tREADME.md - pism - [fork] customized build of PISM, the parallel ice sheet model (tillflux branch)
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tREADME.md (1690B)
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1 Ross ice shelf model (prognostic eigencalving mode)
2 =================
3
4 This example demonstrates prognostic (geometry-evolving) modeling of an
5 ice shelf using the `-calving eigen_calving,thickness_calving` combination.
6
7 The user should probably run the example in `../diagnostic/` before this one,
8 and read the documentation for diagnostic example in section 12.2 of the PISM
9 User's Manual.
10
11 With the applied calving parameterization we reach a (quasi) steady state after
12 runs of a few centuries. Calving parameters, specifically the minimal ice
13 thickness at the front (`-thickness_calving_threshold`) and the eigencalving
14 constant (`-eigen_calving_K`) are among the parameters that can be modified
15 either to get a different steady state or to model changes in the ice shelf.
16
17 As in the diagnostic example, start by running `preprocess.py` in the parent
18 directory. Then do
19
20 $ ./run_prog.sh 4 211 0.6 100
21
22 This 100 model year run on 4 processes and a 5 km grid took about about twenty
23 minutes. It starts with a bootstrapping stage which does a `-y 0` run and then
24 generates `startfile_Mx211.nc`. It then re-initializes to start the prognostic
25 run itself.
26
27 Note `run_prog.sh` accepts four arguments: `run_prog.sh N Mx E Y` does
28 a run with `N` MPI processes, a `Mx`x`Mx` grid, option `-ssa_e E`, and duration
29 `-y Y`.
30
31 To view a "movie" of the resulting thicknesses and surface velocities
32 do
33
34 $ ncview ex-prog_Mx211_yr100.nc
35
36 To see a time-series of ice volume or ice area, among other other quantities,
37 do
38
39 $ ncview ts-prog_Mx211_yr100.nc
40
41 To generate figures comparing the final-time modeled velocity to present-day
42 observed velocity do
43
44 $ ../plot.py prog_Mx211_yr100.nc
45