Assimilating Doppler radar radial velocity and reflectivity observations in the weather research and forecasting model by a proper orthogonal-decomposition-based ensemble, three-dimensional variational assimilation method

2012 ◽  
Vol 117 (D17) ◽  
pp. n/a-n/a ◽  
Author(s):  
Xiaoduo Pan ◽  
Xiangjun Tian ◽  
Xin Li ◽  
Zhenghui Xie ◽  
Aimei Shao ◽  
...  
Keyword(s):  
Radial Velocity ◽  
Proper Orthogonal Decomposition ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Orthogonal Decomposition ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Variational Assimilation ◽  
Proper Orthogonal ◽  
Weather Research

A Comparison of Classic and Snapshot Proper Orthogonal Decomposition on the Three Dimensional Wall Jet Flow Field

2014 ◽  
Author(s):  
Mahdi Hosseinali ◽  
Stephen Wilkins ◽  
Lhendup Namgyal ◽  
Joseph Hall
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Energy Content ◽  
Near Field ◽  
Three Dimensional ◽  
Orthogonal Decomposition ◽  
Wall Jet ◽  
Polar Coordinate ◽  
Wall Jet Flow ◽  
Turbulent Wall ◽  
Proper Orthogonal

In this paper, classic Proper Orthogonal Decomposition (POD) on a polar coordinate and snapshot POD on a Cartesian grid will be applied separately in the near field of a turbulent wall jet. Three-component stereoscopic PIV measurements are performed in the transverse plane of a wall jet formed using a round contoured nozzle with a Reynolds number of 250,000. Eigenfunctions and energy distributions of the two methods are compared. Reconstructions using same number of modes and same content of energy have been compared. The effect of grid resolution on the energy content of the classic method has also been studied.

Characteristics of Turbulent Three-Dimensional Wall Jets

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
M. Agelin-Chaab ◽  
M. F. Tachie
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Orthogonal Decomposition ◽  
The Self ◽  
Shear Stresses ◽  
Spread Rate ◽  
Similar Region ◽  
Self Similar ◽  
Proper Orthogonal

Three-dimensional turbulent wall jet was investigated using a particle image velocimetry technique. Three Reynolds numbers based on the jet exit velocity and diameter of 5000, 10,000, and 20,000 were studied. Profiles of the mean velocities, turbulence intensities, and Reynolds shear stresses as well as two-point velocity correlations and proper orthogonal decomposition analyses were used to document the salient features of the wall jets. The decay and spread rates are independent of Reynolds numbers in the self-similar region. The estimated values of 1.15, 0.054, and 0.255 for the decay rate, wall-normal spread rate, and lateral spread rate, respectively, are within the range of values reported in the literature. The two-point correlation analysis showed that the inclination of the streamwise velocity correlation contours in the inner layer is 11±3 deg in the wall region, which is similar to those of canonical turbulent boundary layers. The results from the proper orthogonal decomposition indicate that low-order modes contribute more to the turbulence statistics in the self-similar region than in the developing region. The Reynolds shear stresses are the biggest benefactors of the low-order mode contribution while the wall-normal turbulence intensities are the least.

scholarly journals Precipitation Forecasting Using Doppler Radar Data, a Cloud Model with Adjoint, and the Weather Research and Forecasting Model: Real Case Studies during SoWMEX in Taiwan

2011 ◽  
Vol 26 (6) ◽  
pp. 975-992 ◽  
Author(s):  
Sheng-Lun Tai ◽  
Yu-Chieng Liou ◽  
Juanzhen Sun ◽  
Shao-Fan Chang ◽  
Min-Chao Kuo
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Reanalysis Data ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Doppler Radar Data ◽  
Background Fields ◽  
Weather Research

Abstract The quantitative precipitation forecast (QPF) capability of the Variational Doppler Radar Analysis System (VDRAS) is investigated in the Taiwan area, where the complex topography and surrounding oceans pose great challenges to accurate rainfall prediction. Two real cases observed during intensive operation periods (IOPs) 4 and 8 of the 2008 Southwest Monsoon Experiment (SoWMEX) are selected for this study. Experiments are first carried out to explore the sensitivity of the retrieved fields and model forecasts with respect to different background fields. All results after assimilation of the Doppler radar data indicate that the principal kinematic and thermodynamic features recovered by the VDRAS four-dimensional variational data assimilation (4DVAR) technique are rather reasonable. Starting from a background field generated by blending ground-based in situ measurements (radiosonde and surface mesonet station) and reanalysis data over the oceans, VDRAS is capable of capturing the evolution of the major precipitation systems after 2 h of simulation. The model QPF capability is generally comparable to or better than that obtained using only in situ observations or reanalysis data to prepare the background fields. In a second set of experiments, it is proposed to merge the VDRAS analysis field with the Weather Research and Forecasting Model (WRF), and let the latter continue with the following model integration. The results indicate that through this combination, the performance of the model QPF can be further improved. The accuracy of the predicted 2-h accumulated rainfall turns out to be significantly higher than that generated by using VDRAS or WRF alone. This can be attributed to the assimilation of meso- and convective-scale information, embedded in the radar data, into VDRAS, and to better treatment of the topographic effects by the WRF simulation. The results illustrated in this study demonstrate a feasible extension for the application of VDRAS in other regions with similar geographic conditions and observational limitations.

Rapid Transient Thermal Analysis of Three-Dimensional Interconnect Structures Using Proper Orthogonal Decomposition Method

2012 ◽  
Author(s):  
Banafsheh Barabadi ◽  
Satish Kumar ◽  
Yogendra K. Joshi
Keyword(s):  
Thermal Analysis ◽  
Proper Orthogonal Decomposition ◽  
Joule Heating ◽  
Hot Spot ◽  
Three Dimensional ◽  
Orthogonal Decomposition ◽  
Computational Time ◽  
Interconnect Architectures ◽  
High Level ◽  
Proper Orthogonal

The increase in the integration of interconnect wiring, as well as the high level of current densities are resulting in increased concerns about hot spot formation due to Joule heating in the metal lines of microprocessors. This temperature rise poses a major challenge in maintaining the quality and reliability of future devices, requiring a focus on physics based approaches for rapid and accurate thermal analysis of interconnect architectures. This work investigates the problem of transient Joule heating in a three-dimensional array of copper interconnects embedded in dielectric layers of SiO2 and Si3N4 using Proper Orthogonal Decomposition (POD) as the reduced order modeling approach. The case of natural convection was assumed on the boundaries. For validation, the results were compared with a three-dimensional finite volume model developed in Fluent and good agreements models were observed. While the Fluent model required hours of computational time, the POD based model predictions were achieved within seconds.

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