Template for daily nowcast figure generation.

SalishSeaCast NEMO Model Daily Nowcast Figures¶

Set-up¶

In [1]:

import datetime
from glob import glob
from importlib import reload
import os

from IPython.core.display import HTML
import netCDF4 as nc

#from nowcast.figures import figures
from nowcast.figures.publish import pt_atkinson_tide
from nowcast.figures.publish import storm_surge_alerts
from nowcast.figures.publish import compare_tide_prediction_max_ssh

import scipy.io as sio

%matplotlib inline

In [ ]:

def results_dataset(period, grid, results_dir):
    """Return the results dataset for period (e.g. 1h or 1d)
    and grid (e.g. grid_T, grid_U) from results_dir.
    """
    filename_pattern = 'SalishSea_{period}_*_{grid}.nc'
    filepaths = glob(os.path.join(results_dir, filename_pattern.format(period=period, grid=grid)))
    return nc.Dataset(filepaths[0])

In [2]:

run_date = datetime.date.today()
run_date = datetime.datetime(2017, 12, 13)
# Results dataset location
results_home = '/results/SalishSea/forecast/'
results_dir = os.path.join(results_home, run_date.strftime('%d%b%y').lower())

Load the results datasets:

In [ ]:

grid_T_hr = results_dataset('1h', 'grid_T', results_dir)
grid_T_dy = results_dataset('1d', 'grid_T', results_dir)
grid_U_dy = results_dataset('1d', 'grid_U', results_dir)
grid_V_dy = results_dataset('1d', 'grid_V', results_dir)

Set lots of paths etc

In [3]:

bathy = nc.Dataset('/ocean/sallen/allen/research/MEOPAR/grid/bathymetry_201702.nc')

In [4]:

tidal_predictions = '/SalishSeaCast/tidal-predictions/'
timezone = 'Canada/Pacific'
names = [
        'Point Atkinson', 'Victoria', 'Campbell River', 'Cherry Point',
        'Friday Harbor', 'Neah Bay', 'Nanaimo', 'Sand Heads', 'Boundary Bay',
        'Port Renfrew', 'Halfmoon Bay', 'Friday Harbor', 'Patricia Bay',
        'Squamish'
    ]
filepath_tmpl = os.path.join(results_dir, '{}.nc')
grids_15m = {
        name: nc.Dataset(filepath_tmpl.format(name.replace(' ', '')))
        for name in names
    }
weather_path = '/results/forcing/atmospheric/GEM2.5/operational'
coastline = sio.loadmat('/ocean/rich/more/mmapbase/bcgeo/PNW.mat')

Display the figures:

In [5]:

HTML('<h2>{:%d%b%y} Figures</h2>'.format(run_date))

Out[5]:

13Dec17 Figures

In [ ]:

fig = figures.ssh_PtAtkinson(grid_T_hr)

Website Figures¶

Website Thumbnail¶

Threshold Website¶

In [23]:

reload(storm_surge_alerts)

Out[23]:

<module 'nowcast.figures.publish.storm_surge_alerts' from '/ocean/sallen/allen/research/Meopar/SalishSeaNowcast/nowcast/figures/publish/storm_surge_alerts.py'>

In [24]:

fig = storm_surge_alerts.make_figure(grids_15m, weather_path, coastline, tidal_predictions)

PA Tidal Predictions¶

In [ ]:

fig = pt_atkinson_tide.make_figure(grid_T_hr, tidal_predictions, timezone)

Victoria, PA, Campbell River, Nanaimo, Cherry Point SSH¶

In [ ]:

fig = compare_tide_prediction_max_ssh.make_figure('Victoria', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)

In [ ]:

fig = compare_tide_prediction_max_ssh.make_figure('Point Atkinson', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)

In [ ]:

fig = compare_tide_prediction_max_ssh.make_figure('Campbell River', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)

In [ ]:

fig = compare_tide_prediction_max_ssh.make_figure('Nanaimo', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)

In [ ]:

fig = compare_tide_prediction_max_ssh.make_figure('Cherry Point', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)

NOAA ssh¶

In [ ]:

fig = figures.compare_water_levels(grid_T_hr, bathy, grids_15m, coastline)

In [ ]:

fig = figures.PA_max_ssh(grid_T_hr,bathy)

In [ ]:

fig = figures.Sandheads_winds(grid_T_hr)

In [ ]:

reload(figures)

In [ ]:

fig = figures.thalweg_salinity(grid_T_dy)

In [ ]:

fig = figures.plot_surface(grid_T_dy, grid_U_dy, grid_V_dy, bathy)

In [ ]: