Hydro forcing comparison#


This recipe can be used to assess the agreement between forcing datasets (i.e. MSWEP, ERA5, ERA-Interim) for a defined catchment. The recipe can be used to:

  1. Plot a timeseries of the raw daily data

  2. Plot monthly aggregrated data over a defined period

  3. Plot the monthly / daily climatology statistics over a defined period

Available recipes and diagnostics#

Recipes are stored in esmvaltool/recipes/hydrology

  • recipe_hydro_forcing.yml

Diagnostics are stored in esmvaltool/diag_scripts/hydrology/

  • hydro_forcing.py: Compares and plots precipitation for MSWEP / ERA5 / ERA-5 interim datasets

User settings in recipe#

All hydrological recipes require a shapefile as an input to select forcing data. This shapefile determines the shape of the basin for which the data will be cut out and processed. All recipes are tested with the shapefiles from HydroSHEDS that are used for the eWaterCycle project. In principle any shapefile can be used, for example, the freely available basin shapefiles from the HydroSHEDS project.

  1. recipe hydrology/hydro_forcing.yml

Optional preprocessor settings:

  • extract_shape: The region specified here should match the catchment

Required settings for script:

  • plot_type: Define which plot function to run. Choices:

    • timeseries: Plot a timeseries for the variable data over the defined period

    • climatology: Plot the climate statistics over the defined period

Required settings for ``timeseries`` plots:

  • time_period: Defines the period of the output for the correct captions/labels. This value should match the period used for the preprocessor. Choices: day, month.


  • pr (atmos, daily or monthly, longitude, latitude, time)


All data can be used directly without any preprocessing.

  • ERA-Interim

  • ERA5


Example plots#


Fig. 190 Precipitation per day for 2015-01-01:2016-12-31.#


Fig. 191 Precipitation per month for 2015-01:2016-12.#


Fig. 192 Precipitation climatology statistics per month number.#


Fig. 193 Precipitation climatology statistics per day of year.#