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:

bash git clone https://github.com/scotthosking/get-station-data.git

• Install along with its dependencies:

bash cd /path/to/my/get-station-data pip install -v -e .

Worked through example

```python from getstationdata import ghcnd from getstationdata.util import nearest_stn

%matplotlib inline ```

Read station metadata

python stn_md = ghcnd.get_stn_metadata()

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

python 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

Download and extract data into a pandas DataFrame

```python df = ghcnd.getdata(mystns)

df.head() ```

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

```python 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() ```

python df.drop(columns=['mflag','qflag','sflag']).tail(n=10)

Save to file

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

Plot histogram of all data

python df['PRCP'].plot.hist(bins=40)

Plot time series for one station

python heathrow = df[ df['name'] == 'HEATHROW' ] heathrow['PRCP'].plot()

<matplotlib.axes._subplots.AxesSubplot at 0x81f0d7240>