Introduction to Numerical Modeling. 7. An Example: QG Barotropic Channel Model (Weather Prediction)

Similar documents
Übung zur Meteorologischen Modellierung (Numerik): Das barotrope Modell

3 Motion with constant acceleration: Linear and projectile motion

15/03/1439. Lecture 4: Linear Time Invariant (LTI) systems

Physic 231 Lecture 4. Mi it ftd l t. Main points of today s lecture: Example: addition of velocities Trajectories of objects in 2 = =

A Kalman filtering simulation

5.1-The Initial-Value Problems For Ordinary Differential Equations

An Integral Two Space-Variables Condition for Parabolic Equations

2D Motion WS. A horizontally launched projectile s initial vertical velocity is zero. Solve the following problems with this information.

PHYSICS 1210 Exam 1 University of Wyoming 14 February points

Chapter Direct Method of Interpolation

2IV10/2IV60 Computer Graphics

THE EXTENDED TANH METHOD FOR SOLVING THE -DIMENSION NONLINEAR DISPERSIVE LONG WAVE EQUATION

Average & instantaneous velocity and acceleration Motion with constant acceleration

A 1.3 m 2.5 m 2.8 m. x = m m = 8400 m. y = 4900 m 3200 m = 1700 m

September 20 Homework Solutions

Physics 101 Lecture 4 Motion in 2D and 3D

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration.

Contraction Mapping Principle Approach to Differential Equations

Physics 2A HW #3 Solutions

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function

IX.2 THE FOURIER TRANSFORM

CHAPTER 11 PARAMETRIC EQUATIONS AND POLAR COORDINATES

Integral Transform. Definitions. Function Space. Linear Mapping. Integral Transform

MTH 146 Class 11 Notes

Scalar Conservation Laws

Phys 110. Answers to even numbered problems on Midterm Map

Kinematics in two Dimensions

CSE-4303/CSE-5365 Computer Graphics Fall 1996 Take home Test

1. Consider a PSA initially at rest in the beginning of the left-hand end of a long ISS corridor. Assume xo = 0 on the left end of the ISS corridor.

Physics 201, Lecture 5

Chapter 10. Simple Harmonic Motion and Elasticity. Goals for Chapter 10

ECE Microwave Engineering. Fall Prof. David R. Jackson Dept. of ECE. Notes 10. Waveguides Part 7: Transverse Equivalent Network (TEN)

CSE 5365 Computer Graphics. Take Home Test #1

Chapter 2. Motion along a straight line. 9/9/2015 Physics 218

Atmospheric Dynamics 11:670:324. Class Time: Tuesdays and Fridays 9:15-10:35

Motion on a Curve and Curvature

Version 001 test-1 swinney (57010) 1. is constant at m/s.

Lecture 8 Backlash and Quantization. Material. Linear and Angular Backlash. Example: Parallel Kinematic Robot. Backlash.

1.0 Electrical Systems

M r. d 2. R t a M. Structural Mechanics Section. Exam CT5141 Theory of Elasticity Friday 31 October 2003, 9:00 12:00 hours. Problem 1 (3 points)

Honours Introductory Maths Course 2011 Integration, Differential and Difference Equations

Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z.

Ch.4 Motion in 2D. Ch.4 Motion in 2D

PHY2048 Exam 1 Formula Sheet Vectors. Motion. v ave (3 dim) ( (1 dim) dt. ( (3 dim) Equations of Motion (Constant Acceleration)

A LIMIT-POINT CRITERION FOR A SECOND-ORDER LINEAR DIFFERENTIAL OPERATOR IAN KNOWLES

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment

LAPLACE TRANSFORM OVERCOMING PRINCIPLE DRAWBACKS IN APPLICATION OF THE VARIATIONAL ITERATION METHOD TO FRACTIONAL HEAT EQUATIONS

LECTURE 5. is defined by the position vectors r, 1. and. The displacement vector (from P 1 to P 2 ) is defined through r and 1.

Kinematics of Wheeled Robots

Flow Networks Alon Efrat Slides courtesy of Charles Leiserson with small changes by Carola Wenk. Flow networks. Flow networks CS 445

Three Dimensional Coordinate Geometry

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x)

UNIT # 01 (PART II) JEE-Physics KINEMATICS EXERCISE I. 2h g. 8. t 1 = (4 1)i ˆ (2 2) ˆj (3 3)kˆ 1. ˆv = 2 2h g. t 2 = 2 3h g

ON A NEW SOLUTION OF FRACTIONAL DIFFERENTIAL EQUATION USING COMPLEX TRANSFORM IN THE UNIT DISK

Motion in a Straight Line

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1.

..,..,.,

REVIEW OF MAXIMUM LIKELIHOOD ESTIMATION

Minimum Squared Error

4.2 Continuous-Time Systems and Processes Problem Definition Let the state variable representation of a linear system be

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 10: The High Beta Tokamak Con d and the High Flux Conserving Tokamak.

1. Find a basis for the row space of each of the following matrices. Your basis should consist of rows of the original matrix.

Earthquake, Volcano and Tsunami

Particle Filtering. CSE 473: Artificial Intelligence Particle Filters. Representation: Particles. Particle Filtering: Elapse Time

Lecture 3: 1-D Kinematics. This Week s Announcements: Class Webpage: visit regularly

Introduction to Bayesian Estimation. McGill COMP 765 Sept 12 th, 2017

ME 425: Aerodynamics

Ex: An object is released from rest. Find the proportion of its displacements during the first and second seconds. y. g= 9.8 m/s 2

Some basic notation and terminology. Deterministic Finite Automata. COMP218: Decision, Computation and Language Note 1

Minimum Squared Error

Chapter 2 PROBLEM SOLUTIONS

An object moving with speed v around a point at distance r, has an angular velocity. m/s m

Name: Per: L o s A l t o s H i g h S c h o o l. Physics Unit 1 Workbook. 1D Kinematics. Mr. Randall Room 705

Probabilistic Robotics

S Radio transmission and network access Exercise 1-2

T-Match: Matching Techniques For Driving Yagi-Uda Antennas: T-Match. 2a s. Z in. (Sections 9.5 & 9.7 of Balanis)

ECE Microwave Engineering

10.6 Parametric Equations

t s (half of the total time in the air) d?

PART V. Wavelets & Multiresolution Analysis

Kinematics in two dimensions

Math Wednesday March 3, , 4.3: First order systems of Differential Equations Why you should expect existence and uniqueness for the IVP

graph of unit step function t

MOVEMENT OF EQUILIBRIUM OF COURNOT DUOPOLY AND THE VISUALIZATION OF BIFURCATIONS OF ITS ADJUSTMENT DYNAMICS

Solutions for Nonlinear Partial Differential Equations By Tan-Cot Method

nonlinear system Signals & systems Output signals Input signals Dynamic system

Laplace Examples, Inverse, Rational Form

Method of Moment Area Equations

Exponential Smoothing

Giambattista, Ch 3 Problems: 9, 15, 21, 27, 35, 37, 42, 43, 47, 55, 63, 76

I = I = I for this case of symmetry about the x axis, we find from

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20

Partial Differential Equations

4.8 Improper Integrals

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

Mathematics 805 Final Examination Answers

MASS, STIFFNESS, AND DAMPING MATRICES FROM MEASURED MODAL PARAMETERS

when t = 2 s. Sketch the path for the first 2 seconds of motion and show the velocity and acceleration vectors for t = 2 s.(2/63)

Convergence of Singular Integral Operators in Weighted Lebesgue Spaces

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 9: The High Beta Tokamak

Transcription:

Inrodcion o Nmericl Modelin 7. An Emple: QG Broropic Chnnel Model Weher Predicion Frnk Lnkei The Broropic Model - Firs fncionin nmericl weher predicion model Chrne, J. G., Fjorof, R. nd on Nemnn, J. 95. Nmericl inerion of he roropic orici eqion. Tells,, 7 5. - Simple model for idelized concepionl sdies Frnk Lnkei

The Broropic Model: Eqions P ρ f P ρ f Eqion of moion: Conini eqion: Hdrosic eqion: z P Homoeneos incompressile flid, consn densi, hdrosic eqilirim, Cresin coordines, z-ssem, roropic,... z w Frnk Lnkei Frnk Lnkei The Broropic Model: Trnsformions/Approimions A Inerin he hdrosic eqion nd replcin he pressre rdien in he eqion of moion: B Inerin he conini eqion o h nd sin ondr condiions for w here: no oom oporph: h f h f h h h h primiie shllow wer eqions

A QG-pproimion of he eqion of moion ß-plin: B QG-pproimion of he conini eqion h f h f Or: QG orici eqion: f h h h h qsi-eosrophic shllow wer eqions The Broropic Model: Trnsformions/Approimions Frnk Lnkei wih eosrophic sremfncion =h /f : J, wih = Ross Rdis of Deformion = h / /f The Broropic Model: Trnsformions/Approimions qsi-eosrophic shllow wer eqions Frnk Lnkei

The Broropic Model: Trnsformions/Approimions non-dieren shllow wer eqions QG-orici eqion non dieren: Or: J, Frnk Lnkei Assmpion: sole le of eloci m chne wih hih no he direcion:,= Ap<>,,,<>,, p s B Bdp p s I follows: The Broropic Model: Trnsformions/Approimions eqilen roropic model * A p s * * J, wih *=<A > ; <A> = * Vlid for he eqilen roropic leel p* wih: Ap*=<A > picll 6-5hP; minimm dierence Frnk Lnkei

Smmr The Broropic Model: Eqions primiie eqions: h f h f h h h h Qsi-Geosrophic: Non-dieren: Eqilen roropic: J, J, * A p s * * J, Frnk Lnkei * From Eqions o Nmericl Model: Model Desin A The eqions: Here: roropic non-dieren J, B The nmericl mehod - enerl Here: rid poin mehod C The nmericl mehod specific riles, operors, rid, discreizions, work flow, ondr condiions, ec. Frnk Lnkei 5

Broropic non-dieren Model: Nmerics J, J, Pronosic rile: Sremfncion Operors: Deriion in ime: Deriion in spce: Jcoi-Operor: Lplce-Operor nd is inerse: J, Frnk Lnkei Broropic non-dieren Model: Nmerics The Grid: Lon-L rid; one pronosic rile onl -> Arkw A The Grid: i-,j+ i,j+ i+,j+ Grido i,j i-,j i,j i+,j i,j,, i-,j- i,j- i+,j- Frnk Lnkei 6

Broropic non-dieren Model: Nmerics Discreizions Time deriie: Lepfro wih Roer-Asselin filer Three leel scheme; conserie non-dissipie ssem; Compion of nd +Δ weihed eres of +Δ, nd -Δ Clclion role: Corn-Friedrich-Le crierion: / <- γ *. f * *. filer cons. * *. ; e.. γ =. sep d/d = f Δ *- + * sep + Δ d/d = f *- + Frnk Lnkei * Broropic non-dieren Model: Nmerics Discreizions Deriion in spce: cenered differences Grid: 6 = i-,j+ = i,j+ 5 = i+,j+ = i-,j = i,j = i+,j 7 = i-,j- = i,j- 8 = i+,j- Lplcin: cenered differences i, j Frnk Lnkei 7

8 Frnk Lnkei Broropic non-dieren Model: Nmerics Discreizions, J Jcoi-Operor:, J nlicll } { } { } { 7 6 8 5 7 8 6 5 7 8 6 5 7 6 8 5 J J J nmericll: J=J +J +J / Arkw `66 ensroph nd ener conserin 6 = i-,j+ = i,j+ 5 = i+,j+ = i-,j = i,j = i+,j 7 = i-,j- = i,j- 8 = i+,j- Grid: Frnk Lnkei Broropic non-dieren Model: Nmerics Discreizions Inerse Lplcin solion of Poisson-eqion: 6= i-,j+ = i,j+ 5= i+,j+ = i-,j = i,j = i+,j 7 = i-,j- = i,j- 8= i+,j- Grid:, G G G Discree Lplcin: Ierie solion: G / ' ' ω / ωε ' G. esime he error:. oer- correc he error sin lred new les: e.. 'Sccessie Oer-Relion' SOR

Broropic non-dieren Model: Nmerics J, Work flow:. Iniilizion define rid se ondr condiions c se iniil condiions. Time loop compe he rih hnd side endenc Inerse Lplcin = solin Poisson-eqion c compe new ime sep. Finlizion wrie resr files Frnk Lnkei Smmr: Nmerics Eqion: roropic non-dieren Mehod: Grid poin Grid: Arkw A Pronosic rile: sremfncion Time seppin: Lepfro wih filer J, Differenils in spce: cenrl differences Jcoi operor: ener nd ensroph conserin Arkw Inerse Lplcin: 'Sccessie Oer-Relion' SOR Frnk Lnkei 9

Modlr srcre: From he Desin o he Code: The FORTRAN prorm ses of sroines for indiidl model prs: inp op rid definiion deriion in spce Lplcin Jcoi operor Lepfro Eler 'Sccessie Oer-Relion' SOR ondr condiions iniil condiions... ornized nd clled min prorm Frnk Lnkei From he Desin o he Code: The FORTRAN prorm How o prorm? se modles for lol prmeers/riles se nme conenion rel/ineer; lol/locl, ec docmen/commen or code he more he eer r o e fleile se prmeers ec. es s freqen s possile Frnk Lnkei

How o es? From he Desin o he Code: The FORTRAN prorm se simple srcres wih know solions sin,cos o check he deriies se nlic solion o check he dnmics e.. Ross-Hrwiz we R-H we: onl one we nmer k nd l in - nd -direcion:,, e J, i kl c K weswrd propin, mplide nd wenmer conserin Frnk Lnkei The Broropic Model: Bondr Condiions Generl: ech ondr Es, Wes, Norh, Soh wo ondr condiions re needed: nd or sremfncion Ψ nd orici ξ Or model: non dieren roropic orici eqion, rid poin mehod, A-rid, Ψ The rid: Emple: one lonide: NY+ Grid Poin j= NY NY- Here:,NY+ = Chnnel ondries,,,...ny = kie i.e. ondr condiions GP nd NY+ needed Frnk Lnkei

Prescried from d Bondr Condiions: Emples Cclic: A =A NY nd A NY+ =A wih A=, or Ψ, ξ c No flow cross ondr: = NY+ =, i.e. Ψ = Ψ NY+ = cons in, s, NY NY+ NY, NY nd c = nd NY+ = NY fll slip ondr condiion, i.e. ξ,ny+ =, s!, NY, NY c,ny+ = no slip ondr condiion, i.e. in or model, NY, NY, NY s j j/ j/ nd /, NY/ /, NY/! nd /, NY/, NY, NY Frnk Lnkei Bondr Condiions: Smmr - Prescried - Cclic - Perpendiclr: No flow cross ondr - Tnenil: No slip nd fll slip Frnk Lnkei

Ellipic Pril Differenil Eqions: Solin Poisson- or Helmholz-Eqion T T T T T c d e f hperolic: -c > prolic: -c = ellipic: -c < Ellipic eqions: ondr le prolem Lplce: Poisson: G, Helmholz: G, G, λ known; Θ wned e.. G=orici; Θ =sremfncion Frnk Lnkei Solin Poisson-Eqion: Specrl Mehod G, Sr: Simple form of he inerse Lplce operor in specrl spce Forier: ˆ k, l Gˆ k, l K Gˆ k, l Gˆ k, l k l wih G ˆ k, l, ˆ k, l = specrl rnsformed of G, nd Θ, => Solion of : k = we nmer in l = we nmer in Noe: Trionomeric fncions Forier, plne or Leendere polnomils sphere re Eienfncions of he Lplce operor, i.e. rnsform G, o specrl spce compe ˆ k, l from rnsform ˆ k, l o rid poin spce Frnk Lnkei

Solin Poisson-Eqion: Grid Poin Mehod! G G 6 5 7 8 Sr: discreizion of, G rid poin nominion For poin : NOTE: rid poins inerdependen -> no direc solion! Frnk Lnkei Solin Poisson-Eqion: Grid Poin Mehod: Jcoi Mehod G G Solion Ierion Jcoi Mehod: Discree Poisson-eqion:. choose iniil field e.. Θ =. or Θ = old known les. compe error ε for ech rid poin: G comped from emple: wih Θ = : ε = G. correc ech Θ wih error ε : / / ε ' G. conine wih. nil he error is sfficienl smll ien n deqe error norm Prolem: er slow nd, herefore, no fesile! Frnk Lnkei

Solin Poisson-Eqion: Gß-Seidel Mehod nd SOR Jcoi Mehod: ' G / Improemen: Gß-Seidel Mehod ' ' ' G / similr o Jcoi sin lred known comped new les Θ,Θ dne: fesile fs enoh 6 5 7 8 More improemen: 'Sccessie Oer-Relion' SOR ' ωε / ω ' ' G / similr o Gß-Seidel oer correc wih < ω < dne: fs disdne: ω needs o e chosen r nd error Frnk Lnkei rid poins Performnce NN Grid: Solin Poisson-Eqion: Grid Poin Mehod Jcoi: N p/ ierions o decrese he iniil error fcor p Gß-Seidel: N p/ ierions o decrese he iniil error fcor p.5 Jcoi. SOR: N p/ ierions o decrese he iniil error fcor p o /N Gß- Seidel Frher improemen: mlirid mehods Ansz: Fser conerence of ierion for lrer scles => Mlirid mehod emple:. inerpole G, nd Θ, o corse rid. sole iere eqion on corse rid e.. SOR. inerpole solion from o finer rid. sole iere eqion on finer rid e.. SOR 5. repe o nil finl resolion rid nd ccrc is reched Frnk Lnkei 5

Ellipic Pril Differenil Eqions Smmr Ellipic eqions: Lplce, Poisson, Helmholz Specrl mehod: Eienfncions Grid poin mehods: Jcoi, Gß-Seidel, SOR Mlirid mehod Frnk Lnkei 6