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:
https://noresm-docs.readthedocs.io/en/latest/diagnostics/diagnostics.html
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 :
&phys_ctl_nl history_aerosol = .true. /
Two more diagnostics are useful:
To enable this, take the file cam/src/physics/cam_oslo$ vim preprocessorDefinitions.h and copy it to your SourceMods/src.cam 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
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 infile.nc outfile.nc
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
or
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
To switch on extra output for cloud diagnostics (mass and number tendencies for liquid water and mass) change the following namelist variable:
&phys_ctl_nl history_budget = .true. /
A python script for plotting the mass and number budgets for the cloud microphysics can be found under:
models/atm/cam/tools/diagnostics/ncl/cloudBudgets
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:
python scriptname.py
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
“aerocom3_<ModelName>_<ExperimentName>_<VariableName>_<VerticalCoordinateType>_<Period>_<Frequency>.nc”
<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/
ESMVALtool http://www.geosci-model-dev-discuss.net/8/7541/2015/gmdd-8-7541-2015-discussion.html
cis tools http://www.cistools.net
JASMIN http://www.jasmin.ac.uk/services/jasmin-analysis-platform/
A tool for post analysis of (multiple) CAM diagnostics ASCII tables can be found in the following repository:
GitHub https://github.com/jgliss/noresm_diag_postproc
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 (https://github.com/jgliss/noresm_diag_postproc/blob/master/analysis_tool.ipynb)
which includes more detailed instructions about setup and options.
Use the notebook
https://github.com/jgliss/noresm_diag_postproc/blob/master/download_tables.ipynb
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:
https://github.com/jgliss/noresm_diag_postproc/blob/master/config/var_groups.ini
NOTE: If you add groups to this file in your local copy of the repository, please consider sending the updated to jonasg@met.no or to submit a pull request, so that the remote repository remains up to date.
Troubleshooting
If you run into problems, please raise an issue in the repository or contact jonasg@met.no