def generate_input(N):
"""Generate a PISM bootstrapping file for a neighborhood number N."""
output_filename = options.output_file_prefix + "_%08d.nc" % N
pism_output_filename = options.output_file_prefix + "_o_%08d.nc" % N
nc = NC(output_filename, 'w')
format_string = "{0:0%db}" % (M * M)
string = format_string.format(N)
x = np.linspace(-options.L * 1000, options.L * 1000, M)
zeros = np.zeros((M, M))
thk = np.zeros(M * M)
topg = zeros.copy() - 0.1 * options.H
topg[1, 1] = -options.H
for j in range(M * M):
if string[j] == '1':
thk[j] = options.H
nc.create_dimensions(x, x)
nc.write("topg", topg, attrs={"units": "m", "long_name": "bed_topography"})
nc.write("climatic_mass_balance", zeros, attrs={"units": "kg m-2 year-1"})
nc.write("ice_surface_temp", zeros, attrs={"units": "Celsius"})
nc.write("thk", thk.reshape(M, M),
attrs={"units": "m", "long_name": "land_ice_thickness"})
nc.close()
return output_filename, pism_output_filename
def create_output_file(filename, grid_size, start_year):
"create the output file and set up the grid"
zero = zeros((grid_size,grid_size))
try:
nc = NC(filename, 'a')
return nc, zero
except:
pass
nc = NC(filename, 'w')
Lx = 750000
Ly = 750000
dx = 2 * Lx / grid_size
dy = 2 * Ly / grid_size
x_min = -Lx + 0.5 * dx
x_max = Lx - 0.5 * dx
y_min = -Ly + 0.5 * dy
y_max = Ly - 0.5 * dy
x = linspace(x_min, x_max, grid_size)
y = linspace(y_min, y_max, grid_size)
nc.create_dimensions(x, y, time_dependent = True,
use_time_bounds = True)
nc.variables['time'].units = "days since %d-1-1" % (start_year)
nc.variables['time'].calendar = "gregorian"
return nc, zero
def generate_input(N):
"""Generate a PISM bootstrapping file for a neighborhood number N."""
output_filename = options.output_file_prefix + "_%08d.nc" % N
pism_output_filename = options.output_file_prefix + "_o_%08d.nc" % N
nc = NC(output_filename, 'w')
format_string = "{0:0%db}" % (M * M)
string = format_string.format(N)
x = np.linspace(-options.L * 1000, options.L * 1000, M)
zeros = np.zeros((M, M))
thk = np.zeros(M * M)
topg = zeros.copy() - 0.1 * options.H
topg[1, 1] = -options.H
for j in range(M * M):
if string[j] == '1':
thk[j] = options.H
nc.create_dimensions(x, x)
nc.write("topg", topg, attrs={"units": "m", "long_name": "bed_topography"})
nc.write("climatic_mass_balance", zeros, attrs={"units": "kg m-2 year-1"})
nc.write("ice_surface_temp", zeros, attrs={"units": "Celsius"})
nc.write("thk",
thk.reshape(M, M),
attrs={
"units": "m",
"long_name": "land_ice_thickness"
})
nc.close()
return output_filename, pism_output_filename
def generate_pism_input(x, y, xx, yy):
stderr.write("calling exactP_list() ...\n")
EPS_ABS = 1.0e-12
EPS_REL = 1.0e-15
# Wrapping r[:]['r'] in np.array() forces NumPy to make a C-contiguous copy.
h_r, magvb_r, _, W_r, P_r = exactP_list(np.array(r[:]['r']), EPS_ABS, EPS_REL, 1)
stderr.write("creating gridded variables ...\n")
# put on grid
h = np.zeros_like(xx)
W = np.zeros_like(xx)
P = np.zeros_like(xx)
magvb = np.zeros_like(xx)
ussa = np.zeros_like(xx)
vssa = np.zeros_like(xx)
for n, pt in enumerate(r):
j = pt['j']
k = pt['k']
h[j, k] = h_r[n] # ice thickness in m
magvb[j, k] = magvb_r[n] # sliding speed in m s-1
ussa[j, k], vssa[j, k] = radially_outward(magvb[j, k], xx[j, k], yy[j, k])
W[j, k] = W_r[n] # water thickness in m
P[j, k] = P_r[n] # water pressure in Pa
stderr.write("creating inputforP.nc ...\n")
nc = PISMDataset("inputforP.nc", 'w')
nc.create_dimensions(x, y, time_dependent=True, use_time_bounds=True)
nc.define_2d_field("thk", time_dependent=False,
attrs={"long_name": "ice thickness",
"units": "m",
"valid_min": 0.0,
"standard_name": "land_ice_thickness"})
nc.define_2d_field("topg", time_dependent=False,
attrs={"long_name": "bedrock topography",
"units": "m",
"standard_name": "bedrock_altitude"})
nc.define_2d_field("climatic_mass_balance", time_dependent=False,
attrs={"long_name": "climatic mass balance for -surface given",
"units": "kg m-2 year-1",
"standard_name": "land_ice_surface_specific_mass_balance"})
nc.define_2d_field("ice_surface_temp", time_dependent=False,
attrs={"long_name": "ice surface temp (K) for -surface given",
"units": "Kelvin",
"valid_min": 0.0})
nc.define_2d_field("bmelt", time_dependent=False,
attrs={"long_name": "basal melt rate",
"units": "m year-1",
"standard_name": "land_ice_basal_melt_rate"})
nc.define_2d_field("bwat", time_dependent=False,
attrs={"long_name": "thickness of basal water layer",
"units": "m",
"valid_min": 0.0})
nc.define_2d_field("bwp", time_dependent=False,
attrs={"long_name": "water pressure in basal water layer",
"units": "Pa",
"valid_min": 0.0})
nc.define_2d_field("bc_mask", time_dependent=False,
attrs={"long_name": "if =1, apply u_ssa_bc and v_ssa_bc as sliding velocity"})
nc.define_2d_field("u_ssa_bc", time_dependent=False,
attrs={"long_name": "x-component of prescribed sliding velocity",
"units": "m s-1"})
nc.define_2d_field("v_ssa_bc", time_dependent=False,
attrs={"long_name": "y-component of prescribed sliding velocity",
"units": "m s-1"})
Phi0 = 0.20 # 20 cm/year basal melt rate
T_surface = 260 # ice surface temperature, K
variables = {"topg": np.zeros_like(xx),
"climatic_mass_balance": np.zeros_like(xx),
"ice_surface_temp": np.ones_like(xx) + T_surface,
"bmelt": np.zeros_like(xx) + Phi0,
"thk": h,
"bwat": W,
"bwp": P,
"bc_mask": np.ones_like(xx),
"u_ssa_bc": ussa,
"v_ssa_bc": vssa}
for name in variables.keys():
nc.write(name, variables[name])
nc.history = subprocess.list2cmdline(argv)
nc.close()
stderr.write("NetCDF file %s written\n" % "inputforP.nc")
bc_mask[thk > 0] = 1
# make the bed deep everywhere except in icy areas, where it is barely
# grounded
z = np.zeros_like(xx) - 1000.0
z[thk > 0] = -(910.0 / 1028.0) * 100.0 + 1
# Velocity Dirichlet B.C.:
ubar = np.zeros_like(thk)
vbar = np.zeros_like(thk)
vbar[bc_mask == 1] = 100.0
try:
nc = NC(options.output, 'w')
nc.create_dimensions(x, y, time_dependent=False)
nc.define_2d_field("topg",
attrs={
"units": "m",
"long_name": "bedrock topography"
})
nc.define_2d_field("thk",
attrs={
"units": "m",
"long_name": "ice thickness"
})
nc.define_2d_field("climatic_mass_balance",
attrs={"units": "kg m-2 year-1"})
nc.define_2d_field("ice_surface_temp", attrs={"units": "Celsius"})
bc_mask[thk > 0] = 1
# make the bed deep everywhere except in icy areas, where it is barely
# grounded
z = np.zeros_like(xx) - 1000.0
z[thk > 0] = -(910.0 / 1028.0) * 100.0 + 1
# Velocity Dirichlet B.C.:
ubar = np.zeros_like(thk)
vbar = np.zeros_like(thk)
vbar[bc_mask == 1] = 100.0
try:
nc = NC(options.output, 'w')
nc.create_dimensions(x, y, time_dependent=False)
nc.define_2d_field("topg", attrs={"units": "m",
"long_name": "bedrock topography"})
nc.define_2d_field("thk", attrs={"units": "m",
"long_name": "ice thickness"})
nc.define_2d_field("climatic_mass_balance", attrs={"units": "kg m-2 year-1"})
nc.define_2d_field("ice_surface_temp", attrs={"units": "Celsius"})
nc.define_2d_field("u_ssa_bc", attrs={"units": "m/year"})
nc.define_2d_field("v_ssa_bc", attrs={"units": "m/year"})
except:
nc = NC(options.output, 'a')
nc.write("topg", z)
exit(1)
def get(name):
global innc
return np.squeeze(innc.variables[name][:])
x = get('x')
y = get('y')
bmelt = get('basal_melt_rate_grounded')
Mx = len(x)
My = len(y)
zero = np.zeros((My, Mx))
nc.create_dimensions(x, y, time_dependent=True, use_time_bounds=True)
def drainage(t):
"""time-dependence of bogus summer runoff event in m/a: a positive wavepacket"""
return np.exp(-(t - 180.0) ** 2 / 80.0) * 20.0 * (np.cos(0.2 * t * 2 * 3.14159) + 1.0)
year = 2012
nc.variables['time'].units = "days since %d-1-1" % (year)
# generate space-time bogus summer runoff event; mask where bmelt > 0
for a in range(1, 366):
nc.append_time(a, (a, a + 1))
inputthisday = (zero + drainage(np.double(a))) * (bmelt > 0)
nc.write("inputtobed", inputthisday, True)
exit(1)
def get(name):
global innc
return np.squeeze(innc.variables[name][:])
x = get('x')
y = get('y')
bmelt = get('basal_melt_rate_grounded')
Mx = len(x)
My = len(y)
zero = np.zeros((My, Mx))
nc.create_dimensions(x, y, time_dependent=True, use_time_bounds=True)
def drainage(t):
"""time-dependence of bogus summer runoff event in m/a: a positive wavepacket"""
return np.exp(
-(t - 180.0)**2 / 80.0) * 20.0 * (np.cos(0.2 * t * 2 * 3.14159) + 1.0)
year = 2012
nc.variables['time'].units = "days since %d-1-1" % (year)
# generate space-time bogus summer runoff event; mask where bmelt > 0
for a in range(1, 366):
nc.append_time(a, (a, a + 1))
inputthisday = (zero + drainage(np.double(a))) * (bmelt > 0)
return nearest.sum() / nearest.size
return fill_value
for j in xrange(1,shape[0]-1):
for i in xrange(1,shape[1]-1):
if data[j,i] == fill_value:
data[j,i] = fix_a_hole(i, j)
fill_holes(usurf)
x = np.linspace(-890500., 1720500., shape[1])
y = np.linspace(-628500., -3410500., shape[0])
nc = NC("NSIDC_Greenland_1km.nc", 'w')
nc.create_dimensions(x, y)
nc.define_2d_field("usurf", time_dependent = False, nc_type='i',
attrs = {"long_name" : "upper surface elevation DEM",
"comment" : "Downloaded from %s" % (ftp_url),
"units" : "cm",
"valid_min" : 0.0,
"mapping" : "mapping",
"_FillValue" : -1})
nc.write_2d_field("usurf", usurf)
nc.define_2d_field("dist", time_dependent = False, nc_type='i',
attrs = {"long_name" : "Mean distance from contributing GLAS data for each grid cell",
"comment" : "Downloaded from %s" % (ftp_url),
"units" : "mm",
"valid_min" : 0.0,
"mapping" : "mapping"})
def vel_mosaic2netcdf(filename_base, output_filename):
files = []
for (short_name, long_name) in [("vx", "ice surface velocity in the X direction"),
("vy", "ice surface velocity in the Y direction"),
("ex",
"error estimates for the X-component of the ice surface velocity"),
("ey",
"error estimates for the Y-component of the ice surface velocity"),
]:
try:
os.stat(filename_base + "." + short_name)
entry = ("%s.%s" %(filename_base,short_name), short_name, long_name)
files.append(entry)
except:
print "Missing %s.%s. If this file ends with ex or ey the script will work just fine" %(filename_base, short_name)
grid = np.loadtxt(filename_base + ".vx.geodat", skiprows=1, comments="&")
shape = (int(grid[0,1]), int(grid[0,0]))
x0 = grid[2,0] * 1e3
y0 = grid[2,1] * 1e3
dx = grid[1,0]
dy = grid[1,1]
x1 = x0 + (shape[1] - 1) * dx
y1 = y0 + (shape[0] - 1) * dx
x = np.linspace(x0, x1, shape[1])
y = np.linspace(y0, y1, shape[0])
nc = NC("%s.nc" % output_filename, 'w')
nc.create_dimensions(x, y)
for (filename, short_name, long_name) in files:
nc.define_2d_field(short_name, time_dependent = False, nc_type='f4',
attrs = {"long_name" : long_name,
"comment" : "Downloaded from %s" % (ftp_url + filename),
"units" : "m / year",
"mapping" : "mapping",
"_FillValue" : -2e+9})
var = np.fromfile(filename, dtype=">f4", count=-1)
nc.write_2d_field(short_name, var)
# Add a mask that shows where observations are present
if options.add_mask == True:
nc.define_2d_field("vel_surface_mask", time_dependent = False, nc_type='i',
attrs = {"long_name" : "Mask observations; 1 where surface vel. available",
"comment" : "Used as vel_misfit_weight in inversion for tauc",
"units" : "",
"mapping" : "mapping",
"_FillValue" : 0})
var = np.fromfile(filename_base + ".vx", dtype=">f4", count=-1)
mask = var/var
mask[var == -2e9] = 0.
nc.write_2d_field("vel_surface_mask", mask)
mapping = nc.createVariable("mapping", 'c')
mapping.grid_mapping_name = "polar_stereographic"
mapping.standard_parallel = 70.0
mapping.latitude_of_projection_origin = 90.0
mapping.straight_vertical_longitude_from_pole = -45.0
mapping.ellipsoid = "WGS84"
nc.Conventions = "CF-1.4"
nc.projection = "+proj=stere +ellps=WGS84 +datum=WGS84 +lon_0=-45 +lat_0=90 +lat_ts=70 +units=m"
nc.reference = "Joughin, I., B. Smith, I. Howat, and T. Scambos. 2010. MEaSUREs Greenland Ice Velocity Map from InSAR Data. Boulder, Colorado, USA: National Snow and Ice Data Center. Digital media."
nc.title = "MEaSUREs Greenland Ice Velocity Map from InSAR Data"
from time import asctime
import sys
separator = ' '
historystr = "%s: %s\n" % (asctime(), separator.join(sys.argv))
nc.history = historystr
nc.close()
x = np.linspace(0, options.length, options.Mx)
y = x[0:3] - x[1]
xx, yy = np.meshgrid(x, y)
zeros = np.zeros((My, options.Mx))
topg = (0.5 * options.length - xx) * bed_slope
thk = zeros.copy()
thk[topg > 200] = ice_thickness
v = zeros.copy()
u = zeros.copy() + U
nc.create_dimensions(x, y)
nc.write("topg", topg, attrs={"units": "m", "long_name": "bed_topography"})
nc.write("climatic_mass_balance", zeros, attrs={"units": "kg m-2 year-1"})
nc.write("ice_surface_temp", zeros, attrs={"units": "Celsius"})
nc.write("thk",
thk,
attrs={
"units": "m",
"standard_name": "land_ice_thickness"
})
nc.write("ubar",
u,
attrs={
"units": "m/year",
"long_name": "x-component of velocity"
})
def grid2netcdf(filename_base, output_filename):
print "Reading txt files with data ..."
x, y, topg, fill_value = readComposite("%sbottom.txt" % filename_base)
x, y, thk, fill_value = readComposite("%sthickness.txt" % filename_base)
x, y, usurf, fill_value = readComposite("%ssurface.txt" % filename_base)
nc = NC("%s.nc" % output_filename, "w")
nc.create_dimensions(x, y)
names = []
for (short_name, long_name) in [
("topg", "bedrock surface elevation"),
("thk", "land ice thickness"),
("usurf", "ice upper surface elevation"),
]:
entry = (short_name, long_name)
names.append(entry)
var = [topg, thk, usurf]
for i, (short_name, long_name) in enumerate(names):
nc.define_2d_field(
short_name,
time_dependent=False,
nc_type="f4",
attrs={
"long_name": long_name,
"comment": "Downloaded from ftp://data.cresis.ku.edu/data/grids/Jakobshavn_2006_2012_Composite.zip",
"units": "m",
"mapping": "mapping",
"_FillValue": fill_value,
},
)
nc.write_2d_field(short_name, var[i])
# Add a mask that shows where observations are present
nc.define_2d_field(
"obs_mask",
time_dependent=False,
nc_type="i",
attrs={
"long_name": "Mask observations; 1 where observations available",
"units": "",
"mapping": "mapping",
"_FillValue": 0,
},
)
mask = np.ones(thk.shape)
mask[thk == fill_value] = 0.0
nc.write_2d_field("obs_mask", mask)
mapping = nc.createVariable("mapping", "c")
mapping.grid_mapping_name = "polar_stereographic"
mapping.standard_parallel = 70.0
mapping.latitude_of_projection_origin = 90.0
mapping.straight_vertical_longitude_from_pole = -45.0
mapping.ellipsoid = "WGS84"
nc.Conventions = "CF-1.4"
nc.projection = "+proj=stere +ellps=WGS84 +datum=WGS84 +lon_0=-45 +lat_0=90 +lat_ts=70 +units=m"
nc.reference = "Gogineni, Prasad. 2012. CReSIS Radar Depth Sounder Data, Lawrence, Kansas, USA. Digital Media. http://data.cresis.ku.edu"
nc.title = "CReSIS Gridded Depth Sounder Data for Jakobshavn, Greenland"
nc.acknowledgement = "We acknowledge the use of data and/or data products from CReSIS generated with support from NSF grant ANT-0424589 and NASA grant NNX10AT68G"
from time import asctime
import sys
separator = " "
historystr = "%s: %s\n" % (asctime(), separator.join(sys.argv))
nc.history = historystr
print "Done writing %s.nc ..." % output_filename
nc.close()
# Run nc2cdo to add lat/lon
print "Adding lat/lon by running nc2cdo.py ..."
os.system("nc2cdo.py %s.nc" % output_filename)
