Land-surface Permafrost - Autoassess diagnostics

Overview

Permafrost thaw is an important impact of climate change, and is the source of a potentially strong Earth system feedback through the release of soil carbon into the atmosphere. This recipe provides metrics that evaluate the climatological performance of models in simulating soil temperatures that control permafrost. Performance metrics (with observation-based estimates in brackets):

  • permafrost area (17.46 million square km)

  • fractional area of permafrost northwards of zero degree isotherm (0.47)

  • soil temperature at 1m minus soil temperature at surface (-0.53 degrees C)

  • soil temperature at surface minus air temperature (6.15 degrees C)

  • annual amplitude at 1m / annual amplitude at the surface (0.40 unitless)

  • annual amplitude at the surface / annual air temperature (0.57 unitless)

Plots:

  • Maps of permafrost extent and zero degC isotherm

  • 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_permafrost.yml

Diagnostics are stored in esmvaltool/diag_scripts/autoassess/

  • autoassess_area_base.py: wrapper for autoassess scripts

  • land_surface_permafrost/permafrost.py: script to calculate permafrost metrics

  • plot_autoassess_metrics.py: plot normalised assessment metrics

User settings in recipe

  1. Script autoassess_area_base.py

    Required settings for script

    • area: must equal land_surface_permafrost to select this diagnostic

    • control_model: name of model to be used as control

    • exp_model: name of model to be used as experiment

    • start: date (YYYY/MM/DD) at which period begins (see note on time gating)

    • end: date (YYYY/MM/DD) at which period ends (see note on time gating)

    • climfiles_root: path to observation climatologies

    Optional settings for script

    • title: arbitrary string with name of diagnostic

    • obs_models: unused for this recipe

    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_permafrost 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

  • tas (atmos, monthly mean, longitude latitude time)

  • tsl (land, monthly mean, longitude latitude time)

  • mrsos (land, monthly mean, longitude latitude time)

  • sftlf (mask, fixed, longitude latitude)

Observations and reformat scripts

None

References

  • Observed permafrost extent is from http://nsidc.org/data/ggd318.html: Brown, J., O. Ferrians, J. A. Heginbottom, and E. Melnikov. 2002. Circum-Arctic Map of Permafrost and Ground-Ice Conditions, Version 2. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. When calculating the global area of permafrost the grid cells are weighted by the proportion of permafrost within them.

  • Annual mean air temperature is from: Legates, D. R., and C. J. Willmott, 1990: Mean seasonal and spatial variability in global surface air temperature. Theor. Appl. Climatol., 41, 11-21. The annual mean is calculated from the seasonal mean data available at the Met Office.

  • The soil temperature metrics are calcuated following: Charles D. Koven, William J. Riley, and Alex Stern, 2013: Analysis of Permafrost Thermal Dynamics and Response to Climate Change in the CMIP5 Earth System Models. J. Climate, 26. (Table 3) http://dx.doi.org/10.1175/JCLI-D-12-00228.1 The locations used for Table 3 were extracted from the model and the modelled metrics calculated.

Example plots

pf_extent_north_america_ACCESS-CM2.png

Fig. 52 Permafrost extent and zero degC isotherm, showing North America

pf_extent_asia_ACCESS-CM2.png

Fig. 53 Permafrost extent and zero degC isotherm, showing Asia and Europe

Permafrost_Metrics.png

Fig. 54 Normalised metrics plot comparing a control and experiment simulation

Additional notes on usage

The landsurface_permafrost area metric is part of the esmvaltool/diag_scripts/autoassess diagnostics, and, as any other autoassess metric, it uses the autoassess_area_base.py as general purpose wrapper. This wrapper accepts a number of input arguments that are read through from the recipe.

This recipe is part of the larger group of Autoassess metrics ported to ESMValTool from the native Autoassess package from the UK’s Met Office. The diagnostics settings are almost the same as for the other Autoassess metrics.

Note

Time gating for autoassess metrics.

To preserve the native Autoassess functionalities, data loading and selection on time is done somewhat differently for ESMValTool’s autoassess metrics: the time selection is done in the preprocessor as per usual but a further time selection is performed as part of the diagnostic. For this purpose the user will specify a start: and end: pair of arguments of scripts: autoassess_script (see below for example). These are formatted as YYYY/MM/DD; this is necessary since the Autoassess metrics are computed from 1-Dec through 1-Dec rather than 1-Jan through 1-Jan. This is a temporary implementation to fully replicate the native Autoassess functionality and a minor user inconvenience since they need to set an extra set of start and end arguments in the diagnostic; this will be phased when all the native Autoassess metrics have been ported to ESMValTool review has completed.

An example of standard inputs as read by autoassess_area_base.py and passed over to the diagnostic/metric is listed below.

scripts:
  plot_landsurf_permafrost: &plot_landsurf_permafrost_settings
    <<: *autoassess_landsurf_permafrost_settings
    control_model: MPI-ESM-LR
    exp_model: MPI-ESM-MR
    script: autoassess/plot_autoassess_metrics.py
    ancestors: ['*/autoassess_landsurf_permafrost']
    title: "Plot Land-Surface Permafrost Metrics"
    plot_name: "Permafrost_Metrics"
    diag_tag: aa_landsurf_permafrost
    diag_name: autoassess_landsurf_permafrost