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Semi-Lagrangian Approach to 4D-Discrete Linear Equations of Atmospheric Dynamics with Arbitrary Stratification and Orography Rein R ˜ o ˜ om , Marko Zirk Tartu University, Estonia [email protected], [email protected] 1
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Page 1: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Semi-Lagrangian Approach to4D-Discrete Linear Equations

of Atmospheric Dynamicswith Arbitrary Stratification

and Orography

Rein Room , Marko Zirk

Tartu University, Estonia

[email protected], [email protected]

1

Page 2: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

1 Introduction

A method for numerical solu-tion of non-hydrostatic linearequations of atmospheric dynam-ics for horizontally homogeneousbut otherwise arbitrary refer-ence state and arbitrary orog-raphy is introduced.

1

Page 3: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

The developed solution is

4D-discrete (x,y,z,t),spectral,

semi-implicit,semi-Lagrangian(SISL) scheme

for both stationary and nonsta-tionary cases

2

Page 4: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Motivation

Originally this algorithm was de-veloped for testing and qualitycheck of nonhydrostatic adia-batic kernels of SISL-based NWPmodels (HIRLAM, in particu-lar)

3

Page 5: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Testing NH HIRLAM

260220

T

600

0

1000

800

400

200

4020

U

U, m/sT, Kp,hPa

Reference temperature and wind

K/km

K/km

γ=4.5

γ=8.0

0

200

400

600

800

10000 20 40 60 80 100 120 140

p, h

Pa

X, km

HIRLAM, Vz: D(Vz)=0.05m/s,ax=3km, h=100m, MLEV=100,dx=.55km,dt=30s,600 steps

260220

T

600

0

1000

800

400

200

4020

U

U, m/sT, Kp,hPa

Reference temperature and wind

K/km

K/km

γ=4.5

γ=8.0

0

200

400

600

800

10000 20 40 60 80 100 120 140

p, h

Pa

X, km

Vz: D(Vz)=0.05m/s; U,T-HIRLAM,h=100m,ax= 3km,dx=.55km,MLEV=200,dz=100m

4

Page 6: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

The actual domain of applica-tion is much wider:

Investigation of specific details of oro-graphic flows for complex wind andtemperature stratification.

Investigation of non-stationary devel-opment and buoyant instability.

Investigation of the impact of discretiza-tion to the solution quality.

5

Page 7: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

2 Model description

Initial continuous equations: Lin-ear, NH pressure-coordinate equa-tions with filtered internal sound-waves(Miller-Pearce-White model)

6

Page 8: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Linearization with respect toT (p) , U(p), ps(x, y)

7

Page 9: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Discretization:

3D staggering with constant hor-izontal grid-step ∆x = ∆y andvariable vertical step ∆pk

Two time level,semi-implicit,semi-Lagrangian time scheme

8

Page 10: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Solution in the form of discreteFourier series

3D (x,y,t) presentation of dis-crete solution:

Ψnijk =

qrsΨs

qrkei(ηx

q i+ηyr j−ds

qrkn),

where

Ψ = {T ′, u, v, ω, ϕ}

9

Page 11: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Discrete spectral equations forspectral amplitudes arrivefrom which a

one-dimensional wave equation

follows for ω-velocity.

10

Page 12: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

The wave equation is solved forboundary conditions :

Free-slip condition on the sur-face

Radiative boundary conditionon the top

11

Page 13: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

A special feature of the waveequation:

As normal mode intrinsic fre-quency ν depends on height, thewave-equation coefficients are func-tions of both ν and ∆ν/∆p

12

Page 14: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

In stationary case height-dependentν presents an ordinary thing;

In nonstationary case it involvesa dispersion equation which isa nonlinear first order differen-tial equation with respect to ν

13

Page 15: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Special: Solution of wave equa-tion is designed as a cumulativeproduct of decrease factors

ωk =k∏

j=1cj, |cj| < 1,

which results in an effective nu-merical algorithm, where solu-tion ωk is alwas an exponent func-tion of a complex argument.

14

Page 16: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

SOLUTION EXAMPLES

I.

Stationary 2D orographic flowover 1D mountain ridge

15

Page 17: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Homogeneous stratification, U = 10 m/s, T = 280 KMountain ridge: ax = 2 km, h = 200 m

0

5

10

15

20

25

30

0 50 100 150 200 250

Z,

km

X, km

Vz: u = 10 m/s, T = 265 K, h = 0.2 km, ax = 2 km, zlev = 300, xlev = 1024, ∆z = 0.1 km, ∆x = 0.4 km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

16

Page 18: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Refraction and reflection on tropopause.U = 12 m/s, γ = 6.5 K/km;

0

12

UT

Z, km30

K/kmγ= 6.5

U, m/s105

T, K160 220 280

0

5

10

15

20

25

30

0 20 40 60 80 100 120 140 160 180 200

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

17

Page 19: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Refraction and reflection on tropopause.U = 12 m/s, γ = 8.5 K/km;

0

12

UT

Z, km30

U, m/s105

T, K160 220 280

K/kmγ= 8.5

0

5

10

15

20

25

30

0 50 100 150 200 250

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

18

Page 20: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Refraction and reflection on tropopause in the case oflinear wind shear in the troposphere.U = 12-15 m/s, γ = 6.5 K/km;

0

12

UT

Z, km30

K/kmγ= 6.5

U, m/sT, K160 220 280 6 12

0

5

10

15

20

25

30

0 50 100 150 200 250 300 350

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

19

Page 21: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Refraction and reflection on tropopause in the case oflinear wind shear in troposphere.U = 12-24 m/s, γ = 6.5 K/km;

Z, km

0

12

30

UT

U, m/sT, K160 220 280 10 20

K/kmγ=6.5

0

5

10

15

20

25

30

0 100 200 300 400 500 600 700 800 900

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

20

Page 22: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Hyperbolic wind, U = 10-30 m/s, γ = 6.5 K/km

30

Z, km

0

12

30

UT

U, m/sT, K160 220 280 10 20

K/kmγ=6.5

0

5

10

15

20

25

30

0 100 200 300 400 500 600 700 800

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

21

Page 23: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

Vertical velocity waves

Hyperbolic wind, U = 10-30 m/s, γ = 6.5 K/km;

30

Z, km

0

12

30

UT

U, m/sT, K160 220 280 10 20

K/kmγ=6.5

0

5

10

15

20

25

30

20 40 60 80 100 120 140 160 180 200

Z, km

X , km

Green - positive, red - negative velocity; ∆Vz = 0.1 m/s

22

Page 24: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

SOLUTION EXAMPLES

II.

Baroclinic instability oflong waves

23

Page 25: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

E-folding time of normal modes in case ofconstant wind shear dU/dz = 2 m/s/km

Z = 0.0: τ1= 28 h, ∆τ= 6h

1.00.1

.01 X

1.00.1

.01.001

Y

24

48

72

96

τ ,h

X = Hkx

Y = Hky

Z = Hkz=0

H = 10 km- scale height

24

Page 26: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

As previous Fig., except Z = 1 (Lz ∼ 10 km)

Z = 1.0: τ1= 64 h, ∆τ= 6h

1.00.1

.01 X1.0

0.1.01

Y

60

80

100

120

τ ,h

25

Page 27: Semi-Lagrangian Approach to 4D-Discrete Linear Equations ...meteo.physic.ut.ee/~room/papers/2005/Room_Zirk_EMS2005.pdf · Rein.Room@ut.ee, Marko.Zirk@ut.ee 1. 1 Introduction A method

3 CONCLUSIONS

Though the numerical scheme was initially developed for testpurpose, its actual application area is wider:

Investigation of specific details of orographic flows forcomplex wind and temperature stratification:

Impact of tropopause, discontinuity of the Brunt-Vaisala fre-quency, wind shear (including directional shear), boundarylayer

Investigation of non-stationary development of lineardisturbances, including buoyant instability study

Investigation of the impact of discretization to numer-ical solution quality:

Vertical discretization (variable ∆z)

Accessible time step size and numerical stability issues

26


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