Downloading the data

Downloading the data#

All data files used in the lecture are available on this webserver.

CERES Data#

For Week 02, we will use climatological data from the CERES (Clouds and the Earth’s Radiant Energy System) mission. We are going to use the EBAF-TOA and the EBAF-Surface data products (both freely available on this webpage) as climatologies (i.e. monthly averages 2005-2015).

The data quality summary of these data (PDF) can be found here, and more accessible publications can be found here for TOA and here for Surface.

Download:

ERA5 data#

ERA5 is an atmospheric reanalysis product.

Invariant:

Monthly surface (3D) data:

Reading data from an url#

You can also open files without downloading them locally. This is somehow inefficient (it will download all data in memory each time you run the notebook), but might be useful e.g. on MyBinder where you can’t store files. You will need the h5netcdf library to be installed for the following to work:

import xarray as xr
import urllib, io

url = 'https://cluster.klima.uni-bremen.de/~fmaussion/teaching/climate/ERA5_LowRes_Invariant.nc'

req = urllib.request.Request(url)
with urllib.request.urlopen(req) as resp:
    ds = xr.open_dataset(io.BytesIO(resp.read()))

ds

<xarray.Dataset> Size: 3MB
Dimensions:    (longitude: 480, latitude: 241, time: 1)
Coordinates:
  * longitude  (longitude) float32 2kB -179.6 -178.9 -178.1 ... 178.9 179.6
  * latitude   (latitude) float32 964B 90.0 89.25 88.5 ... -88.5 -89.25 -90.0
  * time       (time) datetime64[ns] 8B 1979-01-01
Data variables:
    lsm        (time, latitude, longitude) float64 925kB ...
    wmb        (time, latitude, longitude) float64 925kB ...
    z          (time, latitude, longitude) float64 925kB ...
Attributes:
    Conventions:  CF-1.6
    history:      2019-11-18 09:24:36 GMT by grib_to_netcdf-2.14.0: /opt/ecmw...
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