Model Diagnostic Tools

This page links to tools used for the NorESM model evaluation.

NB: The wiki page for the NorESM diagnostic tools is moved!!

Last updated: 12-Dec-2020.

Please go to the following NorESM documentation page for the latest description:

Aerosol and Chemistry, Clouds and Forcing Diagnostics

In both the default CAM5-aerosol packages (MAM3,MAM7) and the Oslo-aerosol packages, the budget terms can be taken out using a variable in the namelist :

Configuring a run with more aerosol diagnostics in (NorESM2)

history_aerosol = .true.

Two more diagnostics are useful:

  • Enable estimates multiple calls to radiation which are necessary for effective radiative forcing estimates
  • Enable diagnostics for AEROCOM

To enable this, take the file cam/src/physics/cam_oslo$ vim preprocessorDefinitions.h and copy it to your SourceMods/ folder

Change both preprocessor definitions to true

#define AEROCOM
#define AEROFFL

The AEROCOM-token turns on diagnostics needed for AEROCOM The AEROFFL-token tells the model to do additional radiation-diagnostics for aerosol indirect effect

Fields produced in monthly average files when running with budgets activated

Running with budgets activated will produce the following terms in the monthly output files:

Output variable name Meaning Comment
SF{Tracer} Emissions from surface
GS_{Tracer} gas phase chemistry 3D-emissions and gas phase washout included in this term
AQ_{Tracer} aquous chemistry
{Tracer}_Mixnuc1 Activation in clouds and evaporation of cloud droplets
{Tracer}_DDF Dry deposition flux (aerosol tracers)
{Tracer}_SFWET Wet deposition flux (aerosol tracers)
{Tracer}_condtend loss/production in condensation/nuclation (CAM-Oslo only)
{Tracer}_coagTend loss/production in coagulation (CAM-Oslo only)
DF_{Tracer} dry deposition flux (gas tracers) output with history_aerosol with CAM-Oslo only
WD_A_{Tracer} wet deposititon flux (gas tracers) output with history_aerosol with CAM-Oslo only
{Tracer}_CLXF 3D-emissions (“external forcing”) output with history_aerosol with CAM-Oslo only
{Tracer}_clcoagTend loss of tracer due to coagulation with cloud droplets output with history_aerosol with CAM-Oslo only

Note: Since 3D-emissions and and gas washout rates are included in the term GS_{Tracer} in the mozart chemistry solver, the individual terms can be found like this (example for SO2):

ncap2 -O -s GS_ONLY_SO2=GS_SO2-WD_A_SO2-SO2_CLXF

More info on SO2 budgets (see /models/atm/cam/tools/diagnostics/ncl/ModIvsModII/ for scripts with info on all tracers):

GS_SO2 contains the SO2 budget terms for all that goes on in the chemistry-routine, which is
1) Gas phase chemistry, 2) Wet deposition, and 3) 3D-emissions.
Gas phase chemistry is both production from DMS (GS_DMS) and loss through OH (GL_OH)
For calculations of net loss, e.g. used to calculate SO2 life-times, we're interested in the
loss through OH from the chemistry-term (GL_OH).
GS_SO2 = GL_OH + SO2_CLXF - WD_A_SO2 - GS_DMS*64/62
GL_OH = GS_SO2 - SO2_CLXF + WD_A_SO2 + GS_DMS*64/62

Estimating chemical loss w.r.t. S (instead of SO2 or DMS), for comparison with CAM4-Oslo numbers:
net chemial loss gas phase = (GS_SO2/1.998 - SO2_CLXF + WD_A_SO2)/1.998 + GS_DMS/1.938
net chemical loss = net chemial loss gas phase + AQ_SO2/1.998

Finally, total net loss (used to calculate life-time = -load/(net loss), where load = cb_SO2/1.998):
net loss =
- WD_A_SO2/1.998 ;wet deposition in kg/m2/sec (positive in output file)
- DF_SO2/1.998 ;dry deposition in kg/m2/sec (positive in output file)
+ AQ_SO2/1.998 ;wet phase production of SO4 in kg/m2/ses (negative in output file)
+ (GS_SO2 - SO2_CLXF + WD_A_SO2)/1.998 + GS_DMS/1.938 ; net chemical loss gas phase

Looking at the aerosol budgets (CAM-Oslo only)

  • Go to the directory models/atm/cam/tools/diagnostics/ncl/budgets
  • Change the filename to use in the file budgets.ncl (“myFileName” around line 18). Should be for example yearly average of month-avg file in a run with budgets
  • Run the script to create a pdf-file (output.pdf)

Making ncl plots of often used aerosol and cloud fields, including ERFs, for two model versions (CAM-Oslo only)

  • Make a local copy (on Linux) of the directory models/atm/cam/tools/diagnostics/ncl/ModIvsModII
  • Assuming that you have produced output data from 4 simulations: two different model versions, each with PD and PI emissions, and all run with #define AEROCOM & AEROFFL:
  • In ModIvsModII.csh (note: read the header info):
  • - edit model info for the first model (shown to the left in the plots): modelI = CAM4-Oslo or modelI = CAM5-Oslo ?
  • - provide paths and partial file names of the model data (PD and PI) for Model I (CAM4-Oslo or CAM5-Oslo) and Model II (must be CAM5-Oslo)
  • - choose desired plot format (plotf=ps, eps, pdf or png)
  • Run the script: ./ModIvsModII.csh
  • Furthermore, to display the plots in an organized form by use of a web browser (only possible if the chosen plot format is png):
  • - edit general model info (only) in ModIvsModII.htm, and manually cut and paste the mass budget numbers from the script output into this file
  • - copy all png (plots) and htm files to the desired output (common) directory
  • - open ModIvsModII.htm in your browser: hyper-links to all other htm files, including plots, are found here

Configuring a run with more cloud diagnostics in NorESM2

To switch on extra output for cloud diagnostics (mass and number tendencies for liquid water and mass) change the following namelist variable:

history_budget = .true.

A python script for plotting the mass and number budgets for the cloud microphysics can be found under:


in the same branch. Copy the script to your local computer or lustre and edit the script to read the correct input file(s) (instructions inside the script). Run the script by typing:


in your terminal.

To prepare output so that it is processed automatically by the aerocom tools, use the script located at models/atm/cam/tools/aerocom/ in the svn repository. The script prepares files such that the idl aerocom tools prepare plots for the aerocom webinterface: URL link to NorESM on AeroCom webinterface

The script requires <ModelName>_<ExperimentName> and <Period> as input.

<Period>: for a climatological average and run choose 9999 , for nudged simulations choose the year of the meteorology

<ModelName>_<ExperimentName>: is the dataset identifier under which the plots appear on the AeroCom webinterface
in the required format NorESM-CAM5_svn{RevisionNumber}_YYMMDD{initials}_Freetext.

Example: “NorESM-CAM5_svn1094_151201AG_CMIP6endelig
Initials AG: Alf Grini, AK: Alf Kirkevåg, DO: Dirk Olivie…

Where the date YYMMDD corresponds to the time when the AeroCom data preparation script has been executed.

The script creates files named like


<ModelName> ⇒ eg NorESM-CAM53
<ExperimentName> ⇒ svn{RevisionNumber}_YYMMDD{initials}_Freetext
<VariableName> ⇒ aerocom variable names
<VerticalCoordinateType> ⇒ “Surface”, “Column”, “ModelLevel”, “SurfaceAtStations”, “ModelLevelAtStations” 
<Period> ⇒ eg “2008”, “2010”, “9999”
<Frequency> ⇒ “timeinvariant”,”hourly”, “daily”, “monthly”, “sat1000”, “sat1330”, “sat2200”, “sat0130”

Note that VerticalCoordinateType is dependent on the variable!! It is not a question about “vertical coordinate type used in model simulations”!

The script copies files on norstore into /projects/NS2345K/CAM-Oslo/DO_AEROCOM/<ModelName>_<ExperimentName>/renamed/

ESMval CIS JASMIN platform and tools

Post analysis and workup of CAM diagnostics output tables

A tool for post analysis of (multiple) CAM diagnostics ASCII tables can be found in the following repository:


To get started, please follow the instructions in repository README (displayed in repository). Currently, the main analysis tool is a jupyter IPython notebook called

analysis_tool.ipynb (

which includes more detailed instructions about setup and options.

Use the notebook

to download local copies of result tables using a list of URL's.

Short summary: The notebook reads multiple diagnostics files (runs) into one long table and creates heatmap plots of Bias, RMSE and RMSE relative error for a subset of variables (rows → y-axis of heatmap) vs. the individual runs (columns → xaxis).

NOTE: In the current version, you need to download all tables that you are interested in as csv or ascii into one directory, that is specified in the header of the notebook.

Variable groups can be defined in this config file:

NOTE: If you add groups to this file in your local copy of the repository, please consider sending the updated to or to submit a pull request, so that the remote repository remains up to date.


If you run into problems, please raise an issue in the repository or contact

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  • noresm/modeldiagnostics.txt
  • Last modified: 2022-05-31 09:29:32
  • (external edit)