Output
Output
In principle, output of ICON-ART variables works the same way as for ICON variables. As described in , the following five quantities of the output have to be specified:
- The time interval between two model outputs.
- The name of the output file.
- The name of the variable(s) and/or variable group(s).
- The type of vertical output grid.
- The type of horizontal output grid.
It is recommended to use NETCDF output on an interpolated grid. A corresponding output namelist for sea salt on model levels can be seen here:
NAMELIST EXAMPLE &output_nml filetype = 4 ! output format: 2=GRIB2, 4=NETCDFv2 dom = 1 ! write output for domain 1 output_start = "JJJJ-MM-DDTHH:MM:SSZ" !put date in output_end = "JJJJ-MM-DDTHH:MM:SSZ" !put date in output_interval = "PT1H" ! \href{ISO8601}{https://en.wikipedia.org/wiki/ISO_8601} steps_per_file = 1 ! max. num. of time steps within one file mode = 1 ! 1: forecast mode (relative t-axis) include_last = .TRUE. ! include the last time step output_filename = '<INSERTFILENAME>' ! file name base ml_varlist = 'seasa','seasb','seasc', 'seasa0','seasb0','seasc0' remap = 1 ! output is transferred to lat long grid reg_lon_def = -180.,0.5,179.5 !start, incr., end, in deg. reg_lat_def = 90.,-0.5, -90. !start, incr., end, in deg.
There is an option to obtain all sea salt variables without having to specifying all of them. Therefore, you may use the group ART_AERO_SEAS.
This changes the namelist variable ml_varlist from the example above to the following:
ml_varlist = 'group:ART_AERO_SEAS'
The output variables that are associated to this group will be written. You can check the groups of output variables in the tables in .
Available Output Variables
The possible prognostic output fields are shown in , the diagnostic fields in and .
Description | Groups | ||
---|---|---|---|
seasa | iart_seasalt = 1 | Sea salt mode A mass concentration | ART_AERO _SEAS |
seasb | iart_seasalt = 1 | Sea salt mode B mass concentration | ART_AERO _SEAS |
seasc | iart_seasalt = 1 | Sea salt mode C mass concentration | ART_AERO _SEAS |
seasa0 | iart_seasalt = 1 | Sea salt mode A number concentration | ART_AERO _SEAS |
seasb0 | iart_seasalt = 1 | Sea salt mode B number concentration | ART_AERO _SEAS |
seasc0 | iart_seasalt = 1 | Sea salt mode C number concentration | ART_AERO _SEAS |
dusta | iart_dust = 1,2 | Mineral dust mode A mass concentration | ART_AERO _DUST |
dustb | iart_dust = 1,2 | Mineral dust mode B mass concentration | ART_AERO _DUST |
dustc | iart_dust = 1,2 | Mineral dust mode C mass concentration | ART_AERO _DUST |
dusta0 | iart_dust = 1,2 | Mineral dust mode A number concentration | ART_AERO _DUST |
dustb0 | iart_dust = 1,2 | Mineral dust mode B number concentration | ART_AERO _DUST |
dustc0 | iart_dust = 1,2 | Mineral dust mode C number concentration | ART_AERO _DUST |
asha | iart_volcano = 2 | Mineral dust mode A mass concentration | ART_AERO _VOLC |
ashb | iart_volcano = 2 | Mineral dust mode B mass concentration | ART_AERO _VOLC |
ashc | iart_volcano = 2 | Mineral dust mode C mass concentration | ART_AERO _VOLC |
asha0 | iart_volcano = 2 | Mineral dust mode A number concentration | ART_AERO _VOLC |
ashb0 | iart_volcano = 2 | Mineral dust mode B number concentration | ART_AERO _VOLC |
ashc0 | iart_volcano = 2 | Mineral dust mode C number concentration | ART_AERO _VOLC |
CS137 | iart_radioact = 1 | Radioactive tracer:Caesium 137 | future release |
I131 | iart_radioact = 1 | Radioactive tracer:Iodine 131 | future release |
TE132 | iart_radioact = 1 | Radioactive tracer:Tellurium 132 | future release |
ZR95 | iart_radioact = 1 | Radioactive tracer:Zirconium 95 | future release |
XE133 | iart_radioact = 1 | Radioactive tracer:Xenon 133 | future release |
I131g | iart_radioact = 1 | Radioactive tracer:Iodine (gaseous) 131 | future release |
I131o | iart_radioact = 1 | Radioactive tracer:Iodine 131 | future release |
BA140 | iart_radioact = 1 | Radioactive tracer:Barium 140 | future release |
RU103 | iart_radioact = 1 | Radioactive tracer:Ruthenium 103 | future release |
ash1 | iart_volcano = 1 | Volcanic ash size bin 1 | future release |
ash2 | iart_volcano = 1 | Volcanic ash size bin 2 | future release |
ash3 | iart_volcano = 1 | Volcanic ash size bin 3 | future release |
ash4 | iart_volcano = 1 | Volcanic ash size bin 4 | future release |
ash5 | iart_volcano = 1 | Volcanic ash size bin 5 | future release |
ash6 | iart_volcano = 1 | Volcanic ash size bin 6 | future release |
TRCHBr3 | iart_chem_mechanism = 0 | Stratospheric tracer:CHBr3 | future release |
TRCH2Br2 | iart_chem_mechanism = 0 | Stratospheric tracer:CH2Br2 | future release |
Description | Groups | ||
---|---|---|---|
seasa_diam | iart_seasalt = 1 lart_diag_out = .true. | Median diameter of sea salt mode A | ART_AERO _SEAS |
seasb_diam | iart_seasalt = 1 lart_diag_out = .true. | Median diameter of sea salt mode B | ART_AERO _SEAS |
seasc_diam | iart_seasalt = 1 lart_diag_out = .true. | Median diameter of sea salt mode C | ART_AERO _SEAS |
dusta_diam | iart_dust = 1,2 lart_diag_out = .true. | Median diameter of mineral dust mode A | ART_AERO _DUST |
dustb_diam | iart_dust = 1,2 lart_diag_out = .true. | Median diameter of mineral dust mode B | ART_AERO _DUST |
dustc_diam | iart_dust = 1,2 lart_diag_out = .true. | Median diameter of mineral dust mode C | ART_AERO _DUST |
tau_seas_550nm | iart_seasalt = 1 lart_diag_out = .true. | Sea salt aerosol optical depth (AOD) at . | ART_AERO _SEAS |
tau_dust_550nm | iart_dust = 1,2 lart_diag_out = .true. | Mineral dust aerosol optical depth (AOD) at . | ART_AERO _DUST |
Description | Groups | ||
---|---|---|---|
ncalls_warm | iart_aci_warm = 1 lart_diag_out = .true. | Number of calls of activation routine (accumulated) | future release |
aci_nnuctot_warm | iart_aci_warm = 1 lart_diag_out = .true. | Number of activated particles (accumulated, warm-phase) | future release |
aci_nnucfhh_warm | iart_aci_warm = 1 lart_diag_out = .true. | Number of activated particles according to FHH theory (accumulated, warm-phase) | future release |
smax_water | iart_aci_warm = 1 lart_diag_out = .true. | Maximum supersaturation over liquid water | future release |
ncalls_cold | iart_aci_cold = 1,2,3,4,5,6 lart_diag_out = .true. | Number of calls of ice nucleation routine (accumulated) | future release |
aci_nnuctot_cold | iart_aci_cold = 1,2,3,4,5,6 lart_diag_out = .true. | Number of total nucleated (homogeneous freezing + heterogeneous nucleation) particles (accumulated, cold-phase) | future release |
aci_nnuchet_cold | iart_aci_cold = 1,2,3,4,5,6 lart_diag_out = .true. | Number of heterogeneously nucleated particles (accumulated, cold-phase) | future release |
smax_ice | iart_aci_cold = 1,2,3,4,5,6 lart_diag_out = .true. | Maximum supersaturation over ice | future release |
Output Checks with SAMOA
SAMOA performs a sanity check on all model outputs that can be read by CDO. It checks if a variable lies in-between a predefined range and if the minimum and maximum value of each variable are the same. For this purpose CDO version 1.6.2rc3 is required currently (see https://code.zmaw.de/projects/cdo).
For more information about the usage please refer to the README-file within the SAMOA package. You can get a copy of the SAMOA script by writing an e-mail to the contact person of the ART code (see http://icon-art.imk-tro.kit.edu). SAMOA is licensed under the GNU GENERAL PUBLIC LICENSE Version 3.
As SAMOA is primarily developed for the usage with COSMO-ART and COSMO-CLM, you have to do a minor change before using it. The latest version of SAMOA has a list for the usage of SAMOA with ICON-ART output included but not loaded automatically. This list is called samoa_list_icon-art. You have to replace the default (COSMO) list that is used by SAMOA by editing samoa.sh:
Search for the following lines:
# Path to the list with variables (is overwritten when -l specified) # Assumed to be on the same path as script path_list=$SCRIPTPATH/list
Change the name of the list to:
path_list=$SCRIPTPATH/samoa_list_icon-art
Now you may use SAMOA with the ICON-ART output file out.nc with the following command:
./samoa.sh out.nc
For all options see:
./samoa.sh --help
Visualisation
The horizontal grid structure of the output is essential for the visualization. In general, there are two possibilities. The output may exist on the ICON grid and it may exist on an interpolated longitude/latitude grid. This can be chosen by adaptions of the output namelist (see ). Although it comes along with a loss in information, it is recommended to use interpolated output. By this, the visualization is much easier to handle.
In the following sections, three tools are introduced which can be used to visualize ICON output. Note, that only NETCDF is supported by ICON-ART so far. With the tool Ncview (see ) it is very easy to have a quick look into the interpolated model output. NCL (see ) is a very comprehensive tool for all kind of data formats and visualization. With ParaView (see ), a nice-looking three-dimensional visualization can be created.
Ncview
"Ncview is a visual browser for netCDF format files. Typically you would use ncview to get a quick and easy, push-button look at your netCDF files. You can view simple movies of the data, view along various dimensions, take a look at the actual data values, change color maps, invert the data, etc." (http://meteora.ucsd.edu/~pierce/ncview_home_page.html)
NCL
"NCL is an interpreted language designed specifically for scientific data analysis and visualization. Portable, robust and free, NCL is available as binaries or open source." (https://www.ncl.ucar.edu/)
ParaView
"ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities.
ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of exascale size as well as on laptops for smaller data." (http://www.paraview.org/)
Python
On the official Website Python describes itself as
Python is powerful... and fast; plays well with others; runs everywhere; is friendly & easy to learn; is Open.
Using Python is a simple but effective way to display ICON-ART model output data. There is a large number of Packages available to help with Visualisation, the most useful Packages for visualising ICON-ART data are given in Table 1.4
numpy | predefined Mathematical functions |
matplotlib | Plotting framework |
xarray | reading in and processing netcdf datasets |
... |
[tab:pythonpackages]