Impact of Time Integration Scheme on Supercell Development

Slides:



Advertisements
Similar presentations
Formal Computational Skills
Advertisements

Wed 20 Sept 06Spin Tracking Meeting1 Positron Capture Simulations: Runge-Kutta vs Boris Leo Jenner, Daresbury Labs.
Chapter 6 Differential Equations
Realistic Simulation and Rendering of Smoke CSE Class Project Presentation Oleksiy Busaryev TexPoint fonts used in EMF. Read the TexPoint manual.
Joint Mathematics Meetings Hynes Convention Center, Boston, MA
Reduction of Temporal Discretization Error in an Atmospheric General Circulation Model (AGCM) Daisuke Hotta Advisor: Prof. Eugenia Kalnay.
Krakow - September, 15th 2008COSMO WG 2 - Runge Kutta1 Further Developments of the Runge-Kutta Time Integration Scheme Investigation of Convergence (task.
1 Internal Seminar, November 14 th Effects of non conformal mesh on LES S. Rolfo The University of Manchester, M60 1QD, UK School of Mechanical,
ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 32 Ordinary Differential Equations.
11 September 2007 KKKQ 3013 PENGIRAAN BERANGKA Week 10 – Ordinary Differential Equations 11 September am – 9.00 am.
P ROJECT : N UMERICAL S OLUTIONS TO O RDINARY D IFFERENTIAL E QUATIONS IN H ARDWARE Joseph Schneider EE 800 March 30, 2010.
CSE 330 : Numerical Methods Lecture 17: Solution of Ordinary Differential Equations (a) Euler’s Method (b) Runge-Kutta Method Dr. S. M. Lutful Kabir Visiting.
Impact of the 4D-Var Assimilation of Airborne Doppler Radar Data on Numerical Simulations of the Genesis of Typhoon Nuri (2008) Zhan Li and Zhaoxia Pu.
Stratified Magnetohydrodynamics Accelerated Using GPUs:SMAUG.
Polynomial Chaos For Dynamical Systems Anatoly Zlotnik, Case Western Reserve University Mohamed Jardak, Florida State University.
Aerosol Microphysics: Plans for GEOS-CHEM
I.Z. Naqavi 1, E. Savory 1 & R.J. Martinuzzi 2 1 Advanced Fluid Mechanics Research Group Department of Mechanical and Materials Engineering The University.
Smoothed Particle Hydrodynamics (SPH) Fluid dynamics The fluid is represented by a particle system Some particle properties are determined by taking an.
In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.
Numerical Integration and Rigid Body Dynamics for Potential Field Planners David Johnson.
DOUBLE PENDULUM By: Rosa Nguyen EPS 109 – Fall 2011.
Computer Animation Algorithms and Techniques
WRF exercise 1 Kessler μ-physics scheme vs Thompson μ-physics scheme Isaac Hankes Joseph Ching.
LES of Turbulent Flows: Lecture 2 (ME EN )
Sensitivity experiments with the Runge Kutta time integration scheme Lucio TORRISI CNMCA – Pratica di Mare (Rome)
FlowFixer: Using BFECC for Fluid Simulation ByungMoon Kim Yingjie Liu Ignacio Llamas Jarek Rossignac Georgia Institute of Technology.
Numerical Simulation and Prediction of Supercell Tornadoes Ming Xue School of Meteorology and Center for Analysis and Prediction of Storms University of.
Mass Coordinate WRF Dynamical Core - Eulerian geometric height coordinate (z) core (in framework, parallel, tested in idealized, NWP applications) - Eulerian.
Test of Supercell Propagation Theory Using Data from VORTEX 95 Huaqing Cai NCAR/ASP/ATD.
Aim Direct impulse measurement for DDT initiation. Calculate impulse from Ballistic pendulum Pressure traces Wave reflection analysis Numerical simulation.
The Impact of Tracer Advection Schemes on Biogeochemical Tracers Keith Lindsay, NCAR Keith Moore, UC Irvine, Scott.
Patient-specific Cardiovascular Modeling System using Immersed Boundary Technique Wee-Beng Tay a, Yu-Heng Tseng a, Liang-Yu Lin b, Wen-Yih Tseng c a High.
Assimilation of Pseudo-GLM Observations Into a Storm Scale Numerical Model Using the Ensemble Kalman Filter Blake Allen University of Oklahoma Edward Mansell.
Introduction In 1904, Bjerknes pointed out that the future state of the atmosphere could be predicted by integrating the partial differential equations.
I NVESTIGATION OF THE IMPACT OF M ICROPHYSICS O PTIONS ON I DEALIZED WRF S UPERCELL Catrin M. Mills Sara T. Strey-Mellema.
Higher Order Runge-Kutta Methods for Fluid Mechanics Problems Abhishek Mishra Graduate Student, Aerospace Engineering Course Presentation MATH 6646.
Animating smoke with dynamic balance Jin-Kyung Hong Chang-Hun Kim 발표 윤종철.
Numerical Methods for Acoustic Problems with Complex Geometries Based on Cartesian Grids D.N. Vedder
Simulations and radiative diagnostics of turbulence and wave phenomena in the magnetised solar photosphere S. Shelyag Astrophysics Research Centre Queen’s.
Operational COSMO of MeteoSwiss
Numerical Calculations Part 5: Solving differential equations
Reporter: Prudence Chien
Numerical Simulations of Solar Magneto-Convection
An accurate, efficient method for calculating hydrometeor advection in multi-moment bulk and bin microphysics schemes Hugh Morrison (NCAR*) Thanks to:
Kazushi Takemura, Ishioka Keiichi, Shoichi Shige
Grid Point Models Surface Data.
Positron Capture Simulations: Runge-Kutta vs Boris
Modeling and simulation of systems
NUMERICAL INVESTIGATIONS OF FINITE DIFFERENCE SCHEMES
Concurrent Visualization (NASA Goddard and Ames)
Modelling of Combustion and Heat Transfer in ‘Swiss Roll’ Micro-Scale Combusters M. Chen and J. Buckmaster Combustion Theory and Modelling 2004 Presented.
SE301: Numerical Methods Topic 8 Ordinary Differential Equations (ODEs) Lecture KFUPM (Term 101) Section 04 Read , 26-2, 27-1 CISE301_Topic8L4&5.
Vector Field Visualization
Ch 8.6: Systems of First Order Equations
Physics-based simulation for visual computing applications
Ordinary differential equaltions:
Monte Carlo Simulation of Neutrino Mass Measurements
WELCOME TO MY CLASS NUMERICAL METHOD Name : Masduki
Just for Kicks: a Molecular Dynamics Simulation by Dino B.
Study of non-uniformity of magnetic field
Problem Set #3 – Part 3 - Remediation
Numerical solution of first-order ordinary differential equations
SE301: Numerical Methods Topic 8 Ordinary Differential Equations (ODEs) Lecture KFUPM Read , 26-2, 27-1 CISE301_Topic8L3 KFUPM.
Numerical Computation and Optimization
Differential equations
Reporter : Prudence Chien
Rupro, breach model used by Cemagref during Impact project
Team Scalar and Momentum Advection
Numerical solution of first-order ordinary differential equations 1. First order Runge-Kutta method (Euler’s method) Let’s start with the Taylor series.
M.PHIL (MATHEMATICS) By Munir Hussain Supervised By Dr. Muhammad Sabir.
Presentation transcript:

Impact of Time Integration Scheme on Supercell Development ATMS-597R Alexandra Jones, Samantha Chiu, David Plummer 8 October 2010

Control vs. Test Simulation Both used Thompson microphysics Control run used 3rd-order Runge-Kutta differentiation in time Test run used 2nd-order Runge-Kutta scheme Larger amplification/phase error with lower-order scheme (Durran 69)

Mesocyclone track (Control run)

Mesocyclone track (Test run)

Low-level reflectivity field at t=60 minutes, when difference in vorticity advective term was most significant

Conclusions Lower-order time differentiation resulted in noisier simulation, but general development was similar In both cases, advection and stretching/divergent terms contributed most to relative vorticity tendency Differences in tendency terms between runs generally small Advection term larger for test run at 60 minutes, but difficult to identify persistent differences visually

Reference Durran, D. R., 1999: Numerical Methods for Wave Equations in Geophysical Fluid Dynamics. Springer, 465 pp.