Climate Normals

Climate normals provide an overview of the typical weather at a given location. Normals are usually calculated over a period of 30 years.

Example

You can use the Normals class to retrieve mean data and prepare the records for further processing. For more complex analysis and visulization tasks you can utilize Pandas.

# Import Meteostat library and dependencies
from datetime import datetime
import matplotlib.pyplot as plt
from meteostat import Normals

# Get Normals data
data = Normals('10637', 1961, 1990)
data = data.fetch()

# Plot line chart including average, minimum and maximum temperature
data.plot(y=['tavg', 'tmin', 'tmax'])
plt.show()

API

• meteostat.Normals
• meteostat.Normals.convert
• meteostat.Normals.fetch
• meteostat.Normals.count

Data Structure

Each month is represented by a Pandas DataFrame row which provides the average weather data recorded during that month. These are the different columns:

Column	Description	Type
station	The Meteostat ID of the weather station (only if query refers to multiple stations)	String
start	The first year (YYYY) of the reference period	Integer
end	The last year (YYYY) of the reference period	Integer
month	The month, represented as an integer	Integer
tavg	The mean air temperature in °C	Float64
tmin	The mean minimum air temperature in °C	Float64
tmax	The mean maximum air temperature in °C	Float64
prcp	The mean monthly precipitation total in mm	Float64
wspd	The mean wind speed in km/h	Float64
pres	The mean sea-level air pressure in hPa	Float64
tsun	The mean sunshine total in minutes (m)	Float64