Calculate the spatial mean of gridded data over an area/bounding box

This notebook demonstrates how to compute the spatial mean of some sample 2m temperature data for a given rectangular area bounding box. This is done via the area keyword argument, it is a dictionary with keys "north", "south", "east", and "west".

from earthkit import data as ekd
from earthkit import transforms as ekt
from earthkit.transforms._tools import earthkit_remote_test_data_file

remote_era5_file = earthkit_remote_test_data_file("era5-Europe-sfc-2m-temperature-3deg-2015-2017.grib")
era5_data = ekd.from_source("url", remote_era5_file)
ds = era5_data.to_xarray()

# Define a bounding box covering central Europe
area = {"north": 55, "south": 45, "east": 20, "west": 5}

# Calculate area mean using the bounding box
area_mean_bbox = ekt.spatial.reduce(ds, area=area, how="mean", weights="latitude")

area_mean_bbox

<xarray.Dataset> Size: 70kB
Dimensions:                  (forecast_reference_time: 4384, index: 1)
Coordinates:
  * forecast_reference_time  (forecast_reference_time) datetime64[us] 35kB 20...
  * index                    (index) int64 8B 0
Data variables:
    2t                       (index, forecast_reference_time) float64 35kB 27...
Attributes:
    Conventions:  CF-1.8
    institution:  ECMWF

xarray.Dataset

• Dimensions:
  • forecast_reference_time: 4384
  • index: 1
• Coordinates: (2)
  • forecast_reference_time
    (forecast_reference_time)
    datetime64[us]
    2015-01-01 ... 2017-12-31T18:00:00

    standard_name :

    forecast_reference_time

    long_name :

    initial time of forecast

    array(['2015-01-01T00:00:00.000000', '2015-01-01T06:00:00.000000',
           '2015-01-01T12:00:00.000000', ..., '2017-12-31T06:00:00.000000',
           '2017-12-31T12:00:00.000000', '2017-12-31T18:00:00.000000'],
          shape=(4384,), dtype='datetime64[us]')

  • index
    (index)
    int64
    0

    [1 values with dtype=int64]

• Data variables: (1)
  • 2t
    (index, forecast_reference_time)
    float64
    271.4 271.3 274.5 ... 280.3 279.5

    standard_name :

    unknown

    long_name :

    mean 2 metre temperature

    units :

    kelvin

    level_type :

    surface

    _earthkit :

    {"message": {"__bytes_b64__": "R1JJQgAAbAEAADSAYv//gKcBAAAPAQEAAAEAAAAAAAAVAAAAAAAAAAAAAAAAAAAAARcCBAEwMDAxAAAAAAAgAP8AAB0AEwE0mIBhqIAAYagA5ngLuAu4AAAAAAAAAAwAgAJEuX1uAAA3Nzc3"}, "bitsPerValue": 16, "grid_spec": {"area": [79, -25, 25, 59], "grid": [3, 3], "reference": [2, 1]}}

    reduce_dims :

    ['latitude', 'longitude']

    array([[271.35822792, 271.30479363, 274.54553389, ..., 276.6322914 ,
            280.30588463, 279.45404046]], shape=(1, 4384))

• Attributes: (2)

  Conventions :

  CF-1.8

  institution :

  ECMWF