor ◽  
Extraction Methods ◽  
Model Parameters ◽  
High Electron ◽  
High Electron Mobility ◽  
Noise Modeling

The noise wave model has appeared as a very appropriate model for the purpose of transistor noise modeling at microwave frequencies. The transistor noise wave model parameters are usually extracted from the measured transistor noise parameters by using time-consuming optimization procedures in microwave circuit simulators. Therefore, three different Computer-Aided Design methods that enable more efficient automatic determination of these parameters in the case of high electron-mobility transistors were developed. All of these extraction methods are based on different noise de-embedding procedures, which are described in detail within this paper. In order to validate the presented extraction methods, they were applied for the noise modeling of a specific GaAs high electron-mobility transistor. Finally, the obtained results were used for the comparative analysis of the presented extraction approaches in terms of accuracy, complexity and effectiveness.

Trend analysis of extratropical cyclones in long-term ERA5 data series (1950-2019)

2021 ◽  
Author(s):  
Richard Blender ◽  
Alexia Karwat ◽  
Christian Franzke
Keyword(s):  
Nearest Neighbor ◽  
Climate Extremes ◽  
Reanalysis Data ◽  
Nearest Neighbor Search ◽  
Data Series ◽  
Extratropical Cyclones ◽  
Weather Forecasts ◽  
Neighbor Search ◽  
Weather And Climate

<p>Extratropical cyclones are the primary natural hazards affecting Europe. With the release of ERA5 reanalysis data from 1950-1978 by the European Centre for Medium-Range Weather Forecasts (ECMWF), new opportunities have arisen to investigate mid-latitude cyclones in terms of climatic features and trends in longer and higher resolution. We analyze cyclones by nearest neighbor search in 1000 hPa geopotential height minima in different high resolutions for different minimum life-times. We find an intensification of North Atlantic cyclones in 1950-2019. Short-lived cyclones grow in radius and depth. In the Mediterranean, however, long-lived cyclones have weakened; but traveled also further in 1950-2019. Additionally, we illustrate relations between cyclone tracks, radii and correlated weather and climate extremes.</p>

scholarly journals Application of STORMTOOLS Coastal Environmental Risk Index (CERI) to Inform State and Local Planning and Decision Making along the Southern RI Shoreline

2020 ◽  
Vol 8 (4) ◽  
pp. 295
Author(s):  
Malcolm L. Spaulding ◽  
Annette Grilli ◽  
Chris Damon ◽  
Teresa Crean ◽  
Grover Fugate
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Rhode Island ◽  
Environmental Risk ◽  
Structural Damage ◽  
Risk Index ◽  
Atlantic Coast ◽  
Wave Model ◽  
Flood Plain ◽  
State And Local

STORMTOOLS coastal environmental risk index (CERI) was applied to communities located along the southern coast of Rhode Island (RI) to determine the risk to structures located in the flood plain. CERI uses estimates of the base flood elevation (BFE), explicitly including the effects of sea level rise (SLR); details on the structure types, from the E911 emergency data base/parcel data, and associated first floor elevation (FFE); and damage curves from the US Army Corp of Engineers North Atlantic Coast Comprehensive Study (NACCS) to determine the damages to structures for the study area. Surge levels and associated offshore waves used to determine BFEs were obtained from the NACCS hydrodynamic and wave model predictions. The impacts of sea level rise and coastal erosion on flooding were modeled using XBeach and STWAVE and validated by observations at selected locations along the coastline. CERI estimated the structural damage to each structure in the coastal flood plain for 100 yr flooding with SLR ranging from 0 to 10 ft. The number of structures at risk was estimated to increase approximate linearly from 3700 for no SLR to about 8000 for 10 ft SLR, with about equal percentages for each of the four coastal communities (Narragansett, South Kingstown, Charlestown, and Westerly, Rhode Island (RI)). The majority of the structures in the flood plain are single/story residences without (41%) and with (46%) basements (total 87%; structures with basements are the most vulnerable). Less vulnerable are structures elevated on piles with 8.8% of the total. The remaining are commercial structures principally located either in the Port of Galilee and or Watch Hill. The analysis showed that about 20% of the structures in the 100 yr flood plain are estimated to be damaged at 50% or greater. This increases to 55% of structures as SLR rises to 5 ft. At higher SLR values the percent damaged at 50% or greater slowly declines to 45% at 10 ft SLR. This behavior is a result of the number of homes below MSL increasing dramatically as SLR values moves higher than 5 ft and thus being removed from the structures damaged pool. Generalized CERI risk maps have developed to allow the managers to determine the broad risk of siting structures at any location in their communities. CERI has recently become available as a mobile phone App, facilitating the ability of state and local decision makers and the public to determine the risk of locating a selected building type at any location in their communities.

Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States

2016 ◽  
Vol 541 ◽  
pp. 421-433 ◽  
Author(s):  
Humberto Vergara ◽  
Pierre-Emmanuel Kirstetter ◽  
Jonathan J. Gourley ◽  
Zachary L. Flamig ◽  
Yang Hong ◽  
...  
Keyword(s):  
United States ◽  
Flash Flood ◽  
A Priori ◽  
Wave Model ◽  
Flood Forecasting ◽  
Model Parameters ◽  
Kinematic Wave ◽  
Kinematic Wave Model ◽  
Flash Flood Forecasting

Sensitivity Studies of Shear Stress Transport Turbulence Model Parameters on the Prediction of Seven-Rod Bundle Benchmark Experiments

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Cale Bergmann ◽  
S. Ormiston ◽  
V. Chatoorgoon
Keyword(s):  
Shear Stress ◽  
Turbulence Model ◽  
Turbulence Modeling ◽  
Sensitivity Study ◽  
Model Parameters ◽  
Rod Bundle ◽  
Shear Stress Transport ◽  
Sst Turbulence Model ◽  
Sensitivity Studies ◽  
Two Parameters

This paper reports the findings of a sensitivity study of parameters in the shear stress transport (SST) turbulence model in a commercial computational fluid dynamics (CFD) code to predict an experiment from the Generation IV International Forum Supercritical-Water-Cooled Reactor (GIF SCWR) 2013–2014 seven-rod subchannel benchmark exercise. This study was motivated by the result of the benchmark exercise that all the CFD codes gave similar results to a subchannel code, which does not possess any sophisticated turbulence modeling. Initial findings were that the CFD codes generally underpredicted the wall temperatures on the B2 case in the region where the flow was supercritical. Therefore, it was decided to examine the effect of various turbulence model parameters to determine if a CFD code using the SST turbulence model could do a better job overall in predicting the wall temperatures of the benchmark experiments. A sensitivity study of seven parameters was done, and changes to two parameters were found to make an improvement.

scholarly journals A PARAMETRIC HURRICANE WAVE PREDICTION MODEL

1988 ◽  
Vol 1 (21) ◽  
pp. 82
Author(s):  
Ian R. Young
Keyword(s):  
Spatial Distribution ◽  
Radiative Transfer Equation ◽  
Synthetic Data ◽  
Wave Model ◽  
Limited Growth ◽  
Forward Movement ◽  
Spectral Wave Model ◽  
Wave Conditions ◽  
Two Parameters ◽  
The Waves

A spectral wave model based on a numerical solution of the Radiative Transfer Equation is used to create a synthetic data base on wave conditions within hurricanes. The results indicate that both the velocity of forward movement and maximum wind velocity within the storm play an important role in determining both the magnitude of the waves generated and also the spatial distribution of these waves. An equivalent fetch for hurricane wave generation which is a function of these two parameters is proposed. This concept, together with the standard JONSWAP fetch limited growth relationships, provide a simple means for estimating wave conditions within hurricanes.

Wind waves modeling in the polar law weather conditions

2020 ◽  
Author(s):  
Alexandra Kuznetsova ◽  
Evgeny Poplavsky ◽  
Nikita Rusakov ◽  
Yuliya Troitskaya
Keyword(s):  
Wind Waves ◽  
Rapid Development ◽  
Free Water ◽  
Wave Model ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
The Arctic ◽  
Geophysical Research ◽  
Polar Lows ◽  
Adverse Weather

<p>Arctic storms pose a great danger to developing commercial and passenger shipping, coastal infrastructure, and also for oil production from offshore platforms. This is primarily due to high waves and extreme winds. Such episodes of adverse weather conditions due to their rapid development are poorly predicted by modern models. For this purpose, the representation of the event of polar law is studied in the wave model WAVEWATCH III.</p><p>Wind waves were simulated under conditions of polar depression on ice-free water. To simulate wind waves under conditions of polar depression, the Barents Sea was selected, where, according to the data of [1, 2], a large number of polar hurricanes are observed. Among the identified polar hurricanes, for example, in [3], a hurricane that took place on 05.02.2009, observed at coordinates 69 N 40 E is chosen. The preliminary results in the wave model are obtained without the ice influence consideration. The developed model was configured using the CFSR wind reanalysis data. The resulting distribution of significant wave heights is obtained. Then, to consider the attenuation by sea ice, the reanalysis data of the Arctic System Reanalysis Version 2 (ASRv2), which is based on Polar WRF with a resolution of 15 km for the Arctic region, is used. Modeling the destruction of ice by waves during an intense arctic storm will be implemented using WW3 models with an IS2 module.</p><p>The work is supported by RFBR grant 18-05-60299.</p><ol><li>Smirnova, J. E., Golubkin, P. A., Bobylev, L. P., Zabolotskikh, E. V., & Chapron, B. (2015). Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data. Geophysical Research Letters, 42(13), 5603-5609.</li> <li>Smirnova, J., & Golubkin, P. (2017). Comparing polar lows in atmospheric reanalyses: Arctic System Reanalysis versus ERA-Interim. Monthly Weather Review, 145(6), 2375-2383.</li> <li>Noer, G., & Lien, T. (2010). Dates and Positions of Polar lows over the Nordic Seas between 2000 and 2010. Norwegian Meteorological Institute Rep.</li> </ol>

A New Method for Parameters Extraction of Extruded Surface

2011 ◽  
Vol 474-476 ◽  
pp. 834-839
Author(s):  
Luo Heng Yan ◽  
Zhong Min Huangfu
Keyword(s):  
Reverse Engineering ◽  
Random Sampling ◽  
Least Squares Method ◽  
Consensus Algorithm ◽  
Measure Data ◽  
Model Parameters ◽  
Cad Model ◽  
Parameters Extraction ◽  
Random Sampling Consensus ◽  
Crucial Parameter

The purpose of reverse engineering is to convert a large points cloud into a CAD model. Parameters extraction for extruded surface from measure data is an important problerm in reverse engineering. Extruded direction is a crucial parameter of extruded surface. In this paper, random sampling consensus algorithm combined with Least-Squares method is used to extract the extruded direction of extruded surface. Experimental results show effectiveness, robustness and accuracy of this proposed approach.

scholarly journals Evaluation of the hydrological cycle of MATCH driven by NCEP reanalysis data: comparison with GOME water vapor field measurements

2004 ◽  
Vol 4 (6) ◽  
pp. 7917-7984 ◽  
Author(s):  
R. Lang ◽  
M. G. Lawrence
Keyword(s):  
Water Vapor ◽  
Regional Differences ◽  
Hydrological Cycle ◽  
Transport Model ◽  
Global Precipitation Climatology Project ◽  
Reanalysis Data ◽  
Model Parameters ◽  
Residence Times ◽  
Ncep Reanalysis ◽  
Inter Tropical Convergence Zone

Abstract. This study examines two key parameters of the hydrological cycle, water vapor (WV) and precipitation rates (PR), as modelled by the chemistry transport model MATCH (Model of Atmospheric Transport and Chemistry) driven by National Centers for Environmental Prediction (NCEP) reanalysis data (NRA). For model output evaluation we employ WV total column data from the Global Ozone Monitoring Experiment (GOME) on ERS-2, which is the only instrument capable measuring WV on a global scale and over all surface types with a substantial data record from 1995 to the present. We find that MATCH and NRA WV and PR distributions are closely related, but that significant regional differences in both parameters exist in magnitude and distribution patterns when compared to the observations. We also find that WV residual patterns between model and observations show remarkable similarities to residuals observed in the PR when comparing MATCH and NRA output to observations comprised by the Global Precipitation Climatology Project (GPCP). We conclude that deficiencies in model parameters shared by MATCH and NRA, like, for example, in the evapotranspiration rates, are likely to lead to the observed differences. Regional differences between MATCH modelled WV columns and the observations can be as large as 2 cm on the basis of a three years monthly average. Differences in the global mean WV values are, however, below 1 mm. Regional differences in the PR between MATCH and GPCP can be above 5 mm per day and MATCH computes on average a higher PR than what has been observed. As a consequence, this leads to shorter model WV residence times by about 1 day as compared to NRA data and the observations. We find that MATCH has problems in modelling the WV content in regions of strong upward convection like, for example, along the Inter Tropical Convergence Zone, where it appears to be generally too dry as compared to the observations. The study therefore suggests that a too rapid conversion of WV to precipitate in MATCH, especially in instances of strong convection, leads to regionally too dry model results and in turn to generally too low WV residence times. The study additionally demonstrates the value of the GOME WV record for model evaluation.

Sign in / Sign up

Export Citation Format

Share Document