Exercise 2

Hint

Execute the notebook on the training platform >>

About

Let us have a closer look at the forecast data from both models for one observation station in Tenerife (Canary Islands). Let us plot the time-series of the CAMS and MONARCH forecasts together in one plot.

Tasks

1. Download and animate the CAMS global forecast for 21 Feb 2020

• Download the CAMS global atmospheric composition forecast for 21 February 2020, with the following specifications:

  Variable on single levels: Dust aerosol optical depth at 550 nm
  Date (Start and end): 2020-02-21
  Time: 12:00
  Leadtime hour: every three hours from 0 to 90
  Type: Forecast
  Restricted area: N: 67, W: -30, E: 71, S: -3
  Format: Zipped netCDF
  

• Hint

  • CAMS global atmospheric composition forecasts - Example notebook

  • Data access

2. Get the coordinates of the AERONET station Santa Cruz, Tenerife

• Hint

  • You can see an overview of all available AERONET Site Names here

3. Select the time-series for CAMS global atmospheric composition forecasts for Santa Cruz, Tenerife

• Hint

  • With the xarray function sel() and keyword argument method='nearest' you can select data based on coordinate information

  • We also recommend you to transform your xarray.DataArray into a pandas.DataFrame with the function to_dataframe() and save it as csv with the function to_csv()

4. Load the MONARCH dust forecasts and select time-series for Santa Cruz, Tenerife

• Hint

  • With the xarray function sel() and keyword argument method='nearest' you can select data based on coordinate information

  • We also recommend you to transform your xarray.DataArray into a pandas.DataFrame with the function to_dataframe() and save it as csv with the function to_csv()

5. Visualize both time-series of CAMS and MONARCH forecasts together in one plot