ADCIRC: Difference between revisions
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==== Importing the fort.14 mesh grid ==== | ==== Importing the fort.14 mesh grid ==== | ||
The {{AddonCmd|v.in.adcirc_grid}} addon module for GRASS 6 will import a | The {{AddonCmd|v.in.adcirc_grid}} addon module for GRASS 6 will import a 2.5D triangular mesh from the [[ADCIRC]] coastal ocean model into a GRASS vector map. | ||
* <tt>v.in.adcirc_grid</tt> does not yet support loading in node type (boundary, etc.) as point attributes -- vector tables can be a bit slow for maps with potentially millions of features. In the mean time here is a little shell script to extract the boundary nodes on the ''first'' open boundary into a separate vector points map: | * <tt>v.in.adcirc_grid</tt> does not yet support loading in node type (boundary, etc.) as point attributes -- vector tables can be a bit slow for maps with potentially millions of features. In the mean time here is a little shell script to extract the boundary nodes on the ''first'' open boundary into a separate vector points map: |
Revision as of 18:30, 26 July 2019
Interfacing with the ADCIRC coastal ocean model
Grid preparation
OceanMesh2D
OceanMesh2D is an open source (GPL3) generator of 2D triangular meshes suitable for use with ADCIRC. It likes to work in lat/lon coordinate system.
You can output your DEM as NetCDF format with r.out.gdal.
You can create a domain boundary polyline with r.contour. You can then output the domain boundary polyline either as Shapefiles with v.out.ogr, or as two column x,y ASCII data with the v.out.ascii.mat addon module for GRASS 6.
Boundary node attribute preparation
You can extract the tidal forcing factor amplitude and phase for boundary nodes needed in the fort.15 setup file from raster maps already loaded into GRASS. In the following example the FES2004 dataset is used. (FES2002 for the K2 constituent as K2 is reputed to be broken in the 2004 edition)
constits="M2 N2 S2 K1 O1 P1 K2 2N2 Q1 M4"
for const in $constits ; do
MAP=fes2004.$const
if [ $const = K2 ] ; then
MAP=fes2002.K2
fi
echo "[$MAP]"
v.what.rast vect=adcirc_grid_open_bdy_nodes \
rast=$MAP.amplitude -pi --q | sort -n > $MAP.ampl.prn
v.what.rast vect=adcirc_grid_open_bdy_nodes \
rast=$MAP.phase -p --q | sort -n > $MAP.phase_raw.prn
v.what.rast vect=adcirc_grid_open_bdy_nodes \
rast=$MAP.phase.u -pi --q | sort -n > $MAP.phase.u.prn
v.what.rast vect=adcirc_grid_open_bdy_nodes \
rast=$MAP.phase.v -pi --q | sort -n > $MAP.phase.v.prn
echo "% $const: grid open boundary nodes" > $MAP.tidal.prn
echo "% node ampl phase phase.u phase.v" >> $MAP.tidal.prn
paste -d'|' $MAP.ampl.prn $MAP.phase_raw.prn \
$MAP.phase.u.prn $MAP.phase.v.prn | \
cut -f1,2,4,6,8 -d'|' | \
tr '|' '\t' >> $MAP.tidal.prn
done
# check for nulls in the source data.
# Manually replace with values from nearby raster cells using d.what.rast
grep '*' *.tidal.prn
Then, in Matlab or Octave:
M2 = load('fes2004.M2.tidal.prn');
N2 = load('fes2004.N2.tidal.prn');
S2 = load('fes2004.S2.tidal.prn');
K1 = load('fes2004.K1.tidal.prn');
O1 = load('fes2004.O1.tidal.prn');
K2 = load('fes2002.K2.tidal.prn');
P1 = load('fes2004.P1.tidal.prn');
Q1 = load('fes2004.Q1.tidal.prn');
c2N2 = load('fes2004.2N2.tidal.prn');
M4 = load('fes2004.M4.tidal.prn');
% compare nearest neighbor phase angle vs. interpolated phase angle reconstructed from components
[M2 cart2pol(M2(:,4), M2(:,5)) * 180/pi]
delta = M2(:,3) - (cart2pol(M2(:,4), M2(:,5)) * 180/pi);
[M2(:,1) delta]
plot(delta), grid
xlabel('boundary node')
ylabel('degrees')
[M2(:,1) M2(:,3) (cart2pol(M2(:,4), M2(:,5)) * 180/pi) delta]
%%%
constits={ 'M2' 'N2' 'S2' 'K1' 'O1' 'P1' 'K2' 'c2N2' 'Q1' 'M4' }
fid = fopen('grid_constits.prn', 'w')
for i = 1: length(constits)
const = char(constits(i));
eval(['data = ' const ';'])
new_phase = cart2pol(data(:,4), data(:,5)) * 180/pi;
for j = 1:length(new_phase)
if (new_phase(j) < 0)
new_phase(j) = new_phase(j) + 360;
end
end
fprintf(fid, ' %s\n', const);
for j = 1:length(new_phase)
fprintf(fid, ' %8.6f %9.5f\n', data(j,2), new_phase(j));
end
end
fclose(fid)
% then manually fix c2N2 -> 2N2
Post processing output data
Importing the fort.14 mesh grid
The v.in.adcirc_grid addon module for GRASS 6 will import a 2.5D triangular mesh from the ADCIRC coastal ocean model into a GRASS vector map.
- v.in.adcirc_grid does not yet support loading in node type (boundary, etc.) as point attributes -- vector tables can be a bit slow for maps with potentially millions of features. In the mean time here is a little shell script to extract the boundary nodes on the first open boundary into a separate vector points map:
infile=fort.14
inmap=mesh_grid_pts
bdymap=mesh_bdy_pts
v.in.adcirc_grid -p in=$infile out=$inmap
num_pts=`grep ' = Number of nodes for open boundary' "$infile" | head -n 1 | awk '{print $1}'`
cat_list=`grep -A"$num_pts" ' = Number of nodes for open boundary' "$infile" | \
tail -n +2 | tr '\n' ',' | sed -e 's/ //g' -e 's/,$//'`
v.extract in=$inmap out=$bdymap list="$cat_list"
Importing elevation or velocity reporting stations
With a little awk you can load in the elevation reporting stations for unit 61 with v.in.ascii.
- example goes here
Visualizing sub-domains
If you wish to have a look at where the sub-domains of a parallel run are, you can use the following Bash script:
mkdir fort14s
for DIR in PE00?? ; do
cp -a $DIR/fort.14 fort14s/${DIR}.14
done
cd fort14s
for file in *.14 ; do
base=`echo "$file" | sed -e 's/PE00//' -e 's/\.14//'`
echo -n "[$base]"
v.in.adcirc_grid in="$file" out="submesh_$base" --quiet
v.in.adcirc_grid -p in="$file" out="submesh_${base}_pts" --quiet
done
Here is a loop for displaying 80 sub-meshes, with random dark colors:
for PE in {00..79} ; do
echo -n "[$PE]"
R=`expr $RANDOM / 256`
G=`expr $RANDOM / 256`
B=`expr $RANDOM / 256`
d.vect "submesh_$PE" color="$R:$G:$B"
done
d.vect US_medium_shoreline color=black width=2
d.vect station_map color=black fcolor=red size=8 icon=basic/circle
Importing unit 61, 62, 63, 64 results
- addme: bash code + r.in.xyz + r.surf.nnbathy
d.barb addon module for GRASS 6 for rendering u,v vector arrows