Please support this Forum and Neven's Blog

Author Topic: State of the ice  (Read 912 times)

johnm33

  • ASIF Middle Class
  • Posts: 714
    • View Profile
State of the ice
« on: June 27, 2017, 06:49:57 PM »
First a couple of posts from A-team, from melt season ,1859 june 8  1834.1850
The N-ICE2015 papers have arrived, 22 of them. These papers represent six months of precious at-sea observations coordinated with simultaneous overhead remote sensing. While somewhat dated at 30 months, they remain very relevant to this spring’s melt season along the Arctic Ocean periphery north of Svalbard.

The papers are listed here along with their key points and download status: http://onlinelibrary.wiley.com/10.1002/(ISSN)2169-9291/specialsection/NICE1/

Some of these are currently paywalled, others are open source or available from https://sci-hub.cc/ (or TOR scihub22266oqcxt.onion) using the doi. Clicking then on ⇣ сохранить статью downloads the article or final draft as a pdf. It’s not currently known if US copyright law applies to Russia under self-anointed US exceptionalism — or vice versa under a stronger principle of Russian exceptionalism. Unblocked supplemental is available separately at journal sites.

The question is, do we muddle along without anyone reading these papers? Frankly, that’s not sustainable; we’re not here to promulgate anachronistic misinformation. There’s a definite need for fresh air in our near real-time interpretation of satellite ice products for the Svalbard-FJL periphery. Six months data from the ice changes everything.

I tried below with one of these papers to see if it is feasible to concisely summarize full texts, lessons learned without the length. No, it is not.

Mixing rates and vertical heat fluxes north of Svalbard from Arctic winter to spring
aMeyer, I Fer, A Sundfjord, A Peterson
3 June 2017 DOI: 10.1002/2016JC012441
http://onlinelibrary.wiley.com/doi/10.1002/2016JC012441/full

The observations cover the deep Nansen Basin, the Svalbard continental slope, and the shallow Yermak Plateau from January to June 2015. Average winter heat fluxes during quiet times in the ice-covered Nansen Basin are 2 watts per sq meter at the ice-ocean interface, 3 within the orderly density gradient (pycnocline) below the surface mixed layer and 1 below.

These heat fluxes are dwarfed In late spring over the Yermak Plateau by heat fluxes of 300 close to the surface. The forcing factors here are wind, near-surface warm Atlantic Water, steep shelf topography and above all, storms:

    Wind forcing increases turbulent dissipation seven times in the upper 50 m, and doubles heat fluxes at the ice-ocean interface. The presence of warm Atlantic Water close to the surface increases the temperature gradient in the water column, leading to enhanced heat flux rates within the pycnocline. Steep topography consistently enhances dissipation rates by a factor of four and episodically increases heat flux at depth. It is, however, the combination of storms and shallow Atlantic Water that leads to the highest heat flux rates observed: ice-ocean interface heat fluxes average 100 W m−2 during peak events and are associated with rapid basal sea ice melt, reaching 25 cm per day.


That would be 2 meter thick ice gone in 8 days if the storms lasted that long at peak intensity (which they don’t).

In the Arctic, sea ice at the surface reduces the transfer of wind energy to the ocean, causing turbulent dissipation rates to be an order of magnitude smaller than at lower latitudes. Away from boundaries, mixing of the Arctic water column is dominated by much smaller lateral intrusions and double diffusive fluxes of temperature and salinity gradients.

Without the sea ice cover, energy from winds, ocean tides, currents and breaking internal waves interact with topographic features on the sea floor to bring turbulent vertical mixing of previously stable stratifications. That’s especially pronounced over the rough topography of the Yermak Plateau northwest of Svalbard which has twice-daily strong barotropic tides. At its coriolis latitude, extracted energy cannot propagate away as linear internal waves and so dissipates locally, with rates of sufficient magnitude to greatly enhance impacts of Atlantic Water on regional ice cover. This water is normally isolated from sea ice by intervening cold Polar Surface Water stratification.

    The Atlantic Water inflow is the main source of oceanic heat to the Arctic Ocean but little of that heat actually has reached the sea ice in the past, though that is changing with newly thinner ice, a longer season of open water, and more frequent and extreme storms from the south.

    The RV Lance completed four drifts in the Arctic north of Svalbard anchored to different floes, the most favorable drift track (Floe #3) running from April 18th to June 5th. Their profiler instruments measured turbulent heat flux in the upper 300 m of the water column.

    The depth of the upper boundary of Atlantic Water, different from the depth of the 0°C isotherm, was found as shallow as 30 m depth and as deep as 300 m.

    The large heat flux values observed at the 0°C isotherm can be explained by the fact that the 0°C isotherm is a natural boundary between waters from the Arctic at the surface (Polar Surface Waters and warm Polar Surface Waters) and waters with Atlantic origin at intermediate depths (either Modified Atlantic Water or Atlantic Water). These two families of water masses have such distinct temperature characteristics that this boundary has large temperature gradients.

    The heat flux peaks coincided with periods of large basal sea ice melt. A major melt event took place on 16 February [see 10.1002/2016JC012011,10.1002/2016JC012403, 10.1002/2016JC012195] during a large winter storm but no data were recorded due to foul weather and sea ice conditions.

    The largest heat flux estimates during N-ICE2015 were recorded when the proximity to Atlantic Water was combined with storms. This happened three times: on 16 February, 2–5 June, and 11–13 June 2015. During each of these events, a storm took place, ice drift speeds were larger than 0.4 m s−1, and Atlantic Water was present at less than 100 m depth. Heat fluxes at the ice-ocean interface averaged 106 W m−2 during the last event in June. These enhanced heat fluxes lead to the warming of the water below the sea ice, which in turn triggered large basal sea ice melt. A basal melt of 25 cm/d was recorded from 5 June at the end of Floe 3, and again during Floe 4 after 10 June 2015.

    Ice mass balance buoys also observed rapid sea ice melt during the 16 Feb 15 basal melt event and derived conductive heat fluxes estimates that peaked at 400 W m−2 These extremely large basal melt events led to the decay of the ice, making it more vulnerable to swell and waves, and ultimately to break up events.

    The combination of storms and shallow Atlantic Water both in winter and summer induced large ocean heat flux of order 100 W m−2 in the upper ocean associated with massive basal sea ice melt events. This highlights the importance of predicted increased storm frequency in the Arctic that could erode local stratification and tap into warm subsurface Atlantic Water. In winter, this would lead to reduced growth, weakening, and even melting of the sea ice, while in spring such events would accelerate the melting and breakup of the sea ice. The warming and shoaling of the Atlantic Water inflow north of Svalbard and in the Barents Sea combined with increased storm frequency could lead to a significant reduction in sea ice cover further along the Atlantic Water inflow.

« Last Edit: June 27, 2017, 06:57:58 PM by johnm33 »

johnm33

  • ASIF Middle Class
  • Posts: 714
    • View Profile
Re: State of the ice
« Reply #1 on: June 27, 2017, 06:54:15 PM »
from melt season post 1956 june 12  1834.1950
Below, highlights from a very readable N-ICE2015 paper relevant to the current melt season, on how to interpret radar imagery (such as Sentinel-1AB) based on ground-truthing by simultaneous ship, helicopter and ground measurements co-located to a satellite track. Here the goal is unattended interpretation of scenes as leads, froze-over leads, pressure ridges, rafted ice, snowed-over features, nilas, open water etc (ie assignment of each image pixel to one of those classes).

The work was bedeviled by frost flowers (below, first frame of 1st gif), internal layers of wetted and refrozen snow, and drifted snow masking features; considerations that raise further questions about ice thickness algorithms that are already mutually inconsistent (2nd frame and 2nd gif).

On these forums, we make two main uses of satellite data. The first is literal, accepting as-is photo-like products, such as a Landsat scene of Nares Strait. We might tile these together, make a time series, or dink with contrast or color palette but don’t often apply a segmentation (classification) algorithm ourselves that allocates each pixel to a bin. Instead we rely on others to provide those products.

For example, NSIDC sea ice age uses data from 6 satellites + buoys to bin Arctic ice into five age classes (which are highly correlated with ice thickness http://www.mdpi.com/2072-4292/8/6/457/htm). Bin occupancy is then scored and graphed, showing the older ice classes pinching out over time in recent years (3rd image below, underlay). It is very rare on the forums to see a palette scored but common to see bin integrals (eg piomas volume summed over thickness cells).

Every segmentation product has four distinct parts: initial satellite image, product map colored by bin, color key to bin definitions, and bin occupancy graphic. Within university-grade cartographic GIS, if the classification results in N bins, the product map uses exactly N colors which are exactly those of the color key. Outside the map, embedded text or grid lines might be dithered (or offered as a separate layer) but colors within the map (or bin usage graphic) never stray from the palette. If they don't conform, the end user is just guessing at what map colors represent.

Image classification can be done either by defining categories in advance (eg land, open water, slush or ice) using pixel properties of fiducial areas to partition the rest of the image, or by algorithmic ab initio determination of best N bin segmentation with class interpretation left to the investigator. Both methods develop issues over time series and even year-on-year.

Combined observations of Arctic sea ice with near-coincident co-located X-band, C-band, and L-band SAR satellite remote sensing and helicopter-borne measurements
AM Johansson JA King, AP Doulgeris, S Gerland, S Singha, G Spreen and T Busche
doi: 10.1002/2016JC012273 (see doi:10.5194/tc-11-755-2017 for related article on melt-pond sensing)

Here a low-flying helicopter (with camera and altimeter) tows a device that induces and detects eddy currents in (conductive) sea water but not in snow or ice (non-conductive unless briny) as various radar satellites pass overhead in mid-April 2015 north of Svalbard. This yields 40m pixels of snow + ice thickness and snow surface roughness that can be compared to same-afternoon satellites (L-, C- and X-band) passing overhead. Here the radar sees the ice, the altimeter the snow surface, and the magnetic field sensor the salt water surface.

The radar is polarized and channel ratios prove quite informative. In conjunction with surface texture, taken as kurtosis (heavy-tailedness) of the roughness distribution, the ‘extended polarimetric feature space’ segmentation algorithm can produce 13 sea ice bins (those specified by the WMO in 1970), though that was simplified to 4 here that aren’t quite any in that system.

The drifting RV Lance saw one of these -- refrozen leads -- develop asymmetric thickness on the downwind side. A second lead had sheets of young grey-white ice with some rafting and a thin layer of snow and frost flowers with thin ice having elevated roughness corresponding to deformation and edge effect transitioning between thin and thick ice.

They also encountered a snow-free lead with barely solid first-year ice adjacent to nilas/young grey ice, followed by wind-blown nilas and young grey-white ice with frost flowers. Here the GoPro camera on the helicopter and snow pit studies were essential as radar struggles with such subtleties (4th image).

Some scenes have large-scale ridge structures. Variations in ice thickness of up to 5.5 m documented by the helicopter unfortunately had no counterpart in radar backscatter despite non-vertical incidence.

Ridges increase surface roughness and indeed the camera saw evidence of old, consolidated ridges now completely snow-covered. These have a star-shaped signature that forms from snow drifts but those are more easily detected by eye.

The snow had undergone thaw and refreezing by mid-April, presumably from a rain-on-snow event giving an ice layer at the surface, later buried by more recent snowfall. This created a uniform ice layer within the snowpack but above the main ice which then fools the radar return; this ice crust was confirmed within the snowpack in snow-pit studies. If the non-coastal piomas thickness blob is artifactual, this is a conceivable explanation.

In short, the authors see a limited potential for future automatic classification of SAR images to distinguish different ice classes because the ice is complicated enough already and processes that fool the radar could be more common as multi-year ice diminishes (or vanishes) as the Arctic amplification of warming precedes.

All the current segmentation schemes like extent, area, age, and volume will need to be seriously tweaked to keep up with once-rare ice formations and interactive atmospheric processes becoming dominant. It may not be feasible however to maintain time series if new bin classes become necessary.

* frost flowers vs 3 ice thickness products.gif (280.88 kB, 700x628 - viewed 2653 times.)

* thickness bins 1979-2017 with 5 year rolling averages and hycom to 17 Jun 17.gif (591.79 kB, 677x426 - viewed 2662 times.)

* ice age classes (Tschudi et al).png (246.28 kB, 666x322 - viewed 2621 times.)

* outcome of radar classification.png (350.27 kB, 700x269 - viewed 2653 times.)
« Last Edit: June 27, 2017, 07:00:10 PM by johnm33 »

johnm33

  • ASIF Middle Class
  • Posts: 714
    • View Profile
Re: State of the ice
« Reply #2 on: June 27, 2017, 07:09:15 PM »
From Andreas T melting season
1884 on: June 10, 2017,
This  photo from Polarstern which went into Fram strait at the end of May shows just that. My interpretation is that ice which is thinning by bottom melt is pushed below the surface by its snow load. The snow is melted away by seawater from the floe edge inward. That the snow does not disappear quickly as soon as the ice sinks must be due to low air temperatures.
Does this make sense?
https://blogs.helmholtz.de/polarstern/2017/06/angekommen-an-der-eiskant

johnm33

  • ASIF Middle Class
  • Posts: 714
    • View Profile
Re: State of the ice
« Reply #3 on: June 27, 2017, 08:57:57 PM »
Melt pond links courtesy Tor Bejnar https://phys.org/news/2017-01-arctic-ponds-meltwater-clogs-ice.html    https://www.sciencedaily.com/releases/2017/01/170123145213.htm   
and gregcharles  https://www.nasa.gov/content/goddard/melt-ponds-shine-in-nasa-laser-altimeter-images/
I'll sort out the above images later, and there's a couple more links I'm looking for but where?

johnm33

  • ASIF Middle Class
  • Posts: 714
    • View Profile
Re: State of the ice
« Reply #4 on: June 28, 2017, 12:30:14 PM »
Necessary conditions for ice formation, one, the lack of waves is going to be difficult to fulfil once we have an ice free ocean. http://eh2r.blogspot.co.uk/2016/10/new-sea-ice-starts-from-3-important.html
https://www.pmel.noaa.gov/arctic-zone/essay_wadhams.html

oren

  • ASIF Upper Class
  • Posts: 1382
    • View Profile
Re: State of the ice
« Reply #5 on: June 28, 2017, 07:08:16 PM »
John, thanks for the link. Very interesting and filled some wide holes in my knowldege.