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Merge pull request #1 from SpeedyWeather/mk/init
initial StochasticStirring and JetDrag
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‎.github/dependabot.yml

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# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
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version: 2
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updates:
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- package-ecosystem: "github-actions"
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directory: "/" # Location of package manifests
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schedule:
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interval: "weekly"

‎.github/workflows/CI.yml

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name: CI
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on:
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push:
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branches:
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- main
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tags: ['*']
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pull_request:
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workflow_dispatch:
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concurrency:
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# Skip intermediate builds: always.
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# Cancel intermediate builds: only if it is a pull request build.
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
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jobs:
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test:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
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runs-on: ${{ matrix.os }}
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timeout-minutes: 60
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permissions: # needed to allow julia-actions/cache to proactively delete old caches that it has created
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actions: write
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contents: read
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strategy:
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fail-fast: false
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matrix:
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version:
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- '1.10'
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- '1.8'
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- 'nightly'
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os:
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- ubuntu-latest
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arch:
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- x64
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steps:
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v1
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: julia-actions/cache@v1
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- uses: julia-actions/julia-buildpkg@v1
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- uses: julia-actions/julia-runtest@v1

‎.github/workflows/CompatHelper.yml

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name: CompatHelper
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on:
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schedule:
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- cron: 0 0 * * *
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workflow_dispatch:
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jobs:
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CompatHelper:
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runs-on: ubuntu-latest
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steps:
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- name: Pkg.add("CompatHelper")
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run: julia -e 'using Pkg; Pkg.add("CompatHelper")'
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- name: CompatHelper.main()
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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COMPATHELPER_PRIV: ${{ secrets.DOCUMENTER_KEY }}
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run: julia -e 'using CompatHelper; CompatHelper.main()'

‎.github/workflows/TagBot.yml

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name: TagBot
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on:
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issue_comment:
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types:
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- created
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workflow_dispatch:
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inputs:
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lookback:
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default: 3
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permissions:
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actions: read
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checks: read
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contents: write
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deployments: read
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issues: read
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discussions: read
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packages: read
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pages: read
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pull-requests: read
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repository-projects: read
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security-events: read
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statuses: read
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jobs:
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TagBot:
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if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
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runs-on: ubuntu-latest
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steps:
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- uses: JuliaRegistries/TagBot@v1
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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ssh: ${{ secrets.DOCUMENTER_KEY }}

‎.gitignore

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.DS_Store
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# Files generated by invoking Julia with --code-coverage
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*.jl.cov
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*.jl.*.cov
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# Files generated by invoking Julia with --track-allocation
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*.jl.mem
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# System-specific files and directories generated by the BinaryProvider and BinDeps packages
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# They contain absolute paths specific to the host computer, and so should not be committed
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deps/deps.jl
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deps/build.log
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deps/downloads/
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deps/usr/
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deps/src/
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# Build artifacts for creating documentation generated by the Documenter package
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docs/build/
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docs/site/
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# PythonCall added .CondaPkg to /docs
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docs/.CondaPkg
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# File generated by Pkg, the package manager, based on a corresponding Project.toml
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# It records a fixed state of all packages used by the project. As such, it should not be
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# committed for packages, but should be committed for applications that require a static
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# environment.
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Manifest.toml
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# no jupyter notebook checkpoints
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.ipynb_*
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# no model output folders
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run_*/
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# no video outputs
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*.mp4

‎Project.toml

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name = "StochasticStir"
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uuid = "c3541e7a-ece5-4a49-9931-82ce8f5cb0be"
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authors = ["Milan Klöwer <[email protected]> and contributors"]
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version = "0.1"
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[deps]
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SpeedyWeather = "9e226e20-d153-4fed-8a5b-493def4f21a9"
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[compat]
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julia = "1.8"
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SpeedyWeather = "0.8"
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[extras]
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[targets]
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test = ["Test"]

‎src/StochasticStir.jl

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module StochasticStir
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using SpeedyWeather
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include("stochasitc_stirring.jl")
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include("jet_drag.jl")
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end

‎src/jet_drag.jl

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export JetDrag
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Base.@kwdef struct JetDrag{NF} <: SpeedyWeather.AbstractDrag{NF}
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# DIMENSIONS from SpectralGrid
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"Spectral resolution as max degree of spherical harmonics"
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trunc::Int
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# OPTIONS
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"Relaxation time scale τ"
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time_scale::Second = Day(6)
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"Jet strength [m/s]"
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u₀::Float64 = 20
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"latitude of Gaussian jet [˚N]"
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latitude::Float64 = 30
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"Width of Gaussian jet [˚]"
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width::Float64 = 6
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# TO BE INITIALISED
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"Relaxation back to reference vorticity"
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ζ₀::LowerTriangularMatrix{Complex{NF}} = zeros(LowerTriangularMatrix{Complex{NF}},trunc+2,trunc+1)
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end
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function JetDrag(SG::SpectralGrid;kwargs...)
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return JetDrag{SG.NF}(;SG.trunc,kwargs...)
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end
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function SpeedyWeather.initialize!( drag::JetDrag,
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model::ModelSetup)
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(;spectral_grid, geometry) = model
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(;Grid,NF,nlat_half) = spectral_grid
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u = zeros(Grid{NF},nlat_half)
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lat = geometry.latds
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for ij in eachindex(u)
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u[ij] = drag.u₀ * exp(-(lat[ij]-drag.latitude)^2/(2*drag.width^2))
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end
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û = SpeedyTransforms.spectral(u,one_more_degree=true)
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v̂ = zero(û)
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SpeedyTransforms.curl!(drag.ζ₀,û,v̂,model.spectral_transform)
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return nothing
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end
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function SpeedyWeather.drag!( diagn::DiagnosticVariablesLayer,
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progn::PrognosticVariablesLayer,
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drag::JetDrag,
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time::DateTime,
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model::ModelSetup)
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(;vor) = progn
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(;vor_tend) = diagn.tendencies
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(;ζ₀) = drag
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(;radius) = model.spectral_grid
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r = radius/drag.time_scale.value
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for lm in eachindex(vor,vor_tend,ζ₀)
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vor_tend[lm] -= r*(vor[lm] - ζ₀[lm])
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end
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end

‎src/stochastic_stirring.jl

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export StochasticStirring
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Base.@kwdef struct StochasticStirring{NF} <: SpeedyWeather.AbstractForcing{NF}
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# DIMENSIONS from SpectralGrid
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"Spectral resolution as max degree of spherical harmonics"
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trunc::Int
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"Number of latitude rings, used for latitudinal mask"
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nlat::Int
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# OPTIONS
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"Decorrelation time scale τ [days]"
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decorrelation_time::Second = Day(2)
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"Stirring strength A [1/s²]"
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strength::Float64 = 1e-11
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"Stirring latitude [˚N]"
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latitude::Float64 = 45
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"Stirring width [˚]"
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width::Float64 = 24
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"Minimum degree of spherical harmonics to force"
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lmin::Int = 8
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"Maximum degree of spherical harmonics to force"
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lmax::Int = 40
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"Minimum order of spherical harmonics to force"
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mmin::Int = 4
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"Maximum order of spherical harmonics to force"
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mmax::Int = lmax
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# TO BE INITIALISED
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"Stochastic stirring term S"
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S::LowerTriangularMatrix{Complex{NF}} = zeros(LowerTriangularMatrix{Complex{NF}},trunc+2,trunc+1)
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"a = A*sqrt(1 - exp(-2dt/τ)), the noise factor times the stirring strength [1/s²]"
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a::Base.RefValue{NF} = Ref(zero(NF))
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"b = exp(-dt/τ), the auto-regressive factor [1]"
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b::Base.RefValue{NF} = Ref(zero(NF))
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"Latitudinal mask, confined to mid-latitude storm track by default [1]"
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lat_mask::Vector{NF} = zeros(NF,nlat)
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end
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function StochasticStirring(SG::SpectralGrid;kwargs...)
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(;trunc,Grid,nlat_half) = SG
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nlat = RingGrids.get_nlat(Grid,nlat_half)
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return StochasticStirring{SG.NF}(;trunc,nlat,kwargs...)
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end
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function SpeedyWeather.initialize!( forcing::StochasticStirring,
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model::ModelSetup)
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# precompute forcing strength, scale with radius^2 as is the vorticity equation
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(;radius) = model.spectral_grid
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A = radius^2 * forcing.strength
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# precompute noise and auto-regressive factor, packed in RefValue for mutability
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dt = model.time_stepping.Δt_sec
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τ = forcing.decorrelation_time.value # in seconds
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forcing.a[] = A*sqrt(1 - exp(-2dt/τ))
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forcing.b[] = exp(-dt/τ)
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# precompute the latitudinal mask
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(;Grid,nlat_half) = model.spectral_grid
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latd = RingGrids.get_latd(Grid,nlat_half)
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for j in eachindex(forcing.lat_mask)
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# Gaussian centred at forcing.latitude of width forcing.width
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forcing.lat_mask[j] = exp(-(forcing.latitude-latd[j])^2/forcing.width^2*2)
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end
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return nothing
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end
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function SpeedyWeather.forcing!(diagn::DiagnosticVariablesLayer,
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progn::PrognosticVariablesLayer,
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forcing::StochasticStirring,
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time::DateTime,
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model::ModelSetup)
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SpeedyWeather.forcing!(diagn,forcing,model.spectral_transform)
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end
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function SpeedyWeather.forcing!(diagn::DiagnosticVariablesLayer,
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forcing::StochasticStirring{NF},
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spectral_transform::SpectralTransform) where NF
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# noise and auto-regressive factors
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a = forcing.a[] # = sqrt(1 - exp(-2dt/τ))
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b = forcing.b[] # = exp(-dt/τ)
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(;S) = forcing
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lmax,mmax = size(S)
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@inbounds for m in 1:mmax
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for l in m:lmax
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if (forcing.mmin <= m <= forcing.mmax) &&
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(forcing.lmin <= l <= forcing.lmax)
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# Barnes and Hartmann, 2011 Eq. 2
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Qi = 2rand(Complex{NF}) - (1 + im) # ~ [-1,1] in complex
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S[l,m] = a*Qi + b*S[l,m]
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end
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end
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end
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# to grid-point space
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S_grid = diagn.dynamics_variables.a_grid
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SpeedyTransforms.gridded!(S_grid,S,spectral_transform)
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# mask everything but mid-latitudes
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RingGrids._scale_lat!(S_grid,forcing.lat_mask)
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# back to spectral space
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(;vor_tend) = diagn.tendencies
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SpeedyTransforms.spectral!(vor_tend,S_grid,spectral_transform)
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SpeedyTransforms.spectral_truncation!(vor_tend) # set lmax+1 to zero
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return nothing
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end

‎test/runtests.jl

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using SpeedyWeather
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using StochasticStir
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using Test
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@testset "StochasticStir.jl" begin
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spectral_grid = SpectralGrid(trunc=31,nlev=1)
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drag = JetDrag(spectral_grid,time_scale=Day(6))
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forcing = StochasticStirring(spectral_grid)
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initial_conditions = StartFromRest()
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# with barotropic model
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model = BarotropicModel(;spectral_grid,initial_conditions,forcing,drag)
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simulation = initialize!(model)
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run!(simulation,period=Day(5))
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@test simulation.model.feedback.nars_detected == false
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# with shallow water model
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model = ShallowWaterModel(;spectral_grid,initial_conditions,forcing,drag)
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simulation = initialize!(model)
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run!(simulation,period=Day(5))
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@test simulation.model.feedback.nars_detected == false
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end

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