Large-scale atmospheric circulation, semi-geostrophic motion and Lagrangian particle methods

Similar documents
A Hamiltonian Numerical Scheme for Large Scale Geophysical Fluid Systems

The semi-geostrophic equations - a model for large-scale atmospheric flows

2.5 Shallow water equations, quasigeostrophic filtering, and filtering of inertia-gravity waves

Stochastic Particle Dynamics for Unresolved Degrees of Freedom. Sebastian Reich in collaborative work with Colin Cotter (Imperial College)

The Hamiltonian Particle-Mesh Method for the Spherical Shallow Water Equations

Evaluation of three spatial discretization schemes with the Galewsky et al. test

Geostrophic and Quasi-Geostrophic Balances

Dynamics Rotating Tank

Curves in the configuration space Q or in the velocity phase space Ω satisfying the Euler-Lagrange (EL) equations,

Resonant excitation of trapped coastal waves by free inertia-gravity waves

The Geometry of Euler s equation. Introduction

The Shallow Water Equations

7 Balanced Motion. 7.1 Return of the...scale analysis for hydrostatic balance! CSU ATS601 Fall 2015

Computational challenges in Numerical Weather Prediction

Understanding inertial instability on the f-plane with complete Coriolis force

Comparison of variational balance models for the rotating shallow water equations

Hamiltonian flow in phase space and Liouville s theorem (Lecture 5)

Comparison of variational balance models for the rotating shallow water equations

Hamiltonian particle-mesh simulations for a non-hydrostatic vertical slice model

Chapter 2. The continuous equations

Balanced models in Geophysical Fluid Dynamics: Hamiltonian formulation, constraints and formal stability

Massachusetts Institute of Technology Department of Physics. Final Examination December 17, 2004

Chapter 9. Geostrophy, Quasi-Geostrophy and the Potential Vorticity Equation

Lecture 25: Ocean circulation: inferences from geostrophic and thermal wind balance

Discrete Dirac Mechanics and Discrete Dirac Geometry

Circulation and Vorticity

= vorticity dilution + tilting horizontal vortices + microscopic solenoid

Barotropic geophysical flows and two-dimensional fluid flows: Conserved Quantities

Semi-implicit methods, nonlinear balance, and regularized equations

Curved spacetime tells matter how to move

Uniformly accurate averaging numerical schemes for oscillatory evolution equations

Model equations for planetary and synoptic scale atmospheric motions associated with different background stratification

+ ω = 0, (1) (b) In geometric height coordinates in the rotating frame of the Earth, momentum balance for an inviscid fluid is given by

M.Sc. in Meteorology. Numerical Weather Prediction Prof Peter Lynch

Physics 5153 Classical Mechanics. Canonical Transformations-1

How is balance of a forecast ensemble affected by adaptive and non-adaptive localization schemes?

Manifolds in Fluid Dynamics

Modified Equations for Variational Integrators

Nonlinear Balance on an Equatorial Beta Plane

New variables in spherical geometry. David G. Dritschel. Mathematical Institute University of St Andrews.

Ergodicity in data assimilation methods

Mixed Mimetic Spectral Elements for Geophysical Fluid Dynamics

We start with some important background material in classical and quantum mechanics.

Physical Dynamics (SPA5304) Lecture Plan 2018

Pendulum with a vibrating base

M3-4-5 A16 Notes for Geometric Mechanics: Oct Nov 2011

Lecture 1: Water waves and Hamiltonian partial differential equations

Hamiltonian flows, cotangent lifts, and momentum maps

Homework 2: Solutions GFD I Winter 2007

A Particle-Mesh Method for the Shallow Water Equations near Geostrophic Balance Jason Frank Λ Sebastian Reich y July 25, 2001 Abstract In this paper w

Lecture 1: Oscillatory motions in the restricted three body problem

CP1 REVISION LECTURE 3 INTRODUCTION TO CLASSICAL MECHANICS. Prof. N. Harnew University of Oxford TT 2017

( ) (9.1.1) Chapter 9. Geostrophy, Quasi-Geostrophy and the Potential Vorticity Equation. 9.1 Geostrophy and scaling.

M3/4A16. GEOMETRICAL MECHANICS, Part 1

Jupiter s Red Spot. Luke McGuire Program in Applied Mathematics University of Arizona. May 21, 2009

PAPER 333 FLUID DYNAMICS OF CLIMATE

BACKGROUND IN SYMPLECTIC GEOMETRY

( ) = 1005 J kg 1 K 1 ;

Chapter 1. Governing Equations of GFD. 1.1 Mass continuity

The kinetic equation (Lecture 11)

Models in Geophysical Fluid Dynamics in Nambu Form

Topics in Relativistic Astrophysics

The equation we worked with for waves and geostrophic adjustment of a 1-layer fluid is η tt

Atmospheric dynamics and meteorology

EART164: PLANETARY ATMOSPHERES

Chapter 5. Shallow Water Equations. 5.1 Derivation of shallow water equations

Governing Equations and Scaling in the Tropics

HAMILTON S PRINCIPLE

APPENDIX B. The primitive equations

Hamiltonian Dynamics

Gradient Flows: Qualitative Properties & Numerical Schemes

Fluid Dynamics. Massimo Ricotti. University of Maryland. Fluid Dynamics p.1/14

M2A2 Problem Sheet 3 - Hamiltonian Mechanics

Internal boundary layers in the ocean circulation

Sobolev regularity for the Monge-Ampère equation, with application to the semigeostrophic equations

Lattice Boltzmann Method

In two-dimensional barotropic flow, there is an exact relationship between mass

GEOMETRIC QUANTIZATION

The Hydrostatic Approximation. - Euler Equations in Spherical Coordinates. - The Approximation and the Equations

g (z) = 1 (1 + z/a) = 1

Numerical Approximation of Phase Field Models

Lecture 4: Birkhoff normal forms

Gauge Fixing and Constrained Dynamics in Numerical Relativity

Treatment of Earth as an Inertial Frame in Geophysical Fluid Dynamics. Dana Duke

Hamiltonian. March 30, 2013

Synchro-Betatron Motion in Circular Accelerators

By convention, C > 0 for counterclockwise flow, hence the contour must be counterclockwise.

(Most of the material presented in this chapter is taken from Thornton and Marion, Chap. 7) p j . (5.1) !q j. " d dt = 0 (5.2) !p j . (5.

2 Canonical quantization

where P a is a projector to the eigenspace of A corresponding to a. 4. Time evolution of states is governed by the Schrödinger equation

A Strategy for the Development of Coupled Ocean- Atmosphere Discontinuous Galerkin Models

Canonical transformations (Lecture 4)

GFD 2012 Lecture 1: Dynamics of Coherent Structures and their Impact on Transport and Predictability

Lecture I: Constrained Hamiltonian systems

The Equations of Motion in a Rotating Coordinate System. Chapter 3

Electric and Magnetic Forces in Lagrangian and Hamiltonian Formalism

CHAPTER 4. Basics of Fluid Dynamics

Some aspects of the Geodesic flow

Parallel-in-time integrators for Hamiltonian systems

Caltech Ph106 Fall 2001

Transcription:

Large-scale atmospheric circulation, semi-geostrophic motion and Lagrangian particle methods Colin Cotter (Imperial College London) & Sebastian Reich (Universität Potsdam)

Outline 1. Hydrostatic and semi-geostrophic approximation 2. Shallow water equations (a) Scaling limits (b) Semi-geostrophic approximation (c) Summary of theoretical approaches 3. Single particle models 4. Lagrangian particle methods and continuum limit References: R Salmon Lectures on geophysical fluid dynamics, M Cullen A mathematical theory of large-scale atmosphere/ocean flow, CJ Cotter & S Reich Semi-geostrophic particle motion and exponentially accurate normal forms.

1. Hyrostatic and semi-geostrophic approximation Euler s equations for a rotating fluid in Cartesian geometry are given by Du Dt + fk u + 1 p + gk ρ = 0, ρ t + (ρu) = 0, θ t + u θ = 0, where u R 3 is the velocity (wind) field, θ is the potential temperature, k = (0, 0, 1) T, f = 2Ω sin φ 0 is the Coriolis parameter, g is the gravitational constant, the ideal gas law becomes θ = T (p 0 /p) R/cp, and material time derivative is df dt := f t + u f.

A good model for large scale circulations is provided by the hydrostatic and semi-geostrophic (SG) model: Du g Dt + fk u + 1 p + gk ρ = 0, ρ t + (ρu) = 0, θ t + u θ = 0, with the geostrophic wind approximation and fu g = 1 ρ u g = [ u g v g 0 ] T p y, fv g = + 1 ρ p x. In northern hemisphere: Stand with your back to the wind, pressure increases to the right.

2. The shallow water equations A single layer approximation is provided by the shallow water equations (SWE): Du fv = g Dt x (h s + η), Dv + fu = g Dt y (h s + η), ( (ηu) η t = x + (ηv) y with material time derivative D Dt = t + u x + v y. Here η is the layer depth, h S is the surface orography, g is the gravitational constant, and f is twice the Earth s angular velocity. )

3. Scaling limits and SG approximation We non-dimensionalize the equations by using scaled variables (denoted with a dash) as follows (x, y) = L(x, y ), t = ( ) L Upon introducing u = (u, v ) T, J 2 = Ro = U fl U t, (u, v) = U(u, v ), η = Hη. ( 0 1 1 0 (Rossby number), F r = U gh ), (Froude number), we obtain the scaled shallow water equations (h s = 0) Du Dt = Ro 1 J 2 u F r 2 η, η t = (η u ).

The semi-geostrophic (SG) scaling regime is ε = F r 2 = Ro 0. This regime is observed for global atmospheric flow patterns. It follows that ε Du Dt = J 2 u η and approximate geostrophic wind balance J 2 u η follows for ε 0 and bounded time-derivatives, i.e., Du /Dt M. Defining u g = J 2 η, we obtain the SG equations ε Du g Dt = J 2u η, η = (η u ).

Historical comments: A first mathematical use of the geostrophic wind approximation goes back to Charney (quasi-geostrophic approximation) and Eliasen (semi-geostrophic (SG) approximation) 1947-1949. The importance of SG to frontogenesis was discovered by Hoskins (1972) who also formulated a simplifying coordinate transformation. Its link to geometric PDEs such as the Monge-Ampere equations was pointed out by Cullen & Purser (1987). Alternatively, Salmon (1985) has studied asymptotic expansions and coordinate transformations on the level of the Lagrangian variational principle. Lorenz studied the existence and non-existence of slow manifolds (1992) with implications to data assimilation and initialization.

4. The single fluid-particle picture Instead of investigating the full SWEs, we consider the following simpler model problem (Gottwald & Oliver, Cotter & Reich). We assume that the layer depth µ(εt, x, y) is a given function of time t and space x = (x, y) T. We may then investigate the motion of a single fluid parcel with coordinates q = (q x, q y ) T R 2. The corresponding Newtonian equations of motion are given by ε d2 q x dt 2 = + dq y dt µ q x (εt, q x, q y ), ε d2 q y dt 2 = dq x dt µ q y (εt, q x, q y ),

We next rescale time and introduce the new time-scale τ = ε t. We denote time derivatives with respect to τ by overdot, e.g., dq x /dτ = q x. We also introducue the momentum p = (p x, p y ) T R 2 and obtain ṗ x = +p y ε µ qx (τ, q x, q y ), ṗ y = p x ε µ qy (τ, q x, q y ), q x = p x, q y = p y. These equations may be expressed in a more compact form: ṗ = J 2 p ε µ(τ, q), ( ) 0 1 J 2 =, 1 0 q = p.

The associated SG equations are given by ṗ g = J 2 p ε µ(τ, q), q = p, with geostrophic wind p g = εj 2 µ(τ, q). For time-independent µ (which we assume from now on), the energy is preserved. The Hoskins transform E = 1 2 u g 2 + εµ(q) q ε = q + ε µ(q) = q + J 2 p g leads to the following equation in the transformed variable q ε : q ε = εj 2 µ(q).

An important observation is that one may view Hoskins transformation as an energy minimization problem in q for given q ε : E qε (q) = 1 2 q ε q 2 + εµ(q). The SG model in transformed variables can be derived from the Lagrangian functional [ 1 L = 2 q ε q 2 + εµ(q) + 1 ] 2 qt ε J 2q ε.

Let us reconsider the energy minimization problem and denote the induced map by q = s(q ε ) with inverse t = s 1. Hence R2 E t(q) (q) da(q) = 1 R 2 2 t(q) q 2 da(q) + C = with ν = s and C = ε R 2 µ(q)da(q). R 2 1 2 q ε s(q ε ) 2 ν da(q ε ) + C This is an optimal transport/coupling problem of a measure dµ 1 = ν da(q ε ) into the Lebesgue measure dµ 2 = da(x) on R 2 in the Wasserstein metric W 2 (µ 1, µ 2 ) = inf λ Γ(µ 1,µ 2 ) R 2 R 2 x y 2 dλ(x, y).

5. Lagrangian and Hamiltonian framework Hamiltonian picture. We introduce the non-canonical symplectic structure operator J = ( J2 I 2 I 2 0 2 so that the equations become with Hamiltonian ) ż = J H 0 (z), R 4 4, H 0 (z) = K(p) + εv (q), K(p) := 1 2 pt p, V (q) := µ(q), and phase space variable z = (p T, q T ) T R 4.

Lagrangian picture. Another approach is to rewrite the system of first-order equations as a second-order equation q J 2 q + ε µ(q) = 0. This is the Euler-Lagrange equation for the Lagrangian functional [ 1 L = dτ 2 q 2 + 1 ] 2 qt J 2 q εµ(q). One may alternatively work with the degenerate Lagrangian [ ( L = dτ p 1 ) T 2 J 2q q H 0 (q, p)].

6. The variational approach to semi-geostrophy Rick Salmon s derivation of semi-geostrophic models starts from the assumption that we may replace p by the geostrophically balanced p g = εj 2 µ(q) in the degenerate Lagrangian formulation. Under this assumption, we may formally collect terms of equal order in ε and rewrite the Lagrangian functional as L = dτ [ εl 0 + ε 2 L 1 ], for suitably chosen Lagrangian densities L 0 and L 1. ignore the O(ε 2 ) term. We then

To improve this approximation, we introduce transformed coordinates q ε via q = ψ ε (q ε ) = q ε + εf 1 (q ε ) + O(ε 2 ). Following Rick Salmon s and Marcel Oliver s work, we set F 1 (q ε ) = 1 2 µ(q ε) + λ µ(q ε ). Upon dropping O(ε 3 ) terms, we obtain the Lagrangian L ε = dτ { 1 2 qt ε J 2 q ε εµ(q ε ) + [ ] } 1 ε 2 + λ µ(q ε ) T J 2 q ε ε 2 λ µ(q ε ) 2.

One can set λ = 0, but the choice λ = 1/2 is of particular interest as it is close (but not identical) to Hoskins transformation and to Rick Salmon s large-scale semi-geostrophic approximation. The associated reduced equations of motion J 2 q ε = ε {µ(q ε ) ε2 } µ(q ε) 2 can be derived from the Lagrangian functional [ 1 L lsg = dτ 2 qt ε J 2 q ε εµ(q ε ) + ε2 2 µ(q ε) 2 ]. These equations look like a Taylor expanded version of Hoskin s SG equation J 2 q ε = ε µ(q), q ε = q + ε µ(q).

7. The normal form approach to semi-geostrophy A more complete picture of the dynamics can be obtained from the Hamiltonian side of things and normal form theory. (Cotter & Reich, 2006) Our aim is to find a canonical near-identity change of coordinates Ψ n so that where H n = H 0 Ψ n = K + εg n + ε n+1 R n, (1) {G n, K} = 0, (2) with {, } being the Poisson bracket obtained from J.

A few key results from Cotter and Reich, 2006. Corollary. Let us assume that the momentum p = q satisfies p(0) = εj 2 µ(q(0)) + O(ε 2 ) at initial time τ = 0, then p(τ) = εj 2 µ(q(τ)) + O(ε 2 ) for all τ < e c/2ε provided the potential V = µ is real-analytic. This means that provided the system is within O(ε 2 ) of the geostrophically balanced state initially, it will stay there for exponentially long time intervals.

If p ε (0) = 0, (i.e., we start on the slow manifold ) then we get the slow equation given in the following corollary: Corollary. If p ε (0) = 0 then for all τ < e c/2ε. J 2 q ε = ε q G(0, q ε ) + O(e c/2ε ), Corollary. To leading order the symplectic change of coordinates reduces on the slow manifold to Hoskins/Salmon tranformation (i.e., λ = 1/2 in Salmon s formula).

8. A step towards the continuum limit So far we have assumed that the fluid depth µ is a given function of space and time and derived equations of motion for a single fluid parcel. Now we consider a numerical approximation for µ of the form µ(t, x) = N i=1 m i ψ( x q i (t) ) in terms of N moving fluid parcels, where q i (t) R 2 denotes the location of the ith fluid parcel at time t with mass m i and shape function ψ(r) 0. The above layer-depth approximation provides the starting point for smoothed particle hydrodynamics (SPH).

Each fluid parcel moves under the Newtonian equations of motion d dt p i = Ro 1 J 2 p i F r 2 x µ(t, x) x=qi, d dt q i = p i After setting F r 2 = Ro = ε and a rescaling of time, these equations become ṗ i = J 2 p i ε x µ(x, t) x=qi, q i = p i.

Without restriction of generality, we may also assume that all fluid parcels carry a constant mass m i = m. Then the equations posses the Hamiltonian function H sph (z) = K(p) + εv (q) = N i=1 1 2 p i 2 + ε m 2 N i,j ψ( q i q j ), Note that a finite fluid depth µ implies that the particle masse m approach zero as the number of particles N. More precisely, m N = const. as N. For a given basis function ψ, the SPH method converges for N to solutions of a regularized set of SWEs (Oelschläger, 1991; Di Lisio et al, 1998). Global existence and uniqueness of solutions follows.

Main findings (Cotter & Reich): 1. The single particle theory goes through for fixed N and ε 0 as well. 2. The estimates do not deteriorate for fixed ψ with increasing N since there is (i) only a single fast frequency determined by f = constant and (ii) m N = constant as N (conservation of total mass). 3. Normal form theory implies that there is hardly any tranfer between potential and kinetic energy. Particles may however exchange their kinetic energy contributions. 4. The analysis collapses however in case the basis functions ψ approach a Dirac delta function as N. But it is perhaps feasible for sufficiently regular initial conditions.

Exchange of kinetic energy between two particles:

A particle simulation of barotropic instability:

9. Summary The semi-geostrophic approximation is one of the most useful theoretical tools in large-scale meteorology (e.g., frontogenesis). A lot of theory has been developed around the SG equations and interesting links to various fields have been made. We have explained some of the main points in terms of a simple single particle model. Hamiltonian normal form theory allows for arbitrarily accurate SG models in terms of a regularized set of fluid equations and is applicable to numerical particle methods. Frontogenesis is still rather poorly approximated by todays NWP codes (Cullen). Can better methods be devised using SG explicitly (Cullen) or implicitly (moving mesh methods (Budd); particle methods)?