def base_model():
"""
Channel
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[1000,100],21,3)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-05 00:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta0=-1
eta_bc=sun_driver.StageBC(name="eta_bc",
geom=np.array([ [0,0],
[0,100]]),
z=eta0)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=34),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=15)] )
model.set_run_dir('rundata_met_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=1 # test single first
model.config['dt']=120
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
return model
def base_model_setup(L=100, dx=10):
g = unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0, 0], [L, 10], 1 + int(L / dx), 2)
g.add_cell_field('depth', -6 * np.ones(g.Ncells()))
model = sun_driver.SuntansModel()
model.num_procs = 1
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start = np.datetime64("2018-01-01 00:00")
model.run_stop = np.datetime64("2018-01-02 00:00")
# 50m2, 5.0 m3/s, 0.1m/s
source = sun_driver.FlowBC(name='inflow',
geom=np.array([[0, 0], [0, 10]]),
Q=10.0)
outlet = sun_driver.StageBC(name='outflow',
geom=np.array([[100, 0], [100, 10]]),
z=-1)
model.add_bcs([source, outlet])
model.set_run_dir('rundata_2d_average', mode='pristine')
model.projection = 'EPSG:26910'
model.config['dt'] = 2.5
model.config['ntout'] = 100
model.config['ntaverage'] = 100
model.config['calcaverage'] = 1
model.config['averageNetcdfFile'] = "average.nc"
model.config['thetaramptime'] = 100
model.config['Cmax'] = 2
model.config['Nkmax'] = 1
model.config['stairstep'] = 0
model.config['mergeArrays'] = 0
return model
nx=int(L/dx_lon),ny=int(W/dy_lat))
g.add_cell_field('depth',bathy(g.cells_center()))
model.set_grid(g)
model.config['maxFaces']=4
model.z_offset=0
from shapely import geometry
feats=np.zeros( 2, [ ('name','O'),
('geom','O') ] )
feats[0]['name']='left'
# HALF STEP:
feats[0]['geom']=geometry.LineString( [ [0,W/2], [0,W] ] )
feats[1]['name']='right'
feats[1]['geom']=geometry.LineString( [ [L,0], [L,W] ] )
model.add_gazetteer(feats)
Q_left=drv.FlowBC(name='left',Q=200.0)
h_right=drv.StageBC(name='right',z=0.0)
model.add_bcs([Q_left,h_right])
model.write()
model.partition()
#model.run_simulation()
n1 = g.select_nodes_nearest([300, 0])
n2 = g.select_nodes_nearest([300, 500])
model = sun_driver.SuntansModel()
model.load_template('sun-template.dat')
model.set_grid(g)
model.run_start = np.datetime64("2018-01-01 00:00")
model.run_stop = np.datetime64("2018-01-01 10:00")
dt = np.timedelta64(600, 's')
times = np.arange(model.run_start - dt, model.run_stop + 2 * dt, dt)
secs = (times - times[0]) / np.timedelta64(1, 's')
eta_values = -6 + 0.75 * np.cos(secs * np.pi / 7200)
eta_da = xr.DataArray(eta_values, coords=[('time', times)])
eta_bc = sun_driver.StageBC(name="eta_bc",
geom=np.array([[0, 0], [0, 500]]),
z=eta_da)
model.add_bcs(eta_bc)
model.add_bcs([
sun_driver.ScalarBC(parent=eta_bc, scalar="S", value=1),
sun_driver.ScalarBC(parent=eta_bc, scalar="T", value=1)
])
# point source that is typically dry
hill_source = sun_driver.SourceSinkBC(name='inflow',
geom=np.array([150, 150]),
z=-10,
Q=1.0)
# on a saddle
model.add_gazetteer("gis/forcing-v00.shp")
Q_upstream = drv.FlowBC(name='SJ_upstream', Q=250.0)
Qdown = -100 # target outflow
# ramp up to the full outflow over 1h
h = np.timedelta64(1, 'h')
Qdown = xr.DataArray(
data=[0, 0, Qdown, Qdown, Qdown],
name='Q',
dims=['time'],
coords=dict(time=[
model.run_start - 24 * h, model.run_start, model.run_start +
ramp_hours * h, model.run_stop, model.run_stop + 24 * h
]))
Q_downstream = drv.FlowBC(name='SJ_downstream', Q=Qdown)
h_old_river = drv.StageBC(name='Old_River', z=2.2 - 0.65)
model.add_bcs([Q_upstream, Q_downstream, h_old_river])
model.write()
#--
if 0:
# Add in variable roughness
ec = model.grid.edges_center()
z0_map = field.GdalGrid("../../bathy/composite-roughness.tif")
z0 = z0_map(ec)
z0[np.isnan(z0)] = float(model.config['z0B'])
model.ic_ds['z0B'] = ('time', 'Ne'), z0[None, :]
model.write_ic_ds()
def test_point_source_3d():
"""
A square 3D grid with wetting and drying.
the bathymetry is a wavy cos(x)*cos(y) function.
two point sources and an oscillating freesurface.
one point source at a saddle point, and the other
on top of a bump which goes dry.
This currently does pretty well, but it could be
better -- see the test thresholds near the end which
have been relaxed somewhat.
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[500,500],50,50)
# wavy bed
half_wave=150
cc=g.cells_center()
cell_depth=-6 + np.cos(cc[:,0]*np.pi/half_wave) * np.cos(cc[:,1]*np.pi/half_wave)
g.add_cell_field('depth',cell_depth)
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-01 10:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta_values=-6 + 0.75*np.cos(secs*np.pi/7200)
eta_da=xr.DataArray(eta_values,coords=[ ('time',times) ])
eta_bc=sun_driver.StageBC(name="eta_bc",geom=np.array([ [0,0],
[0,500]]),
z=eta_da)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=1),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=1)] )
# point source that is typically dry
hill_source=sun_driver.SourceSinkBC(name='inflow',geom=np.array([150,150]),
z=-10,Q=1.0)
# on a saddle
saddle_source=sun_driver.SourceSinkBC(name='inflow',geom=np.array([220,225]),
z=-10,Q=1.0)
model.add_bcs(hill_source)
model.add_bcs(saddle_source)
model.add_bcs( [sun_driver.ScalarBC(parent=hill_source,scalar="S",value=1),
sun_driver.ScalarBC(parent=hill_source,scalar="T",value=1)] )
model.add_bcs( [sun_driver.ScalarBC(parent=saddle_source,scalar="S",value=1),
sun_driver.ScalarBC(parent=saddle_source,scalar="T",value=1)] )
model.set_run_dir('rundata_point_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=4
model.config['dt']=2.5
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
model.write()
model.ic_ds.eta.values[:]=eta_da.values[1]
model.ic_ds.salt.values[:]=1.0
model.ic_ds.temp.values[:]=1.0
model.write_ic_ds()
model.partition()
model.sun_verbose_flag='-v'
model.run_simulation()
for map_fn in model.map_outputs():
ds=xr.open_dataset(map_fn)
dzz=ds.dzz.values
# This is not as strict as it should be.
# should be 0.001 or less.
dzz_thresh=0.05
salt=ds.salt.values
valid=np.isfinite(dzz) & (dzz>=dzz_thresh)
salt_errors=salt[valid] - 1.0
# This is not as strict as it should be.
# we should be able to get this down to 1e-4 or
# better.
assert np.max( np.abs(salt_errors) )<0.01
ds.close()
model.add_gazetteer("grid-lsb/linear_features.shp")
##
ocean_salt_bc = drv.ScalarBC(name='ocean', scalar='salinity', value=25)
ocean_temp_bc = drv.ScalarBC(name='ocean', scalar='temperature', value=10)
msl_navd88 = 0.94 # m
ocean_bc = drv.NOAAStageBC(
name='ocean',
station=9414575, # Coyote - will come in as MSL
# station=9414750, # Alameda.
cache_dir=cache_dir,
filters=[dfm.Lowpass(cutoff_hours=1.5)])
ocean_offset_bc = drv.StageBC(name='ocean',
mode='add',
z=z_offset_manual + msl_navd88)
model.add_bcs([ocean_bc, ocean_salt_bc, ocean_temp_bc, ocean_offset_bc])
import sfb_common
# sfb_common.add_usgs_stream_bcs(model,cache_dir) # disable if no internet
# sfb_common.add_potw_bcs(model,cache_dir)
if __name__ == '__main__':
if args.write_grid:
model.grid.write_ugrid(args.write_grid, overwrite=True)
else:
model.write()
try:
shutil.copy(__file__, model.run_dir)
def base_model(run_dir,run_start,run_stop,
restart_from=None,
grid_option=None,
steady=False):
if restart_from is None:
model=SuntansModel()
model.load_template(os.path.join(here,"sun-template.dat"))
model.num_procs=num_procs
else:
old_model=SuntansModel.load(restart_from)
model=old_model.create_restart()
model.manual_z_offset=-4
model.z_offset=0.0 # moving away from the semi-automated datum shift to manual shift
model.projection="EPSG:26910"
model.set_run_dir(run_dir,mode='pristine')
if model.restart:
model.run_start=model.restart_model.restartable_time()
else:
model.run_start=run_start
model.run_stop=run_stop
model.config['grid_option']=grid_option or 'snubby'
if restart_from is None:
ramp_hours=1 # how quickly to increase the outflow
else:
ramp_hours=0
if not model.restart:
# dt=0.25 # for lower friction run on refined shore grid
# with new grid that's deformed around the barrier can probably
# get away with 0.5
# dt=0.5 # for lower friction run on refined shore grid
dt=0.25 # bit of safety for high res grid.
# dt=0.1 # for shaved cell grid. still not stable.
model.config['dt']=dt
model.config['metmodel']=0 # 0: no wind, 4: wind only
model.config['nonlinear']=1
if 0:
model.config['Nkmax']=1
model.config['stairstep']=0
if 1:
model.config['Nkmax']=50
model.config['stairstep']=1 # 3D, stairstep
model.config['thetaM']=-1 # with 1, seems to be unstable
model.config['z0B']=5e-4 # maybe with ADCP bathy need more friction
# slow, doesn't make a huge difference, but does make w nicer.
model.config['nonhydrostatic']=0
model.config['nu_H']=0.0
model.config['nu']=1e-5
model.config['turbmodel']=10 # 1: my25, 10: parabolic
model.config['CdW']=0.0 #
model.config['wetdry']=1
model.config['maxFaces']=4
model.config['mergeArrays']=1 # hopefully easier to use than split up.
if model.config['grid_option']=='snubby':
# 2019-07-11: refine near-shore swaths of grid, snubby-01 => snubby-04
# 2019-07-12: further refinements 04 => 06
#grid_src="../grid/snubby_junction/snubby-06.nc"
#grid_src="../grid/snubby_junction/snubby-07-edit45.nc"
#grid_src="../grid/snubby_junction/snubby-08-edit06.nc"
#grid_src="../grid/snubby_junction/snubby-08-edit24.nc"
#grid_src="../grid/snubby_junction/snubby-08-edit50.nc" # good
grid_src="../grid/snubby_junction/snubby-08-edit60.nc" # higher res in hole
#grid_src="../grid/snubby_junction/snubby-08-refine-edit03.nc" # double res of edit60
elif model.config['grid_option']=='large':
grid_src="../grid/merge_v16/merge_v16_edit09.nc"
else:
raise Exception("Unknown grid option %s"%grid_option)
# bathy_suffix=''
# post_suffix='med0' # on-grid bathy postprocessesing:
#bathy_suffix='smooth' # pre-smoothed just in sand wave areas
bathy_suffix='smoothadcp' # pre-smoothed just in sand wave areas, and revisit ADCP data.
#bathy_suffix='smoothadcp2' # same, but extend ADCP data upstream.
post_suffix=''
# bathy_suffix='adcp'
# post_suffix=''
grid_bathy=os.path.basename(grid_src).replace('.nc',f"-with_bathy{bathy_suffix}{post_suffix}.nc")
if utils.is_stale(grid_bathy,[grid_src]):
g_src=unstructured_grid.UnstructuredGrid.from_ugrid(grid_src)
g_src.cells_center(refresh=True)
bare_edges=g_src.orient_edges(on_bare_edge='return')
if len(bare_edges):
ec=g_src.edges_center()
for j in bare_edges[:50]:
print("Bare edge: j=%d xy=%g %g"%(j, ec[j,0], ec[j,1]))
raise Exception('Bare edges in grid')
add_bathy.add_bathy(g_src,suffix=bathy_suffix)
add_bathy.postprocess(g_src,suffix=post_suffix)
g_src.write_ugrid(grid_bathy,overwrite=True)
g=unstructured_grid.UnstructuredGrid.from_ugrid(grid_bathy)
g.cells['z_bed'] += model.manual_z_offset
g.delete_edge_field('edge_z_bed')
#g.edges['edge_z_bed'] += model.manual_z_offset
model.set_grid(g)
model.grid.modify_max_sides(4)
dt=float(model.config['dt'])
# with 0.01, was getting many CmaxW problems.
model.config['dzmin_surface']=0.05 # may have to bump this up..
model.config['ntout']=int(1800./dt)
model.config['ntaverage']=int(1800./dt)
model.config['ntoutStore']=int(86400./dt)
# isn't this just duplicating the setting from above?
model.z_offset=0.0 # moving away from the semi-automated datum shift to manual shift
if model.config['grid_option']=='snubby':
model.add_gazetteer(os.path.join(here,"../grid/snubby_junction/forcing-snubby-01.shp"))
elif model.config['grid_option']=='large':
model.add_gazetteer(os.path.join(here,"../grid/merge_v16/forcing-merge_16-01.shp"))
def fill(da):
return utils.fill_tidal_data(da,fill_time=False)
if steady:
# Would like to ramp these up at the very beginning.
# Mossdale, tested at 220.0 m3/s
Q_upstream=drv.FlowBC(name='SJ_upstream',flow=220.0,dredge_depth=None)
Q_downstream=drv.FlowBC(name='SJ_downstream',flow=-100,dredge_depth=None)
# had been 1.75. but that's showing about 0.75m too much water.
# could be too much friction, or too high BC.
h_old_river=drv.StageBC(name='Old_River',water_level=1.75 + model.manual_z_offset)
else:
# 15 minute data. The flows in particular have enough overtide energy
# that the lowpass interval shouldn't be too large. Spot checks of plots
# show 1.0h is pretty good
lp_hours=1.0
data_upstream=common.msd_flow(model.run_start,model.run_stop)
Q_upstream=drv.FlowBC(name="SJ_upstream",flow=data_upstream.flow_m3s,dredge_depth=None,
filters=[hm.Lowpass(cutoff_hours=1.0)])
data_downstream=common.sjd_flow(model.run_start,model.run_stop)
# flip sign to get outflow.
Q_downstream=drv.FlowBC(name="SJ_downstream",flow=-data_downstream.flow_m3s,dredge_depth=None,
filters=[hm.Lowpass(cutoff_hours=1.0)])
or_stage=common.oh1_stage(model.run_start,model.run_stop)
h_old_river=drv.StageBC(name='Old_River',water_level=or_stage.stage_m,
filters=[hm.Transform(fn=lambda x: x+model.manual_z_offset),
hm.Lowpass(cutoff_hours=1.0)])
model.add_bcs([Q_upstream,Q_downstream,h_old_river])
model.write()
assert np.all(np.isfinite(model.bc_ds.boundary_Q.values))
if not model.restart:
# bathy rms ranges from 0.015 to 1.5
# 0.5 appears a little better than 1.0 or 0.1
# cfg007 used 0.1, and the shape was notably not as good
# as steady008.
# cfg008 will return to 0.5...
# BUT - now that I have more metrics in place, it looks like cfg007
# was actually better, in terms of MAE over top 2m, and smaller bias.
# with that in mind, steady012 will try an even smaller factor, and infact
# something more in line with Nikuradse.
# best roughness using constant z0B was 5e-4.
# so map 0.1 to that...
if 1:
print("Adding roughness")
grid_roughness.add_roughness(model.grid)
cell_z0B=(1./30)*model.grid.cells['bathy_rms']
e2c=model.grid.edge_to_cells()
nc1=e2c[:,0]
nc2=e2c[:,1]
nc2[nc2<0]=nc1[nc2<0]
edge_z0B=0.5*( cell_z0B[nc1] + cell_z0B[nc2] )
model.ic_ds['z0B']=('time','Ne'), edge_z0B[None,:]
model.write_ic_ds()
if int(model.config['metmodel'])>=4:
# and how about some wind?
times=np.array( [model.run_start - np.timedelta64(10,'D'),
model.run_start,
model.run_stop,
model.run_stop + np.timedelta64(10,'D')] )
nt=len(times)
met_ds=model.zero_met(times=times)
pnts=model.grid.cells_center()[:1]
for comp in ['Uwind','Vwind']:
met_ds['x_'+comp]=("N"+comp,),pnts[:,0]
met_ds['y_'+comp]=("N"+comp,),pnts[:,1]
met_ds['z_'+comp]=("N"+comp,),10*np.ones_like(pnts[:,1])
met_ds['Uwind']=('nt',"NUwind"), 0.0 * np.ones((nt,len(pnts)))
met_ds['Vwind']=('nt',"NVwind"),-5.0 * np.ones((nt,len(pnts)))
model.met_ds=met_ds
model.write_met_ds()
model.partition()
model.sun_verbose_flag='-v'
return model
def base_model():
"""
A channel, uniform bathy.
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[1000,100],21,3)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-01 10:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta0=-2
eta_bc=sun_driver.StageBC(name="eta_bc",
geom=np.array([ [0,0],
[0,100]]),
z=eta0)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=1),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=1)] )
model.set_run_dir('rundata_sedi_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=1 # test single first
model.config['dt']=30
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
# Sediment:
model.config['computeSediments']=1 # whether include sediment model
model.config['Nlayer']=0 # Number of bed layers (MAX = 5)
model.config['Nsize']=3 # Number of sediment fractions (Max = 3)
model.config['TBMAX']=1 # whether to output tb for each cell
model.config['SETsediment']=0 # When Nlayer>5 or Nsize>3, SETsediment=1 to use SetSediment
model.config['WSconstant']=1 # if 1, ws for sediment = ws0
model.config['readSediment']=0 # if 1, read sediment concentration data as IC. only work with Nsize==1
model.config['bedInterval']=150 # the interval steps to update bed change
model.config['bedComplex']=0 # whether to consider the possibility to flush away a whole layer
model.config['ParabolKappa']=0 # whether to use parabolic tubulent diffusivity
model.config['Ds90']=0.000008 # ds90 for calculation of erosion taub
model.config['Ds1']=0.00000057 # sediment diameter for fraction No.1 (m)
model.config['Ds2']=0.0002 # sediment diameter for fraction No.2
model.config['Ds3']=0.0002 # sediment diameter for fraction No.3
model.config['Ws01']= 0.0001 # constant settling velocity for fraction No.1 (m/s)
model.config['Ws02']= 0.01 # constant settling velocity for fraction No.2
model.config['Ws03']=-0.01 # constant settling velocity for fraction No.3
model.config['Gsedi1']=2.65 # relative density for fraction No.1
model.config['Gsedi2']=2.65 # relative density for fraction No.2
model.config['Gsedi3']=2.65 # relative density for fraction No.3
model.config['Prt1']=1 # Prandtl Number for fraction No.1
model.config['Prt2']=1 # Prandtl Number for fraction No.2
model.config['Prt3']=1 # Prandtl Number for fraction No.3
model.config['Consolid1']=0.00 # Consolidation rate (g/m^2/s) for layer No.1
model.config['E01']=0.1 # Basic Erosion Rate Constant (g/m^2/s) for layer No.1
model.config['Taue1']=0.0 # Erosion Critical Shear Stress (N/m^2) for layer No.1
# Taud1 isn't actually used in current code. Deposition always occurs at the rate
# of w_s.
model.config['Taud1']=0.0 # Deposition Critical Shear Stress (N/m^2) for layer No.1
model.config['Drydensity1']=530000 # Dry density (g/m^3) for layer No.1
model.config['Thickness1']=0.0 # Thickness (m) for layer No.1
model.config['softhard1']=1 # 0 soft or hard for layer No.1 to decide how to calculate erosion
model.config['Bedmudratio1']=0.8 # Bed mud ratio for layer No.1
model.config['Chind']=1000000 # Concentration (in volumetric fraction) criterion for hindered settling velocity
model.config['Cfloc']=500000 # Concentration (in volumetric fraction) criterion for flocculated settling velcoity
model.config['k']=0.0002 # Constant coefficient for settling velocity as a function of conc.
model.config['Sediment1File']='sedi1.dat'
model.config['Sediment2File']='sedi2.dat'
model.config['Sediment3File']='sedi3.dat'
model.config['LayerFile']='sedilayer.dat'
model.config['tbFile']='Seditb.dat'
model.config['tbmaxFile']='Seditbmax.dat'
return model
xy for xy in xys
if model.grid.select_cells_nearest(xy, inside=True) is not None
]
np.savetxt(os.path.join(model.run_dir, model.config['DataLocations']),
np.array(valid_xys))
##
# spatially varying
hycom_ll_box = [-124.9, -121.7, 35.9, 39.0]
ocean_bcs = []
if ocean_method == 'eta-otps':
ocean_bc = drv.MultiBC(drv.OTPSStageBC, name='Ocean', otps_model='wc')
ocean_offset_bc = drv.StageBC(name='Ocean',
mode='add',
water_level=z_offset_manual)
ocean_bcs += [ocean_bc, ocean_offset_bc]
elif ocean_method == 'flux-otps':
ocean_bc = drv.MultiBC(drv.OTPSFlowBC, name='Ocean', otps_model='wc')
ocean_bcs.append(ocean_bc)
elif ocean_method == 'velocity-otps':
ocean_bc = drv.MultiBC(drv.OTPSVelocityBC, name='Ocean', otps_model='wc')
ocean_bcs.append(ocean_bc)
elif ocean_method.startswith('velocity-hycom'):
# explicity give bounds to make sure we always download the same
# subset.
# z_offset here is the elevation of MSL in the model vertical datum.
# NAVD88 is offset by z_offset_manual, but MSL is a bit higher than
# that.
ocean_bc = drv.HycomMultiVelocityBC(ll_box=hycom_ll_box,