Welcome to Metos3D’s documentation!¶
metos3d cheat sheet¶
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metos3d info
~/.metos3drc
version
data
model
petsc
4.
$> metos3d
usage: metos3d [command] ...
metos3d
--help, -h
--verbose, -v
info # print version, config file, docs, etc ...
simulate # compile sources, perform a simulation, ...
update # not needed, handled externally, pip, conda
optimize # save for later
$>
metos3d info
metos3d update
metos3d simulate HAMMOC-mitgcm-128x64x15-3h.yaml
metos3d simulate N-DOP-mitgcm-360x160x23-
metos3d simulate HAMMOC-mpiom-default-mitgcm-128x64x15-3h.yaml
metos3d simulate HAMMOC-ballasting-0.3-mitgcm-128x64x15-3h.yaml
mpirun -n 128 metos3d simulate HAMMOC-mitgcm-128x64x15-3h.yaml
3.
metos3d
init
data
model
simulation (sim)
optimization (opt)
info
update
2.
metos3d (m3d)
init
data
model
experiment (exp)
1.
metos3d
info
update
data
petsc
run
model
compile
bgc
tmm
matrix
update¶
info¶
Metos3D BGC API¶
Application programming interface (API) for biogeochemical (BGC) models
Definition, realization in Fortran
metos3dbgcinit(...)
metos3dbgcbegin(...)
metos3dbgc(...)
metos3dbgcend(...)
metos3dbgcfinal(...)
Description¶
The interface decouples biogeochemical models and driver routines (ocean circulation, forcing, geometry) programmatically.
It gives the modeler the possibility to provide a free number of tracers, parameters, boundary and domain conditions. It suits well an optimization as well as an Automatic Differentiation (AD) context.
The interface changed (more or less) since it was introduced for the first time. The initial version can be found at \citep[][]{PiwSla16}.
What is it?¶
Ther Metos3D BGC API is a convention how biogeochemical models can be coupled to ocean circulation.
What for?¶
modelers that want to their marine ecosystem or biogeochemical models, coupled to a global ocean circulation,
Why?¶
climate research, ocean simulation, bgc models, uncertainties, parameters, processes, require assessment, at global-basin scale, sophisticated general circulation model,
How?¶
C model template¶
Fortran model template¶
Example 1¶
in the simplest case, assuming you have a model written in Fortran,
File: simple_bgc_model.f90
subroutine metos3dbgc(ny, nx, nu, nb, nd, ndg, dt, q, t, y, u, b, d, dg, ctx)
integer :: ny ! tracer count
integer :: nx ! layer count
integer :: nu ! parameter count
integer :: nb ! boundary condition count
integer :: nd ! domain condition count
integer :: ndg ! diagnostic variable count
real(8) :: dt ! ocean time step
real(8) :: q(nx, ny) ! bgc model output
real(8) :: t ! point in time
real(8) :: y(nx, ny) ! bgc model input
real(8) :: u(nu) ! parameters
real(8) :: b(nb) ! boundary conditions
real(8) :: d(nx, nd) ! domain conditions
real(8) :: dg(nx, ndg) ! diagnostic variables
integer :: ctx ! unsed variable, place holder for bgc context
! your code here ...
end subroutine
Example 2¶
File: bgctype.h90
type bgcctx
sequence
real(8) :: a
real(8) :: b
logical(4) :: yesOrNo
real(8), pointer :: ptr(:)
end type
File: more_sophisticated_bgc_model.f90
subroutine metos3dbgc(ny, nx, nu, nb, nd, ndg, dt, q, t, y, u, b, d, dg, ctx)
#include "bgctype.h90"
integer :: ny ! tracer count
integer :: nx ! layer count
integer :: nu ! parameter count
integer :: nb ! boundary condition count
integer :: nd ! domain condition count
integer :: ndg ! diagnostic variable count
real(8) :: dt ! ocean time step
real(8) :: q(nx, ny) ! bgc model output
real(8) :: t ! point in time
real(8) :: y(nx, ny) ! bgc model input
real(8) :: u(nu) ! parameters
real(8) :: b(nb) ! boundary conditions
real(8) :: d(nx, nd) ! domain conditions
real(8) :: dg(nx, ndg) ! diagnostic variables
type(bgcctx) :: ctx ! own bgc context
! your code here ...
end subroutine
Example 3¶
Good practice,
- store constants in a module,
- store pointers for own memory allocation, (usually not needed at all), in data type
- use
metos3dbgcinitto allocate memory - use
metos3dbgcfinalto free memory
- use
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