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Co-limitation of photosynthesis #472

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rosiealice opened this issue Feb 11, 2019 · 23 comments
Closed

Co-limitation of photosynthesis #472

rosiealice opened this issue Feb 11, 2019 · 23 comments

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@rosiealice
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@walkeranthonyp has a very compelling argument from MAAT that co-limitation of photosynthesis should either be removed, or the parameters controlling it should be increased. Adding this as a placeholder to remember to do this. Can you add some detail to what you would advocate Anthony?

@walkeranthonyp
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A very simple fix would be to increase both the theta and beta (Collatz et al., 1991) parameter values from 0.95 and 0.98 to 0.999 for both of them. This preserves the smoothing which can benefit the current solver and is a very simple fix. A value of 0.999 for both parameters would give a maximum reduction in gross assimilation of 3.1 % compared to selecting the minimum rate. The current parameter values give a maximum reduction of ~25%, so if we go ahead with this we can expect quite a jump in GPP, a rough guess would be ~10% increase but it's difficult to say.

Once we've progressed the semi-analytical solver to a point where it's faster than the current solver in FATES we'll have a greater overhaul of the photosynthesis code and we can decide to keep a small amount of smoothing or delete it completely. A small amount of smoothing is probably realistic, but it comes at the cost of two quadratic solves for every calculation of photosynthesis.

@alistairrogers
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alistairrogers commented Feb 13, 2019 via email

@rosiealice
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rosiealice commented Feb 14, 2019

So, it looks like these numbers are hard wired in here:

real(r8),parameter,dimension(0:1) :: theta_cj = [0.80_r8,0.98_r8]

and used here-ish:
aquad = theta_cj(c3c4_path_index)

There appear to be three relevant thetas, theta_cj, which is 0.8(!) for C3 and 0.98 for C4, and theta_ip (0.95) for adding in the TPU colimitation. I'm not sure what 'beta' maps on to in this instance @walkeranthonyp. Is that the theta_ip?

Do we think these should be in the parameter file @rgknox and @ckoven? My feeling is that that might make people think they need to go out and measure these things, which don't really exist. On the other hand, having them in the file facilitates the type of sensitivity analysis that Anthony just did with MAAT which would have been impossible with them hard-wired in!

I'll set off a simulation with all three numbers at 0.999 now and see what happens...

@alistairrogers
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alistairrogers commented Feb 14, 2019 via email

@rosiealice
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rosiealice commented Feb 14, 2019 via email

@rgknox
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rgknox commented Feb 14, 2019

@rosiealice , I think the indexing on those is reversed.

! photosynthetic pathway: 0. = c4, 1. = c3

For c3 we are using theta_cj = 0.98, can you confirm?

real(r8),parameter,dimension(0:1) :: theta_cj = [0.80_r8,0.98_r8]

@rosiealice
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rosiealice commented Feb 14, 2019 via email

@rosiealice
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So, this does seem to have a large effect. This is what happens after 6 years and 9 months (it's nearly bedtime here) with our default evergreen broadleaf notionally tropical trees. These runs aren't equilibrated in any sense yet, but you can see that the Amazon is looking quite a lot healthier.

lai
gpp

@alistairrogers
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alistairrogers commented Feb 14, 2019 via email

@walkeranthonyp
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Very cool! ... and mad that this has such an effect. Nice to see the Amazon looking healthier.

@walkeranthonyp
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@rosiealice I forget which way round theta and beta are in the original paper. I wouldn't worry about it though if we just set them both to 0.999.

I'm not sure what to do about C4, it will obviously have an influence, probably too much. I'm less familiar with the theory tho. The C4 a-ci curves I have seen have a pretty strong inflection point but I don't know about the a-par curves. @alistairrogers thoughts?

Lastly I would caution against putting these in the parameter file @rosiealice, @rgknox, @ckoven. This would just encourage people to vary them when really the reason we're leaving them in the model is for numerical expediency with a longer view to chucking them out, unless we have any good data. @alistairrogers looking at you for them high-res aci curves ;)

@alistairrogers
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alistairrogers commented Feb 15, 2019 via email

@rosiealice
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There weren't actually any C4's in my simulation... Could test it though, just to check. We have been, both in CLM and FATES, a bit concerned about over-productivity of the C4 algorithm in general, but haven't had any time or expertise to go through it in enough detail...

@rosiealice
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rosiealice commented Feb 15, 2019

Here's some quick figures (apologies for their sketchiness) from the 10th year (I just did 10 years, will run them out longer now). Indeed, as suspected/predicted from Anthony's results, the understory does much better here...

lai_total
biomass_understory
gpp_understory
gpp_total

@alistairrogers
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alistairrogers commented Feb 15, 2019 via email

@rosiealice
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Thanks @alistairrogers. Guess I should have asked you this (about C4's) a while ago!

@jkshuman
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@alistairrogers I have a set of C4 simulations, and would like to update them according to this thread. Will follow up with you on the details this week. As @rosiealice indicated the C4 is highly competitive.

@rosiealice
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rosiealice commented Feb 18, 2019 via email

@jkshuman
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Good idea @rosiealice I will create a separate C4 issue. There may already be a C4 issue floating around, so will confirm that as well.

@rosiealice
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Some better equilibrated figures (57 years and counting) from the changes to the smoothing parameter global 4x5 runs. Trivially, GPP and LAI are higher. They don't completely eradicate the low central/Eastern Amazon LAI issue though. My first thought was that this was to do with water limitation, but BTRAN is not associated with the low LAI values at all, so maybe it's low humidity or high temperature that's driving that.

@ckoven I've been trying to get the vertical profile of GPP. There's a net assimilation output that's stratified like that, but it's complicated by the issue of partially filled layers and it's annual counting mandate, so I'm going to try and add GPP by leaf layer directly.

I'll try and make some figures that more usefully highlight the differences, rather than y'all having to squint.

smoothing__y2057tlai1
smoothing__y2057gpp1
smoothing__y2057btran1

@jkshuman
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jkshuman commented Mar 7, 2019

Finally posting figures for this issue. These are sets of 2 PFT (Evergreen Tropical Tree and C3 grass, and Evergreen Tropical Tree and C4 grass) runs with and without theta set to 0.99 in tag: sci.1.21.0_api.7.0.0 (from mid January) Results for annual average for understory biomass, GPP and LAI for years 52 and 53 of simulation. C3 is on the top of the panel, C4 bottom. Theta=0.99 on the left and default on the right.
GPP_Diff_theta-default

photo_smoothing_test_GPP_0052-0053
photo_smoothing_test_TLAI_0052-0053
photo_smoothing_test_BIOMASS_UNDERSTORY_0052-0053

@rosiealice
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This could technically be closed now, with PR #482, right?

@rgknox
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rgknox commented Mar 15, 2019

I think so, nice to tidy up the "open issues" list when possible

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