Land-surface Soil Moisture - Autoassess diagnostics#

Overview#

Soil moisture is a critical component of the land system, controling surface energy fluxes in many areas of the world. This recipe provides metrics that evaluate the skill of models’ spatial and seasonal distribution of soil moisture against the ESA CCI soil moisture ECV.

Performance metrics:

  • median absolute error (model minus observations)

Metrics are calculated using model and observation multi-year climatologies (seasonal means) for meteorological seasons:

  • December-January-February (djf)

  • March-April-May (mam)

  • June-July-August (jja)

  • September-October-November (son)

Plots:

  • Normalised assessment metrics plot comparing control and experiment

The recipe takes as input a control model and experimental model, comparisons being made with these two models.

Available recipes and diagnostics#

Recipes are stored in esmvaltool/recipes/

  • recipe_autoassess_landsurface_soilmoisture.yml

Diagnostics are stored in esmvaltool/diag_scripts/autoassess/

  • land_surface_soilmoisture/soilmoisture.py: script to calculate soil moisture metrics

  • plot_autoassess_metrics.py: plot normalised assessment metrics

User settings in recipe#

  1. Script soilmoisture.py

    Required settings for script

    • area: must equal land_surface_soilmoisture to select this diagnostic

    • control_model: name of model to be used as control

    • exp_model: name of model to be used as experiment

    Optional settings for script

    none

    Required settings for variables

    none

    Optional settings for variables

    none

  2. Script plot_autoassess_metrics.py

    Required settings for script

    • area: must equal land_surface_soilmoisture to select this diagnostic

    • control_model: name of model to be used as control in metrics plot

    • exp_model: name of model to be used as experiment in metrics plot

    • title: string to use as plot title

    Optional settings for script

    none

    Required settings for variables

    none

    Optional settings for variables

    none

Variables#

  • mrsos (from models: land, monthly mean, longitude latitude time)

  • sm (from observations: land, monthly mean, longitude latitude time)

Observations and reformat scripts#

1999-2008 climatologies (seasonal means) from ESA ECV Soil Moisture Dataset v1. Produced by the ESA CCI soil moisture project: https://www.esa-soilmoisture-cci.org/node/93

References#

  • Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001.

  • Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth System Science Data 11, 717-739, https://doi.org/10.5194/essd-11-717-2019

Example plots#

Soilmoisture_Metrics.png

Fig. 65 Normalised metrics plot comparing a control and experiment simulation#