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A-Team

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Re: The 2017/2018 freezing season
« Reply #200 on: October 16, 2017, 05:58:11 PM »
Quote
According to the weather forecasts no significant coldness will come or even things may get warmer
Here is the ESRL forecast out to Oct 24th for 80ºN. Forty 2m air temperature maps are provided at 6hr intervals and the average determined. The identical result is displayed in a variety of color tables with a scale that runs from -22º to +6º C. These variations illustrate how interpretations can be helped or hindered by presentation choices.

 Warmer air appears to be intruding well into the interior from the North Atlantic though the CAA remains cold. However it is not warm enough to melt any snow on ice. This time of year, snow retards bottom ice formation by insulating the top ice from air.

The second animation shows these temperatures for the Arctic Ocean as a whole over the same time frame. This shows air flow well but it is not easy to get a sense of the time-averaged temperature from it. The averaged whole ocean temperature has a red line indicating the southern boundary of sea water above its freezing temperature of -1.8ºC

Technical note: Panoply was run in linear grayscale mode on REB.2017-10-15.nc. The 40 frames are then averaged to a single grayscale in Gimp. All extraneous pixels are removed, leaving only the image plus its palette as 256 grays. Lookup tables in ImageJ are applied, those that seem informative are saved as .png, reloaded as an ImageJ stack, and saved out as a gif. Gimp has a bad bug in gifs that causes it to seek a global color table whereas gif89 allows each frame to have its own color table. The cluts used here are gray, glow, redHot, ICA3, physics, royal, rainbow, rire, cool, and inverted glasbey with the addition of G'mic contouring in some instances.
« Last Edit: October 18, 2017, 11:43:17 PM by A-Team »

A-Team

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Re: The 2017/2018 freezing season
« Reply #201 on: October 18, 2017, 09:46:40 AM »
It's that time of year again, when thousands of abstracts for AGU meeting become available. Hardly anyone discloses results, posters aren't available for poster sessions, talks won't be videoed, their powerpoints won't be archived, and already-published articles won't be linked.

Still, AGU17 does allow a look ahead to the coming year of journal articles. A name search can show what a particular scientist has been up to; for example Neven asked upforum what J Stroeve is doing, she is on three of the abstracts.

https://agu.confex.com/agu/fm17/meetingapp.cgi/SearchResults/0

Snow on Arctic sea ice is an active topic. Like ice thickness and clouds, it is very difficult to characterize basin-wide, in part because depth alone doesn't capture its insulating properties in freeze season: it's blown into windrows, it may be dunked in sea water on a floe with negative freeboard, or be rained upon and refreeze. Still, it looks like some better products than what we have now may be in the pipeline.

C23E-08: Merging observations and reanalysis data to improve estimates of snow depth on Arctic sea ice
NT Kurtz et al

Snow is an important controlling factor in the heat and radiation balance of the Arctic sea ice pack. Knowledge of snow on sea ice is also required for retrievals of sea ice thickness from airborne and spaceborne altimeters, and is presently the largest source of uncertainty in the conversion of freeboard to sea ice thickness from these altimetry data.

Multiple sources of observational snow depth data exist such as those from the Operation IceBridge (OIB) snow radar, passive microwave satellites, and ice mass balance buoys. However, these observational data sources are limited in spatial and/or temporal extent, which makes their usage impractical when used for basin-wide sea ice thickness retrievals in a standalone fashion.

We show how the use of snow depth observations from the OIB snow radar can be used as a primary means to improve basin-scale snow depth results from a simple snow model forced by reanalyses and satellite-derived ice drift estimates. We also show how different observational data sets impact the snow depth estimates, and how best to incorporate data sets of differing temporal and spatial scales to provide snow thickness estimates of consistent quality over the entire sea ice growth season. Particular focus is given to the new 2017 OIB data set which included new flights into the eastern Arctic sector where interesting differences were seen between the first year and multiyear ice areas.

C32B-02: Snow accumulation on Arctic sea ice: is it a matter of how much or when?
M Webster  et al

Snow on sea ice plays an important, yet sometimes opposing role in sea ice mass balance depending on the season. In autumn and winter, snow reduces the heat exchange from the ocean to the atmosphere, reducing sea ice growth. In spring and summer, snow shields sea ice from solar radiation, delaying sea ice surface melt. Changes in snow depth and distribution in any season therefore directly affect the mass balance of Arctic sea ice.

In the western Arctic, a decreasing trend in spring snow depth distribution has been observed and attributed to the combined effect of peak snowfall rates in autumn and the coincident delay in sea ice freeze-up. Here, we present an in-depth analysis on the relationship between snow accumulation and the timing of sea ice freeze-up across all Arctic regions.

A newly developed two-layer snow model is forced with eight reanalysis precipitation products to: (1) identify the seasonal distribution of snowfall accumulation for different regions, (2) highlight which regions are most sensitive to the timing of sea ice freeze-up with regard to snow accumulation, and (3) show, if precipitation were to increase, which regions would be most susceptible to thicker snow covers. We also utilize a comprehensive sensitivity study to better understand the factors most important in controlling winter/spring snow depths, and to explore what could happen to snow depth on sea ice in a warming Arctic climate.

C33C-1215: Rainy Days in the New Arctic: A Comprehensive Look at Precipitation from 8 Reanalysis
L Boisvert  et al

Precipitation in the Arctic plays an important role in the fresh water budget, and is the primary control of snow accumulation on sea ice. However, Arctic precipitation from reanalysis is highly uncertain due to differences in the atmospheric physics and use of data assimilation and sea ice concentrations across the different products. More specifically, yearly cumulative precipitation in some regions can vary by 100-150 mm across reanalyses. This creates problems for those modeling snow depth on sea ice, specifically for use in deriving sea ice thickness from satellite altimetry.

In recent years, this new Arctic has become warmer and wetter, and evaporation from the ice-free ocean has been increasing, which leads to the question: is more precipitation falling and is more of this precipitation rain? This could pose a big problem for model and remote sensing applications and studies those modeling snow accumulation because rain events will can melt the existing snow pack, reduce surface albedo, and modify the ocean-to-atmosphere heat flux via snow densification.

In this work we compare precipitation (both snow and rain) from 8 different reanalysis: MERRA, MERRA2, NCEP-R1, NCEP-R2, ERA-Interim, ERA-5, ASR and JRA-55. We examine the annual, seasonal, and regional differences and compare with buoy data to assess discrepancies between products during observed snowfall and rainfall events. Magnitudes and frequencies of these precipitation events are evaluated, as well as the “residual drizzle” between reanalyzes. Lastly, we will look at whether the frequency and magnitude of “rainy days” in the Arctic have been changing over recent decades.

C21B-1122: Synoptic weather conditions, clouds, and sea ice in the Beaufort and Chukchi Seasonal Ice Zone
Z Liu et al
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0887.1

The connections between synoptic conditions and clouds and sea ice over the Beaufort and Chukchi Seasonal Ice Zone are examined. Four synoptic states with distinct thermodynamic and dynamic spatial and vertical signatures are identified using a k-means classification algorithm and the ERA-Interim reanalysis data from 1979 to 2014.

The combined CloudSat and Calipso cloud observations suggest control of clouds by synoptic states. Warm continental air advection is associated with the fewest low-level clouds, cold air advection under low pressure generates the most low-level clouds. Low-level cloud fractions are related to lower-tropospheric stability and both are regulated by synoptic conditions. Observed cloud vertical and spatial variability is reproduced well in ERA-Interim, but winter low-level cloud fraction is overestimated.

Sea ice melt onset is related to synoptic conditions. Melt onsets occur more frequently and earlier with warm air advection states. The warm continental air advection state with the highest temperature is the most favorable for melt onsets even though fewer low-level clouds are associated with this state. The other warm advection state is cloudier but colder.

In the Beaufort and Chukchi Seasonal Ice Zone, the much higher temperature and total column water of the warm continental air advection state compensate the smaller cloud longwave radiative fluxes due to the smaller low-level cloud fraction. In addition, the higher shortwave radiative fluxes and turbulent fluxes to the surface are also favorable for sea ice melt onset.

C21G-1186: There goes the sea ice: following Arctic sea ice parcels and their properties.
MA Tschudi et al
http://www.mdpi.com/2306-5729/2/3/25

Arctic sea ice distribution has changed considerably over the last couple of decades. Sea ice extent record minimums have been observed in recent years, the distribution of ice age now heavily favors younger ice, and sea ice is likely thinning. This new state of the Arctic sea ice cover has several impacts, including effects on marine life, feedback on the warming of the ocean and atmosphere, and on the future evolution of the ice pack.

The shift in the state of the ice cover, from a pack dominated by older ice, to the current state of a pack with mostly young ice, impacts specific properties of the ice pack, and consequently the pack’s response to the changing Arctic climate. For example, younger ice typically contains more numerous melt ponds during the melt season, resulting in a lower albedo. First-year ice is typically thinner and more fragile than multi-year ice, making it more susceptible to dynamic and thermodynamic forcing.

To investigate the response of the ice pack to climate forcing during summertime melt, we have developed a database that tracks individual Arctic sea ice parcels along with associated properties as these parcels advect during the summer. Our database tracks parcels in the Beaufort Sea, from 1985 – present, along with variables such as ice surface temperature, albedo, ice concentration, and convergence.

We are using this database to deduce how these thousands of tracked parcels fare during summer melt, i.e. what fraction of the parcels advect through the Beaufort, and what fraction melts out? The tracked variables describe the thermodynamic and dynamic forcing on these parcels during their journey. The attached image (it’s not) shows the ice surface temperature of all parcels (right) that advected through the Beaufort Sea region (left) in 2014.

C33C-1210: Towards development of an operational snow-on-sea-ice product
GE Liston et al

While changes in the spatial extent of sea ice have been routinely monitored since the 1970s, less is known about how the thickness of the ice cover has changed. While estimates of ice thickness across the Arctic Ocean have become available over the past 20 years based on data from ERS-1/2, Envisat, ICESat, CryoSat-2 satellites and Operation IceBridge aircraft campaigns, the variety of these different measurement approaches, sensor technologies and spatial coverage present formidable challenges. Key among these is that measurement techniques do not measure ice thickness directly – retrievals also require snow depth and density.

Towards that end, a sophisticated snow accumulation model is tested in a Lagrangian framework to map daily snow depths across the Arctic sea ice cover using atmospheric reanalysis data as input. Accuracy of the snow accumulation is assessed through comparison with Operation IceBridge data and ice mass balance buoys (IMBs). Impacts on ice thickness retrievals are further discussed.
« Last Edit: October 18, 2017, 09:24:01 PM by A-Team »

A-Team

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Re: The 2017/2018 freezing season
« Reply #202 on: October 18, 2017, 12:15:22 PM »
Here are those same three RASM-ESRL precipitation forecasts at 24 hour intervals out to Oct 24th. A moderate amount of rain-on-snow is foreseen for a small area north of Svalbard. Snow depth is moderate, at most 0.25m, and quite uneven in providing thermal insulation after wind-blown drifting is considered (2nd image),
« Last Edit: October 18, 2017, 12:43:57 PM by A-Team »

Neven

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Re: The 2017/2018 freezing season
« Reply #203 on: October 18, 2017, 02:31:44 PM »
Snow on Arctic sea ice is an active topic. Like ice thickness and clouds, it is very difficult to characterize basin-wide, in part because depth alone doesn't capture its insulating properties in freeze season: it's blown into windrows, it may be dunked in sea water on a floe with negative freeboard, or be rained upon and refreeze. Still, it looks like some better products than what we have now may be in the pipeline.

Thanks for those abstracts, A-Team. Very interesting stuff. Snow on ice is one of those things I'd always known about, but my interest in it really got kindled during this past melting season.

A couple of days ago I also received this interesting message in my mailbox:

Quote
Dear colleagues and sea ice friends,

POLAR2018 is a *unique**joint event* organized by the Scientific
Committee on Antarctic Research SCAR and the International Arctic
Science Committee IASC, which will take place in Davos, Switzerland,
from 15 - 26 June 2018 with the open science conference from 19 - 23
June; see http://www.polar2018.org for general information.

Following up with our first invitation on September 27 we would like to
encourage you to submit your presentation to the conference session
entitled "*The role of snow on sea ice for sea-ice parameter retrieval
and variability*".

We invite studies dealing with in situ observations, with retrieval from
satellite observations, modeling and combinations thereof for snow
parameters on sea ice. We also invite studies on methods for quantifying
the influence of (unknown) snow properties on the satellite retrieval of
sea-ice parameters, on reducing the noise, improving the accuracy of
retrieved sea-ice parameters due to snow properties, and related studies.

Conveners of this session are: Stefan Kern, Burcu Ozsoy, Georg Heygster and Leif T. Pedersen

Please find details about the program as well as deadlines here:
http://www.polar2018.org/program.html
The enemy is within
Don't confuse me with him

E. Smith

A-Team

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Re: The 2017/2018 freezing season
« Reply #204 on: October 18, 2017, 09:12:41 PM »
Quote
unique event which will take place in Davos, Switzerland
I am skipping both Bilderberg and Davos this year in favor of a staycation. ;) 

The abstracts below speak to common themes on the forum; it's hard to say which will emerge as game-changers vs incremental improvements vs never-to-be-seen-agains.

C21G-1188: Estimation of Melt Ponds over Arctic Sea Ice using MODIS Surface Reflectance Data
Y Ding et al

Melt ponds over Arctic sea ice is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and ice. In recent years, a large number of melt ponds have been observed during the melt season in Arctic. Moreover, some studies have suggested that late spring to mid summer melt ponds information promises to improve the prediction skill of seasonal Arctic sea ice minimum.

In the study, we extract the melt pond fraction over Arctic sea ice since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, ice and open water. The preliminary comparison shows our derived Arctic-wide melt ponds are in good agreement with that derived by the University of Hamburg, especially at the pond distribution. We analyze seasonal evolution, inter-annual variability and trend of the melt ponds, as well as the changes of onset and re-freezing.

The melt pond fraction shows an asymmetrical growth and decay pattern. The observed melt ponds fraction is almost 25% in early May and increases rapidly in June and July with a high fraction of more than 40% in the east of Greenland and Beaufort Sea. A significant increasing trend in the melt pond fraction is observed for the period of 2000-2017.


C21G-1179: A Novel Approach To Retrieve Arctic Sea Ice Thickness For Prediction And Analysis
L Brucker et al

In spite of October-November Arctic-sea-ice-volume loss exceeding 7000 km3 in the decade following ICESat launch, most global ocean reanalysis systems are not able to reproduce such a drastic decline.

Knowledge of the sea ice properties and its thickness distribution is critical to our understanding of polar ocean processes and the role of the polar regions in the Earth's climate system. Existing large-scale sea ice thickness datasets are derived from freeboard observations made by different satellite altimeters (radar and lidar). These datasets are significantly different due to the remote sensing technique and spacecraft orbit, and they are limited in time. These differences increase the difficulty of using such data for sea ice initialization and assimilation, and increase the challenge for studying sea ice processes and interactions with the ocean and atmosphere.

For the first time, we were able to reproduce the Arctic sea ice thickness field at 10 km resolution with success for fall, winter, and spring (April/May depending on melt conditions) from passive microwave data. Our results reveal the same patterns of thickness distribution in the Arctic basin and peripheral seas as CryoSat-2, and the majority of the retrievals are within 0.5 m of CryoSat-2. The range of CryoSat-2 ice thickness is correctly retrieved, including in the upper range (3-5 m). The amplitude is well reproduced too, as the distribution of differences is centered on 0 m (no bias).

Some underestimations are visible between islands of the Canadian Archipelago, but due to the size of the field of view our confidence will always be lower in this region where there is land contamination. An initial comparison of the AMSR2 ice thickness with IceBridge airborne products in different sectors (Beaufort sea, central Arctic) demonstrates the quality of the retrievals.

We will also quantify the prediction and nowcast gain obtained from assimilating these new retrievals. We carried-out the integration of 36 members of coupled NASA Goddard Earth Observing System Model, version 5 (GEOS-5) to enable the implementation of an Ensemble Kalman Smoother (EnKS) over the period September 2012 - January 2013. Assimilating our retrievals improves the nowcast of ice volume, the forecast and the retrospective forecast.


C11D-06: Regional Arctic sea-ice prediction: A direct comparison of potential versus operational seasonal forecast skill
M Bushuk et al

Seasonal predictions of Arctic sea ice on regional spatial scales are a pressing need for a broad group of stakeholders, however, most forecast skill assessments to date have focused on pan-Arctic sea-ice extent (SIE). In this work, we present a direct comparison of potential and operational seasonal prediction skill for regional Arctic SIE. This assessment is based on two complementary suites of seasonal prediction ensemble experiments performed with a global coupled climate model.

First, we assess the operational prediction skill for de-trended regional SIE using a suite of retrospective initialized seasonal forecasts spanning 1980-2017. These retrospective forecasts are found to skillfully predict regional winter SIE at lead times of 3-11 months and regional summer SIE at lead times of 1-4 months, owing partially to subsurface ocean temperature and sea-ice thickness initial conditions, respectively. Second, we present a suite of perfect model predictability experiments with start dates spanning the calendar year, which are used to quantity the potential regional prediction skill of this system.

These perfect model experiments reveal that regional Arctic SIE is potentially predictable at lead times beyond 12 months in many regions, substantially longer than the current operational skill of this system. Both the retrospective forecasts and perfect model experiments display a spring prediction skill barrier for regional summer SIE forecasts, indicating a fundamental predictability limit for summer regional predictions. The skill gap identified in this work indicates a promising potential for future improvements in regional SIE predictions.


C21G-1190: Assessing surface radiative fluxes and developing surface turbulent heat fluxes over Arctic sea ice
M Song et al

In this study, we have developed a new satellite-based surface heat and moisture flux data set over the ice-covered ocean in the Arctic using a recently developed flux algorithm based on the theory of maximum entropy production (MEP model). First, the accuracy and uncertainty associated with surface radiative fluxes and temperature for three available satellite products are evaluated against the assembled in-situ data.

The three satellite products are the Surface Radiation Budget project (SRB), the International Satellite Cloud Climatology Project (ISCCP), and the Extended AVHRR Polar Pathfinder version-2 (APP-x).

Our comparisons suggest that 1) in terms of the overall bias, root mean square error, and correlation, the net surface radiative flux of ISCCP is closer to in-situ observations than that of SRB and APP-x; 2) in terms of the bias by local times, it is not very clear which satellite product is superior to others; and 3) in terms of inter-annual variability of the bias, the net surface radiative flux of ISCCP is more accurate than that of SRB and APP-x. Based on the above comparison, we use the ISCCP surface radiative fluxes as input values for the MEP model to calculate surface turbulent heat fluxes over Arctic sea ice.


C21G-1184: Improving Arctic sea ice edge forecasts by assimilating high resolution VIIRS sea ice concentration data into the U.S. Navy’s ice forecast system
OM Smedstad et al

This study presents the improvement in ice edge error within the U.S. Navy’s operational sea ice forecast system gained by assimilating the high horizontal resolution visible/infrared satellite-derived VIIRS ice concentration products. A series of hindcast studies are performed for the period of 1 January – 31 December 2016 using Global Ocean Forecast System (GOFS 3.1), a 1/12° HYbrid Coordinate Ocean Model (HYCOM) that is two-way coupled to the Community Ice CodE (CICE) in a daily update cycle with the Navy Coupled Ocean Data Assimilation (NCODA).

Comparisons using the VIIRS ice concentration products (< 1km resolution) show lower ice edge location errors than the current system, which assimilates near real-time passive microwave data from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMIS) and the Advanced Microwave Scanning Radiometer (AMSR2) ice concentration products (25 and 12.5km resolution, respectively).

The daily ice edge locations from the model simulations are compared against independent observed ice edge locations. Results from the Pan-Arctic and regional areas along with seasonal time scales will be presented. A previous study using the Arctic Cap Nowcast/Forecast System (ACNFS), a 1/12° coupled HYCOM/CICE/NCODA for the Northern Hemisphere only, has shown that by assimilating the VIIRS (along with SSMIS and AMSR2) ice concentration products reduced the ice edge location errors by 25% in the pan-Arctic region for the same year-long time period.
« Last Edit: October 18, 2017, 09:19:16 PM by A-Team »

A-Team

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Re: The 2017/2018 freezing season
« Reply #205 on: October 18, 2017, 11:31:33 PM »
Speaking of snow depth, here is another ESRL product, snowdepthchange.gif from their web page or archival REB_plots. It is somewhat peculiar in that D0 is not provided, only the D5 forecast. Thus the animation is of these day fives -- 15 Sep to 22 Oct -- rather than the presumably more accurate initial states.

Still, it gives an idea how rapidly snow depth changes from day to day as well as the expected prevailing wind. The final frame averages these out, even though the palette is not really designed to support this.

This time of year, when thermal insulation not solar insolation is the issue for the rate of bottom ice growth induced by frigid surface air, the relevant property of snow is its conductivity.

Is it still, as often assumed, a uniform basin-wide porous medium with a large immobilized air component (like a foam pad) after being blown around for weeks, possibly getting dunked, rained on, and soaked with sea spray? If so, is the current ankle-deep mean snowpack enough to seriously inhibit bottom growth, relative to not-so-cold prevailing mean air temperatures?

That's hard to say directly with no buoys, no ships, and no one out there but satellites can measure bulk properties. The scale though is not commensurate with that of snow features, though Sentinel-1 comes fairly close.

http://www.inscc.utah.edu/~campbell/snowdynamics/reading/Pomeroy.pdf
http://acwc.sdp.sirsi.net/client/search/asset/1005644;jsessionid=CE14DA1FFAEF3D6FD98ABAD517B04B81.enterprise-15000
http://www.sciencedirect.com/science/article/pii/S0165232X1100187X
http://arc.lib.montana.edu/snow-science/objects/issw-1994-176-184.pdf
« Last Edit: October 18, 2017, 11:42:09 PM by A-Team »

Peter Ellis

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Re: The 2017/2018 freezing season
« Reply #206 on: October 19, 2017, 10:58:44 AM »
Speaking of snow depth, here is another ESRL product, snowdepthchange.gif from their web page or archival REB_plots. It is somewhat peculiar in that D0 is not provided, only the D5 forecast.

Given that it's a depth change, then surely it has to be estimated over a given period?  At D0, there is no change from D0...

Images for the absolute values of snow/ice thickness and area are in one tab, images for the 5-day changes are in another.
https://www.esrl.noaa.gov/psd/forecasts/seaice/


Edit to add: Moreover, given that the "5 day change" values from two successive days' forecasts will necessarily include four out of the same 5 days, then I think rapid changes from day to day may be more indicative of model variability than anything to do with actual weather.

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Re: The 2017/2018 freezing season
« Reply #207 on: October 19, 2017, 06:37:53 PM »
Right. ESRL is primarily interested in making forecasts whereas we are primarily interested in archival initial state time series because short-term predictions have such a limited shelf life. The idea here was to finish scrolling through all their precipitation products to see which are worth scripting (Panoply --> ImageMagick --> cloud --> forum) into hindcasts + today + forecast time series.

The ESRL web site presents this one well enough, though too large to display well here. It might be of heads-up interest should more moisture-laden storm sweeps north from the Caribbean again this fall. However ice thickening takes place on a much slower time scale, so daily comings and goings of the insulating blanket of snow are of less interest than mean snowpack.

While it's hard to see the thermal relevance of blowing ankle-deep snow to bottom ice formation rates, maybe it will be knee-deep by late winter and suppress early melt pond formation through reflectance.

There being little purpose in simply replicating daily changes in NOAA's web site, the question becomes where we can 'add value'. Among the many opportunities explored in previous posts (eg SMOS-ESRL thin ice hybrids), are combined time series across the three ESRL (and other) archives.

These can be seasonal: the forecast below combines an open water property with a sea ice measure, namely temperature. That product diminishes in utility along with residual exposed water later in the fall. Salinity is another option; it mixes SMOS bulk ice salinity with that of ESRL open water. That too is seasonal since UH SMOS availability is melt-limited.

Note the Chukchi north of the Bering Strait is still far too warm for ice to form. That stayed open to mid-December last year. The map also shows a pronounced intrusion of warm surface water in the Yermak Plateau area north of Svalbard. Spurious open water is shown around CAA islands which are very difficult to get at accurately with gridded data (UH AMSR3 3.125 km is a better option there).

Technical note: these are easy to make since 'not sea ice' on the sea ice layer provides a pixel-perfect cut-out allowing any open water characteristic to show through. As long as the data sources are both available to Panoply as netCDF files, Gimp will receive the maps in perfect co-registration with compatible and operable palette legends. This readily scales to times series via tile 'n' slice.
« Last Edit: October 20, 2017, 10:02:39 AM by A-Team »

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Re: The 2017/2018 freezing season
« Reply #208 on: October 19, 2017, 10:54:01 PM »
Here are 27 days of sea water salinity from RASM-ESRL for October. As noticed before, each ten day forecast series begins at hour 24 rather than hour 00, the initial state. (Some even start at hour 48, skipping the first two days.) The odd boundary on the Svalbard side apparently results from a lack of data (or maybe it's off-scale on the high side).

There's ample room in a netCDF file for an explanation of the satellite (or oceanographic) source of the data but there is none. It's not clear what salinity under the ice pack means in terms of depth. The salinity range is also mistakenly set, showing large negative salinities.

Indeed, the whole file system of this project is seriously mis-configured. File names for a given product are all the same; they're supposed to be inseparably concatenated with their date. The daily RASM-ESRL archive is presented as nine separate files but these in effect just represent an animatable time sequence. They could have been folded into a single file with each time an animation frame (and there's a simple command line for doing just that).

This project reminds me of an autonomous 18-wheeler driving without incident from NY to LA but continuing on, only to plunge off the Santa Monica pier. That is, is anyone really driving this project, who is using it without reporting the flat tires, and how long can it run on fumes without  interventional refueling?

Whatever, it's interesting to watch salinity evolve along the Alaskan and East Siberian coasts. Salinity lowers the freezing point of sea water somewhat but here it is not determinative because though the remaining open water is fresher, its temperature (and that of the air above) are warmer.

SMOS provides bulk ice salinity of the ice pack surface which is more or less directly observable from its dielectric. As sea ice ages, it extrudes its brine which lowers its perceived bulk salinity here.
« Last Edit: October 20, 2017, 07:11:11 PM by A-Team »

Michael

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Re: The 2017/2018 freezing season
« Reply #209 on: October 20, 2017, 11:08:31 AM »
Here are 27 days of sea water salinity from RASM-ESRL for October. As noticed before, each ten day forecast series begins at hour 24 rather than hour 00, the initial state. (Some even start at hour 48, skipping the first two days.) The odd boundary on the Svalbard side apparently results from a lack of data.

The "t024" / "t48" indicate "hours since analysis" (Tau) rather than a time period.

Quote
variables:
   double tau ;
      tau:long_name = "Tau" ;
      tau:units = "hours since analysis" ;
   double time(time) ;
      time:long_name = "Valid Time" ;
      time:units = "hour since 2000-01-01 00_00_00" ;
   double time_bounds(time, d2) ;
      time_bounds:long_name = "boundaries for time-averaging interval" ;
      time_bounds:units = "days since 0000-01-01 00:00:00" ;
data:

 tau = 24 ;
 time = 155856 ;
 time_bounds =
  736488.75, 736489 ;

"time" in the RASM-ESRL files is calendar hours, "time" in the REB files is model days ("All years have exactly 365 days").

These data in the RASM-ESRL files are the same as the fourth set of data in the REB files but converted from float to short, in the process removing the Nans.

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Re: The 2017/2018 freezing season
« Reply #210 on: October 20, 2017, 04:51:05 PM »
Thanks. You are talking about ice and snow thicknesses?

Salinity, compressive strength, sea water temperature, the three melts, and two precips are not to be found in REB. None of these are attributed within RASM_ESRL. Their model might be able to derive some from others but salinity, water temperature and so on must be external inputs. From where though, there might be something better out there that could be stubbed in.

The REB files overlap do considerably in name. And they do provide start-stop ranges. However they provide 40 animation frames, the first of which I've been taking as t00 whereas RASM_ESRL provide only 9.

So I'm not sure what you mean by same as every 4th bit of data is the same. That would only use up 4x9 = 36 (sometimes 4x8 = 36) of the 40, suggesting the initial (or final?) state is missing in RASM_ESRL. Or rather, the latter uses intervals, n times has n-1 intervals but what does this mean in tangible terms for observational validation or animation frames, very little.

It seems better just to use REB whenever possible since they didn't see the merge app as applicable to RASM_ESRL intervals. But REB doesn't have the data to generate all the forecast animations that RASM_ESRL can. No way am I going to interpolate four 6hr frames out of one 24 hour to complete the file set in REB.

NaNs, float etc seem to be non-issues suppressed by Panoply and have no impact on visualizations or grepped csv coming out of ncdump.

It appears that not nearly enough information is provided in RASM_ESRL and REB.nc together to draw all the REB plots. That's unfortunate, those files might have been provided so users could correct the many inept products provided in REB plots, make omitted ones, compare to other observational sources, run an alternative model, or compare to competitive products like ECMWF. 

NOAA states this project is experimental. Fair enough but in its 3rd year, it's time to pull things together, maybe lay on some documentation and make the five minute fixes. It's true though that they didn't need to provide a public archive at all, much less the most thorough one around providing comprehensive Arctic forecasts. Expired forecasts have such limited interest that the real value may lie in archival initial states (or their reanalysis), which need attending to before letting this go on as unattended robo-ware.

Going around the web to the netCDF data sources we commonly use for forum graphics, I see a tremendous range in quality from zero (take this map and shove it), outdated (defective variable treatment disabling Geo2D), inadequately commented files, okay, and fantastic. In the instances where I know the authors, there's been a perfect correlation of open sourcing effort with the quality of their journal publications.

Data is not open source accessible in my view if it can't be viewed and manipulated without purchasing proprietary software, working in terminal mode, or emailing a deceased author. Site users and journal readers should have the capacity in most instances to reproduce major graphics.

I see a goodly number of totally incompetent graphical products, both in archives and after peer review. That is the real purpose of posting netCDF files -- the next person who comes along might have the skills to fix the graphic, re-project or re-palette it, delete over-writing  layers, test it for accuracy, or combine it in novel ways with other data sources. There is no purpose to climate science if it is not communicated.

In every collaborative project I've worked on, everyone including myself had moved on and lost all interest long before the draft worked its way through the publication process. We all knew what was in the data, making derivative charts from it was considered a total bore, the only thing worse being a remake six months later. Here again it's in everyone's interest to have a proper archive.

Other scientific communities with even bigger data sets, such as genomics, laid down the law fifteen years ago (GenBank) and enforce it via conditions in the grant (both govt and foundation). There was a lot of initial resistance to sharing, people acted like they somehow 'owned' the data even though the public had bought and paid for every scrap of it with the understanding they could see it.

Nobody has to share: just click the 'Don't Accept' option on the grant application, do the work at home, pay for it out of your non-salaried savings, and post on your facebook page to sidestep journal data requirements. If you don't go that route, then an adequate open archive is, scientifically speaking, obligatory. And it's especially important in the case of climate change.
« Last Edit: October 20, 2017, 07:22:49 PM by A-Team »

Michael

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Re: The 2017/2018 freezing season
« Reply #211 on: October 21, 2017, 10:46:50 AM »
So I'm not sure what you mean by same as every 4th bit of data is the same. That would only use up 4x9 = 36 (sometimes 4x8 = 36) of the 40, suggesting the initial (or final?) state is missing in RASM_ESRL. Or rather, the latter uses intervals, n times has n-1 intervals but what does this mean in tangible terms for observational validation or animation frames, very little.

Apologies, this is very much off topic.

My explanation. was very poor.  If the first file in the RASM-ESRL archive is labeled t048 it simply means that the ensemble hasn't been run and and the previous day 2 has been carried forward as day 1 etc.

To get the relationship between the RASM-ESRL and REB files, I would suggest extracting the relevant data from all the RASM-ESRL files in an archive and comparing it with the same data from the corresponding REB file.

ncdump -v tau,time,time_bounds "RASM-ESRL_2017-10-dd-00_t0hh.nc" > RASM-ESRL201710ddhh.txt
ncdump -v time,time_bounds "REB.2017-10-dd.nc" > REB20171010time.txt

To convert RASM-ESRL "time" to REB "time" :  time =  (time + 17519880) / 24

The actual source for the data in the individual .nc files can be found near the bottom of the history section of the header.
The syntax is ncrcat -v [variable list] [source files] [ouput files]
and ncks -v [variable list] [source file] [ouput files]

Feeltheburn

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Re: The 2017/2018 freezing season
« Reply #212 on: October 21, 2017, 09:09:14 PM »

Yes, there is substantially more Arctic sea ice extent now than there was on this same day last year. But it should be noted that the NSIDC ASIE increase of 1.038 km2 since October 1 is less than that measured in 2015, 2014, 2013, 2012, or 2010. Month-to-date, NSIDC SIE is still running below the ten-year average, and year-to-date, 2017 extent is deeply entrenched in second place. Bottom line, then: I'm not sure how "nicely" once can say it's recovering.

As of October 20, 2017, the SIE is running *ahead* of the 10-year average (2007 to 2016) and is currently in "5th place" behind 2007, 2016, 2011, and 2012, and has just about caught up with, and may soon surpass, 2009.

Update:

NSIDC SIE - October 20

Year          SIE (million km2)         Rank (for 11 year period)             2017 vs Year

2007         6.279                                1st                                       +958,000 km2
2008         8.026                                11th                                      -789,000 km2
2009         7.307                                6th                                           -7,000 km2
2010         7.508                                7th                                        -271,000 km2
2011         6.496                                3rd                                       +741,000 km2
2012         6.582                                4th                                       +655,000 km2
2013         7.992                                10th                                      -755,000 km2
2014         7.805                                9th                                        -568,000 km2
2015         7.548                                8th                                        -311,000 km2
2016         6.310                                2nd                                      +927,000 km2
2017         7.237                                5th                                                   0 km2

10-Year Average (2007 through 2016) = 7.185 km2

2017 vs 10 year average 2007 to 2016: +51,700 km2

Given the very poor start that 2017 had (the worst ever), I think it's accurate to say that 2017 has rebounded nicely, and better than almost anyone expected. Someone showed the predictions in the SIE surveys for NSIDC and Jaxa, and almost everyone predicted way low, suggesting deeply engrained negative bias. My predictions were just about dead on for all surveys. That is not to brag. Far from it. I come with no experience compared to most here. But I am also not weighed down by negative bias. I just look at the data and then make my predictions.
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Feeltheburn

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Re: The 2017/2018 freezing season
« Reply #213 on: October 21, 2017, 09:16:50 PM »
The 2017 global sea ice extent trend line is at a point where it has to decide whether it will join the pack of trend lines, or tag along with the 2016 trend line:

I think the decision has been made. Arctic sea ice is now in 5th place for past 11 years, and Antarctic sea ice is no longer in last place, but 3rs place according to published graph. So it stands to reason the composite graph line should be trending upward with the pack.
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Feeltheburn

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Re: The 2017/2018 freezing season
« Reply #214 on: October 21, 2017, 09:20:59 PM »
The 2017 global sea ice extent trend line is at a point where it has to decide whether it will join the pack of trend lines, or tag along with the 2016 trend line:

Here are the graphs, showing the decision has been made to stay with the pack.

https://sites.google.com/site/arctischepinguin/home/sea-ice-extent-area/grf/nsidc_global_area_byyear_b.png

https://sites.google.com/site/arctischepinguin/home/sea-ice-extent-area/grf/nsidc_global_extent_byyear_b.png
 :D
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Re: The 2017/2018 freezing season
« Reply #215 on: October 22, 2017, 02:21:40 PM »
As of October 20, 2017, the SIE is running *ahead* of the 10-year average (2007 to 2016) and is currently in "5th place" behind 2007, 2016, 2011, and 2012, and has just about caught up with, and may soon surpass, 2009.

Update:

NSIDC SIE - October 20

Year          SIE (million km2)         Rank (for 11 year period)             2017 vs Year

2007         6.279                                1st                                       +958,000 km2
2008         8.026                                11th                                      -789,000 km2
2009         7.307                                6th                                           -7,000 km2
2010         7.508                                7th                                        -271,000 km2
2011         6.496                                3rd                                       +741,000 km2
2012         6.582                                4th                                       +655,000 km2
2013         7.992                                10th                                      -755,000 km2
2014         7.805                                9th                                        -568,000 km2
2015         7.548                                8th                                        -311,000 km2
2016         6.310                                2nd                                      +927,000 km2
2017         7.237                                5th                                                   0 km2

Of course, I wasn't using single-day numbers; I specifically referred to longer time scales, which are more "truthful". And those long-term scales show that October-to-date NSIDC SIE growth is running below the ten-year average; October 2017 has seen less ice growth than that measured in 2008, 2010, 2012, 2013, 2014, or 2015. So, again: hard to call that a "nice" recovery. But, you know, whatever makes you happy.

Someone showed the predictions in the SIE surveys for NSIDC and Jaxa, and almost everyone predicted way low, suggesting deeply engrained negative bias.

Oh, is that what it "suggests"? Personally, I think that's insulting and dismissive. But let's go with it anyway. So, then, when you have in the past predicted more ice than there actually turned out to be, can we assume you were exhibiting a "deeply engrained positive bias"? Or does it actually simply suggest that the majority of the people here, most who know far more about Arctic ice than either you or I ever will, made the best, most accurate predictions they could based on the available data and observations?

My predictions were just about dead on for all surveys. That is not to brag. Far from it. I come with no experience compared to most here. But I am also not weighed down by negative bias. I just look at the data and then make my predictions.

I'll have my grandmother bake you a cookie.

A-Team

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Re: The 2017/2018 freezing season
« Reply #216 on: October 22, 2017, 05:26:35 PM »
Quote
my predictions were perfect
Preposterous. Without some idea of what the weather is going to do a few months to a year out, it's just numerology trending off hindcasts. No one had or has the slightest idea where the weather is going, least of all you.

The basic idea in measuring 'forecast skill' is assigning a baseline score of 0.00 to physics-free continuation. Thus I can predict with very high confidence that the weather in Tucson AZ will be sunny on 22 Oct 2025 but the skill there is 0.00 because it's been like that for centuries.

To get a grasp on just how incredibly complicated it is to make real predictions, try reading this article on k-means synoptic states over the Beaufort-Chukchi. The cloud component alone is extremely difficult yet is very important all year long to sea ice extent and thickness for seasonally different reasons.

Can you share with us where you got the necessary data for this summer?  Cloudsat is essential for prediction but it broke a reaction wheel on June 4th and went into standby mode, not sending any more data down. The problems with Cloudsat and Calypso data are all but intractable even when they are operational; no one here has ever made any headway with the CSU data repository.

The best that can be hoped for is some rules of thumb will emerge that provide some after-the-fact understanding:

Synoptic Conditions, Clouds, and Sea Ice Melt Onset in the Beaufort and Chukchi Seasonal Ice Zone
Z Liu, A Schweiger APL UW

Cloud response to synoptic conditions over the Beaufort and Chukchi seasonal ice zone is examined. Four synoptic states with distinct thermodynamic and dynamic signatures are identified using ERA- Interim reanalysis data from 2000 to 2014.

CloudSat and CALIPSO observations suggest control of clouds by synoptic states. Warm continental air advection is associated with the fewest low-level clouds, while cold air advection generates the most low-level clouds. Low-level clouds are related to lower-tropospheric stability and both are regulated by synoptic conditions.

High-level clouds are associated with humidity and vertical motions in the upper atmosphere. Observed cloud vertical and spatial variability is reproduced well in ERA-Interim, but winter low-level cloud fraction is overestimated. This suggests that synoptic conditions constrain the spatial extent of clouds through the atmospheric structure, while the parameterizations for cloud microphysics and boundary layer physics are critical for the life cycle of clouds in numerical models. Sea ice melt onset is related to synoptic conditions.

Melt onsets occur more frequently and earlier with warm air advection. Synoptic conditions with the highest temperatures and precipitable water are most favorable for melt onsets even though fewer low-level clouds are associated with these conditions.

Quote
[Already by 2014, it had been shown] synoptic patterns better explain the variability of sea ice than climate indices such as the Arctic Oscillation, the North Atlantic Oscillation and the Arctic dipole.
These are in effect rudimentary synoptic patterns: for example the daily AO index is constructed by projecting the daily 1000mb height anomalies poleward of 20°N onto its loading pattern, the leading mode of Empirical Orthogonal Function (basis states) of monthly mean 1000mb height during 1979-2000 period.
 
http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.loading.shtml
=-=-=-=-=

Meanwhile, back to ESRL's modest but already ambitious day 10 forecasts and whether they're useful for winter ice thickness growth (which we need for melt season preconditioning). There was a computer mishap resulting in no data for Oct 20th affecting all three archive sections. [This got fixed by the 23rd.] This happened previously on Sept 12th. REB_plots had a glitch on the 16th and so on. To enumerate these, just look down file list for size anomalies.

There's no going back, so the practical impact will be a small but permanent gaps in the initial state time series. That is no different from UH AMSR2 and all the other product archives. In the animations up-forum, the gaps are filled with a duplicate frame from the day before (or if multi-day, from above and below). It is feasible to interpolate within Panoply but with the ice edge moving and so forth, the accuracy is problematic whereas a stalled frame conveys the notion of missing data.
« Last Edit: October 23, 2017, 02:00:50 PM by A-Team »

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Re: The 2017/2018 freezing season
« Reply #217 on: October 23, 2017, 12:05:17 PM »
Given the very poor start that 2017 had (the worst ever), I think it's accurate to say that 2017 has rebounded nicely, and better than almost anyone expected.

I agree with this statement. A rebound that most probably places the <1 mkm2 event beyond 2020.

A-Team

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Re: The 2017/2018 freezing season
« Reply #218 on: October 23, 2017, 02:52:11 PM »
Quote
most probably places the <1 mkm2 event beyond 2020.
The same rubbish every fall, catastrophism after low years, recovery chatter after upticks. What could possibly serve as a scientific basis for a 4+ year weather-ocean-ice forecast? In some ways, 2007 was the most disturbing year to date; neither it nor 2012 were foreseen or foreseeable.

Very few of our registrants seem to take any substantive interest in the 2017/18 freezing season, the topic of this forum. Sharing of ungrounded speculation and personal hunches is very boring. Maybe we should just shut it down and come back in May. Visitation levels don't justify the effort.

SMOS 3.1 thin ice thickness is an interesting way to track the season though. If ice doesn't thicken much during the winter (as expected from Arctic amplification), there's that much less to melt during the melt season. Thinner ice also responds very differently to wind dispersion and export.

The first animation compares newly formed ice from 2012-2017 for the 21st of October; there's quite a bit of variability. The still image shows the same years side by side. The bottom animation computes the six year average for this date and flickers 2017 over it.

Whole Arctic trend-lining is far less informative than regional trend-lining, itself little done on our forums even though wipneus posts the necessary data. 2D maps take regional trend-lining to its end state, the resolution of the data. As there's no physical basis for drawing 'Beaufort' or 'Chukchi' boundaries etc, maps can show what is going on free of nomenclatural bias. To first order, that is latitudinal freeze-up about the cold pole (rather than the north pole).

SMOS in a sense integrates all the heat fluxes between atmosphere, newly forming ice and ocean. Since the weather has been so uneventful for so long, bottom growth prediction for older ice will have fewer problems than in past years. The interest right now is the date of final freeze-over, which is going rather slowly in the Beaufort-Chukchi-ESAS regions and unremarkably above Svalbard.

The freeze season settles down more into straight thermodynamics after freeze-over, though low clouds remain important for net heat loss. I've inquired about getting near-real time cloud synaptic state; for now we can only get at those indirectly (but quantitatively) through RASM-ESRL energy fluxes.
« Last Edit: October 23, 2017, 03:09:36 PM by A-Team »

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #219 on: October 23, 2017, 03:54:07 PM »
No one should be surprised that our warm fall and winter is setting up as it has for over a decade. (The new Arctic climate regime) The FDD anomaly only trails 2016.

Will we have low volume at the beginning of next years melt season?

Oh...and with regards to my predictions about this just completed melt season? The next time I record any prediction on this site will be my 1st. While this may be fun for some, it is little more than placing a bet on a roulette wheel. If you want to weed out the fools who don't have a clue, require the person making a prediction include a $1000 bet and watch how the votes drop.

Daniel B.

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Re: The 2017/2018 freezing season
« Reply #220 on: October 23, 2017, 07:52:23 PM »
Quote
most probably places the <1 mkm2 event beyond 2020.
The same rubbish every fall, catastrophism after low years, recovery chatter after upticks. What could possibly serve as a scientific basis for a 4+ year weather-ocean-ice forecast? In some ways, 2007 was the most disturbing year to date; neither it nor 2012 were foreseen or foreseeable.

Very few of our registrants seem to take any substantive interest in the 2017/18 freezing season, the topic of this forum. Sharing of ungrounded speculation and personal hunches is very boring. Maybe we should just shut it down and come back in May. Visitation levels don't justify the effort.

SMOS 3.1 thin ice thickness is an interesting way to track the season though. If ice doesn't thicken much during the winter (as expected from Arctic amplification), there's that much less to melt during the melt season. Thinner ice also responds very differently to wind dispersion and export.

The first animation compares newly formed ice from 2012-2017 for the 21st of October; there's quite a bit of variability. The still image shows the same years side by side. The bottom animation computes the six year average for this date and flickers 2017 over it.

Whole Arctic trend-lining is far less informative than regional trend-lining, itself little done on our forums even though wipneus posts the necessary data. 2D maps take regional trend-lining to its end state, the resolution of the data. As there's no physical basis for drawing 'Beaufort' or 'Chukchi' boundaries etc, maps can show what is going on free of nomenclatural bias. To first order, that is latitudinal freeze-up about the cold pole (rather than the north pole).

SMOS in a sense integrates all the heat fluxes between atmosphere, newly forming ice and ocean. Since the weather has been so uneventful for so long, bottom growth prediction for older ice will have fewer problems than in past years. The interest right now is the date of final freeze-over, which is going rather slowly in the Beaufort-Chukchi-ESAS regions and unremarkably above Svalbard.

The freeze season settles down more into straight thermodynamics after freeze-over, though low clouds remain important for net heat loss. I've inquired about getting near-real time cloud synaptic state; for now we can only get at those indirectly (but quantitatively) through RASM-ESRL energy fluxes.

I agree with you first paragraph, as bad news breed negativism, and good news optimism.  The current Arctic sea ice extent is fifth lowest, as stated.  Although the current trend is likely to pass 2009 in the next day or two into sixth lowest, and possibly 2010 soon.  The growth of the sea ice from the September minimum until today is quite average.  The growth thus far this season is 2.6 sq. km., compared to a 10-year average of 2.7, and a longer term average of 2.5, although there is a slight tendency of low minimum years to have greater ice growth.  Not only is <1 mkm2 likely pushed beyond 2020, it is likely pushed mush farther beyond.

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Re: The 2017/2018 freezing season
« Reply #221 on: October 23, 2017, 08:51:46 PM »
You've confused rapid fall extent onset, which is a bad thing for ice future because it holds the ocean heat in, with volume growth which puts more of a burden on the next melt season but is disfavored by heat-retaining water under a skin of ice.

Which melt season is driven by future weather that you (and everyone else) have not the slightest clue about, a la 2007 and 2012. Watch that 30 year sea ice age video of Tschudi's -- it's all right there.

When will the Bering Strait and Chukchi freeze over this year, relative to 2016? No one has the slightest idea. That date has nothing whatsoever to do with whole-ocean trend mumbo-jumbo.

Oren is on point. (Note attached on-topic data supporting views.)  It's the dog walking on its two hind legs: we applaud not so much that the air cold enough for volume recovery but that is cold and dark enough to have open water freezing in late October. How much the ice will thicken over the winter depends quantitatively on HOW cold the air is, not merely that it is cold (below -1.8ºC).

This is the freeze forum, one of our rare science areas. We have dedicated forums for extent, area and volume trend-trackers. Please delete off-topic, unsupported speculation and move it somewhere appropriate.
« Last Edit: October 23, 2017, 09:13:27 PM by A-Team »

Neven

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Re: The 2017/2018 freezing season
« Reply #222 on: October 23, 2017, 10:57:12 PM »
This is the freeze forum, one of our rare science areas. We have dedicated forums for extent, area and volume trend-trackers. Please delete off-topic, unsupported speculation and move it somewhere appropriate.

Agreed, never mind the fact that what you say, makes no sense.

I'm planning on becoming more active here in November. I want to be ready for next year's melting season.
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Re: The 2017/2018 freezing season
« Reply #223 on: October 24, 2017, 12:12:38 AM »
What I've marked from the current freezing:
  • The Garlic Press worked hard and there's a lot of thick ice in the CAA already
  • The Fram export resumes but still low. There could be more MYI in the CAB by the end of the freezing than last year.
I don't know what to say more. It's cold and the water freezes - the summary of the freezing season

oren

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Re: The 2017/2018 freezing season
« Reply #224 on: October 24, 2017, 12:43:55 AM »
What I've marked from the current freezing:
  • The Garlic Press worked hard and there's a lot of thick ice in the CAA already
  • The Fram export resumes but still low. There could be more MYI in the CAB by the end of the freezing than last year.
I don't know what to say more. It's cold and the water freezes - the summary of the freezing season
Well said Pavel. Last winter the arctic kept moving towards the Atlantic side, which was what kept the Chukchi open for quite a while, the Beaufort mostly free of MYI, and the max volume at a low level (coupled with low FDDs of course). OTOH, this same phenomenon may have stalled this summer's Atlantic melt, as a lot of volume was stuck on this side of the arctic. I suspect the same happened in the CAA, where last year's garlic press brought a lot of ice this summer that insisted on not melting out, despite warm temps and a lot of melt ponds.
A-Team, thanks as usual for the deep-level animations and data.
And SH, thanks for reminding about the FDD anomaly chart, though I prefer the seasonal version (attached) that better tracks the effects of temps on refreeze.

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Re: The 2017/2018 freezing season
« Reply #225 on: October 24, 2017, 01:28:18 AM »
it is likely pushed mush farther beyond.

Pushed mush? Freudian slip, Daniel ?

Sounds appropriate though  :)

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Re: The 2017/2018 freezing season
« Reply #226 on: October 24, 2017, 10:25:51 AM »
Quote
most probably places the <1 mkm2 event beyond 2020.
... Not only is <1 mkm2 likely pushed beyond 2020, it is likely pushed mush farther beyond.

Respectfully, are we not watching the winding down of a series of bounded but inherently chaotic events.  We have all the things we know (ice states, energy balance etc) plus a goodly swarm of known and unknown unknowns.  I wish Cryosphere was still maintaining the Tale of the Tape which showed us the on-going anomalies in polar ice extent etc. 

That to me presented the wriggles found in any decaying complex system where some seasons were strong and others weak, when it looked hopeless it sometimes rebounded, when it looked staunch sometimes it fell through the bottom.  The recent monthly and even annual wriggles mean little, only the really long term trends give us a hint of what to expect.   <1M sqkm will happen.  And right now nothing humanity is doing will extend the date it does. 
https://www.esrl.noaa.gov/gmd/ccgg/trends/

The PIOMAS volume anomaly chart seems to disguise the somewhat exponential nature of the downward trend because it looks like it annually increments the base used to calculate the anomaly (currently 1979-2016),
http://psc.apl.uw.edu/wordpress/wp-content/uploads/schweiger/ice_volume/BPIOMASIceVolumeAnomalyCurrentV2.1.png

Perhaps the quiet-time of the 2017 freezing season could be usefully spent keeping a weather-eye out for black swans, and watching for impacts of the Artic ice and weather on climate further afield.

« Last Edit: October 25, 2017, 01:10:33 AM by Adam Ash »

Iceismylife

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Re: The 2017/2018 freezing season
« Reply #227 on: October 25, 2017, 08:28:46 PM »
<snip>
Which melt season is driven by future weather that you (and everyone else) have not the slightest clue about, a la 2007 and 2012. Watch that 30 year sea ice age video of Tschudi's -- it's all right there.
<snap>
In eastern tradition in the i ching they talk about rain makers. People that influence weather.  This is entirely discounted in the west.  The farmers almanac has a proprietary method for predicting the weather with good results.

My prediction is that the artic basin will be quiet this season. sea ice recovery.  But starting early and trapping heat in

StopTheApocalypse

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Re: The 2017/2018 freezing season
« Reply #228 on: October 26, 2017, 10:15:23 PM »
Probably on the wrong side of predictability, but GFS suggests some pretty large heat anomalies next week. This is the 168h.

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #229 on: October 26, 2017, 10:48:38 PM »
Looking at the actual temperature forecast for this day, these warm temps appear to coincide with an arctic storm.

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #230 on: October 26, 2017, 10:50:14 PM »
And here is the cloud and precipitation forecast.

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Re: The 2017/2018 freezing season
« Reply #231 on: October 27, 2017, 02:40:40 PM »
Looking at the actual temperature forecast for this day, these warm temps appear to coincide with an arctic storm.

Shared Humanity
« on: October 26, 2017, 10:48:38 PM » Insert Quote
Looking at the actual temperature forecast for this day, these warm temps appear to coincide with an arctic storm.


The Polar Vortex hadn't had time to even form, it is already shredded to Pieces.

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #232 on: October 27, 2017, 04:58:56 PM »
Forecast has changed significantly in the last 24 hours. November 2, now 144 hours out is not nearly as warm.

Supports the opinion of many here that 7 day forecasts cannot be trusted.

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #233 on: October 27, 2017, 05:05:44 PM »
The low that was forecast to enter the CAB is now expected to traverse the Bering and Chukchi but it will advect a lot of moisture into the CAB and the pole is very cloudy. Can't be good.

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Re: The 2017/2018 freezing season
« Reply #234 on: October 27, 2017, 05:10:33 PM »
I'm actually struggling to understand these forecast maps. Both precipitation and cloud cover are supposed to be forecast. It is easy to see the precipitation forecasts but I'll be damned if I can understand cloud cover here. How are you supposed to see % overcast?

Does solid white mean thick cloud cover? If so the Arctic is forecast to be solidly overcast for the entire next week.

jdallen

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Re: The 2017/2018 freezing season
« Reply #235 on: October 28, 2017, 12:28:47 AM »
Very few of our registrants seem to take any substantive interest in the 2017/18 freezing season, the topic of this forum. Sharing of ungrounded speculation and personal hunches is very boring. Maybe we should just shut it down and come back in May. Visitation levels don't justify the effort.
Please continue.  I apologize for my lack of participation over the last few weeks - personal events have overtaken me (including surgery and full recovery from thereof).  I hope to be back on the saddle shortly.

I've been catching up on your graphing A-Team, and rolling around in my noggin is a notion of trying to model heat flow via a comparison of sea water temperatures, estimates of sea ice and snow thickness, sea surface temperatures and net atmospheric moisture content.

It is ambitious, but I'm going to start looking on in the developers forum for standards, sources and methods to assemble gridded data.

With that, the next set would be to apply various heat flow equations to each of the layers to come up with a composite heat loss number for each grid cell.  I think an average over time is indicated here.

Overall goal is to have that as a tool we can use which would help understand the refreeze dynamics.  Net heat loss I think is key.
« Last Edit: October 28, 2017, 12:45:17 AM by jdallen »
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StopTheApocalypse

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Re: The 2017/2018 freezing season
« Reply #236 on: October 28, 2017, 12:38:26 AM »
I'm actually struggling to understand these forecast maps. Both precipitation and cloud cover are supposed to be forecast. It is easy to see the precipitation forecasts but I'll be damned if I can understand cloud cover here. How are you supposed to see % overcast?

Does solid white mean thick cloud cover? If so the Arctic is forecast to be solidly overcast for the entire next week.

It's incredibly frustrating that both sea ice and clouds are essentially the same color. A product with off color ice/clouds would be helpful, I think. And yes, a better color scheme with more variation for cloud cover would be useful as well.

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Re: The 2017/2018 freezing season
« Reply #237 on: October 28, 2017, 12:42:25 AM »
The farmers almanac has a proprietary method for predicting the weather with good results.
*What*?!

Ok, I'll overlook that, but I agree that we will see rapid recovery of SIE and commensurate trapping of enthalpy in the Arctic Ocean.

SIE *will* appear to recover faster against past years and the average *exactly* because as per the last 10 years, there is far more open water to be covered.

I keep seeing this sort of thing cited as recovery.  It isn't.

Here are the *only* things which I think can be accurately described as Arctic "recovery":

1) Net multiple (at least 3, preferably 5) year over year decreases in Arctic Ocean total enthalpy.
2) Net multiple year over year increases in total Arctic sea ice volume.

That's *it*.

Any other metrics are going to be derivative of and affected by other forces in play which are far more volatile.

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Re: The 2017/2018 freezing season
« Reply #238 on: October 28, 2017, 12:52:32 AM »
trying to model heat flow

That sounds very interesting.

With all this talk of early ice growth trapping summer heat in the water underneath the ice, I've been wondering what data there is on that... and at what depth the water temperature is most relevant for a seasonal ice outlook.

I know ARGO floats have some capability to operate under sea ice and save up the data until it's safe to transmit... but I've never seen any actual data beyond 65N.

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Re: The 2017/2018 freezing season
« Reply #239 on: October 28, 2017, 01:03:26 AM »
trying to model heat flow

That sounds very interesting.

With all this talk of early ice growth trapping summer heat in the water underneath the ice, I've been wondering what data there is on that... and at what depth the water temperature is most relevant for a seasonal ice outlook.

I know ARGO floats have some capability to operate under sea ice and save up the data until it's safe to transmit... but I've never seen any actual data beyond 65N.
Almost by definition there will be guess work involved regarding water temperatures, as once the ice is in place we no longer have satellite data.  For data on temperatures at depth, we're much worse off - but that's exactly one of the factors I need for following what I think is a key metric - total arctic ocean enthalpy.  I'm mulling how to source that, and I think it's key to the refreeze as well.
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Re: The 2017/2018 freezing season
« Reply #240 on: October 28, 2017, 02:23:09 AM »
The Polar Vortex hadn't had time to even form, it is already shredded to Pieces.

Hi meddoc, what metric or timeframe are you looking at? Our developing PV doesn't seem that unusual to me.

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Re: The 2017/2018 freezing season
« Reply #241 on: October 28, 2017, 04:01:33 PM »

""Arctic Sea-Ice is much thinner than we thought""
https://www.youtube.com/watch?time_continue=146&v=L6kndSJiu8c

meddoc

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Re: The 2017/2018 freezing season
« Reply #242 on: October 28, 2017, 05:39:17 PM »
The Polar Vortex hadn't had time to even form, it is already shredded to Pieces.

Hi meddoc, what metric or timeframe are you looking at? Our developing PV doesn't seem that unusual to me.

I was looking at surface Temps by the French Meteo Animation. It looked like that to me.
But, now checking nullschool.com it "only" shows it being tossed around.

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Re: The 2017/2018 freezing season
« Reply #243 on: October 28, 2017, 07:14:05 PM »
I'm actually struggling to understand these forecast maps. Both precipitation and cloud cover are supposed to be forecast. It is easy to see the precipitation forecasts but I'll be damned if I can understand cloud cover here. How are you supposed to see % overcast?


Much better depiction of cloud cover to be had here :

https://weather.us/model-charts/standard/north-pole/total-cloud-coverage/20171102-0000z.html

Can be broken down into low,middle and high cloud also.

Shared Humanity

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Re: The 2017/2018 freezing season
« Reply #244 on: October 28, 2017, 08:26:59 PM »
Thanks. Much better except for the choice to use dark gray for 100% cover. Clearly the clouds only cover a portion of the Arctic Ocean.

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Re: The 2017/2018 freezing season
« Reply #245 on: October 29, 2017, 07:45:56 AM »
Much better depiction of cloud cover to be had here :

https://weather.us/model-charts/standard/north-pole/total-cloud-coverage/20171102-0000z.html

Can be broken down into low,middle and high cloud also.
Incredibly useful!  Thanks!
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Re: The 2017/2018 freezing season
« Reply #246 on: October 29, 2017, 03:24:28 PM »
Much better depiction of cloud cover to be had here :

https://weather.us/model-charts/standard/north-pole/total-cloud-coverage/20171102-0000z.html

Can be broken down into low,middle and high cloud also.
Incredibly useful!  Thanks!

Is this available on ASIB's chart tab?

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Re: The 2017/2018 freezing season
« Reply #247 on: October 29, 2017, 03:32:21 PM »
Is this available on ASIB's chart tab?

You mean the ASIG? I had a look yesterday evening, as it would be a great addition, but I can't link to the images.
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Re: The 2017/2018 freezing season
« Reply #248 on: October 29, 2017, 03:55:00 PM »
Yes, meant ASIG. Too bad. Could you set these kinds of resources up as just a link to the site?

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Re: The 2017/2018 freezing season
« Reply #249 on: October 29, 2017, 04:02:35 PM »
Looks like another very rare Earthquake close to the NP. M 6.0!!!
When the Top of the World moves- You can bet it will move the whole Northern Hemisphere.

Isostatic Rebound kicking in big- time. This, along with the ramping up of Extreme Weather Eevents in spite of a "Rebound Year" is Worrying.

https://watchers.news/2017/10/28/shallow-m6-0-earthquake-hits-north-of-franz-josef-land-arctic-ocean/