Skip to content

Commit

Permalink
Merge pull request #313 from apaloczy/master
Browse files Browse the repository at this point in the history 
Option to specify topographic PV large-scale gradients in `MultiLayerQG`
  • Loading branch information
@apaloczy
apaloczy committed Dec 22, 2022
2 parents 85a79b4 + d93251f commit 386fd9a
Show file tree
Hide file tree
Showing 4 changed files with 184 additions and 115 deletions.
2 changes: 1 addition & 1 deletion Project.toml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ name = "GeophysicalFlows"
uuid = "44ee3b1c-bc02-53fa-8355-8e347616e15e"
license = "MIT"
authors = ["Navid C. Constantinou <[email protected]>", "Gregory L. Wagner <[email protected]>", "and co-contributors"]
version = "0.15.0"
version = "0.15.1"

[deps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
Expand Down
151 changes: 83 additions & 68 deletions src/multilayerqg.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -28,28 +28,29 @@ nothingfunction(args...) = nothing

"""
Problem(nlayers :: Int,
dev = CPU();
nx = 128,
ny = nx,
Lx = 2π,
Ly = Lx,
f₀ = 1.0,
β = 0.0,
g = 1.0,
U = zeros(nlayers),
H = 1/nlayers * ones(nlayers),
ρ = Array{Float64}(1:nlayers),
eta = nothing,
μ = 0,
ν = 0,
nν = 1,
dt = 0.01,
stepper = "RK4",
calcFq = nothingfunction,
stochastic = false,
linear = false,
aliased_fraction = 1/3,
T = Float64)
dev = CPU();
nx = 128,
ny = nx,
Lx = 2π,
Ly = Lx,
f₀ = 1.0,
β = 0.0,
g = 1.0,
U = zeros(nlayers),
H = 1/nlayers * ones(nlayers),
ρ = Array{Float64}(1:nlayers),
eta = nothing,
topographic_pv_gradient = (0, 0),
μ = 0,
ν = 0,
nν = 1,
dt = 0.01,
stepper = "RK4",
calcFq = nothingfunction,
stochastic = false,
linear = false,
aliased_fraction = 1/3,
T = Float64)
Construct a multi-layer quasi-geostrophic problem with `nlayers` fluid layers on device `dev`.
Expand All @@ -70,7 +71,8 @@ Keyword arguments
- `U`: The imposed constant zonal flow ``U(y)`` in each fluid layer.
- `H`: Rest height of each fluid layer.
- `ρ`: Density of each fluid layer.
- `eta`: Topographic potential vorticity.
- `eta`: Periodic component of the topographic potential vorticity.
- `topographic_pv_gradient`: The ``(x, y)`` components of the topographic PV large-scale gradient.
- `μ`: Linear bottom drag coefficient.
- `ν`: Small-scale (hyper)-viscosity coefficient.
- `nν`: (Hyper)-viscosity order, `nν```≥ 1``.
Expand All @@ -80,44 +82,45 @@ Keyword arguments
- `stochastic`: `true` or `false` (default); boolean denoting whether `calcF` is temporally stochastic.
- `linear`: `true` or `false` (default); boolean denoting whether the linearized equations of motions are used.
- `aliased_fraction`: the fraction of high-wavenumbers that are zero-ed out by `dealias!()`.
- `T`: `Float32` or `Float64`; floating point type used for `problem` data.
- `T`: `Float32` or `Float64` (default); floating point type used for `problem` data.
"""
function Problem(nlayers::Int, # number of fluid layers
dev = CPU();
function Problem(nlayers::Int, # number of fluid layers
dev = CPU();
# Numerical parameters
nx = 128,
ny = nx,
Lx = 2π,
Ly = Lx,
nx = 128,
ny = nx,
Lx = 2π,
Ly = Lx,
# Physical parameters
f₀ = 1.0, # Coriolis parameter
β = 0.0, # y-gradient of Coriolis parameter
g = 1.0, # gravitational constant
U = zeros(nlayers), # imposed zonal flow U(y) in each layer
H = 1/nlayers * ones(nlayers), # rest fluid height of each layer
ρ = Array{Float64}(1:nlayers), # density of each layer
eta = nothing, # topographic PV
f₀ = 1.0, # Coriolis parameter
β = 0.0, # y-gradient of Coriolis parameter
g = 1.0, # gravitational constant
U = zeros(nlayers), # imposed zonal flow U(y) in each layer
H = 1/nlayers * ones(nlayers), # rest fluid height of each layer
ρ = Array{Float64}(1:nlayers), # density of each layer
eta = nothing, # periodic component of the topographic PV
topographic_pv_gradient = (0, 0), # tuple with the ``(x, y)`` components of topographic PV large-scale gradient
# Bottom Drag and/or (hyper)-viscosity
μ = 0,
ν = 0,
nν = 1,
μ = 0,
ν = 0,
nν = 1,
# Timestepper and equation options
dt = 0.01,
stepper = "RK4",
calcFq = nothingfunction,
stochastic = false,
linear = false,
dt = 0.01,
stepper = "RK4",
calcFq = nothingfunction,
stochastic = false,
linear = false,
# Float type and dealiasing
aliased_fraction = 1/3,
T = Float64)
aliased_fraction = 1/3,
T = Float64)

if dev == GPU() && nlayers > 2
@warn """MultiLayerQG module is not optimized on the GPU yet for configurations with
3 fluid layers or more!
See issues on Github at https://github.com/FourierFlows/GeophysicalFlows.jl/issues/112
and https://github.com/FourierFlows/GeophysicalFlows.jl/issues/267.
To use MultiLayerQG with 3 fluid layers or more we suggest, for now, to restrict running
on CPU."""
end
Expand All @@ -134,7 +137,7 @@ function Problem(nlayers::Int, # number of fluid layers

grid = TwoDGrid(dev; nx, Lx, ny, Ly, aliased_fraction, T)

params = Params(nlayers, g, f₀, β, ρ, H, U, eta, μ, ν, nν, grid; calcFq)
params = Params(nlayers, g, f₀, β, ρ, H, U, eta, topographic_pv_gradient, μ, ν, nν, grid; calcFq)

vars = calcFq == nothingfunction ? DecayingVars(grid, params) : (stochastic ? StochasticForcedVars(grid, params) : ForcedVars(grid, params))

Expand Down Expand Up @@ -168,6 +171,8 @@ struct Params{T, Aphys3D, Aphys2D, Aphys1D, Atrans4D, Trfft} <: AbstractParams
U :: Aphys3D
"array containing the topographic PV"
eta :: Aphys2D
"tuple containing the ``(x, y)`` components of topographic PV large-scale gradient"
topographic_pv_gradient :: Tuple{T, T}
"linear bottom drag coefficient"
μ :: T
"small-scale (hyper)-viscosity coefficient"
Expand Down Expand Up @@ -205,8 +210,10 @@ struct SingleLayerParams{T, Aphys3D, Aphys2D, Trfft} <: AbstractParams
β :: T
"array with imposed constant zonal flow ``U(y)``"
U :: Aphys3D
"array containing topographic PV"
"array containing the periodic component of the topographic PV"
eta :: Aphys2D
"tuple containing the ``(x, y)`` components of topographic PV large-scale gradient"
topographic_pv_gradient :: Tuple{T, T}
"linear drag coefficient"
μ :: T
"small-scale (hyper)-viscosity coefficient"
Expand Down Expand Up @@ -246,8 +253,10 @@ struct TwoLayerParams{T, Aphys3D, Aphys2D, Trfft} <: AbstractParams
H :: Tuple
"array with imposed constant zonal flow ``U(y)`` in each fluid layer"
U :: Aphys3D
"array containing topographic PV"
"array containing periodic component of the topographic PV"
eta :: Aphys2D
"tuple containing the ``(x, y)`` components of topographic PV large-scale gradient"
topographic_pv_gradient :: Tuple{T, T}
"linear bottom drag coefficient"
μ :: T
"small-scale (hyper)-viscosity coefficient"
Expand Down Expand Up @@ -297,7 +306,7 @@ function convert_U_to_U3D(dev, nlayers, grid, U::Number)
return A(U_3D)
end

function Params(nlayers, g, f₀, β, ρ, H, U, eta, μ, ν, nν, grid; calcFq=nothingfunction, effort=FFTW.MEASURE)
function Params(nlayers, g, f₀, β, ρ, H, U, eta, topographic_pv_gradient, μ, ν, nν, grid; calcFq=nothingfunction, effort=FFTW.MEASURE)
dev = grid.device
T = eltype(grid)
A = device_array(dev)
Expand All @@ -311,9 +320,15 @@ function Params(nlayers, g, f₀, β, ρ, H, U, eta, μ, ν, nν, grid; calcFq=n
Uyy = real.(ifft(-l.^2 .* fft(U)))
Uyy = CUDA.@allowscalar repeat(Uyy, outer=(nx, 1, 1))

# Calculate periodic components of the topographic PV gradients.
etah = rfft(A(eta))
etax = irfft(im * kr .* etah, nx)
etay = irfft(im * l .* etah, nx)
etax = irfft(im * kr .* etah, nx) # ∂η/∂x
etay = irfft(im * l .* etah, nx) # ∂η/∂y

# Add topographic PV large-scale gradient
topographic_pv_gradient = T.(topographic_pv_gradient)
@. etax += topographic_pv_gradient[1]
@. etay += topographic_pv_gradient[2]

Qx = zeros(dev, T, (nx, ny, nlayers))
@views @. Qx[:, :, nlayers] += etax
Expand All @@ -325,7 +340,7 @@ function Params(nlayers, g, f₀, β, ρ, H, U, eta, μ, ν, nν, grid; calcFq=n
rfftplanlayered = plan_flows_rfft(A{T, 3}(undef, grid.nx, grid.ny, nlayers), [1, 2]; flags=effort)

if nlayers==1
return SingleLayerParams(T(β), U, eta, T(μ), T(ν), nν, calcFq, Qx, Qy, rfftplanlayered)
return SingleLayerParams(T(β), U, eta, topographic_pv_gradient, T(μ), T(ν), nν, calcFq, Qx, Qy, rfftplanlayered)

else # if nlayers≥2

Expand Down Expand Up @@ -354,9 +369,9 @@ function Params(nlayers, g, f₀, β, ρ, H, U, eta, μ, ν, nν, grid; calcFq=n
CUDA.@allowscalar @views Qy[:, :, nlayers] = @. Qy[:, :, nlayers] - Fm[nlayers-1] * (U[:, :, nlayers-1] - U[:, :, nlayers])

if nlayers==2
return TwoLayerParams(T(g), T(f₀), T(β), A(ρ), (T(H[1]), T(H[2])), U, eta, T(μ), T(ν), nν, calcFq, T(g′[1]), Qx, Qy, rfftplanlayered)
return TwoLayerParams(T(g), T(f₀), T(β), A(ρ), (T(H[1]), T(H[2])), U, eta, topographic_pv_gradient, T(μ), T(ν), nν, calcFq, T(g′[1]), Qx, Qy, rfftplanlayered)
else # if nlayers>2
return Params(nlayers, T(g), T(f₀), T(β), A(ρ), A(H), U, eta, T(μ), T(ν), nν, calcFq, A(g′), Qx, Qy, S, S⁻¹, rfftplanlayered)
return Params(nlayers, T(g), T(f₀), T(β), A(ρ), A(H), U, eta, topographic_pv_gradient, T(μ), T(ν), nν, calcFq, A(g′), Qx, Qy, S, S⁻¹, rfftplanlayered)
end
end
end
Expand Down Expand Up @@ -615,7 +630,7 @@ case of a two fluid layer configuration. In this case we have,
```
where ``Δ = k² [k² + f₀² (H₁ + H₂) / (g′ H₁ H₂)]``.
(Here, the PV-streamfunction relationship is hard-coded to avoid scalar operations
on the GPU.)
"""
Expand Down Expand Up @@ -680,7 +695,7 @@ end

"""
calcN!(N, sol, t, clock, vars, params, grid)
Compute the nonlinear term, that is the advection term, the bottom drag, and the forcing:
```math
Expand All @@ -704,7 +719,7 @@ end

"""
calcNlinear!(N, sol, t, clock, vars, params, grid)
Compute the nonlinear term of the linearized equations:
```math
Expand Down Expand Up @@ -846,7 +861,7 @@ Update all problem variables using `sol`.
"""
function updatevars!(vars, params, grid, sol)
dealias!(sol, grid)

@. vars.qh = sol
streamfunctionfrompv!(vars.ψh, vars.qh, params, grid)
@. vars.uh = -im * grid.l * vars.ψh
Expand Down Expand Up @@ -895,7 +910,7 @@ set_q!(prob, q) = set_q!(prob.sol, prob.params, prob.vars, prob.grid, q)
set_ψ!(params, vars, grid, sol, ψ)
set_ψ!(prob, ψ)
Set the solution `prob.sol` to the transform `qh` that corresponds to streamfunction `ψ`
Set the solution `prob.sol` to the transform `qh` that corresponds to streamfunction `ψ`
and update variables.
"""
function set_ψ!(sol, params, vars, grid, ψ)
Expand Down Expand Up @@ -936,7 +951,7 @@ The kinetic energy at the ``j``-th fluid layer is
𝖪𝖤_j = \\frac{H_j}{H} \\int \\frac1{2} |{\\bf ∇} ψ_j|^2 \\frac{𝖽x 𝖽y}{L_x L_y} = \\frac1{2} \\frac{H_j}{H} \\sum_{𝐤} |𝐤|² |ψ̂_j|², \\ j = 1, ..., n ,
```
while the potential energy that corresponds to the interface ``j+1/2`` (i.e., the interface
while the potential energy that corresponds to the interface ``j+1/2`` (i.e., the interface
between the ``j``-th and ``(j+1)``-th fluid layer) is
```math
Expand All @@ -949,7 +964,7 @@ function energies(vars, params, grid, sol)

@. vars.qh = sol
streamfunctionfrompv!(vars.ψh, vars.qh, params, grid)

abs²∇𝐮h = vars.uh # use vars.uh as scratch variable
@. abs²∇𝐮h = grid.Krsq * abs2(vars.ψh)

Expand Down Expand Up @@ -1002,7 +1017,7 @@ energies(prob) = energies(prob.vars, prob.params, prob.grid, prob.sol)
fluxes(prob)
Return the lateral eddy fluxes within each fluid layer, lateralfluxes``_1,...,``lateralfluxes``_n``
and also the vertical eddy fluxes at each fluid interface,
and also the vertical eddy fluxes at each fluid interface,
verticalfluxes``_{3/2},...,``verticalfluxes``_{n-1/2}``, where ``n`` is the total number of layers in the fluid.
(When ``n=1``, only the lateral fluxes are returned.)
Expand All @@ -1017,7 +1032,7 @@ while the vertical eddy fluxes at the ``j+1/2``-th fluid interface (i.e., interf
the ``j``-th and ``(j+1)``-th fluid layer) are
```math
\\textrm{verticalfluxes}_{j+1/2} = \\int \\frac{f₀²}{g'_{j+1/2} H} (U_j - U_{j+1}) \\,
\\textrm{verticalfluxes}_{j+1/2} = \\int \\frac{f₀²}{g'_{j+1/2} H} (U_j - U_{j+1}) \\,
v_{j+1} ψ_{j} \\frac{𝖽x 𝖽y}{L_x L_y} , \\ j = 1, ..., n-1.
```
"""
Expand Down Expand Up @@ -1047,7 +1062,7 @@ end

function fluxes(vars, params::TwoLayerParams, grid, sol)
nlayers = numberoflayers(params)

lateralfluxes, verticalfluxes = zeros(nlayers), zeros(nlayers-1)

updatevars!(vars, params, grid, sol)
Expand Down
Loading

2 comments on commit 386fd9a

@navidcy
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@JuliaRegistrator register

@JuliaRegistrator
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Registration pull request created: JuliaRegistries/General/74531

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.15.1 -m "<description of version>" 386fd9a5f9f54a78c5c99b8fcc79dc45983d6b83
git push origin v0.15.1

Please sign in to comment.