tREADME.md - pism - [fork] customized build of PISM, the parallel ice sheet model (tillflux branch)
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       tREADME.md (3559B)
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            1 # laboratory validation example
            2 
            3 This example is a validation of [PISM's](http://www.pism-docs.org) isothermal
            4 SIA numerical model using a laboratory experiment with a
            5 [Xanthan gum](http://en.wikipedia.org/wiki/Xanthan_gum) suspension in water.
            6 This fluid is more strongly shear-thinning than ice but it has nearly the same
            7 density.  This example is documented in section 12.2 of the PISM User's Manual.
            8 
            9 The source of the set-up is the "constant flux" experiment in
           10 
           11   R. Sayag and M. G. Worster, 2013. *Axisymmetric gravity currents of
           12   power-law fluids over a rigid horizontal surface*, J. Fluid Mech. 716,
           13   [doi:10.1017/jfm.2012.545](http://dx.doi.org/10.1017/jfm.2012.545).
           14 
           15 See also
           16 
           17   R. Sayag, S. S. Pegler, and M. G. Worster, 2012. *Floating extensional flows*,
           18   Physics of Fluids 24 (9),
           19   [doi:10.1063/1.4747184](http://dx.doi.org/10.1063/1.4747184).
           20 
           21 In the laboratory experiment, fluid is pushed through the bottom of a flat table
           22 from a tube of radius 8 mm (R. Sayag, personal communication) at a mass rate of
           23 about 3 g/s (Sayag & Worster, 2013).  The glaciological analog is an ice sheet
           24 on a flat bed fed by positive surface mass balance in the vicinity of the dome,
           25 but with zero surface mass balance everywhere else.
           26 
           27 Sayag & Worster (2013) estimate n = 5.9 using regression of laboratory
           28 measurements of the radius; see Figures 2(c) and 2(d) in the paper.  More
           29 precisely, they compare radius data to a similarity solution of the thickness
           30 evolution equation to infer the exponent n.
           31 
           32 See `preprocess.py` for settings of various parameters which are appropriate to
           33 this fluid problem.  The final total mass of fluid, about 1 kg, is about 18
           34 orders of magnitude smaller than the mass of the Greenland ice sheet.)
           35 
           36 The flow rate in the pipe is assumed to be constant across the pipe,
           37 so the input "climate" has given `climatic_mass_balance` which is constant in
           38 the pipe and zero outside the pipe.
           39 
           40 ## basic usage
           41 
           42 The preprocessing stage builds a NetCDF file suitable for PISM bootstrapping.
           43 It is built at exactly the run-time resolution in order to make the flux
           44 into the center of the "ice" sheet have the correct value given the small size
           45 of the positive mass flux area.  Also it creates `gumparams.nc` which contains
           46 `pism_overrides` attributes, the special parameters for this experiment.
           47 
           48     $ ./preprocess.py
           49 
           50 Now view `initlab52.nc`.  Only the `climatic_mass_balance` variable is
           51 interesting.
           52 
           53 Now we run for 746 model seconds (Sayag & Worster, 2013) on a 10 mm grid
           54 (520 mm / 52 subintervals) using 4 processors:
           55 
           56     $ ./rungum.sh 4 52 &> out.lab52
           57 
           58 This run generates `out.lab52` from `stderr` and `stdout`,
           59 and it also generates diagnostic NetCDF files `ts_lab52.nc` and `ex_lab52.nc`.
           60 It takes about 5 minutes on a 2013 laptop.
           61 
           62 Results are better on finer grids because the input pipe radius is only 8 mm.
           63 For example, this uses a 5 mm grid, and takes about an hour to run:
           64 
           65     $ ./preprocess.py -Mx 104 -o initlab104.nc
           66     $ ./rungum.sh 4 104 &> out.lab104
           67 
           68 You can compare multiple runs to the experimental data on radius (R. Sayag,
           69 personal communication):
           70 
           71     $ ./showradius.py -o foo.png -d constantflux3.txt ts_lab*.nc
           72 
           73 ## higher resolutions
           74 
           75 For a 2.5 mm grid taking several hours to run, do:
           76 
           77     $ ./preprocess.py -Mx 208 -o initlab208.nc
           78     $ ./rungum.sh 4 208 &> out.lab208
           79 
           80 More processors (NN) are recommended for a 1.0 mm grid:
           81 
           82     $ ./preprocess.py -Mx 520 -o initlab520.nc
           83     $ ./rungum.sh NN 520 &> out.lab520
           84 
           85 To experiment with different configuration constants, edit and rerun
           86 `preprocess.py`.
           87