Jessie ENT allometry parameter updates

[rosiealice]

these updates are primarily to improve the size distribution of the ENT's, and are taken from calibration by Adrianna for Black Spruce.

Pairs with
NorESMhub/CTSM#199

Description:

I can;t tag Jessie here, but she can provide more detail on the outcome of this new calibration. Example size class distributions are here: https://ns9560k.web.sigma2.no/datalake/diagnostics/noresm/rosief/NFM-L2-PFCLM51-SPITFIRE24-ECAregion2-RCcase35-c231222_r386_hist_GSWP3-W5E5/gifs/fates_vegc_szpf_trees_y1-80_ENT.gif

Collaborators:

Expectation of Answer Changes:

Checklist:

• My change requires a change to the documentation.
• I have updated the in-code documentation .AND. (the technical note .OR. the wiki) accordingly.
• I have read the CONTRIBUTING document.
• FATES PASS/FAIL regression tests were run
• If answers were expected to change, evaluation was performed and provided

Test Results:

CTSM (or) E3SM (specify which) test hash-tag:

CTSM (or) E3SM (specify which) baseline hash-tag:

FATES baseline hash-tag:

Test Output:

[rosiealice]

Noting that the diffs here SHOULD look like Jessie's diffs. (to make this parameter file, I implemented these by hand as I couldn't access the path to Jessie's file.)

Diff from the file in Matvey's branch (the new 16 hlm pft version of the current default) is here: diff

fates_params_sci.1.88.6_api.42.0.0_14pft_nor_sci3_api1_c260209.cdl fates_params_sci.1.88.6_api.42.0.0_14pft_nor_sci3_api1_c260209_mortupdates.cdl
1037c1037
<  fates_allom_agb1 = 0.0673, 0.3956093, 0.0421922, 0.1375641, 0.0673, 
---
>  fates_allom_agb1 = 0.0673, 0.01581217, 0.0421922, 0.1375641, 0.0673, 
1041c1041
<  fates_allom_agb2 = 0.976, 0.8295028, 1.0761814, 0.8956504, 0.976, 1.0221543, 
---
>  fates_allom_agb2 = 0.976, 1.109661, 1.0761814, 0.8956504, 0.976, 1.0221543, 
1055c1055
<  fates_allom_blca_expnt_diff = -0.12, -0.34, -0.32, -0.22, -0.12, -0.35, 0, 
---
>  fates_allom_blca_expnt_diff = -0.12, -0.25, -0.32, -0.22, -0.12, -0.35, 0, 
1469c1469
<  fates_mort_bmort = 0.004, 0.004, 0.004, 0.004, 0.004, 0.004, 0.004, 0.004, 
---
>  fates_mort_bmort = 0.004, 0.02, 0.02, 0.004, 0.004, 0.04, 0.004, 0.004, 
1483c1483
<  fates_mort_ip_size_senescence = 140, 135, 175, 175, 140, 135, 175, _, _, _, 
---
>  fates_mort_ip_size_senescence = 140, 155, 175, 175, 140, 135, 175, _, _, _, 
1500c1500
<  fates_mort_scalar_cstarvation = 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.1, 
---
>  fates_mort_scalar_cstarvation = 0.05, 0.1, 0.1, 0.05, 0.05, 0.15, 0.1, 
1728c1728
<  fates_wood_density = 0.548327, 0.44235, 0.454845, 0.754336, 0.548327, 
---
>  fates_wood_density = 0.548327, 0.434, 0.454845, 0.754336, 0.548327,

[JessicaNeedham]

Those parameter changes look correct to me @rosiealice .
Adrianna sent us a bunch of allometry updates, and we tested them sequentially and found the agb allom updates were sufficient to allow ENTs to grow to more reasonable sizes (instead of remaining <15cm dbh). However, this increased high LAI and GPP biases in the boreal zone. The update to the fates_allom_blca_expnt_diff parameter reduces LAI a little. Updates to mortality parameters were to reduce resulting high veg C biases.

Here is previous LAI (before any udpates to ENTs):

With the updates to AGB allometry to allow large trees:

With compensating fates_allom_blca_expnt_diff:

Sorry the years don't match. I can redo these to make comparison easier.

[JessicaNeedham]

LAI with updated AGB v non updated AGB:

And LAI with updated AGB and fates_allom_blca_expnt_diff v non updated FATES:

[JessicaNeedham]

And for reference this is the AGB allometry

[JessicaNeedham]

Here's Veg C with the mortality updates

Still too high in China, but it is proving difficult to reduce that bias without making the boreal forest low biased if we have a single ENT.

[JessicaNeedham]

and Veg C without the mortality updates

[JessicaNeedham]

Actually, @rosiealice can you revert the cstarvation scalar parameters. I realized I haven't tested with those increased, and with the increase in hydraulic failure that is coming, it might be too much mortality.