Analyze SCM results

Analyze SCM results carson Fri, 12/20/2019 - 15:27

Let’s analyze the results

The output directory for each case is controlled by its case configuration namelist. For this exercise, a directory containing the output for each integration is placed in the bin directory. You may now inspect that each of these output directories (e.g. bin/output_$CASE_$SUITENAME) now contains a populated output.nc file.

At this point, one could use whatever plotting tools they wish to examine the output. For this course, we will use the basic Python scripts that are included in the repository. The script is called gmtb_scm_analysis.py and expects a configuration file as an argument. The configuration file specifies which output files to read, which variables to plot, and how to do so.

Run the following to generate plots for the LASSO case:

./gmtb_scm_analysis.py lasso_short_course.ini

The script creates a new directory within the bin directory called plots_LASSO_2016051812/comp/full.

Open plot files for variables, such as mean profiles of water vapor specific humidity, cloud water mixing ratio, temperature, and temperature tendencies due to forcing and physics processes.

cd plots_LASSO_2016051812/comp/full

eog profiles_mean_qv.png

Supplemental slide 16 provides some context for how the simulation changes through time and slides 17-20 show the plots mentioned above. You may ignore any warnings about libGL.

Despite using very different physics suites, there is relatively little difference in the results.

Q: Why do you think that is?

A: This particular continental shallow convection case is very weakly forced. Two of the suites (csawmg and GSD_v1) produce a very small amount of cloud water. Moist processes tend to produce the largest differences among physics suites, so the fact that none of the suites produce much in the way of cloud cover means that there is less of a chance for the solutions to diverge.