Replies: 33 comments 43 replies
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The simulation is indeed cold. We have identified that the net shortwave flux being passed to the ocean model is identically zero. Other surface components are getting non-zero shortwave, and the ocean is getting non-zero net longwave flux. Jim Edwards is investigating this bug, which appears to have been introduced in the tag |
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Diagnostics from the newest CESM3 dev simulation discussed at co-chairs today: The case is: b.e23_alpha14a.BLT1850.ne30_t232.032 I don't see anything concerning from a land viewpoint. Sounds like this will continue running for a bit. A new simulation with tuning to get a more reasonable RESTOM will be run. |
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The next in this series of simulations is b.e23_alpha16b.BLT1850.ne30_t232.033, as discussed in NCAR/amwg_dev#356.
The "hole", as defined below, is 98% vegetated and is comprised of roughly 50%/40% deciduous boreal shrub and C3 arctic grass. Timeseries plot shows that snow cover is not near zero until Aug-Sep.
Just to start a discussion. I'll be able to do more analysis once cheyenne is back up. |
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Maybe it's worth bringing up these plots at co-chairs? |
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Yes indeed the time axis is messed up, sorry, I've fixed this. I've added in 033 and the first 10 years of the AD spinup, where it looks like vegetation is trying to get established but dies out. Maybe we can start by diagnosing that. |
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@olyson would you be willing to do these regional line plots over the "hole" for the surface energy budget components? Or do you already know which component is responsible for initiating this cold bias? I can see reductions in FLDS at high latitudes compared to CESM2 in your linked diagnostics; but that's the only lead I got. |
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Surface energy balance:
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Almost seems like there are too few clouds in the first half of the year -- the incoming shortwave is larger than CESM2 & GSWP, whereas the incoming longwave (from ice clouds?) is smaller compared with CESM2 & GSWP. |
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Updated diagnostics through year 26 Looks like the simulation is going cold... |
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Oh, it is getting quite cold and snowy, especially in the Arctic. Is the Lab sea freezing again? |
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We should recheck in a run with the SNICAR updates from Cenlin, but based
on the land-only results comparing the new SNICAR to the control, I think
that snow albedo is likely to go up (i.e., not helping). I don't think
there is a clear figure in Cenlin's paper that shows the snow albedo bias,
especially the spring snow albedo bias, in the high latitudes, but that is
something we could look into further. I kind of doubt that this is a snow
albedo issue, but it's worth confirming.
…On Fri, Aug 4, 2023 at 10:43 AM Keith Oleson ***@***.***> wrote:
Yes indeed the time axis is messed up, sorry, I've fixed this. I've added
in 033 and the first 10 years of the AD spinup, where it looks like
vegetation is trying to get established but dies out. Maybe we can start by
diagnosing that.
The 033 does look like it's going off the rails, the last diagnostics I
saw indicated that the lab sea was probably on it's way to freezing up.
Despite that, maybe a couple of these plots would be useful to show at
co-chairs if only to indicate the problem we are looking at.
Other plots to follow once I'm back in the office next Tues.
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Another thing to probably check is what the snow melt timing looks like in
present day CESM climate in these regions. Does the snow persist too long
into summer even in today's climate? Probably can only check this in
CESM2, but based on these results from CESM3 beta sims, it doesn't look as
if anything changed much.
…On Fri, Aug 4, 2023 at 1:25 PM David Lawrence ***@***.***> wrote:
We should recheck in a run with the SNICAR updates from Cenlin, but based
on the land-only results comparing the new SNICAR to the control, I think
that snow albedo is likely to go up (i.e., not helping). I don't think
there is a clear figure in Cenlin's paper that shows the snow albedo bias,
especially the spring snow albedo bias, in the high latitudes, but that is
something we could look into further. I kind of doubt that this is a snow
albedo issue, but it's worth confirming.
On Fri, Aug 4, 2023 at 10:43 AM Keith Oleson ***@***.***>
wrote:
> Yes indeed the time axis is messed up, sorry, I've fixed this. I've added
> in 033 and the first 10 years of the AD spinup, where it looks like
> vegetation is trying to get established but dies out. Maybe we can start by
> diagnosing that.
> The 033 does look like it's going off the rails, the last diagnostics I
> saw indicated that the lab sea was probably on it's way to freezing up.
> Despite that, maybe a couple of these plots would be useful to show at
> co-chairs if only to indicate the problem we are looking at.
> Other plots to follow once I'm back in the office next Tues.
>
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Just wanting to note that I have not looked at it much, but anecdotally hearing from people running CLM at high latitude sites (with site forcing) that the snow is very persistent in general. Do we know the status of the biases in offline forcing mode?
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It's a good question, @rosiealice . I don't remember seeing this jump out as strongly with the land only CTSM5.1bgc simulations @olyson ran a while back, but it's a good idea to look at CTSM5.1 CPLHIST vs. uncoupled CTSM5.1 results in this area? Can you help with this later this week @olyson? There's the climatology across the Russian Arctic region in the diasnostics for coupled and uncoupled runs. Snow is much deeper in the CESM2-piControl and CTSM5.1-CPLHIST simulations than the land only results. The it's hard to tell, but the biggest differences I see are colder temperatures, lower incoming long wave radiation, and maybe higher spring precipitation in the coupled and CPLHIST simulations compared to the GSWP3 results. |
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@wwieder , @dlawrenncar , @rosiealice , annual cycle of snow cover fraction, snow depth, snow water equivalent, exposed leaf area index for the "hole".
I'm in the office Tues, but out on PTO the rest of the week. |
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Thanks Keith, could you also plot snowfall and surface air temperature
and maybe also snow melt?
If we ignore 033, which seems to be freezing up (?), then we can see that
CESM2 and CESM3beta seem to have the same problem (snow persisting too
long), but with a pretty different surface energy budget. Seems like there
must be fewer clouds in CESM3 with higher incoming solar and less
downwelling longwave. But, irrespective, the main feature that may be
leading to the snow persisting too long is that there is quite a bit more
snow at the end of the accumulation period (May). So, that's probably part
of the problem.
…On Mon, Aug 7, 2023 at 5:00 PM Keith Oleson ***@***.***> wrote:
Surface energy balance:
[image: annual_cycle_radiation_Siberia1]
<https://user-images.githubusercontent.com/18671367/258942392-44d97548-68d9-4bb7-a677-6055baff2abd.png>
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Thanks. These are all helpful. I think these plots support the idea that
there is more snowfall in the coupled simulations than GSWP3, especially in
the fall. We should obviously be cautious with GSWP3 snowfall since there
wouldn't be much data going into it. There is also an indication that snow
melt starts earlier (quite a bit of snow melt in May in land-only, but
little snow melt in May in coupled model). So, it seems like we could
focus in on the surface energy budget in May as one thing to examine more
closely. Since the CESM2 present day plot indicates that the excessive
snow (and snowfall) persists to present day, maybe we can use present day
obs to try to diagnose the problem against observations.
But, first, I am finding it hard to look through these plots because (a)
there is the 033 run which is clearly bad and (b) the CESM2 run is from
present-day so from a different climate. Keith, could you replot these
with just GSWP3, CESM2 pre-industrial (or first 10 years of historical),
and the CPLHIST from CESM3beta. And, in addition to these plots, could you
add net radiation and surface albedo? I think with that info, we should be
able to start understanding what is going on. If easy, a similar set of
plots for present day from CESM2 and GSWP3 could also be useful.
…On Tue, Aug 8, 2023 at 11:06 AM Keith Oleson ***@***.***> wrote:
[image: annual_cycle_other_Siberia1]
<https://user-images.githubusercontent.com/18671367/259174683-0c9ddd01-9fe2-4c29-ab4e-fcc31c12a27a.png>
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~1850 plots:
1995-2014 plots:
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Interesting. Trying to make sense of all the plots is hard, but one thing
that I think stands out is that the surface albedo is lower in land-only
runs, even when snow cover fraction is pegged at one for both coupled and
uncoupled models. That difference in surface albedo is about 0.1, which
would equate to about 20W/m2 more energy absorbed at the surface, which is
about the amount of energy going into the melt flux. What's interesting is
that even in present-day conditions, there is greater snow melt flux (and
lower albedo) in land0-only, even when snow depth is actually larger and
SWE about the same between coupled and land-only. So, this kind of
possibly implies that the snow is melting more in land-only because the
albedo is lower. Now, is the albedo lower because there are trees growing
in the land-only run for part of the domain and therefore there is some
snow masking, or is it because the aerosol dep is different or is it
because the snow grain size growth across the season is different. The
albedo difference is there throughout the year, which implies that it is
the trees that is reducing the albedo, but that could be checked. So, to
diagnose further, we might need to focus in on regions without any trees
(if that is indeed the source of the albedo different) or take a look at
the snow albedo itself (rather than surface albedo) to see if that could
explain things. We may want to have a small meeting to discuss. Seems
worth pursuing this now while we are thinking about it since this does
substantially mess up the permafrost carbon stocks across much of the
Arctic.
…On Tue, Aug 8, 2023 at 1:59 PM Keith Oleson ***@***.***> wrote:
~1850 plots:
[image: annual_cycle_new_Siberia1_1850]
<https://user-images.githubusercontent.com/18671367/259212918-995f8c9c-8e82-4ea7-b278-b4c94a8a93da.png>
[image: annual_cycle_radiation_new_Siberia1_1850]
<https://user-images.githubusercontent.com/18671367/259212982-e42535ad-b7d7-4d2b-aefb-29616ae1dbc5.png>
1995-2014 plots:
[image: annual_cycle_new_Siberia1_1995_2014]
<https://user-images.githubusercontent.com/18671367/259213372-e18b66c3-6eba-4c88-8bca-4f1c2b1bafde.png>
[image: annual_cycle_radiation_new_Siberia1_1995_2014]
<https://user-images.githubusercontent.com/18671367/259213399-21d34fa8-cf91-4314-8d7f-56f8bd17a4a4.png>
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I agree, a quick chat could be helpful. After that, the next time we can all talk is likely not until next Thursday at around the same times. I'll go ahead and get something on the calendar for today that we can move to a later time/date if needed. |
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Diagnostics for two new coupled simulations (b.e23_alpha16b.BLT1850.ne30_t232.034: NCAR/amwg_dev#361 and b.e23_alpha16b.BLT1850.ne30_t232.035: NCAR/amwg_dev#362) compared to 026g: Vegetation at high latitudes looks similar to results shown previously, e.g., 033. Two new runs are underway, 036 and 037. |
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Prior to our chat on Thursday, Keith, could you try to see if you could
confirm whether or not the differences in albedo between land-only and
coupled are due to vegetation masking or to the snow albedo itself. Our
hypothesis is that the difference in albedo is due to shrubs (and maybe a
few trees) surviving spinup in land-only runs, but not in coupled runs,
rather than it being a difference in actual snow albedo.
A test, which would be a bit challenging, would be to run with CLMSP mode
in coupled (or maybe just CAM-CLM) simulations. If we see the same earlier
melt out, then that would support the idea that the vegetation not
surviving is leading to the lengthy snow-on-ground season. If that is what
is happening, then we need to think about why the vegetation is dying in
coupled run and if there is something we could do to fix that.
…On Tue, Aug 15, 2023 at 10:41 AM Keith Oleson ***@***.***> wrote:
Diagnostics for two new coupled simulations
(b.e23_alpha16b.BLT1850.ne30_t232.034: NCAR/amwg_dev#361
<NCAR/amwg_dev#361> and
b.e23_alpha16b.BLT1850.ne30_t232.035: NCAR/amwg_dev#362
<NCAR/amwg_dev#362>) compared to 026g:
034
<https://webext.cgd.ucar.edu/BLT1850/b.e23_alpha16b.BLT1850.ne30_t232.034/lnd/b.e23_alpha16b.BLT1850.ne30_t232.034.15_24-b.cesm3_cam058_mom_e.B1850WscMOM.ne30_L58_t061.camdev_cice5.026g.15_24/setsIndex.html>
035
<https://webext.cgd.ucar.edu/BLT1850/b.e23_alpha16b.BLT1850.ne30_t232.035/lnd/b.e23_alpha16b.BLT1850.ne30_t232.035.15_24-b.cesm3_cam058_mom_e.B1850WscMOM.ne30_L58_t061.camdev_cice5.026g.15_24/setsIndex.html>
Vegetation at high latitudes looks similar to results shown previously,
e.g., 033.
Two new runs are underway, 036 and 037.
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The hole itself is about 3.5% boreal trees, with the rest being shrub and grasses. |
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One more question, what land initial conditions were being used for the 026g coupled test a while back? I seem to remember this was an older CESM2-CLM5 initial state? I ask because LAI peaks higher for this region of the Siberian Arctic, compared to the 035 test. |
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For 026g, we had switched to an initial file from a CESM3 development simulation that had less snow at high latitudes (/glade/p/cesmdata/cseg/inputdata/cesm2_init/b.cesm3_cam058_mom_e.B1850MOM.f09_L32_t061.cam6_cice5.016/0058-01-01/b.cesm3_cam058_mom_e.B1850MOM.f09_L32_t061.cam6_cice5.016.clm2.r.0058-01-01-00000.nc). |
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Some plots for discussion that include results from the CESM3 SP simulation (b e23_alpha16b BLT1850 ne30_t232 034SP, years 2-3).
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We can compare the recent GSWP3V1 forced historical simulation for present day with MODIS data as below:
We don't seem too far off, except in far eastern Siberia. Interestingly, we see a small hole in the MODIS data located in about the same spot as our larger hole, possibly due to the presence of lakes (I haven't looked at lake fraction here). The observations have viable vegetation further north in the Canadian Arctic than in our simulation. |
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You are welcome to look at the coupled PPE runs for insight which cover 18
parameters with 1850 conditions. They are located here:
/glade/campaign/cgd/tss/czarakas/CoupledPPE/coupled_simulations
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I peaked at the latin hypercube PPE and found that we don't have a ton of leverage on the LAI in the "hole" using the plant parameters, the highest we could achieve is peak LAI=0.55. Only 13 of our 500 members achieved LAI>0.3 during August (1850-1855). Those parameter sets are rather aggressive, doubling August pan-arctic LAI (>66N) from 0.9 (default params) to 1.8 in 1850. The aggressive parameter sets have pan-arctic annual max LAI=2.5 at the end of transient (2010-2015) as compared to 1.27 (default params). I don't have a good sense of what the broader Arctic LAI should be. In addition to FUN_fracfixers and froot_leaf, leafcn and jmaxb0 are among the strongest levers. But jmaxb0 is not pft-specific, so probably won't be useful. zsno showed up as a lever for TLAI in the "hole" within the OAAT simulations, where raising zsno to 0.07 (from 0.0024 default) increased "hole" peak LAI from 0.18 (default params) to 0.28. zsno was the sixth biggest lever on "hole" lai in our cold ensemble. But you might want to peak at the snow in that simulation to make sure it's not a catastrophic degradation. /glade/campaign/asp/djk2120/PPEn11/AF1855/hist/PPEn11_AF1855_OAAT0034.clm2.h0.2005-02-01-00000.nc |
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agreed! |
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Here's the rankings plot, for August LAI in the subset under cold forcing, updated with Katie's fix. They are sorted by the +LAI effect code here:https://github.com/djk2120/oaat_clm5_ppe/blob/main/pyth/template.ipynb 
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At first I was wondering why froot_leaf didn't show up on this plot, but I think that's because you're selecting parameters that increase LAI when they are moved to their max value? So that explains why @olyson was able to get comparably good responses by increasing FUN_fracfixers and decreasing froot_leaf in the tests. (@djk2120 Side note, we could also filter these ranking plots by PFT-specific parameters to hone in on that information, since you previously mentioned jmaxb0 might not be as useful despite being a large lever.) |
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@katiedagon , I was wondering the same thing. I had picked froot_leaf based on your own plot above since it was a pft-dependent parameter and we could perturb just the values for broadleaf deciduous shrub and C3 arctic grass. FUN_fracfixers also showed up as significant levers in both your and Daniel's plots. I also see the pft-dependent parameter leafcn in your plot but not in Daniel's? I guess this is because your plot is based on annual mean LAI while Daniel's is based on August LAI? |
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I should mention that we have moved this conversation to NCAR/LMWG_dev#3 |
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Interesting. I guess you may have already looked to see if any of the
parameter sets that produce the higher LAI in 1850 have a less strong
increase in LAI over the historical period so as to not produce such a
large LAI in present day. I guess overall I wouldn't be surprised if this
is just a limitation of the resolution of the number of pfts and that there
is more adapted vegetation as you move northward and furthermore that there
has likely been species shifts as climate has changed.
Also, the zsno is interesting, but looking at Ronnie Meier's paper for the
new roughness param that is coming in soon, he is actually recommending
zsno getting smaller (0.0007), but also that there is an increase in zsno
as snow starts to melt, which might accelerate snow melt during the melt
season. https://gmd.copernicus.org/articles/15/2365/2022/ (see section 2.4)
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Diagnostics for the two new fully coupled simulations (b.e23_alpha16b.BLT1850.ne30_t232.040 and b.e23_alpha16b.BLT1850.ne30_t232.041) Vegetation at high latitudes looks about the same as in previous simulations, maybe a bit worse in 041. 041 looks like it is going cold (RESTOM=-1.51, if the tables are correct). |
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Wow, 41 is really cold at high latitudes. Here are some plots for boreal Alaska. I had to duck out of co-chairs before hearing about the latest issues with these runs, are their other concerns about these simulations? |
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41 is a tuning exercise that didn't work out, it has been stopped. |
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I feel like these impacts of shrubs in high latitude temperatures in CESM need documenting better. Any chance one of the runs could -just- experiment with that and the output could be saved? I know this is in Dave’s old paper, but it is such a massive incentive to study boreal vegetation it would be super useful if it were somehow recorded in this round of tuning… |
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@martynpclark and @marysa may be working on this, Rosie! |
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yes indeed, we have a all-C3-grass-north-of-60N converted to shrub run, though in the cesm2.3 release code version of the model |
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Jmaxb0 is one of the parameters in the coupled PPE. I’m not able to analyze anything until later next week at the earliest but someone else is welcome to do check the LAI in that run.
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Results from some spinups. CPLHIST is the coupler history spinup we ran to provide initial conditions for fully coupled simulations, GSWP is a land-only control forced by GSWP, and then there are two perturbed parameter runs informed by the PPE. I see improvements in TLAI in both of the parameter runs, in particular a boost in TLAI in July and August in the Siberian hole (good job PPE!).
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Cool. It does look a bit better. I guess another diagnostic would be the
area across the Arctic (excluding ice sheets) where LAI isn't greater than
some threshold (0.2?). The other diagnostic that we could be looking at to
try to see if the extra growth is helping with the snow melt problem is
canopy height. While LAI is higher in the summer, the surface albedo looks
essentially the same, which suggests that it's either only grasses that are
growing better or if shrubs are growing better, it's only marginal ... or
only growing better in places where the shrubs were already growing ok.
Anyway, I guess the point is that the metric that we are looking for that
would indicate a possible change in behavior in coupled runs is either a
surface albedo change or a change in spring melt timing/amplitude.
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I kind of agree with @dlawrenncar here, the changes to TLAI in JJA in regions that were previously dark blue (<0.1) are pretty subtle- maybe a big in Canadian Arctic and the impacts on albedo and snow melt are pretty negligible. Do we want to:
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I agree we're not seeing much movement in albedo and snow melt. Good ideas, sounds like we'll be talking about this more this week... |
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I like this 'dead area' metric and the HTOP plot, Keith. Thanks. In the regional climatology plots it's interesting that HTOP is > Snow Depth in all of the offline cases. Given the dead area in the region, it makes me wonder what HTOP, LAI and snow dynamics look like in dead vs. undead grid cells over this domain? Are growing verdant Arctic tundra in more favorable grids to try and get vegetation to grow at all in less favorable climates? Alternatively, are the grasses, that can be buried by snow, (but not shrubs) responding more strongly to these parameter changes? To clarify, I'm not asking for additional anaysis here, Keith. Just typing to avoid rubbing my head to hard... |
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Let's leave this thread for discussion of coupled model simulations.Additional discussion or diagnostics related to dead in Arctic vegetation should be posted on LMWG-dev page, discussion #3 |
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Some annual cycle results for recent fully-coupled simulations (075, 079, 080), plus the CMIP6-piControl. I've added in the observations for snow water equivalent from CanSISE which is a dataset used by ILAMB (although noted that this is for present day).
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The next round of coupled CESM3 development simulations has started. b.e23_alpha17f.BLT1850.ne30_t232.091 is the first simulation out of the box using cesm2_3_alpha17f. Standard diagnostics compared to the previous baseline (b.e23_alpha16g.BLT1850.ne30_t232.082b) are here: It looks like we've maintained most of our desired increase in high latitude vegetation productivity as indicated by these plots (top: 091, middle (082b), bottom (091-082b):
Polar air temperatures are colder in winter and warmer in summer: |
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Percent Decrease in 091 dead_veg from CESM2 piControl (km2): -59.8236.
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Regarding snow over the Canadian Arctic and Greenland, here are plots of annual mean SNOWDP for 091 and 082b. As I mentioned in the CESM project meeting, a lot less snow over the Canadian Arctic in 091 (annual mean depths of about 2m in 091 compared to about 8m in 082b). Still lots of snow in 091 over most of Greenland, although smaller amounts on the western and northeastern coast. Annual mean depths of about 15m in 091 and 18m in 082b.
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Oh my, 82b looks like it would've grown a Laurentide Ice Sheet. |
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I don't know if the lower snowpacks on western and northeastern Greenland is a concern now. |
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This question came up at the CAM meeting today too, but these diagnostics suggest we're maybe OK for regional snowpack? A polar view may for DJF and MAM snow depth may be helpful, though? |
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Thanks for posting these, @olyson |
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Diagnostics for the most recent runs are here: https://webext.cgd.ucar.edu/BLT1850/$SIMULATION/lnd/ where $SIMULATION = b.e23_alpha17f.BLT1850.ne30_t232.092, etc. In particular, the most recent simulations (095 - HYCOM1 vertical coordinates in MOM + rrtmgp, and 092 - HYCOM1 vertical coordinates in MOM) are compared here: Here are JJA TLAI, and DJF, MAM, and JJA H2OSNO for these simulations:
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The first fully coupled simulation in the next series of CESM3 development is underway.
The case is:
b.e23_alpha13b.BLT1850.ne30_t232.031
Data are here:
/glade/scratch/hannay/archive/b.e23_alpha13b.BLT1850.ne30_t232.031
It has run 9 years thus far.
I've run some diagnostics comparing it to b.cesm3_cam058_mom_e.B1850WscMOM.ne30_L58_t061.camdev_cice6.026h, which was the last simulation in the previous round that didn't have a frozen Labrador Sea:
https://webext.cgd.ucar.edu/B1850/b.e23_alpha13b.BLT1850.ne30_t232.031/lnd/b.e23_alpha13b.BLT1850.ne30_t232.031.2_9-b.cesm3_cam058_mom_e.B1850WscMOM.ne30_L58_t061.camdev_cice6.026h.2_9/setsIndex.html
It does look like there is something wrong with the new simulation as it is very cold (which may be why the simulation appears to be stopped). I haven't heard anything about what might be wrong with this simulation.
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