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Get daily weather station data (Global)

A set of Python tools to make it easier to extract weather station data (e.g., temperature, precipitation) from the Global Historical Climatology Network - Daily (GHCND)

"The Global Historical Climatology Network daily (GHCNd) is an integrated database of daily climate summaries from land surface stations across the globe. GHCNd is made up of daily climate records from numerous sources that have been integrated and subjected to a common suite of quality assurance reviews. GHCNd contains records from more than 100,000 stations in 180 countries and territories. NCEI provides numerous daily variables, including maximum and minimum temperature, total daily precipitation, snowfall, and snow depth. About half the stations only report precipitation. Both record length and period of record vary by station and cover intervals ranging from less than a year to more than 175 years." source

More information on the data can be found here

Installation

  1. Install from the source code:
  • Clone the repository source code:
git clone https://github.com/scotthosking/get-station-data.git
  • Install along with its dependencies:
cd /path/to/my/get-station-data
pip install -v -e .

Worked through example

from get_station_data import ghcnd
from get_station_data.util import nearest_stn

%matplotlib inline

Read station metadata

stn_md = ghcnd.get_stn_metadata()

Choose a location (lon/lat) and number of nearest neighbours

london_lon_lat = -0.1278, 51.5074
my_stns = nearest_stn(stn_md, 
                        london_lon_lat[0], london_lon_lat[1], 
                        n_neighbours=5 )
my_stns
station lat lon elev name
52113 UKE00105915 51.5608 0.1789 137.0 HAMPSTEAD
52165 UKM00003772 51.4780 -0.4610 25.3 HEATHROW
52098 UKE00105900 51.8067 0.3581 128.0 ROTHAMSTED
52191 UKW00035054 51.2833 0.4000 91.1 WEST MALLING
52131 UKE00107650 51.4789 0.4489 25.0 HEATHROW

Download and extract data into a pandas DataFrame

df = ghcnd.get_data(my_stns)

df.head()
station year month day element value mflag qflag sflag date lon lat elev name
0 UKE00105915 1959 12 1 TMAX NaN 1959-12-01 0.1789 51.5608 137.0 HAMPSTEAD
1 UKE00105915 1959 12 2 TMAX NaN 1959-12-02 0.1789 51.5608 137.0 HAMPSTEAD
2 UKE00105915 1959 12 3 TMAX NaN 1959-12-03 0.1789 51.5608 137.0 HAMPSTEAD
3 UKE00105915 1959 12 4 TMAX NaN 1959-12-04 0.1789 51.5608 137.0 HAMPSTEAD
4 UKE00105915 1959 12 5 TMAX NaN 1959-12-05 0.1789 51.5608 137.0 HAMPSTEAD

Filter data for, e.g., a single variable

var = 'PRCP'   # precipitation
df = df[ df['element'] == var ]

### Tidy up columns
df = df.rename(index=str, columns={"value": var})
df = df.drop(['element'], axis=1)

df.head()
station year month day PRCP mflag qflag sflag date lon lat elev name
93 UKE00105915 1960 1 1 2.5 E 1960-01-01 0.1789 51.5608 137.0 HAMPSTEAD
94 UKE00105915 1960 1 2 1.5 E 1960-01-02 0.1789 51.5608 137.0 HAMPSTEAD
95 UKE00105915 1960 1 3 1.0 E 1960-01-03 0.1789 51.5608 137.0 HAMPSTEAD
96 UKE00105915 1960 1 4 0.8 E 1960-01-04 0.1789 51.5608 137.0 HAMPSTEAD
97 UKE00105915 1960 1 5 0.0 E 1960-01-05 0.1789 51.5608 137.0 HAMPSTEAD 
df.drop(columns=['mflag','qflag','sflag']).tail(n=10)
station year month day PRCP date lon lat elev name
83938 UKE00107650 2016 12 22 0.0 2016-12-22 0.4489 51.4789 25.0 HEATHROW
83939 UKE00107650 2016 12 23 1.4 2016-12-23 0.4489 51.4789 25.0 HEATHROW
83940 UKE00107650 2016 12 24 0.0 2016-12-24 0.4489 51.4789 25.0 HEATHROW
83941 UKE00107650 2016 12 25 1.0 2016-12-25 0.4489 51.4789 25.0 HEATHROW
83942 UKE00107650 2016 12 26 0.0 2016-12-26 0.4489 51.4789 25.0 HEATHROW
83943 UKE00107650 2016 12 27 0.0 2016-12-27 0.4489 51.4789 25.0 HEATHROW
83944 UKE00107650 2016 12 28 0.2 2016-12-28 0.4489 51.4789 25.0 HEATHROW
83945 UKE00107650 2016 12 29 0.4 2016-12-29 0.4489 51.4789 25.0 HEATHROW
83946 UKE00107650 2016 12 30 0.0 2016-12-30 0.4489 51.4789 25.0 HEATHROW
83947 UKE00107650 2016 12 31 0.4 2016-12-31 0.4489 51.4789 25.0 HEATHROW

Save to file

df.to_csv('London_5stns_GHCN-D.csv', index=False)

Plot histogram of all data

df['PRCP'].plot.hist(bins=40)
<matplotlib.axes._subplots.AxesSubplot at 0x11ae36898>

png

Plot time series for one station

heathrow = df[ df['name'] == 'HEATHROW' ]
heathrow['PRCP'].plot()
<matplotlib.axes._subplots.AxesSubplot at 0x81f0d7240>

png