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SSH changes #23

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wghuneke opened this issue Jul 28, 2021 · 26 comments
Closed

SSH changes #23

wghuneke opened this issue Jul 28, 2021 · 26 comments
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@wghuneke
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wghuneke commented Jul 28, 2021

Check how the sea surface height changes for the perturbation experiments.

@wghuneke wghuneke changed the title SSh changes SSH changes Jul 28, 2021
@wghuneke wghuneke self-assigned this Jul 28, 2021
@wghuneke
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Effective sea level for the control experiment (average over the last 5 years). Values are negative, but sloping upward towards Antarctica.

Fig_SSH_map_control

@wghuneke
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Anomaly between (left) UP and control and (right) DOWN and control.

  • Response is symmetric between the two experiments.
  • Sea level is lower in the UP case.
  • Signal of change is uniform near the coast

Fig_SSH_map_anomaly_UP_DOWN

@wghuneke
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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?

Fig_SSH_transects

@adele-morrison
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adele-morrison commented Jul 30, 2021 via email

@PaulSpence
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PaulSpence commented Jul 30, 2021 via email

@matthew-england-unsw
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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. :-)

@julia-neme
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Have you looked at the first years? In case the Ekman response is fast and then gets obscured by something else.

@wghuneke
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wghuneke commented Aug 5, 2021

Below the anomaly for year 1 which shows indeed opposite signs, @julia-neme !! (Note the smaller range of values.)

Fig_SSH_map_anomaly_UP_DOWN_year1

@adele-morrison
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adele-morrison commented Aug 6, 2021

Nice, that all seems to fit with the following dynamics:

  1. Southward Ekman transport increases in the UP simulation, and this is seen in the first year with an increased SSH around the Antarctic coast.
  2. DSW increases in the UP simulation, making the water column denser around the whole Southern Ocean, this results in a steric height adjustment with widespread decreased SSH seen after the first year.

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)?

@matthew-england-unsw
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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.

@wghuneke
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wghuneke commented Aug 6, 2021

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!

@adele-morrison
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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.

@StephenGriffies
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Beautiful! Is there anyway to animate the story to show the DSW overflows? Age tracer perhaps to see the ventilation?

@adele-morrison
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@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?

@StephenGriffies
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Yes, that could be interesting to see. Would be nice to see the two-time scales and the associated patterns. Age or something else...?

@wghuneke
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wghuneke commented Aug 11, 2021

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.

animation.mp4

@wghuneke
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Ok. I'm failing to upload the animation. Here are the second and the last frame:

Fig_SSH_anomaly_animation_01

Fig_SSH_anomaly_animation_14

@StephenGriffies
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Very nice indeed. I like this!

@wghuneke
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I now also had a look a the monthly data. The first plot shows the monthly anomaly from the total mean (control, circumpolar average):

Fig_SSH_timeseries_anomaly

The second plot is the monthly climatology of the control run:

Fig_SSH_control_monthly_climatology

And lastly, the monthly anomaly to the monthly climatology:

Fig_SSH_timeseries_anomaly_clima

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.

@wghuneke
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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.

animation.mp4

@wghuneke
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wghuneke commented Aug 16, 2021

Here is a snapshot for June, year 2:
Fig_SSH_anomaly_animation_clima_017

@adele-morrison
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adele-morrison commented Aug 16, 2021 via email

@wghuneke
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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).

@adele-morrison
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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.

Screen Shot 2021-08-16 at 10 58 30 am

@StephenGriffies
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I think the SSH story is quite compelling.

Are there many regional variations to these results or are they mostly consistent around the continent?

@wghuneke
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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).

@wghuneke wghuneke mentioned this issue Sep 10, 2021
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