Scripts to compare LASSO LES and CCPP SCM data #14
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CCPP SCM LASSO cases.
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Thank you for this contribution. I only reviewed the README file - everything was well explained. @bluefinweiwei is now reviewing some other aspects of the PR.
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Hi @evankalina Thanks so so much for the great effort and the very detailed instructions. All look very nice to me and I've only left some minor comments. I have to say I should have more carefully reviewed Dan's scripts but I didn't due to multiple reasons (sorry about that!)... Anyway, I think we can merge this PR very soon.
| qtend_scm = f_cases[:]->q_tend_profile_SCM | ||
| wspdtend_scm = f_cases[:]->wspd_tend_profile_SCM | ||
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| ; Calculate the lapse rate of potential temperature. |
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Since the calculation is based on theta not actual temperature (T), we probably would want to call it static stability criteria for dry air but not lapse rate (or gamma).
| ; creates kinks because the derivative of a line is a | ||
| ; constant value. Need to preserve the original structure | ||
| ; within the surface layer, which requires some tricks. | ||
| gamma_scm_smoo=runave(gamma_scm,8,0) |
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Why applying 8-point (but not others) moving average? For removing kinks?
| ; within the surface layer, which requires some tricks. | ||
| gamma_scm_smoo=runave(gamma_scm,8,0) | ||
| gamma_scm_smoo(:,:,1)=gamma_scm(:,:,1) | ||
| gamma_scm_smoo(:,:,2)=dim_avg_n(gamma_scm(:,:,1:3),2) |
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3-point moving average applied to 3rd level, correct?
| gamma_scm_smoo=runave(gamma_scm,8,0) | ||
| gamma_scm_smoo(:,:,1)=gamma_scm(:,:,1) | ||
| gamma_scm_smoo(:,:,2)=dim_avg_n(gamma_scm(:,:,1:3),2) | ||
| gamma_scm_smoo(:,:,3)=dim_avg_n(gamma_scm(:,:,1:5),2) |
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5-point moving average applied to 4th level, correct?
| ; constant value. Need to preserve the original structure | ||
| ; within the surface layer, which requires some tricks. | ||
| gamma_scm_smoo=runave(gamma_scm,8,0) | ||
| gamma_scm_smoo(:,:,1)=gamma_scm(:,:,1) |
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Do we have gamma_scm_smoo(:,:,0)?
| hgtscm3d = conform(ttendctl_nat_Khr,hgtscm_m,(/0,1/)) | ||
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| ; SCM specific humidity to water vapor mixing ratio. | ||
| rvctl_nat_kgkg = qvctl_nat_kgkg/(1.-qvctl_nat_kgkg) |
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This is neat and accurate (as I usually just assume SH = Qv...).
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| ; Finding the density of air using the ideal gas law to convert surface tau | ||
| ; (wind stress) to surface winds | ||
| rhoscm = psfcscm / (tmpscm_K(:,0) * R_dry) |
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Considering moisture, virtual temperature (Tv) should be used?
| case_files = True | ||
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| ; Directory to write results. | ||
| diro = "/work/noaa/ufs-phys/ekalina/lasso-les/comparison_data/" |
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Okay, now I see what this directory is all about.
| Evan Kalina. | ||
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| * LASSO_SCM_plot_composite.ncl - Generate composites of the LASSO LES and | ||
| CCPP SCM results from all of the cases. Not run by LASSO_wrapper.ncl. |
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What does "Not run by LASSO_wrapper.ncl." mean? Why highlight this?
| * LASSO_SCM_plot_composite.ncl - Generate composites of the LASSO LES and | ||
| CCPP SCM results from all of the cases. Not run by LASSO_wrapper.ncl. | ||
| * LASSO_SCM_multicase_comp.ncl - Plot the results from each individual case | ||
| on the same plot. The computation of the potential temperature lapse rate |
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Still, not sure about the term "potential temperature lapse rate" here... do we really have such a thing, or it's simply the static stability criteria for dry air?
@bluefinweiwei and @ligiabernardet, this PR adds scripts to compare LASSO LES data subsets from Wayne Angevine (CIRES at NOAA/CSL) to output from CCPP SCM runs of the 2018 LASSO cases. For a full explanation of the capabilities, please see lasso-scm_comp/README_wa_subsets.txt.