NDBC station info

[rgcoe]

It would super nice if your ndbc module could easily pull station info such as location (longitude, latitude), buoy type, water depth, etc.

[ssolson]

Ryan agreed. I had been thinking about needing to do this. I believe that information is held in this location.

https://www.ndbc.noaa.gov/data/stations/station_table.txt

A simple string parser to match the head of the table. The longest part will just be writing the tests and going through reviews. I'll look into adding this during the quarter.

[rgcoe]

Good idea. That table does not appear to include depth, watch circle, and probably a couple of other useful details that the station page does list.

[rgcoe]

confession: I asked this question because I needed this functionality for a paper ;)

with the station_table.txt file I was able to make an ad hoc solution; thought I'd post it here in case it is helpful:

import pandas as pd
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.ticker as mticker
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER


def parseLatLon(s):
    lat = float(s.split(' N')[0])
    lon = -1*float(s.split('N ')[1].split(' W')[0])
    return [lat, lon]

def label_point_orig(df, ax):
    # https://stackoverflow.com/questions/15943945/annotate-scatterplot-from-a-pandas-dataframe
    a = pd.concat({'x': df['lon'], 'y': df['lat'], 'val': df['STATION_ID']}, axis=1)
    for i, point in a.iterrows():
        ax.text(point['x'], point['y'], str(point['val']))

df = pd.read_csv('station_table.txt', 
                     delimiter='|', 
                     header=0, 
                     names=['STATION_ID', 'OWNER', 'TTYPE', 'HULL', 'NAME', 
                            'PAYLOAD', 'LOCATION', 'TIMEZONE', 'FORECAST', 
                            'NOTE'])

lat = []
lon = []
for idx, row in df.iterrows():
    # stid = str(row['STATION_ID'])
    # print(stid)
    try:
        tmp_lat, tmp_lon = parseLatLon(row.LOCATION)
        lat.append(tmp_lat)
        lon.append(tmp_lon)
    except:
        lat.append(np.nan)
        lon.append(np.nan)
        
df['lat'] = lat
df['lon'] = lon

fig = plt.figure(figsize=[10,4])
ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines()
gl = ax.gridlines(alpha=0.5, linestyle='--', draw_labels=True,
                  linewidth=1, color='gray')
gl.ylocator = mticker.FixedLocator([-30, 0, 30, 60, 90])
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER

df.plot.scatter(ax=ax, x='lon',y='lat', s=30, 
                       linewidths=0.5,
                       edgecolors='k')
# label_point_orig(df,ax)
plt.show()

[ssolson]

Ryan this is great. I had been thinking about making a check_location that would help a user know if they had the right buoy/ coordinates which it looks like this could be adapted to do. You are right though it is missing the depth and other metadata about the buoy. I cannot find it in the https://www.ndbc.noaa.gov/data/ folder which will mean we would need to write a new custom function to web scrape the actual buoy page and make it a bit more of a job to do. I'll keep it on the radar as it is very useful to not need to look up the station on the web and copy/paste this information.

[cmichelenstrofer]

We will need this for the DLC project.