Closed wghuneke closed 3 years ago
Effective sea level for the control experiment (average over the last 5 years). Values are negative, but sloping upward towards Antarctica.
Anomaly between (left) UP and control and (right) DOWN and control.
Here is a plot of SSH along the temperature and salinity cross-slope transects. The response might be slightly larger for the UP case than for the DOWN case?
Hmmm, that's the opposite of what I would have expected (stronger easterlies should pile up more water against the coast). Anyone have an explanation?
On Fri, 30 Jul 2021 at 14:42, Wilma Huneke @.***> wrote:
Here is a plot of SSH along the temperature and salinity cross-slope transects https://github.com/adele157/easterlies-collaborative-project/issues/16. The response might be slightly larger for the UP case than for the DOWN case?
[image: Fig_SSH_transects] https://user-images.githubusercontent.com/15355753/127601275-056447e2-1ef0-47e4-8fd0-b2e058126ae0.png
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It's a southerlies experiment :)
P
On Fri, Jul 30, 2021 at 3:18 PM Adele Morrison @.***> wrote:
Hmmm, that's the opposite of what I would have expected (stronger easterlies should pile up more water against the coast). Anyone have an explanation?
On Fri, 30 Jul 2021 at 14:42, Wilma Huneke @.***> wrote:
Here is a plot of SSH along the temperature and salinity cross-slope transects <https://github.com/adele157/easterlies-collaborative-project/issues/16 . The response might be slightly larger for the UP case than for the DOWN case?
[image: Fig_SSH_transects] < https://user-images.githubusercontent.com/15355753/127601275-056447e2-1ef0-47e4-8fd0-b2e058126ae0.png
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Got to be interior T-S (i.e. steric height) adjustments acting against the Ekman transport? Pretty impressive that those steric height adjustments are big enough to overwhelm the Ekman anomalies. I also still wonder about a negative feedback wherein sea-ice changes act to reverse (or at least dampen) the wind perturbations. i.e. Ekman UP -> sea-ice increase -> Ekman down (or neutral). Paul's southerly winds experiment comment too - agreed. :-)
Have you looked at the first years? In case the Ekman response is fast and then gets obscured by something else.
Below the anomaly for year 1 which shows indeed opposite signs, @julia-neme !! (Note the smaller range of values.)
Nice, that all seems to fit with the following dynamics:
Might be nice to plot a time series to show this. Perhaps SSH averaged over the continental shelf?
It seems like the emerging story is that the DSW changes overwhelm all of the Ekman-driven changes that are seen in the first year. I'm not sure applying a zonal only perturbation would change this story. Perhaps applying a zonal average wind anomaly or CMIP wind anomaly might be a way to avoid the DSW changes (if that's what we want)?
That's a very nice emergent story - always fun when model simulations don't confirm the original suspicions, especially when a physical mechanism emerges that is plausible and easy to demonstrate. In that regard, I agree, there doesn't seem to be any need for those decomposition \tau_x-only, \tau_y-only experiments.
I agree, there is definitely a two-time scales story which we didn't expect. I'm surprised though that the increase in DSW formation (rather local) results in such a homogeneous steric height adjustment - if that's what's going on.
Happy to look at a time series of circumpolar averaged ssh next!
The DSW might form locally, but it very quickly overflows and spreads throughout the Southern Ocean as AABW. The uniformity of the bottom temperature change around the Southern Ocean is pretty consistent with the longer term SSH change.
Beautiful! Is there anyway to animate the story to show the DSW overflows? Age tracer perhaps to see the ventilation?
@StephenGriffies there's figures of the bottom age change towards the end of the simulation here. Did you have in mind an animation of this?
Yes, that could be interesting to see. Would be nice to see the two-time scales and the associated patterns. Age or something else...?
I looked at the annual SSH anomalies (from the control run) on the continental shelf over time. The animation shows the UP (left) and DOWN (right) anomaly fields for each year and the time series (bottom) shows the evolution of the circumpolar average. It nicely shows the two time scale response with a positive anomaly in the UP case over the first 2-3 years before it becomes a negative anomaly - possibly due densification of the shelf waters.
Ok. I'm failing to upload the animation. Here are the second and the last frame:
Very nice indeed. I like this!
I now also had a look a the monthly data. The first plot shows the monthly anomaly from the total mean (control, circumpolar average):
The second plot is the monthly climatology of the control run:
And lastly, the monthly anomaly to the monthly climatology:
Things to note:
And here is an animation of the monthly anomalies showing the spatial variability. The DOWN case shows more spatial variability, in particular in the Bellingshausen and Amundsen Seas. There is a positive signal in winter (June) while the rest of the continental shelf has a negative signal.
Here is a snapshot for June, year 2:
So can we say something about what time of year the initial positive and slower negative anomalies are occurring in the UP case? Maybe it would be helpful if you could mark on vertical lines for say every January on the time series? Or put the UP climatology on the control climatology plot also?
On Mon, 16 Aug 2021 at 10:31, Wilma Huneke @.***> wrote:
I now also had a look a the monthly data. The first plot shows the monthly anomaly from the total mean (control, circumpolar average):
[image: Fig_SSH_timeseries_anomaly] https://user-images.githubusercontent.com/15355753/129497222-d24d5048-c65d-443d-a1ed-1419db9a21e6.png
The second plot is the monthly climatology of the control run:
[image: Fig_SSH_control_monthly_climatology] https://user-images.githubusercontent.com/15355753/129497312-2f9b1ba7-5fa2-47b3-8ddb-04369cc212ed.png
And lastly, the monthly anomaly to the monthly climatology:
[image: Fig_SSH_timeseries_anomaly_clima] https://user-images.githubusercontent.com/15355753/129497354-8336b5a5-8c5a-41d1-9313-7900cce21ac7.png
Things to note:
- There is a seasonal signal, but it's not smooth: there are three maxima. These are consistent between the runs and there doesn't seem to be a shift in time.
- The amplitude of the seasonality changes between the UP and DOWN case - stronger for the UP case.
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The motivation for looking at the monthly data was to see if the transition from pos to neg anomalies occurs 1) at a specific time in the year and 2) starting in a certain region.
The negative anomalies occur first in the summer months (~Nov - April), starting from year 1, but really kicking in in year 3.
From the maps, I cannot identify certain regions that stand out as the where the anomaly changes first.
@adele157 : the time series starts with January, so every new year is a January (not sure if I understand your suggestion on adding vertical lines). I can add the climatology for the UP case (let's say the last 10 years).
I think that's consistent with what we proposed the other day (initial positive SSH driven by Ekman pumping, followed by negative SSH driven by DSW changes). See attached, what I meant by vertical lines (each January). It looks like in the UP case, the first half of each year (for the first 4 years at least), the SSH anomaly ramps up. This would be consistent with the seasonality of the winds (stronger in winter). But then starting about mid year (looks like July or August?), this positive SSH anomaly is reduced each year, which is consistent with when DSW would start to be produced seasonally.
I think the SSH story is quite compelling.
Are there many regional variations to these results or are they mostly consistent around the continent?
I'd say they are mostly consistent around the continent. At least the maps of SSH change are rather uniform (maybe with the exception of the Amundsen/Belingshausen Seas in the first years of the DOWN case).
Check how the sea surface height changes for the perturbation experiments.