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dveg option for NOAH-MP LSM

Alessandro Delo

New member
Dear all,

I'm running several exps with WRF (v. 4.4.1) + WRF-HYDRO (v. 5.2) and I'm facing some issues related to the evaluation of the 2 meter temperature in a specific region of Europe (Balkan area in details). My simulations show a difference of more than 10˚ over this region with respect ERA5 dataset. I suspect it is something related to the LAI (Leaf area index) parameter. I'm trying to do a bit of sensitivity about the dveg option that can be used within NOAHMP LSM. Reading the WRF userguide, there are several choices that one can do related on how to set the dveg option in the WRF namelist:
- "lai predicted" (options 2 e 5): we are activating a model, within NOAMP, related to the vegetation;
- "lai from table" (options 1 and 3, maybe 7, 8 and 9), reads this variable from Table.
- "lai from input" (options 7, 8 e 9): takes monthly LAI from geo_em (I/m actually using MODIS dataset, 30arcsec resolution).

To me, it is not clear enough the difference between the options "Lai from table" and "Lai from input". Can someone help me to fully get this point? Which is the difference between them?

Many many thanks in advance!


Ming Chen

Staff member

If "Lai from table", it means that LAI will be read from VEGPARM.TBL based on land use type

if ""Lai from input"", it indicates that the model will suit LAI from static data.

The nameliust option "rdlai2d" determines which option will be used.

rdlai2d = .false. ! use LAI from input; false means using values from table

Alessandro Delo

New member
Hi Ming,
thank you very much for your precious and very explicative message! Now everything is clear.
We missed to include, in the WRF namelist, the "rdlai2d" option, so I fear we have run all our experiments performed till now without taking LAI from input files (MODIS dataset), even if devg option=7 was activated. I already submitted a new run by adding the option you suggested us: it should work now!

I'll update you when the run will finish!

Thank you very much again!


Alessandro Delo

New member
Dear Ming, dear all,

I just finished to validate the results of my last exp by adding the voice in the namelist you suggested me last time (rdlai2d set to true), so to consider LAI from input files (dveg option =7 for NOAH-MP LSM). I compared my results with ERA5 dataset for T2M (but also for rainfall and wind speed). The exp refers to 2019. Unfortunately, I was not able to obtain a sensible improvement for T2M, the issue I evidenced last time over the Balkan region still remains evident. I attach 2D lat/lon seasonal maps I produced so you can have an idea on what I'm referring to. I'm also facing a strong underestimation of rainfall.
I attach also the namelist I'm using to run my exps (the one I'm sending is referred to a 30 days simulation), maybe you/somebody can have a look and could suggest me something to improve my results. I fear I'm missing something there (i.e, not using the proper physical parameterization or, maybe, some static fields are not good enough for my region of interest, even if I'm using the latest ones available and downloadable for WRF website). The version of WRF I'm using is 4.4.1, WRF-HYDRO is 5.2.0.

Thank you very much in advance for your help!



  • T2m_2019.png
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  • rainfall_2019.png
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  • wind_speed_2019.png
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  • namelist_input_1.txt
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Ming Chen

Staff member
Hi Alessandro,
I looked at your namelist.inout. Both the physics and dynamic options look appropriate.
The only concern I have is the resolution of your case. Note that cumulus scheme works fine for grid interval larger than 10km, and it should be turned off when grid interval is smaller than 3-4km. The resolution between 4-10km is the so called grey-zone, over which cumulus scheme no longer woks fine yet the convection cannot be well resolved. In your case, delx = 6km, and I would suggest you run with and without cumulus scheme, then compare the results and see which can give you better results.