Access Model and Observations using RESTful web services

Using the NOAA ERDDAP web service, extract the latest data from a specified NDBC Station. Then using the Unidata "grid as point" NetCDF Subset Service, extract a time series closest to a specified lon,lat location.

At first we use the NetCDF Subset Web Form below to construct the query, but then reuse the URL generated by the form directly in the Python code below. In this way different time periods, depths or variables may be extracted without returning to the form, and analyzed and visualized in Python without saving and loading CSV files.



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from IPython.display import HTML



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import pandas as pd
import time
import datetime as dt

Specify NDBC Buoy Station



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station = '44098'  #  Block Island



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# Specify desired time range
# ....relative to right now ....
tstart = dt.datetime.utcnow() - dt.timedelta(days=4)
tstop = dt.datetime.utcnow() + dt.timedelta(days=1)

start=tstart.strftime('%Y-%m-%dT%H:%M:%SZ')
stop=tstop.strftime('%Y-%m-%dT%H:%M:%SZ')

# ... or specific times (UTC)

#start = '2014-08-24T00:00:00Z'
#stop =  '2014-08-28T00:00:00Z'

print start,'\n', stop









    



2014-08-23T15:54:54Z 
2014-08-28T15:54:54Z

Read NDBC Wave Buoy Data using ERDDAP



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#HTML('http://coastwatch.pfeg.noaa.gov/erddap/tabledap/cwwcNDBCMet.html')



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url='http://coastwatch.pfeg.noaa.gov/erddap/tabledap/cwwcNDBCMet.csv?\
station,time,longitude,latitude,wvht\
&station="%s"&time>=%s&time<=%s' % (station,start,stop)
print url









    



http://coastwatch.pfeg.noaa.gov/erddap/tabledap/cwwcNDBCMet.csv?station,time,longitude,latitude,wvht&station="44007"&time>=2014-08-23T15:54:54Z&time<=2014-08-28T15:54:54Z



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# read CSV observations into Pandas DataFrame
df_obs = pd.read_csv(url,index_col='time',parse_dates=True,skiprows=[1])



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lon=df_obs['longitude'][0]
lat=df_obs['latitude'][0]
print lon,lat









    



-70.144 43.531

Read COAWST Wave Data at the NDBC Buoy Location using the Unidata NetCDF Subset Service



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#HTML("http://geoport.whoi.edu/thredds/ncss/grid/bbleh/spring2012/pointDataset.html")



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var = 'Hwave' 
url='http://geoport.whoi.edu/thredds/ncss/grid/coawst_4/use/fmrc/coawst_4_use_best.ncd?\
var=%s&latitude=%f&longitude=%f&time_start=%s&time_end=%s&\
vertCoord=&accept=csv' % (var,lat,lon,start,stop)
print(url)









    



http://geoport.whoi.edu/thredds/ncss/grid/coawst_4/use/fmrc/coawst_4_use_best.ncd?var=Hwave&latitude=43.531000&longitude=-70.144000&time_start=2014-08-23T15:54:54Z&time_end=2014-08-28T15:54:54Z&vertCoord=&accept=csv



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#load model data CSV into Pandas DataFrame
df_mod = pd.read_csv(url,index_col='date',parse_dates=True)

Plot the time series



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fig, ax = plt.subplots(figsize=(12, 4))
ax = df_mod['Hwave[unit="meter"]'].plot(ax=ax, legend=True)
df_obs['wvht'].plot(ax=ax, legend=True)
ax.set_title('Wave Height at Station %s' % station);



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