# General plotting settings
sns.set_style('whitegrid')
sns.set_context("talk", font_scale=1.5, rc={"lines.linewidth": 2.5})
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E = ed.EsioData.load()
# Directories
all_models = ['usnavygofs', 'usnavyncep', 'usnavysipn']
runType = 'forecast'
updateall = False
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stero_grid_file = E.obs['NSIDC_0051']['grid']
obs_grid = import_data.load_grid_info(stero_grid_file, model='NSIDC')
# Ensure latitude is within bounds (-90 to 90)
# Have to do this because grid file has 90.000001
obs_grid['lat_b'] = obs_grid.lat_b.where(obs_grid.lat_b < 90, other=90)
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# Regridding Options
# method='conservative_normed' # ['bilinear', 'conservative', 'nearest_s2d', 'nearest_d2s', 'patch']
method = 'nearest_s2d'
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# Set models that are different
var_dic = {'aice': 'sic'}
model = 'gfdlsipn'
runType = 'forecast'
base_dir = r'/home/disk/sipn/nicway/data/'
ftp_dir = r'/home/disk/sipn/upload/'
data_dir = os.path.join(ftp_dir, model, runType)
data_out = os.path.join(base_dir, 'model', model, runType, 'sipn_nc')
model_grid_file = os.path.join(base_dir, 'grids', 'GFDLFLOR_gridinfo.nc')
stero_grid_file = os.path.join(base_dir, 'grids', 'stereo_gridinfo.nc')
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updateall = False
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gfdl_grid = import_data.load_grid_info(model_grid_file, model='GFDL')
gfdl_grid.dims
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# # Plot the input Grid
# %matplotlib notebook
# plt.figure(figsize=(10,8));
# ax1 = plt.axes(projection=ccrs.PlateCarree())
# ax1.scatter(gfdl_grid['lon_b'], gfdl_grid['lat_b'], s=6, c='r', transform=ccrs.PlateCarree()) # plot grid locations
# ax1.scatter(gfdl_grid['lon'], gfdl_grid['lat'], s=3, c='b', transform=ccrs.PlateCarree()) # plot grid locations
# plt.xlabel('lon')
# plt.ylabel('lat')
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