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)