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%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from nansat import Nansat
# access online SST data via OpenDAP
n1 = Nansat(
'http://thredds.met.no/thredds/dodsC/sea_ice/SST-METNO-ARC-SST_L4-OBS-V2-V1/sst_arctic_aggregated',
date='2012-06-01',
bands=['analysed_sst'])
# access online Cholorphyll data via OpenDAP
n2 = Nansat(
'https://rsg.pml.ac.uk/thredds/dodsC/CCI_ALL-v2.0-8DAY',
date='2012-06-01',
bands=['chlor_a'])
# get transects from points given by longitutde, latitude
t1 = n1.get_transect([[24, 24], [71, 77]], ['analysed_sst'])
t2 = n2.get_transect([[24, 24], [71, 77]], ['chlor_a'])
# fetch values from transect
sst_lat = t1['lat']
sst_val = t1['analysed_sst']
chl_lat = t2['lat']
chl_val = t2['chlor_a']
# mask invalid SST values
sst_val[sst_val < 0] = np.nan
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from IPython.core.display import Image
Image(filename='chl_vs_sst.png')
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n2.write_map('n2map.png')
In [16]:
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
# setup Basemap
m = Basemap(projection='cyl',resolution='l',
llcrnrlon=10.,llcrnrlat=65,
urcrnrlon=30.,urcrnrlat=80.)
m.etopo()
m.plot([24,24],[71,77], '.-')
plt.savefig('basemap_transect.png', dpi=300, bbox_inches='tight')
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