229
Accuracy of Sea Ice Data from Remote Sensing
Methods, its Impact on Safe Speed Determination and
Planning of Voyage in Ice-Covered Areas
T.Pastusiak
GdyniaMaritimeUniversity,Gdynia,Poland
ABSTRACT:Thedatarelatedtoicefloeconcentrationandicethicknesswereanalysed.Sourcesofdatahave
beenverifiedbyvisualobservationandbycomparisoninbetweeninformationfromdifferentremotesensing
sources.Theresultsofthisworkexceededinitialexpectations.
The discrepancies of the information provided by va
rious data sources result from the error of the
measurementmethod,whichcanbeashighas15%oftheconcentrationoficefloes.Itshouldalsobebornein
mindthatthemoregeneralizedinformationaboutthestateoftheicecover,thelowerprobabilityofdetection
oficefloepa
tchesofahighconcentrationandspatialextent.Eachvesselthatisplanningvoyageiniceshould
takeintoconsiderationinaccurateestimationofconcentrationandthicknessoficefloesreceivedbymeansof
satelliteremotesensingmethods.Themethodofdeterminingpermissiblespeedofvariousiceclassvesselinice
on ba
sis of safe speed graph for the icebreaker was developed. A well‐defined equation approximates
relationshipbetweenspeedoftheicebreakerandthevesselsofspecifiediceclasses.
Averagedistanceof24.1Nmfromseaiceextentlinewasrelatedtoallanalysedlinesrepresenting30‐40%ice
floe concentration (IUP product excluded) and 30.6 Nm for analysed lines representing 70‐81‐91% ice floe
concentration.Thema
ximalaveragedistanceofthefurthestanalysedline(IUPproductexcluded) wasequal
37.2Nm.Theaveragestandarddeviationofthatresultswasequal8.3Nmonly.Averagedistancesofanalysed
linesfromseaiceextentlinetoma
ximalicedatavalueswerefoundasfollow:8.4Nm(23%)forNSIDC‐CCAR
iceage,12.3Nm(33%)forminimaldistanceof30‐40%iceconcentration,15.4Nm(41%)forOSISAFicetype
“ambiguous”zonefromOpenWaterside,25Nm(67%)forminima
ldistanceof70‐81‐91%iceconcentration,
26.6Nm(72%)forOSISAFicetype“ambiguous”zonefrom1styeariceageside,35.9Nm(97%)formaximal
distanceof30‐40%iceconcentrationand36.3Nm(98%)formaximaldistanceof70‐81‐91%iceconcentration
data.Intheparenthesespla
cedrelativedistancesfromfirsticedataincludingIUP40%concentrationisolines.
Seaiceextentofmostofavailabledatasourcesdelineatedtheedgeof“areatobeavoided”forvesselsofice
classlowerthanL1.
EstimatedaveragespeedofL3iceclassvesselwasfrom3.3knotstill5.2knotsatav
eragespeed5.0knots.For
L1 ice class vessel estimated average speed was from 6.5 knots till 12.1 knots at average speed 9.7 knots.
Relativestandarddeviationofaveragedspeedforbothiceclassvesselswasequal18%.Thehighestrelative
deviationswerefoundupto50%belowtheav
eragespeedvalue.Thehighestrelativedeviationsupwardwere
equal22%.AbovespeedsforL3andL1iceclass vesselscorresponded well with averagetechnical speed of
“NorilskSA‐15”ULAclassvesselequal12,6knots.
Theresultsoftheworkwerenotintendedtobeusedfordecisionma
kingonspot‐“on‐scene”‐duringdirect
guidingvesselinice.Theyshouldbeusefulforinitialvoyageplanningtoallowdecision‐makerstoidentifythe
best freely available data sources for considered voyage and vessel of defined ice class; to understand
advantagesandlimitationsofavailableintheinternetdatasources;toesti
matevessel’smaximalsafespeedin
encounterediceconditions,toestimatespatialdistributionandcorrelationsinbetweenvariouslevelsofseaice
concentrationandthickness.Allabovedataallowestimatevoyagetimethatis,inadditiontofuelconsumption,
basiccriterionofmaritimetrans
p
orteconomics.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 10
Number 2
June 2016
DOI:10.12716/1001.10.02.06
230
1 INTRODUCTION
Planningavoyageofashipinice‐coveredareasinthe
Arcticdiffersfromthepreparationofastandardone.
Themainthreatstoshippingarecomplex,variablein
timeandspaceiceconditions.Theymay,inextreme
cases, completely disable the voyage in the whole
route
orpartofitandpotentiallymayposeathreatto
itssafetyallthetime.
A significant number of new sources of
information characterizing the conditions for the
Arcticiceappearedinrecentyears.Theyareobtained
bymeans of satelliteremote sensing methods. Some
of them are compiled
automatically, other are
prepared with the support of highly qualified
specialists.Propertiesandformatsofthesesourcesare
verydiverse.Thesesourcesareplannedfirstandthen
analysed indetail in terms of theircompliance with
terrestrial observations. For this purpose, the results
ofvisual observationsoficecoverrecordedin
tableof
components of voyage plan, collected during the
voyage of the vesselʺHoryzont IIʺ from
Longyearbyen (78° 13ʹ N, 015° 38ʹ E) to Kinnvika
(Murchisonfjorden,80°02ʹN,18°30ʹE)ontheNorth
of Svalbard on 10th of August 2009, and from
KinnvikatoLongyearbyenon15‐16th
ofAugust2009
wereused.Routeingwasdeterminedonthebasisof
previouslyexecutedvoyage.Themapcontentsofthe
current ice conditions were not taken into account.
Thenextstepwastocompare theconsistencyofdata
betweentheselectedsources.
The results of the study should answer a few
questions:
1 What data sources of ice concentration and ice
thickness are freely available in nearly real‐time
fortheregionofinterest?
2 What is the precision of the information and
spatialdistribution provided by eachseaicedata
source?
3 Isthe scaleof iceconcentration and ice
thickness
presented by particular data source enough
detailedforpredictionofsafespeedofa vesselin
ice?
4 What is the usefulness of particular sources for
planning of route and schedule consecutively
appointedaftereachtrip?
5 Istheusefulnessofparticular seaicedatasources
thesameforeach
iceclassofvessels?
6 Could vessel determine more favourable route if
thecontentofseaicedatasourceswastakeninto
account?
7 Couldvesselavoidmovementthroughthefieldof
higherconcentrationoficefloesattheinitialstage
ofplanningtheroute?
8 Is possible to define
equation that approximates
relationship between speed of the icebreaker and
thevesselsofspecifiediceclasses?
9 Is possible to extract general relationships in
between various sea ice concentration and
thickness isolines that will be useful for initial
voyageplanning?
2 PRELIMINARYASSUMPTIONSAND
RESEARCHMETHOD
Concentrationandthickness(ageor
type)oficewere
adoptedasbasicparametersoficetochooseoptimal
route of the vessel (Arikaynen & Tsubakov 1987,
Arikaynen1990).Canadianadministrativemethodof
assessingthefeasibilityofthevesselpassageiniceis
based on ice class of the vessel,the concentration
andageofice
utilizingicenumeralmethod(Timcoat
all2005,CanadianHydraulicsCentre2003).Canadian
Ice Services provide ice charts on CIS web site for
concentration of ice pack and stage of ice
development. Russian Federation also adopted
administrative method of assessing the feasibility of
the vessel passage through particular NSR seas
(RMSR
2015).Inthiscasethecriteriaareiceclassof
vessel, period of year and ice conditions (extreme,
hard, medium and easy). AARI publishes ice
concentration maps in the summer time on ESIMO
web site. Maps of ice thickness (age) are published
duringthewintertime.
Concentration and thickness of
ice were adopted
asacriterionoficemapsevaluation.Vesselsarebuilt
accordingtotheplannedconditionsofnavigationin
ice.AARIcriterionof“ice‐free”navigationcapability
wasalsotakenintoconsiderationwhenassessingthe
abilityof the vessel with specified reinforcements of
thehullstructurefornavigationin
ice(Table1).
Table1.Capabilityof‘ice‐free’ navigation in Arctic waters
forvariousiceclassvessels(followingArikaynen,1987)
_______________________________________________
IceClassCriteriaof“ice‐free”
navigationcapability
_______________________________________________
IcebreakersorULAIcepackconcentration
withicebreaker’sassistanceCT>70‐80%
ULA(withoutNorilskIcepackconcentration
classships)CT≤70‐80%
UL,L1Icepackconcentration
CT≤40‐60%
L2,L3,L4Icepackconcentration
CT≤10‐30%
_______________________________________________
2.1 Precisionofdeterminedseaiceconditionsfromdata
sourcesderivedfromremotesensingmethods
Atfirst, compliance of the information presented on
maps derived from remote sensing methods with
visualandradarobservationsmadeonthevesselwas
verified. Then, the compliance of ice floe
concentrationedgesfromvarious
sourcesreceivedby
remote sensing methods were verified. For this
purpose were used availableonline files in JPG and
GeoTIFFrasterformatsandinGRIBandNetCDFgrid
formats as well as in Shapefile / SIGRID‐3 vector
format. The raster format maps were calibrated.
Routes of the vessel and
ice floe field boundaries
obtained from visual and radar observations have
beensavedinShapefileformat.Thisallowedthedata
contained in all files to be visualized on a single
screeninageoreferencedsystem.
Displaying all examined maps from remote
sensingandobservedicefloefieldboundariesfound
by the
vessel on a single screen was designed to
facilitate the comparison of results from different
sourcesofinformationandtoincreasetheaccuracyof
231
thepositionandparametersoftheicecover.Onthis
basis,itwasintendedtodeterminewhichsourcesof
information more accurately visualize the actual
limitsoficefloeconcentrationfieldsastothevalueof
concentration, position and spatial distribution. In
this way it was intended to determine which
files
(maps) are best suited on board of conventional
vessel,non‐conventional vessel, a yacht or a boat or
ashore in the owner’s officeor planner’s office in
voyageplanninginice‐coveredareas.
The work is a scientific analysis. That is why
sources of information were not divided into
the
official (derived from authorized nautical providers)
andunofficial (for scientific climateresearch).Itwas
expectedthatthequalitativediversityofinformation
sourceswillresultfromthecorrectnessandaccuracy
of georeferenced files, resolution and precision of
concentration and thickness of scale used. This
diversity should also comprise the width of
filtered
band around land (omitted when making the map)
and the value added to automatic results by the
scientists(whodevelopmaps).Finally,this diversity
should verify information from remote sensing data
bymeans of visua l and radar observations made by
the author of the work that carried out during
the
voyageofthevesselintheNorthofSvalbard.
Conditions observed on board vessel were
recordedbytakingvideooftheradarscreenandby
takingpicturesofvisualviewofseasurfaceaheadof
the vessel. The most difficult ice conditions were
identified by means of recorded waypoints position,
speed of the vessel and concentration of ice floe.
Positionsandparametersofthedetectededgesofice
floe patches of higher concentration and theirs
thickness (pictures 3a, 3b) were also reconstructed.
Thespeedofthevesselintheicewasthesmaller,the
greatertheconcentrationoficefloe
was.Fullspeedof
11 knots reflected lack of ice in the vicinity (0.5‐1
Mm).Reducedspeedof6knotsindicatednavigation
in the area of ice floe concentration below 35%.
Reduced speed below3.5 knots was connected with
navigation in close proximity of ice. The speed was
below2.5
knotswhenpassingthroughthefieldofice
floeofconcentrationabove50%.
2.2 Differenceintraveltimeestimationresultingfrom
inaccuraciesofdeterminedspeedofvesselinice
Second matter raised in this work was influence of
discrepancy in between ice cover parameters
presented by data sources from remote
sensing
methodsandrealiceconditionsonestimationoftime
requiredforthevoyage.Icedatasourcesfromremote
sensing may serve for initial voyage planning,
includingspeedandtimerequiredtocompletewhole
voyage.
The IMO included vessel speed related to
individual parameters of ice conditions in Ice
Passport.These
dataareapproximateandsupportthe
decisionsofthevessel’scaptain.Ifthevesseldoesnot
have Ice Certificate (Ice Passport), it is necessary to
determine the maximum safe speed as a function of
ice conditions. This issue can be solved in an
approximate way. Two parameters were used to
determine the speed of the vessel. These are the
concentration and thickness of ice – the most
frequently available data.Availability of these
parameters allows to use Arikaynen nomogram
(1990).Thisnomogramisusedtoestimatethespeed
of the vessel (the icebreaker) in the Russian Arctic.
Mathematical equation was developed
for more
precise and moreconvenient computing of speed of
the vessel in the ice instead of using Arikaynen
nomogram. First, the speed, concentration and
thicknessoftheiceonanomogramstoredinatable
in a text file. So summarized data were analyzed
searching three‐dimensional data nearest
approximation method of least squares using
“TableCurve 3D” software.At first, searched for
mathematicalformulathatallowsdirectcalculationin
MSExcelspreadsheet.Secondly, searchedforathree‐
dimensional mapping, which will be the most
coincidentwiththespeeddistributionforzerovalues
forconcentrationoficeandthemostcoincident
with
thespeeddistributionforzerovaluesoficethickness.
Itwaschosenequationforthetopposition(rank)that
mettherequirementslistedabove(Equation1).
22
i
Vabxcydxey fxy
(1)
where V
i ꞊ speed of the icebreaker in knots; x ꞊
concentrationoficefloeinpercent;y꞊thicknessofice
in meters; and coefficients a ꞊ 22.638294; b ꞊
0.061043651;c꞊−0.025492605;d꞊−0.00094047619;e꞊
0.00011634199;f꞊−0.0010144048.
Parameters of transformation are as follow: r
2
꞊
0.99056544,DegreeofFreedomAdjustedr
2
꞊0.98936102,
Fit Standard Error ꞊ 0.5920998, F‐statistic ꞊ 1007.9351.
The highest relative values of residuals are equal
67.57215, 12.740919 and 19.842322 % (for
concentration꞊ 100%and thickness 180 cm, 160 and
140 cm respectively). Due to low absolute values of
speedatthesepoints,theabsolutevalue
ofresiduals
is also low like at other points. They are far away
fromconcentrationandthicknessallowedforvessels
oflowiceclassL4tillL1(RMRS2015).Twelvedata
pointsareintherange9.097–4.211%.Nextonesare
in the range between 3.890 and 0.035 %.
For
comparisonpurposes, thetransformationparameters
for equation of the highest position named
„ChebyshevX,YBivariantePolynominalOrder5”are
asfollow:r
2
꞊0.99827402,DegreeofFreedomAdjustedr
2
꞊0.99714135,FitStandardError꞊0.30543242,F‐statistic
꞊954.33037.Thehighestvaluesofresidualsareequal
13.36013%and11.331476%.Nextonesdonotexceed
value of 3.547791 %. Based on a comparison of
transformation parametersfor both models assumed
that Equation 1 accurately reflects the Arikaynen
(1990)nomogram.
232
Figure1. Surface‐fit graph of ice floe concentration and
thicknessandtechnicalspeedofthevesselin.Developedby
authorbasedonArikaynennomogram(1990).
Table2.Relationshipinbetweeniceclassofvessels,icefloe
concentration, ice thickness and speed correction factor F.
DevelopedbyauthorbasedonRMRS
2015andEquation1.
______________________________________________
Iceclass Concentration Thickness FactorF
___________ _____________________
[%] [cm]‐‐‐
______________________________________________
Ice1(L4) 60400.25
Ice1(L4) 100 350.20
Ice2(L3) 60550.27
Ice2(L3) 100 500.26
Ice3(L2) 60700.29
Ice3(L2) 100 650.26
Arc4(L1) 70800.52
Arc5(UL) 701000.58
Arc6901300.68
Arc7(ULA) 901702.00
______________________________________________
Todeterminethespeedofvesselsoflowericeclasses
onthebasisofArikaynennomogramshouldbeused
speed correcting factor F. Value of the factor F
dependsonvessel’siceclass,concentrationoficefloe
andthicknessofice.Itwasdeterminedvalueofspeed
correctingfactorF (Table
2)following rulesincluded
in RMRS (2015). Value of factor F is of clearly
different range for vessels of low ice class (L4 – L2)
and vessels of medium ice class (L1 – ULA). The
technical speed of vessel of lower ice class can
thereforebeestimatedfromEquation2.
Itwasfound
relativelyhighvalueoffactorFforULAclassvessels
due to unknown reason. Therefore assumed ULA
classdatapresentedinTable1tobeunreliable.
Figure2.Speedcorrectingfactorforvariousiceclassvessels
ti
VFV (2)
whereV
t꞊technicalspeedofvessel;Vi꞊speedofthe
icebreaker according to Equation 1; F ꞊ speed
correctingfactor.
3 CHARACTERISTICSOFTHEDATASOURCES
USEDINTHESTUDY
3.1 TheNISmapsoficeconcentrationinrasterJPG
formatwithgeographiccoordinates
The producer of these maps is the Norwegian Ice
Service(met.no).The
mapsaredevelopedonthebasis
of SAR images of European and Canadian
RADARSATandENVISATsatellitesataresolutionof
75‐150 meters. Spatial resolution of these charts is
1.000 m (NIS, http://polarview.met.no/documenta‐
tion.html).Inthiswaytheyallowdeterminationofice
conditions in the fjords and straits which have
a
width of a few kilometres only. The files adopt a
standard name c_map3.jpg. Examined files were
downloaded from the website http://polarview.‐
met.no/.Thescaleoficeconcentrationisdiscreteand
includesthefollowinginformation:OpenWater(CT=
0‐10%),VeryOpenDriftice(CT=10‐40%),Open
Drift
ice(CT=40‐70%),closeDriftice(CT=70‐90%),Very
CloseDriftice(CT=90‐100%),Fastice.
3.2 TheNICvectormapsoftheiceconcentration,iceage
andfloesizeinPDForShapefileformat
Thesemaps areactually discontinued.The producer
ofthese
mapswastheUSNational/NavalIceCenter.
Examined files were downloaded from the website
http://www.natice.noaa.gov/products/
weekly_products.html and tab “Barents Sea NW”.
ThesemapsareavailableinvectorPDFformat(files
named barnwYYMMDDcolor.PDF with plotted
geographiccoordinates) orinvectorShapefileformat
(filenamedbarnwYYMMDD.zipwhichcontainsSHP,
DBF,
SHX, and PRJ files). The files contained
particular data on weekly or bi‐weekly basis. They
represent the ice conditions for the week in which
they were published.Data for the analyses went
back96hoursfromwhentheywerecompleted.They
were dated with the week they were published.
Additional
information included in the scale
determined:Fastice,Iceshelf,Undefined.Theywere
based on ananalysis and integrationof all available
data on ice conditions, including weather and
oceanographicinformation, visual observations from
shore, ship and aircraft, airborne radar, satellite
imagery (RADARSAT, ENVISAT, MODIS, and
GMM) and climatological information.
These
products were mainly used for climate analysis,
climate change studies and as input to the Global
DigitalSeaIceDataBank(GDSIDB)buttheycanalso
provide ice information to marine community to
enhance the safety and the efficiency of marine
operationsinicecoveredwaters.
3.3 TheAARImaps
ofconcentrations,ageandofice
formsinvectorShapefileformat
Theproducer ofthese maps isthe Ice Center AARI.
Theyarecompiledonthebasisofsatelliteinformation
(inthevisible, infraredandradarbands)andreports
fromthe Arcticand coastalstations same likeships.
Thedata
arecollectedduringthe period of2‐5 days
andafteraveragingareissuedeveryThursdaywhich
is the reference date. An example name of file is
aari_bar_YYYYMMDD_pl_a.ZIP (which contains
233
SHP,DBF,SHX,PRJfiles)elaboratedfortheBarents
Sea.Mapsofconcentration,ageandformsof ice for
the Arctic Ocean in vector SIGRID‐3 format with a
sample name aari_arc_YYYYMM‐DD_pl_a.ZIP
(whichcontainsSHP,DBF,SHX,PRJfiles) aretaken
into account as equivalent maps. Examined files
downloaded
from the website
http://www.aari.ru/projects/ecimo/index.php?im=10‐
0. Scale of the map is 1: 5,000,000 (adopted on the
basisofitsrasterequivalent).Itshouldbenotedthat
the raster equivalent map for aari_arc_YYYY‐
MMDD_pl_a.ZIP file is drawn up on a scale of 1:
10,000,000.
3.4 TheIUPmapsoftheconcentrationof
iceinraster
GeoTIFFformat
The producer of these maps is the Institute of
Environmental Physics, University of Bremen. The
mapsaredevelopedonthebasisofAMSR‐Eimages
(currently AMSR2) using the ASI algorithm. The
resolutionofthesemapsisequalto3.125meters.An
example name of
file is asi‐n3125‐YYYYMMDD.tif.
The examined files were downloaded from the
website
http://iup.physik.unibrmen.de:8084/amsredata/‐
asi_daygrid_swath/l1a/n3125/.Thescaleofvisualized
ice concentration is available on website
http://iup.physik.uni‐brmen.de:8084/amsredata/asi_‐
daygrid_swath/l1a/n3125/2009/aug/Svalbard/asi‐n3‐
125‐0090810_nic.png and on website http://iup.‐
physik.uni‐brmen.de:8084/amsredata/asi_daygrid_‐
swath/l1a/n3125/README.TXT. Colours of the scale
reflectincrementsofconcentrationforevery10%fora
valuebetween0and80%andforevery5%ofvalues
between 80 and 100%. Global Mapper software
displaysdigitalvalue incrementsof concentration of
0.5%.However,theunitofthedisplayedparameteris
notdisplayed.
3.5 TheNIC“dailyproducts”mapsoftheMIZice
concentrationscaleinvector
Shapefileformat
TheproducerofthesemapsistheNationalIceCenter
(US). They are compiled from a variety of sources
with a resolution better than 50 meters per pixel.
Sourcesofinformationinclude(butarenotlimitedto)
ENVISAT, DMSP OLS, AVHRR i RADARSAT
(http://www.natice.noaa.gov/ products/‐
daily_products.html).TheNICanalysts
carry outthe
necessaryinterpretation ofimagesthat improvesthe
valueofthesesourcesforthecorrectidentificationof
theextentoftheiceedges.Anexamplenameoffiles
isnic_mizYYYYDDDnc_pl_a.zip(whichincludeSHP,
DBF, SHX, PRJ files) drawn upfor the entire Arctic
Ocean.Examined files were downloaded
from the
website http://www.natice.noaa.‐
gov/products/daily_‐ products.html and tab “MIZ
Shape”.Thescaleoficeconcentrationisavailableon
website http://www.natice.noaa.gov/produts/pro‐
ducts_on_demand.html. Field CT81 means
concentrationabove 80%, CT18 (MariginalIce Zone)
means concentration between 18% and 80%, “Open
water”meansconcentrationoficefloefromzeroto
17%.
MIZ maps issued
by NIC (products on demand)
on the concentration of ice for the Arctic Ocean in
vectorShapefileformatshowidenticaledgelines.An
example name of files is arctic_daily_MMDDYYYY.
Examined files were downloaded from the website
http://www.natice.‐
noaa.gov/products/products_on_demand.html.
Information concerning these files is consistent with
the data described in the
related files
nic_mizYYYYDDD‐nc_pl_a.zip. The research made
useofnic_miz‐YYYYDDDnc_pl_a.zipfiles.
3.6 TheNCEPmapsoficeconcentrationingriddedGRIB
formatinaresolutionof5minutesofarc
The producers of these maps are the NWS, NOAA,
NCEP,NOMADS.Spatialresolutionofthesemapsis
5’oflatitude
by5’oflongitude(geographicalgreed).
Examined files were downloaded from the website
ftp://polar.ncep.noaa.gov/cdas/archive/. An example
name of files is ice5min.YYYYMM.grb. This file
contains particular data for each day of the month.
Thescaleoficefloeconcentrationiscontinuousinthe
range between 0 and 100% with increments of
one
percent. Additional scale includes the following
information:Land, Weather, Bad data, Coast, No
data (Grumbine R, 1996, ftp://polar.ncep.‐
noaa.gov/pub‐/pub/mmab/papers/ssmi120.ps.gz).
3.7 TheIFREMERmapsoficeconcentrationingridded
NetCDFformatwithoutgeographicalcoordinates
plotted
The producer of these maps is the CERSAT that is
partofIFREMER.They
arecompiledonthebasisof
satellite SSMI and QUIKSSCAT images. Spatial
resolutionofthesechartsis12,500meters(Erzatyand
others, 2007). An example name of file is
YYYYMMDD.nc. Examined files were downloaded
from the website ftp://ftp.ifremer.fr/ifremer/cersat‐
/products/gridded/psi‐concentration/data/arctic/daily/
netcdf/2009/. In order to eliminate the pixels
associated with the
land, grid masks have been
enlarged up to two pixels (25 miles) away from the
land.Inconnectionwiththeuseofweatherfilter,an
areaconsideredtobefreeoficeisdeterminedbythe
15% ice concentration limit. The scale of ice floe
concentration is continuous in the range
between 0
and100%.
3.8 TheNICmapsoftheseaiceextentandseaiceedge
boundaryinvectorShapefileformat
TheproduceroftheseMASIEmapsistheNIC.These
charts use a wide variety of data sources such as
MODIS, AVHRR‐VIS, GOES, SEVIRI, MTSAT,
AMSR‐E,
SSM/I, AMSU, SAR imagery from
RADARSAT‐2, ERS‐2, ALOS, PALSAR, ASAR. The
ice charts and ice edge products from ice charting
agencies in the US, Canada, Norway, Denmark,
Russia, Germany, Sweden and Japan also serve as
data sources in the absence of direct satellite data.
These charts are constructed by
analysts trained in
remote sensing imagery interpretation and sea ice
climatology.Spatialresolutionofthesechartsis4km.
An example name of file is masie_ice_r00‐
234
_v01_YYYYDDDD_4km.ZIP (containing SHP, SHX,
DBF and PRJ files).Examined files were
downloaded from the website http://nsidc.org/data/‐
docs/noaa/g02186_masie/index.html. The analysts
integrate all data sources for the best estimate of
spatialcoverageoficecover.Acellisconsideredice
covered if more than 40 percent of the 4 km cell is
covered with ice. This is regardless of the ice
thicknessoricetype.Itisworthmentioningthatthe
dailyiceedgeproductisusedtowarnnavigatorsand
others in the Arctic where ice exists or is likely to
format any concentration. The primary users of the
ice
charts and ice edge products are marine
transportationinterests.TheinputproductforMASIE
is IMS product that is designed primarily for
modellers. It is produced relatively consistently in
comparison with chart and edge products. It also
benefitsfromthesamecarefulmanualanalysisthatis
usedforchartandedge
products.
3.9 TheOSISAFmapsoficeconcentrationingridded
NetCDFformatwithgeographicalcoordinates
TheproducerofthesemapsistheEUMETSATOcean
And Sea Ice Satellite Application Facility,High
LatitudeCentre(osisaf.met.no).Isbeingimplemented
byaconsortiumCDOPestablishedbyMeteo‐France,
as managing authority. Implementing bodies
are:
Met.no (Norway), DMI (Denmark), IFREMER
(France),KNMI(Holland) andSMHI(Sweden).These
mapsaredevelopedwithEUMETSATsatelliteimages
on the basis of SAF program. The sea ice
concentration product uses SSMIS data. Spatial
resolutionofthesemapsis10,000meters.Anexample
name of file is ice_conc_‐ nh_polstere‐
100_multi_YYYYMMDDHH00.nc.
Examined files
were downloaded from the website
ftp://osisaf.met.no/archive/ice/conc/2009/08/.Thelimit
betweenwaterandopendrifticeisdefinedtobe35%
ice concentration. Scale of ice floe concentration
continuous in range of 0 to 100%. Additional
informationofscaleinclude:Overland,Unclassified
or No data. They are described on
web site
http://osisaf.met.no/docs/osisaf_ss2_pum_ice‐conc‐
edge‐type.pdf (Eastwood 2014). It must be
highlighted,thattheonlynavigationicechartsbased
on subjective interpretation of high resolution SAR,
MODISandAVHRR dataareusedintheevaluation
oftheOSISAFproducts.
The same information on ice floe concentration
contain gridded GRIB type
files named
ice_conc_nh_201105211200.grb.gz of same producer.
Forthisreason,theywerenotanalysedinthework.
3.10 TheOSISAFmapsoficeconcentrationingridded
NetCDFformatinsimlifiedscalewithgeographical
TheproducerofthesemapsistheEUMETSATOcean
And Sea Ice Satellite Application Facility,High
Latitude Centre
(osisaf.met.no). Is being im‐
plemented by a consortium CDOP established by
Meteo‐France, as managing authority. Implementing
bodies are: Met.no (Norway), DMI (Denmark),
IFREMER (France), KNMI (Holland) and SMHI
(Sweden). Multi sensor methods with a Bayesian
approachisusedtocombineSSMISandASCATdata
for ice concentration simplified (edge)
classification.
Spatialresolutionofthesemapsis10.000meters.An
example name of file is ice_edge_nh_‐ polstere‐
100_multi_YYYYMMDDHH00.nc. Examined files
were downloaded from the website
ftp://osisaf.met.no/archive/ice/edge/2009/08/. The li‐
mitbetweenwaterandopendrifticeisdefinedtobe
35% ice concentration. The limit between open drift
ice and close drift/very
close drift ice is defined
around 70 % ice concentration.Thus defined,
simplifiedscaleMIZincludesthenotionsof:Icefree
(CT=0‐35%),Openice(CT=35‐70%),Closedice(CT
= 70‐100%). Additional information of scale include:
Over land, Unclassified or No data (OSISAF 2009).
They are described on web site
http://osisaf.met.no/docs/osisaf_ss2_pum_ice‐conc‐
edge‐type.pdf (Eastwood 2014). It must be
highlighted,thattheonlynavigationicechartsbased
on subjective interpretation of high resolution SAR,
MODISandAVHRR dataareusedintheevaluation
oftheOSISAFproducts.
The same information on ice floe concentration
contain gridded GRIB type files named
ice_edge_nh_201105211200.grb.gzofsameproduc‐er.
Forthisreason,theywerenotanalysedinthework.
3.11 TheOSISAFmapsoficetypeingriddedNetCDF
formatwithgeographicalcoordinates
TheproducerofthesemapsistheEUMETSATOcean
And Sea Ice Satellite Application Facility,
High
Latitude Centre (osisaf.met.no). Is being im‐
plemented by a consortium CDOP established by
Meteo‐France, as managing authority. Implementing
bodies are: Met.no (Norway), DMI (Denmark),
IFREMER (France), KNMI (Holland) and SMHI
(Sweden). They are developed from EUMETSAT
satellite images. An example name of file is
ice_type_nh_polstere‐100_multi_YYYYMMDDH‐
H00.nc. Examined files
were downloaded from the
websiteftp://osisaf.met.no/archive/ice/type/2009/08.
They are described on web site http://osisaf.met.no‐
/docs/osisaf_ss2_pum_ice‐conc‐edge‐type.pdf
(Eastwood1014)).
Sea ice data are daily means centered for time
moment of 12:00 UTC (noon). Spatial resolution of
thesechartsis10.000meters.Thelimitofdataisthe
limitinbetween
waterandopendrifticeanddefined
to be 35% ice concentration (OSISAF 2009). Multi
sensormethodswithaBayesianapproachisusedto
combine SSMIS and ASCAT data for ice type
classification. It must be highlighted, that the only
navigation ice charts based on subjective
interpretation of high resolution SAR,
MODIS and
AVHRR data by skilled analysts are used in the
evaluation of all OSI SAF products (concentration,
edge and type). The map identify following classes:
first‐year,multi‐yearseaiceand“uncertain”.During
summer period from June to September, when the
first‐yearicedecreasesorbecomesmulti‐
yearice, the
distinction between ice types is difficult due to ice
melting(wet ice and water on the ice). In case no
information on ice type in the data, the ice type is
classifiedas“uncertain”.
False ice filtering is implemented by setting all
gridpointswithtemperatureon2
meterslevel>8.0°C
235
to open water. To avoid the improper removal of
extreme ice extents, the NSIDC climatological
maximum of sea ice edgeis extended towards open
waterby50km.Thisseaiceedge(determinedbythe
15%iceconcentrationcontour)fromthedaybefore,
is expanded towards open water by
100 km and
added.
The same information on ice floe concentration
contain gridded GRIB type files named
ice_type_nh_201105211200.grb.gz of same produc‐er.
Forthisreason,theywerenotanalysedinthework.
3.12 TheNSIDC‐CCARmapsofseaiceageinrasterGIF
format
Data were originally provided by
Mark Tschudi,
CCAR, University of Colorado, UCB 431, Boulder,
Colorado,USA,providedviaStefanKern,Integrated
Climate Data Center (ICDC, http://icdc.zmaw.‐de),
University of Hamburg, Hamburg, Germany. They
are described on web page http://icdc.‐
zmaw.de/seaiceage_arctic.html?&L=1 and http://n‐
sidc.org/data/docs/daac/nsidc0611‐sea‐ice‐age/#de‐
rivtechnique(attempt15.03.2015).Examined file was
namedage2009_33.GIF.Spatialresolution
ofthegrid
was12.5km.Seaiceagedataareweeklymeans.
It was assumed the age of ice from 1 till 5 years
representmeanthicknessofice1.49m,2.02m,2.28m,
2.47mand2.68m(Maslanikatall.2007).Thechanges
in age and
thickness in the period 1997‐2007 reflect
lossoficeintheChukchiandBeaufortseasearlierin
thisperiod,combinedwithlossesintheEastSiberian
Sea during the last 4 years. Over that 10 years,
thicknessassociatedwithiceagehasincreasedinthe
LaptevSea, the Fram and
the Nansen basins, which
were previously regions of ice loss (from the late
1980stillmid1990s).
Theseaiceagedatawereestimatedbyusingdata
fromsatellitepassivemicrowaveinstruments(SMMR,
SSMI, SSMIS), drifting buoys (IAPB) and a weather
model (NCEP/NCAR/CDAS). AVHRR data were
used in 2014 also.
The formation, movement and
disappearance of sea ice was observed using these
data. Same in turn was used to estimate ice age
(Maslaniketal.2007).
More detailed, sea ice concentration and sea ice
drift were used to investigate sea ice drift. Sea ice
extentwascalculatedforeveryweek.Only
gridcells
withatleast40%ofseaiceconcentrationwereusedin
the computation to minimize inclusion of artefacts.
Largest uncertainties to be expected during melt
periodandintheMarginalIceZonewhenandwhere
sea ice concentration and drift have the largest
uncertainties.
Eachofabovementioned
gridcellsweretreatedas
particlewhichmovesaccording totheweeklyseaice
drift. The position of that cell is tracked for every
week and the number of weeks was counted. Every
year in between week 37 and 38 (September), upon
commence of freezing conditions the age of still
existing
gridcellsisroundeduptothesuccessivefull
year. To be noted, first‐year sea ice means in the
currentwinter, second‐yearseaicehassurvivedone
melting season, third‐year sea ice has survived two
melting seasons, and so on. No minimum thickness
norrangeofeach
agethicknessnordecayoficewere
takenintoconsiderationbytheauthorduringcurrent
analysisofthework.
4 VISUALOBSERVATIONS
In August 2009, the shipʺHorizon IIʺ performed a
returnvoyagefromLongyearbyentoKinnvikawithin
the ongoing project IPY‐58 KINNVIKA and special
project111/IPY/2007/01.The hullof
thevessel meets
the criteria for ice class L1. Due to the lower main
enginepowertheiceclassofthevesselisreducedto
L2.Duringthisvoyagevisualandradarobservations
of hydro‐meteorological and ice conditions were
made, as well as the records of ship motion
parameters
from safety of navigation point of view.
These conditions documented through photographs
andvideosofthevessel’ssurroundingsandtheradar
screen. The identified parameters are presented
separately in the tables for the voyage from
Longyearbyen to Kinnvika (Table 3) and for the
voyage from Kinnvika to Longyearbyen (Table 4).
High
valuesofconcentrationarerelatedtotheplaces
wherethevesselpassedthroughorpassedinvicinity
oficeedge.Threelocationsofhigherconcentrationof
icefloewerefoundonthewaytoKinnvika.Onlyone
place was found during way back. The edges of a
higherconcentrationof
icehadsequentiallyassigned
name,dateandtime:Edge‐1‐2009.08.1012:00UTC,
Edge‐2‐2009.08.10 13:25 UTC, Edge‐3‐2009.08.10
15:45UTCandEdge‐42009.08.1414:30UTC.Foreach
oftheseplacessketchoftheicefloeedgewasmade.
TheywerethenstoredinaShapefilefile.The
spatial
distribution of the observed ice edge and
implementedvesselroutesareshowninFigure3.
The sea ice thickness also was taken into
consideration. Ice floe freeboard in vicinity of the
vessel evaluated equal normally from 10 cmto 20
cmwithinclusionsofhummockedfloewithaverage
freeboard
of50cm.Itwassameatthelimitsoficefloe
fields Edge‐1 to Edge‐4. Only in exceptional cases
foundinclusionsofhummocksreachedupto80cm.
There was found higher ice floe freeboard at the
centre of analysed ice floe fields and inthe ice Floe
fields far away North from the route of the vessel.
Following above observations the sea ice floe
thickness(high)wasestimatedequalfrom36to72cm
withinclusionsofhummocked ice floe180cm high,
inexceptionalcases288cm.
Table3.VoyageplantablefromLongyearbyentoKinnvika
_______________________________________________
Way‐Long. Lat. Speed Concentration Floesize
PointE[°] N[°] [knots] [%][meters]
_______________________________________________
22 80.1405 14.1171 11.1 00
23 80.1475 14.3073 11.1 70(Edge‐1) 110
24 80.1285 14.4828 11.1 40(Edge‐1) 70
25 80.1285 14.5555 11.1 30(Edge‐1) 70
26 80.1295 14.8633 11.0 20(Edge‐1) 110
27 80.1208 15.0516 11.1 170
28 80.1298 16.5333 11.2 00
29
80.0391 17.4273 8.4170
30 80.0310 17.5203 5.170(vesselout 110
ofEdge‐2)
31 80.0308 17.5750 9.070(vesselout 110
ofEdge‐2)
32 80.0096 17.6745 10.9 5(vesselout 20
236
ofEdge‐2)
33 80.8333 17.7133 11.1 40(vesselout 90
ofEdge‐2)
34 80.0053 17.7190 8.7140
35 80.0053 17.7461 10.4 140
36 80.0048 17.8013 5.1540
37 80.0103 17.8558 1.860(Edge‐3) 70
38 80.0130 17.8851 3.260(Edge‐3) 70
39 80.0096
17.8920 1.340(Edge‐3) 70
40 80.0103 18.0640 3.140(Edge‐3) 70
41 80.0156 18.0800 1.440(Edge‐3) 70
42 80.0135 18.1215 0.540(Edge‐3) 70
43 80.0148 18.1323 1.350(Edge‐3) 54
44 80.0168 18.1531 3.440(Edge‐3) 50
45 80.0233 18.1648 1.5
30(Edge‐3) 50
_______________________________________________
Table4.VoyageplantablefromKinnvikatoLongyearbyen
_______________________________________________
Way‐Long. Lat. Speed ConcentrationFloesize
PointE[°] N[°] [knots] [%][meters]
_______________________________________________
1 18.2007 80.0335 6.0250
2 18.1229 80.0130 11.3 433
3 18.0283 80.0093 11.3 433
4 17.8818 80.0117 11.3 455
5 17.7750 80.0075 11.3 440
6 16.4837 80.1311 11.3 133
7 15.4168 80.1260 11.3 00
8 15.1554 80.0843 11.3 25(Edge‐4) 33
9
15.0587 80.0910 10.4 60(Edge‐4) 90
10 15.0139 80.0941 4.065(Edge‐4) 83
11 14.9870 80.0965 11.0 250
12 14.9215 80.1036 11.0 250
13 14.8945 80.1069 6.0270
14 14.8624 80.1093 1.2670
15 14.8329 80.1115 8.2270
16 14.7701 80.1148 11.3 1
50
17 14.7392 80.1165 11.3 150
18 14.6918 80.1180 11.3 170
19 14.5586 80.1205 11.3 150
20 14.3460 80.1222 11.3 150
21 14.0571 80.1206 11.3 150
22 13.9682 80.1159 11.3 150
_______________________________________________
Figure3. The vesselʹs routes North of Svalbard and
observed ice floe edges: a – route towards Kinnvika, b –
route towards Longyearbyen, c – area covered by the
research.Symbols:
─►─routetowardsKinnvika,◄─route
towards Longyearbyen,
▬▬▬ edge of ice pack. Ice floe
edges marked respectively (Edge‐1, Edge‐2, Edge‐3, Edge‐
4).
5 DISCUSSIONOFRESULTS
5.1 Verificationofinformationfromremotesensingusing
visualobservations
Only few data sources were in vicinity of vessel‘s
route.Most ofthem wereout ofsight. However the
characteristic shapes of the edge of all sources were
analysed. Searched correlations (or lack of
correlations)anddistances
inbetweenpatterns.
5.1.1 NISmapsoftheconcentrationoficeinrasterJPG
formatwithgeographiccoordinatesplotted
Map named c_map3.jpg was assessed. The exact
timeoftheNISmapwasnotspecified.Thereforethe
date indicated on the map equivalent sarmap2.jpg‐
2009.08.1008:47UTCwasadopted.Theice
edge(CT=
40‐70%)shownontheNISmapisobservedfromthe
vessel offset of ice edge (Edge‐1) of 4.0 Nm in the
direction 000°. The map did not demonstrate the
existence of an ice floe wedges with a width of less
than 1.0Nm. The ice edge
(CT = 40‐70%) shown on
theNISmapisobservedfromthevesseloffsetofice
edge(Edge‐2)of4.4Nminthedirection046°.Theice
edge (CT = 40‐70%) shown on the NIS map is
observedfromthevesseloffsetoficeedge(Edge‐3)
of
2.6 Nm in the direction 113°. The map did not
demonstratetheexistenceofanicefloewedgeswitha
widthoflessthan0.3Nm. It seems thatNISmapis
offset,inrelationtoallthreeobservedfromthevessel,
oficefloesedgesofhigherconcentrationsin
different
directions. Average offset distance was 3.7Nm. The
timedifferencebetweensuccessiveiceedgesabeamof
thevesselwas1.4hoursand2.3hours.Theyshowed
an increasing delay in relation to the publication of
theNISmapby3.2hours,4.6hoursand6.9hours.
Map named c_map3 dated
2009.08.14 14 06:30
UTC used for comparison with the edge of the ice
floes observed from the vessel (Edge‐4) was dated
2009.08.1422:30UTC.Theiceedge(CT=40‐70%)and
fieldofice floe ofconcentrationCT =10‐40% thatis
shown on the NIS map were
offsetsfrom the vessel
observed ice edge of the concentration of 25‐60%
(Edge‐4) of 2.4 Nm in the direction 042°. It seemed
thatthescaleoftheiceconcentrationoftheNISmap
depicted accurately the spatial distribution of ice
observed from the ship. The undetected field of
ice
floeof higherconcentration witha widthof 1.5 Nm
arepresentedinFigure4.Itwasincludedinsidethe
field with a concentration of CT = 10‐40%. It was
assumed that NIS map in an accurate way depicted
thestateof theicecover at thetime of
reference for
thesourcedata.
5.1.2 VectorNICmapoftheiceconcentration,iceage
andfloesizeinPDFformat
Thesemapswerepublishedatintervalsof14days.
The closest map corresponding to the observation
date was ice edge map dated 2009.08.17. For this
reason,onlyEdge‐4
referencedtothedate2009.08.14
22:30UTCwas analysed.Thetimedifferencewas49.5
hours(equal to2.06 days).Mapof 2009.08.03 (mean
time of source data dating 2009.08.04 0:00 UTC)
showed a general ice drift in the direction of 253 °
withanaveragedistanceof20Nminseven
days.
237
Figure4.LocationoficecoveraccordingtoNISc ‐map3map
dated2009.08.1406:30UTCandicefloeedgeobservedfrom
ship
Map of 2009.08.17 (average time of data source
dating 0:00 UTC) showed a general ice drift in the
directionof245°atanaveragespeedof35Nautical
milesinsevendays.Thismeansdrifticeequalto10
Nauticalmiles of the time difference betweenvisual
observations and the
dating of the ice edge map
source data. After moving, the ice edge position on
the map of a concentration of 40‐60% for estimated
resultant drift ice noted the consistency of data in
comparisonwiththeobservedEdge‐4(Figure5).
Figure5. Locations of ice cover according to NIC
barnw090817color map and ice floe edge observed from
shipafterapproximate adjustments of time difference and
driftoficecover.
It was assumed that the NIC map accurately
reflectsthestateoftheicecoverforreferencetimeof
thedatasource.Itwasassumedthatremotesensing
methoddidnotdetecttheicepackfieldwithawidth
of less than 1.5 Nm.When only the information
abouttheice
driftfromthemapdated2009.08.17was
considered, the position of the edge of the ice floe
wouldbeshifted16Nminthedirectionof130°with
respecttotheobservedicefloeedgefromthevessel.
5.1.3 AARImapsofconcentration,ageandiceformsin
vector
Shapefileformat
Theaari_bar_20090811_pl_a(SHP,SHX,DBF,PRJ)
filewas usedforcomparisonwiththeobservedfrom
thevesselicefloefieldedgesdatedrespectivelyEdge‐
1 (2009.08.10 12:00 UTC), Edge‐2 (2009.08.10 13:25
UTC) and Edge‐3 (2009.08.10 15 45 UTC. It was
assumed that the map represented ice conditions
dated 2009.08.10 12:00 UTC because it reflected the
average ice cover for the last three days. Another
assumptionwasmade thatthetimedifferenceequal
to 0‐3.75 hours is negligible. Edge‐1 field had no
equivalentontheAARImap.Theclosestedgeofthe
icefloefieldof
concentrationCT=13%onAARImap,
that was coincident with shape of the Edge‐1, was
locatedatadistanceof6Nminthedirectionof350°.
Theclosestedgeoftheicefloefieldofconcentration
CT=78%onAARImapresemblingtheshapeofthe
Edge
‐2 was found at a distance of 4 Nm in the
direction of 014°. The Edge‐3 field generally
corresponded to the position of ice floe field of
concentrationCT =13% situated ata distance of 1‐5
Nminthedirectionof090°.Itwasassumedthatthere
wasmoderateharmonyofdata.
Theaari_bar_20090818_pl_a(SHP,SHX,DBF,PRJ)
filewas usedforcomparisonwiththeobservedfrom
the vessel edge of ice floe field Edge‐4. It was
assumed that the map represented ice conditions
dated 2009.08.17 12:00 UTC because it reflected the
average ice cover for the
last three days. The time
differencewas2.56 days. Theclosest edge of theice
floefield(CT=91%)wasoffset,inrelationtotheedge
oftheiceedgeofconcentration25‐60%observedfrom
the vessel (Edge‐4) at a distance 27 Nm in the
direction of
312 °. It was assumed, therefore, that
there was no relationship between these data. Mean
offsetpositionwithrespecttotheedgeoftheicefloe
that was observed from the vessel was 10 Nautical
miles.
5.1.4 TheIUPmapsoficefloeconcentrationinraster
GeoTIFFformat
The asi‐n3125
‐20090810.TIF file was used for
comparisonwiththeobservedfromthevesselicefloe
field edges dated respectively Edge‐1 (2009.08.10
12:00UTC),Edge‐2(2009.08.1013:25UTC)andEdge‐
3 (2009.08.10 15 45 UTC. It was noted that the Geo‐
TIFFmapwasoffsetfromtheedgesofthe
icefields
andlandmasks6Nminthedirectionof120°.Itwas
found out that, after taking this offset into account,
the nearest edge of the field of concentration CT =
10%onGeoTIFFmapwascoincidentwiththeshape
of the Edge‐1 located at a distance of
17 Nm in the
directionof350°andwascoincidentwiththeshapeof
theEdge‐2atadistanceof23Nminthedirectionof
346°. At the same time the edge of ice floe field of
concentrationCT= 20‐40%consistentwiththeshape
ofthe
Edge‐3waslyingatadistanceof4Nminthe
directionof065°.Thusconfigurationoftheicefields
edgeon the IUP map was distinctiveand consistent
withtheedges oftheicefloeseenfromthevesselbut
atrelativelylargedistance.
The asi‐n3125‐20090815.TIF file
was used for
comparisonwiththeobservedfromthevesselicefloe
fieldEdge‐4dated2009.08.1510:43UTC.Itwasnoted
that this GeoTIFF map was offset from the edges of
238
theicefieldandlandmask6Nminthedirectionof
120°.Itwas foundoutthat,aftertakingthisoffsetinto
account,thenearestedgeofthefieldofconcentration
CT = 20% on GeoTIFF map was coincident with the
shapeoftheEdge‐4locatedata
distanceof34Nmin
the direction of 013°. Configuration of the ice floe
edgeonIUPmapisnotveryclear.
5.1.5 TheNICmapsoftheiceconcentrationinaMIZ
scaleinvectorShapefileformat
The nic_miz2009222nc_pl_a.zip (SHP, SHX, DBF,
PRJ) file dated 2009.08.10 was used for
comparison
withtheobservedfromthevesselicefloefieldedges
dated respectively Edge‐1 (2009.08.10 12:00 UTC),
Edge‐2(2009.08.1013:25UTC)andEdge‐3(2009.08.10
1545UTC.TheicefloefieldEdge‐1waslocatedlike
borderCT=18‐81%presentedbyMIZfile.Thislimit
was
also the beginning of the route in the area
covered by ice. The MIZ wedge of a high
concentration of ice floe shown on NIC map was
offset 4 Nm in the direction of 028° with respect to
Edge‐2. Field of Edge‐3 was found to be entirely
located
in the area of CT = 18‐81%concentration as
shown by the MIZ map. It was assumed that data
wereingeneralharmony.
Thenic_miz2009227nc_pl_a(SHP,SHX,DBF,PRJ)
file dated 2009.08.15 was used for comparison with
the observed from the vessel ice floe field Edge‐4
dated 2009.08.15 10:43 UTC.
The nearest edge of ice
(CT = 18‐81%) on NIC map passed exactly through
the area of the observed Edge‐4field. Instead of the
expected wedge with a higher concentration of ice
extended to the South this map showed the general
ice limit on NW‐SE direction. This was
consistent
withtheobserved fieldoflowice floe concentration
ontheroutefromKinnvikatotheareaofEdge‐4(see
Table3).TheclosestedgeoficefloefieldofCT>81%
concentration was offset from the observed edge of
ice of 25‐60% concentration (Edge‐4) 20
Nm in the
directionof000°.Itmightbeassumedthattherewasa
general correlation between data. However, it was
lowindetailduetothedifferentedgesconcentration
presented on map nic_miz2009227nc_pl_a and the
edgeobservedfromthevessel.
5.1.6 TheNCEPmapsoficeconcentrationingridded
GRIBformatinaresolutionof5minutesofarc
Theice5min.200908.grbfileforthedate2009.08.10
wasusedforcomparisonwiththeobservedfromthe
vessel ice floe field edges dated respectively Edge‐1
(2009.08.1012:00UTC),Edge‐2(2009.08.1013:25UTC)
and Edge‐3 (2009.08.10 15 45 UTC. Field
of ice floe
Edge‐1 was situated in the area of 40‐50%
concentration; Edge‐2 in the area of 0‐5%
concentration, Edge‐3 was located in the area of 0‐
40%shownonGRIBmap.Dataconsistencyiscorrect
for Edge‐1 and Edge‐3. However, the lack
of
continuitypresentedbytheGRIBmapraisedconcern
that the results of the comparison may be largely
random. I was assumed that there was only very
generalharmonyofdata.
Theice5min.200908.grbfileforthedate2009.08.15
wasusedforcomparisonwiththeobservedfromthe
vesselicefloefield
Edge‐4.Theclosestcorresponding
totheshapeoftheedgeoficefloeconcentrationfield
CT=25‐35%wasoffsetfromthevesselobserved25‐
60%iceedge(Edge‐4)8Nminthedirectionof013°.It
might be assumed that there was a general
consistency between
data. However, it was low in
detailduetothe different concentrationedgesbeing
on map ice5min.2009‐08.grb and the edge observed
fromthevessel.
5.1.7 TheIFREMERiceconcentrationmapsingridded
NetCDFformatwithoutgeographicalcoordinates
The20090810.ncfilewasusedforcomparisonwith
theobservedfromthevessel
icefloefieldedgesdated
respectively Edge‐1 (2009.08.10 12:00 UTC), Edge‐2
(2009.08.10 13:25 UTC) and Edge‐3 (2009.08.10 15 45
UTC.FieldoficefloeEdge‐1wasintheareaof0‐11%
concentration, Edge‐2 in the area of 11‐22%
concentration, Edge‐3 was in
the area of 11‐44%
visualisedbyNetCDFmap.Thusithasbeenassumed
that this grid map does not recognize the local
significantchangesinicefloeconcentration.
The20090815.ncfilewasusedforcomparisonwith
the observed from the vessel ice floe field Edge‐4
dated2009.08.1422:30.The
closestNetCDFmaparea
oftheCT=22‐44%concentrationcorrespondingtothe
shapeoftheicefloeedgeobservedfromthevessel25‐
60% (Edge‐4) was offset 32 Nm in the direction of
354°. It might be assumed that there was a general
consistency between data. However,
it was low in
detail due to different concentration edges being on
map 20090815.nc and the edge observed from the
vessel.
5.1.8 TheNICmapsofseaiceextentandseaicelimitin
vectorShapefileformat
The masie_ice_r00_v01_2009222_4km.ZIP (SHP,
SHX, DBF, PRJ) file dated 2009.08.10 was used for
comparisonwith
theobservedfromthevesselicefloe
field edges dated respectively Edge‐1 (2009.08.10
12:00UTC),Edge‐2(2009.08.1013:25UTC)andEdge‐
3(2009.08.101545UTC.TheshapeofMASIElinewas
notcorrelated with the observed from the vessel ice
floe edges. The closest corresponding to the
MASIE
lineoficefloeCT>40%concentrationislocatedwith
respect to the observed from the vessel 25‐60% ice
edge(Edge‐1)atadistanceof25Nminthedirection
of 003°. It might be assumed that there is no
correlationbetweenthedata.
The masie_ice_r00_v01_2009227_4km (SHP, SHX,
DBF, PRJ) file dated 2009.08.15 was used for
comparisonwiththeobservedfromthevesselicefloe
field Edge‐4. The closest MASIE line of CT > 40%
corresponding to the observed ice edge (Edge‐4) of
25‐60% concentration was offset 28 Nm in the
directionof354°.It
mightbeassumedthattherewasa
general consistency between data. However, it was
low in detail due to the different concentrations of
edgeprovidedbytheMASIEmapand ice floeedge
observedfromthevessel.
5.1.9 TheOSISAFiceconcentrationandicetypemapsin
griddedNetCDFformatwith
geographical
coordinates
The ice_conc_nh_YYYYMMDDHHMM.nc,
ice_edge_nh_YYYYMMDDHHMM.nc and ice_ ‐
239
type_nh_YYYYMMDDHHMM.nc file were used for
comparisonwiththeobservedfromthevesselicefloe
field Edge‐4 dated 2009.08.14 22:30. The closest
ice_conc_nh_YYYYMMDDHHMM.ncmapareaofthe
CT=0%concentrationcorrespondingtotheshapeof
the ice floe edge observed from the vessel 25‐60%
(Edge‐4)wasoffset
10Nminthedirectionof300°.It
might be assumed that there was a general
consistency between data. However, it was low in
detail. Thus it has been assumed that this grid map
recognizegenerallythelocalsignificantchangesinice
floeconcentration.
Theclosestice_edge_nh_YYYYMMDDHH‐MM.nc
map area
of the CT = 40% concentration
correspondingtothelineoftheicefloeedgeobserved
fromthevessel25‐60%(Edge‐4)wasoffset23Nmin
thedirectionof330°andtheCT=70%concentration
corresponding to the same was offset 32 Nm in the
direction 330°. Thus
it has been assumed that these
twogridmaps do notrecognizethe local significant
changesinicefloeconcentration.
The closest ice_type_nh_YYYYMMDDHH‐MM.nc
map area of the ambiguous type (Open Water side)
correspondingtothelineoftheicefloeedgeobserved
fromthevessel25‐60%(Edge‐4)
wasoffset19Nmin
thedirectionof330°.Thisedgedoesnotrecognisethe
local significant changes in ice floe concentration.
Same time the ambiguous type (First year ice side)
correspondingtothelineoftheicefloeedgeobserved
fromthevessel25‐60%(Edge‐4)wasoffset25
Nmin
the direction of 315°. This ambiguous edge shape
correspondedgenerallytotheshapeofEdge‐4.Thus
it has been assumed that these ambiguous edges
recognizegenerallythelocalsignificantchangesinice
floeconcentration.
Need to remember that following visual
observationsfromthevesselthesea ice
floethickness
was estimated to be equal from 36 to 72 cm with
inclusions of hummocked ice floe 180 cm high and
onlyinexceptionalcasesthehummockedicefloewas
288 cm. Following these observations was assumed
that the higher ice floe thickness at the centre of
analysed ice floe
fields and in the ice floe fields far
awayNorthfromtherouteofthevesselwereshown
onOSISAFiceagemap.Thismapnotrecognizedsea
ice floe of lower thickness especially of smaller
coveragethencellsizeandlowerconcentrationthen
70%.Thelandfilteralsowas
thelimitation.
5.1.10 TheNSIDC‐CCARiceagemapsinrasterGIF
formatwithoutgeographicalcoordinates
The age2009_33.gif file was used for comparison
withtheobservedfromthevesselicefloefieldEdge‐4
dated 2009.08.14 22:30. The closest age2009_33.gif
map areaof age data corresponding to the shape of
the
ice floe edge observed from the vessel 25‐60%
(Edge‐4)wasoffset12Nminthedirectionof315°.It
might be assumed that there was a general
consistency between data. However, it was low in
detail. Thus it has been assumed that this grid map
recognizegenerallythe
localsignificantchangesinice
floeconcentration.
The NSIDC‐CCAR ice age map shown high
volatilityofcourseandgeneralsimilarityoftheedge
patterns with other maps or observations form the
vesselintwolocationsaroundposition80°N/009°E
and80°N/015°Ealong160Nmofanalysedsea
ice
limit. The 1
st
and 2
nd
year ice age along this pattern
representedmeanthicknessofice149cmand202cm
respectively. Following visual observations from the
vesseltheseaicefloethickness(high)wasestimated
equalfrom36to72cmwithinclusionsofhummocked
ice floe 180 cm high and only in exceptional
cases
reaching 288 cm high. Following these observations
wasassumedthatthehighericefloefreeboardatthe
centre of analysed ice floe fields and in the ice floe
fieldsfarawayNorthfromtherouteofthevesselare
shown on NSIDC‐CCAR map. This map not
recognizedseaice
floeoflowerthicknessespeciallyof
smaller coverage then cell size and lower
concentration then 70%. The land filter also was the
limitation.
5.2 VerificationoficedatapresentedbyNISremote
sensingsourcemapsnamedc_map3
The first, the content of the NIC map named
barnwYYMMDDcolor and NIS map
named c_map3
was compared. The analysis included offset of ice
edgepositionontheNICmapbarnwYYMMDDcolor
described in section 5.1.1. A 30‐50% concentration
boundary on the map barnwYYMMDDcolor was
consistent with the edge of 40‐70% concentration on
c_map3map.Theconcentrationlimitsof70‐90%and
90‐100%
on the map c_map3 coincided with 50‐70%
edgeonbarnwYYMMDDcolormapand90%edgeon
barnwYYMMDDcolormapwheretheedgeof50‐70%
wasnotshownonthemap.
Theedge oftheconcentrationof81%ontheNIC
map named nic_mizYYYYDDDnc_pl_a reflected
approximately 40% concentration edge on the
NIS
map namedc_map3. The limitconcentration of 18%
on the map nic_mizYYYYDDDnc_pl_a reflected
approximately0‐10%concentrationedgeonthemap
c_map3.
Theedge oftheiceconcentrationof90(91)%on
theAARImapnamedaari_bar_20090818_pl_aclearly
reflectedtheedgeoftheconcentrationof90%onNIS
map
named c_map3. Fields with a concentration of
13‐78%ontheaari_bar_200908‐18_pl_amapreflected
10‐40% and 40‐90% concentration field on the map
c_map3.Fieldofconcentrationof40‐70%onthemap
c_map3waslyinginsidethefieldofconcentrationof
46‐78% on the map aari_bar_20090818_pl_a.
Fields
with a concentration of 78‐90% on the map
aari_bar_20090818_pl_a reflected field of
concentration of 40‐70% on the map c_map3. The
edgesof the iceconcentration of0% wereconsistent
on both maps. The edge of the ice concentration of
40% on the NIC map named
masie_ice_r00_v01_2009227_4kmmostlyreflected
the
edgeoftheconcentrationof40%onNISmapnamed
c_map3.
5.2.1 NICmapsnamedbarnwYYMMDDcolor
Theanalysisincludedoffsetoficeedgeposition on
theNICmapnamedbarnwYYMMDDcolordescribed
insection5.1..2.Theedgeoftheiceconcentrationof
81% on the NIC map named
nic_mizYYYYDDDnc_pl_a was
consistent with the
240
edge of 50‐70% and 90% on the map
barnwYYMMDDcolor where the edge of the
concentration of 50‐70% was not shown on the map
barnwYYMMDDcolor.Theedgeoftheconcentration
of 18% on the map nic_mizYYYYDDDnc_pl_a
coincided with the edge of the concentration of 50‐
70% on the map
barnwYYMMDDcolor. In this case,
theedgeof50‐70%wasthelimitofdatarelatedtosea
ice.
Fieldswithaconcentrationof46%and78%from
thelowerlimitofthefieldedgeandconcentrationof
90% as the upper limit on aari_bar_20090818_pl_a
mapswereconsistentwiththeedge
ofconcentration
of90%onthemapbarnwYYMMDDcolor.Theedgeof
the ice coverage (concentration of 0%) on the map
barnwYYMMDDcolor North of the Nordaustlandet
Island was the same as on the map
aari_bar_YYYYMMDD_pl_a but the edge of 0% on
the North and Northwest of Svalbard on the map
barnwYYMMDDcolorwas
locatedmoretotheSouth
and contained more details than
aari_bar_YYYYMMDD_pl_amap.
Theedge ofice concentrationof 40% on the NIC
map named masie_ice_r00_v01‐_2009227_4km
roughly coincided with the edge of 30‐50% on the
NIC map named barnwYYMMDDcolor. Just like in
the case of AARImaps, the edge of
the ice
concentration of 30‐50% on the map
barnwYYMMDDcolorwaslocatedmoretotheSouth
thanonthemapmasie_ice_r00_v01_2009227_4km.It
alsocontainedmoredetailsthanMASIEmap.
5.2.2 IFREMERmapsnamedYYYYMMDD
Thefieldswiththespecifiedconcentrationonthe
IFREMER map represented fairly the ice
concentration field on
the NIS map named c_map3.
Thelimitationwasthe relative largesizeof the grid
(cell) on IFREMER map. Similar difficulties for
comparison were due to lack of information in the
fieldsappearingontheIFREMERmap.
The edge of the ice concentration of 81% on the
NIC map named
nic_mizYYYYDDDnc_pl_a
approximately reflected the distribution of
concentrationfieldsof44‐78%ontheIFREMERmaps
namedYYYYMMDD.nc.However,theedgeoftheice
ontheNICmapsranparallelthroughthefieldswith
smallervaluesofconcentrationofIFREMERmaps.
The edge of the concentration of 78 (90)%on the
AARI
maps named aari_bar_YYYYMMDD_ pl_a
reflected 78% concentration field on the IFREMER
map named YYYYMMDD.nc. The edge of the
concentration of 13% on the AARI maps reflected
fields of the concentration of 33% on the IFREMER
map.
The edge of the ice concentration of 40% on the
NIC map named masie_ice_r00_v01_2009227_4km
runs
throughornearthefieldsofconcentrationof44‐
56%on the IFREMER maps. The spatial distribution
oftheseedgeswasveryconsistent.
5.2.3 NCEPmapsnamedice5min.YYYYMM
Theedge oftheconcentrationof81%ontheNIC
mapsnamednic_mizYYYYDDDnc_pl_agenerallyran
along the edge of the concentration of 40%
on the
NCEP map named ice5min.YYYYMM. There were
discrepancies. The edge of the ice on the
nic_mizYYYYDDDnc_pl_a map ran through the
lower concentration values on the NCEP map. The
edge of the concentration of 18% on the
nic_mizYYYYDDDnc_pl_a maps generally ran along
the edge of the concentration of 0 ‐20%
on the
ice5min.YYYYMMmapbuttherewasderogation.The
fieldsonbothmapswereconsistent.
Theedgeoftheconcentrationof90%ontheAARI
map named aari_bar_YYYYMMDD_pl_a mostly ran
throughthefields ofconcentration of70‐80% onthe
mapice5min.YYYYMMbuttherewasderogation.The
edgeoftheice
concentrationbelow13%ontheAARI
map edge reflected approximately edge of 20%
concentration on the NCEP map.The edges of the
concentration of 46% and 78% on the AARI map
reflected data on the NCEP map only in a very
generalway.
The edge of 40% concentration on the
NIC map
named masie_ice_r00_v01_2009227_4km mostly ran
through the fields of concentration of 40% on the
ice5min.YYYYMM map. There was derogation. In
such cases, the NCEP map showed mostly lower
concentrationvaluesthanMASIEmap.
Fields with 85% concentrationon the NCEPmap
named ice5min.YYYYMM quite accurately reflected
edge of 90% concentration
on NIS map named
c_map3. The edge of the concentration 70% on the
NCEP map was less coincident with the field of 50‐
70% concentration on NIS map. The limit of ice 0%
concentration on the NCEP map corresponded
roughly the edge of concentration of 0‐10% on NIS
map.
5.2.4 IUPmapsnamedasi‐n3125‐YYYMMDD
Theedgeof40%concentrationonNISmapnamed
c_map3 reflected roughly the fields of concentration
20%or70‐80%ontheIUPmap.Itwasnotedthatthe
edge of 0% concentration on the IUP map
correspondedtotheedgeofthe40%
concentrationon
the NIS map. The higher the concentration, the
smaller is discrepancy of position for each ice floe
concentration.
The edge of 81% concentration on the NIC map
named nic_mizYYYYDDDnc_pl_a accurately
reflected edge of 0% concentration on the IUP map
namedasi‐n3125‐YYYYMMDD.
Theedgeof90(91)
%concentrationontheAARI
map named aari_bar_YYYYMMDD_pl_a accurately
reflected fields of 80‐90% concentration on the IUP
map. The edge of 78% concentration on the AARI
map accurately reflected 10‐20% concentration field
ontheIUPmap.
The edge of 13‐46% concentration on the AARI
map took place in
areas of 0% concentration on the
IUPmap.Theedgeof40%concentrationontheNIC
map named masie_ice_r00_v01_2009227_4km mostly
reflected edge of concentrationof 0‐10% on the IUP
map.
241
5.2.5 OSISAFiceconcentrationmapsnamed
ice_conc_nh_YYYYMMDDHHMM
Thelimitofconcentration0%ontheOSISAFmaps
named ice_conc_nh_YYYYMMDDHHMM reflected
veryroughlyOpenWater(10%)limitmarkedonNIS
map named c_map3. Maximal discrepancies of
characteristiclimitslocationreachedupto16Nmin
both directions (North or South). Ice limits
of
concentration0%onOSISAFmapwerelocatedonthe
averagedistance6NmNorthfromOpenWater(10%)
limit on NIS map at a standard deviation error
around 12 Nm. There was found that the OSISAF
concentrationmapnotidentifiedicefieldsupto5Nm
wide nor rectangles
of ice fields of 10‐70%
concentration up to 12‐24 sq. Nm marked on NIS
map.
The 40% concentration limit on the OSISAF
ice_conc_nh_YYYYMMDDHHMMmapveryroughly
correspondedtocenterof40‐70%concentrationfield
markedonNISc_map3map.The40%concentration
limit on the OSISAF map was offset
average 8 Nm
South from c_map3 40‐70% field with a standard
deviation error5 Nm. The OSISAF
ice_conc_nh_YYYYMMDDHHMMmapnotidentified
icefieldsupto5Nmwidenorrectanglesoficefields
of40‐70%concentration up to15‐46 sq.Nm marked
onc_map3map.
The 40%
concentration limit on OSISAF
ice_conc_nh_YYYYMMDDHHMM map was offset
average 5 Nm North from 40‐50% concentration
limitonbarnwYYMMDDcolormapwithastandard
deviationerror7Nm.
The 40% concentration limit on OSISAF
ice_conc_nh_YYYYMMDDHHMMmapnotidentified
40‐50% concentration ice fieldsup to 14 Nm wide
norrectanglesofice
fieldsof40‐50%concentrationup
to150sq.NmontheNICbarnwYYMMDDcolormap.
5.2.6 OSISAFiceconcentrationmapsinsimplifiedscale
namedice_edge_nh_YYYYMM‐DDHH‐MM
Spatialdistribution of70% concentration limiton
the OSISAF maps named ice_edge_nh_YYYY‐
MMDDHHMMwasconsistentwiththetrendsof40%
ice concentration limit
on the IUP map named asi‐
n3125‐YYYYMMDD but 40% concentration limit on
theIUPmapranmoretotheNorthinrelationto70%
concentration limit presented on the OSISAF
ice_edge_nh_YYYYMMDDHHMMmapabout7Nm.
Spatialdistributionof40%concentrationlimitonthe
IUP map was significantly much more volatile
than
70%concentration limit on OSISAF
ice_edge_nh_YYYYMMDDHHMMmap.
The course of 70% concentration limit on the
OSISAFice_edge_nh_YYYYMMDDHHMMmapwas
also coincident with 40% concentration limit on the
NCEP map but 70% concentration limit on the
OSISAF ice_edge_nh_YYYYMMDDHHMM ran on
the average distance 2 Nm more to the North than
40% concentration limit on the NCEP map. This
relationshipseemedquiteproperlytookintoaccount
averagerealdistributionoficeconcentrations.
The 70% ice concentration limit on OSISAF map
named ice_edge_nh_YYYYMMDDHHMM ran
similarly with 81% ice concentration limit presented
ontheNICMIZmapnamednic_miz2009‐222nc_pl_a
and also a little
better with 46% (or 91%)
concentration limit presented on the AARI map
named aari_bar_YYYYMMDD_pl_a limit beginning
NWofSvalbarduptoNordaustlandetIsland.
The 70% concentration limit on OSISAF
ice_edge_nh_YYYYMMDDHHMMmaprangenerally
same way like 40% concentration limit on NIC
MASIE. Standard deviation error of both limits
locationswas
equal5Nm.
The 70% concentration limit on OSISAF
ice_edge_nh_YYYYMMDDHHMM map ran average
2 Nm South in relation to 70% concentration limit
placedonNISc_map3mapwithastandarddeviation
errorequal4Nm.
The 70% concentration limit on OSISAF
ice_edge_nh_YYYYMMDDHHMMmapranaver‐age
7NmSouthinrelation
to70‐90%concentrationlimit
ontheNICmapnamedbarnwYYMMDDcolorwith
astandarddeviationerror6Nm.
5.2.7 OSISAFiceagemapsnamedice_type‐
_nh_YYYYMMDDHHMM
The 70% concentration limit on the OSISAF
ice_edge_nh_YYYYMMDDHHMM map coincided
withthe„ambiguous”edgeofice(fromOpenWater
side) on OSISAF ice_type_nh_YYYYMMDD‐HHMM
map almost in its entirety a few minor variations in
bothdirections.
The 40% concentration limit on the OSISAF
ice_conc_nh_YYYYMMDDHHMM ran mostly in the
middle of the „ambiguous” zone of the OSISAF
ice_type_nh_YYYYMMDDHHMM map (from Open
Waterlimittill1
st
yearicelimit).
The limit of ice covered area on NSIDC‐CCAR
mapnamedageYYYY_WW coincided relativelywell
with limit of the „ambiguous” zone of the OSISAF
ice_type_nh_YYYYMMDDHHMM map (from 1st
yearicelimit).Bothmapsidentified
5.2.8 NSIDC‐CCARiceagemapsnamedage‐
YYYY_WW
The limit of ice
covered area on NSIDC‐CCAR
mapnamedageYYYY_WWcoincidedmostlywith0%
concentration limit on OSISAF ice_conc_nh_ ‐
YYYYMMDDHHMM map. However, there were
derogation.Trendsofbothlineswereconsistentover
theentirelengthofexaminedlinesfromthewestern
part of North Svalbard to the western edge of
Nordaustlandet Island despite
significant standard
deviationerrorof8Nm.Theaveragedeviationofthe
position of each line was null. This meant that
averagedlinescompletelyoverlapped.
The edge of ice age data on NSIDC‐CCAR
ageYYYY_WWmapreflectedrelativelywellthe40%
iceconcentrationlimitpatternplacedonNISc_map3
map.
TheNSIDC‐CCARiceagedatalimitwasoffset
average 13 Nm South in relation to c_map3 40%
concentration on NIS c_map3 limit with a standard
deviation 5 Nm. The NSIDC‐CCAR map not
identified40‐70%concentrationicefieldsupto5Nm
widenorrectanglesoficefieldsup
to25sq.Nmon
OSISAFice_conc_nh_YYYYMMDD‐HHMMmap.
242
TheedgeoficeagedatamarkedonNSIDC‐CCAR
map reflected relatively well 40‐50% concentration
limit being on NICmap named
barnwYYMMDDcolor. The NSIDC‐CCAR ice age
datalimitwasoffsetaverage10NmSouthinrelation
to 40‐50% concentration on NIC
barnwYYMMDDcolormap with a standard
deviation 6 Nm.Ice edge features being on NIC
barnwYYMMDDcolor map ran same to those of
NSIDC‐CCAR ice edge that were offset on
approximatedirection160°.
5.3 Spatialdistributionofanalysedlines
The next examination was related to the spatial
distributionofindividual lines inthe studiedregion
for
the 15
th
August 2009. There was analyzed the
distributionofisolinesfromthefirstboundaryofsea
ice occurrence up to the line with the highest
concentrationof icein the range from70 to 91% of
ice floe concentration. These lines were lying in
general direction 050°‐230°. Some of
them did not
show extraordinary variation from this general
direction.TheonlylinesofNISmapsnamedc_map3,
NIC maps named barnwYYMMDDcolor and IUP
maps named asi‐n3125‐YYYYMMDD shown a very
diverse course. Nearly all data sources shown high
volatility of course only in two locations around
position 80°N /
009°E and80°N / 015°E along 160
Nm of analysed sea ice edge.One of them was
identifiedbyobservationsfromthevessel.
The mean value ofstandard deviations of all
lines shown in Figure DDD was equal 8.3 Nm
irrespectiveofthedistancefromthebeginningofice.
The
standard deviation of these mean values was
equal0.85Nm.Assumeditwasverysmall value.In
step 6 (Figure DDD) occurred anomaly associated
with high volatility of course in locations around
position 80°N / 009°E. The convexity of the ice field
boundary was demonstrated well by the NSIDC‐
CCARmap
(19Nm),thentheNICMIZmap(11Nm)
and NIS c_map3 map (7 Nm). In step 12‐13 (Figure
DDD) occurred anomaly associated with high
volatilityofcourseinlocationsaroundposition80°N/
015°E. The convexity of the ice field bounda ry was
demonstratedwellbytheNICbarnwYYMMDDcolor
(29 Nm), then the NIC MIZ map (24 Nm) and NIS
c_map3 map (24 Nm). The line of NSIDC‐CCAR
(figureDDD)shownnoclearcorrelationwithchanges
in the course with other boundary lines. The most
distantfromtheiceedgelinewas40%concentration
lineshownonIUPmap.
Itreachedmostlyfurtherto
the North than the lines of high 70‐81‐91%
concentration.Duetothissignificantderogationfrom
the other lines, the IUP line was not taken into
account in the following analysis. It is worth
mentioningthatanotherfarawayfrombeginningof
sea ice
was 40% concentration line shown on NIC
MASIE map and next was 40% concentration line
shownonNCEPmap.
Interestinglookscorrelationofsamekindofedges
inrelationto thedistance fromthe beginningof sea
icefield.Averagedistance ofcenterof “ambiguous”
zonepresentedonOSISAFiceage
mapswasequal21
Nm. Average distance of all analysedlines
representing 30‐40% ice floe concentration (IUP
product excluded) was equal 24.1 Nm, Average
distanceofall analysedlinesrepresenting 70‐81‐91%
ice floe concentration was equal 30.6 Nm. The
maximum average value of distance of the furthest
analysedline(IUPproductexcluded)wasequal37.2
Nm.Theaveragestandarddeviationofthataverages
was equal 8.3 Nm only. It is worth mentioning that
tendencies of distance changes were very well
correlated(Figure6).
Figure6.Distanceofselected edgesfrom thefirst minimal
seaicelimitdataalonggeneraldirectionoficelimit.
Also interesting looks correlation of maximal
distances in the groups of same kind of edges in
relationtothedistancefromthebeginningofsea ice
field. Distance of “ambiguous” zone edge presented
onOSISAFiceagemapsfromOpenWatersidewas
equal 15.4 Nm. Distance of “ambiguous” zone edge
presented on OSISAF iceage maps from 1
st
year ice
sidewasequal26.6Nm.Maximaldistanceofanyline
fromlinesrepresenting30‐40%icefloeconcentration
(IUPproductexcluded)wasequal35.9 Nm,Maximal
distanceofanyanalysedlinefromlinesrepresenting
70‐81‐91% ice floe concentration product excluded)
wasnearlysamelike30‐40%
andequal36.3Nm.The
maximum value of distance of the furthest analysed
line(IUPproductexcluded)wasequal37.2Nm.The
average standard deviation of that averages was
equal 8.3 Nm only. It is worth mentioning that
tendencies of distance changes were very well
correlated (Figure 6). The minimal distance
of any
analysed line from lines representing 70‐81‐91% ice
floeconcentration(IUPproductexcluded)wasequal
25Nm. Thisline was alsovery well correlated with
allabove mentionededges. The minimal distance of
anyanalysedlinefromlinesrepresenting30‐40%ice
floeconcentration(IUPproductexcluded)
wasequal
12.3Nmbutthislinewasnotsowellcorrelatedwith
otherabovementionededges.
243
6 EVALUATIONOFUSEFULNESSOFREMOTE
SENSINGDATAFORROUTEINGPURPOSES
NIS maps named c_map.jpg accurately reflected the
edgesoftheicefloesfieldobservedfromthevesselat
themomentofreference.Meanoffsetpositionwas3.7
Nm. The ice floe patches of a width of less than 1.0
Nmwere not detected by remote sensing. Also NIC
map named barnwYYMMDDcolor accurately
reflectedconditionoftheicecoverobservedfromthe
shipatthemomentofreference. Itwasassumedthat
wedgeoficefieldofawidthoflessthan1.5Nmwas
not detected by remote sensing.
Based on
observations made from the vessel, the two maps
seemed to be appropriate for voyage planning and
routeingofthevesseliniceforeveryiceclassvessel
(see section 4). It is also possible to optimize the
routeing using these maps in accordance with the
criteria specified by Kjerstad
(2011), Arikaynen and
Tsubakov(1987)andCCG(1992).Itisrouteingofthe
vesselalongthelightesticeconditions.
NIC maps named nic_mizYYYYMMDDnc_pl_a
showgeneralcompliancewiththeshapesoftheedge
of the ice fields observed onthe vessel. Mean offset
positionforthecharacteristicshapesoftheedge
ofthe
ice fields was 6.5 Nm. AARI maps named
aari_bar_YYYYMMDD_pl_a seemed to be highly
generalizedanddidnotreflectedthestateofthe ice
coverobservedfromthevessel.Meanoffsetposition
for the characteristic shapes of the edge of the ice
fieldswas5.8Nm.Itwasassumedthat
icefieldofa
widthlessthan5Nmremainedundetectedbyremote
sensing.Both of these maps showed a consistent
locationofMIZlowerlimitof0‐18%andMIZupper
limit of 70‐90% visualised onthe maps c_map3 and
NIC NIS barnwYYMMDDcolor. Despite greater
numberofconcentration
levelsprovidedbytheAARI
map, AARI map seemed to be less precise in detail
thantheNICMIZmap.Duetothelimitationofthe
precisionofthescaleofconcentrationorprecisionof
position,theabovemapsseemedtobeusefulforthe
preliminary voyage planning and routeing of
the
vessel. They were not useful for optimizing the
routeingofthevesselinaccordancewiththecriteria
specifiedbyKjerstad(2011),ArikaynenandTsubakov
(1987)andCCG(1992).
NCEP maps named ice5min.YYYYMM showed
generalconsistencybetweenthedata. Itwasassumed
that the average position offset of ice fields
shapes
correspondedtothedimensionsofthegridof9.4Nm.
However,lackofcontinuity(consistency)ofthedata
on the NCEP map was noted. This raised concerns
that the concentration field visualized by the map
maynotaccuratelyreflecttheactualiceconditionsin
a particula r place and thus lead
to an incorrect
assessment of navigational situation or prevent
properdeterminationtherouteingofthevessel.
NIC maps named masie_ice_r00_v01_2009‐
222_4kmwererelatedtoicefloeconcentrationof40%.
Averageoffsetof icefield shapes on MASIE map in
relationtoicefieldsobservedfromthevesselwas20.6
Nm.
IFREMERmapsnamedYYYYMMDDshoweda
slight similarity with the observations of ice cover
made from the vessel, with NIC maps
barnwYYMMDDcolor and NIS c_map3 maps.
However,theshapeoftheedgeoftheicefloefieldof
concentration above 11% on IFREMER map most
closelycorrespondedtotheshapeof
iceedgeonthe
IUP map. It was assumed that the average position
offset of the characteristic shapes of ice edge fields
wasasmuchasasideofthegrid(cell)ofIFREMER
map equal to 6.7 Nm. IUP maps named asi‐n3125‐
YYYYMMDD showed average position offset of
the
ice field shapes equal to 19.5 Nm. Therefore it was
assumedthatthefieldsoficefloeonIUPmapdidnot
reflected directly the ice edge observed from the
vessel. The edge of 0‐10% concentration on the IUP
map corresponded to the edge of concentration of
40%on
c_map3NISmap,totheedgeofconcentration
of30‐50%onNICbarnwYYMMDDcolormap,tothe
edgeofconcentrationof40%onNICMASIEmap,to
the edge of concentration of 81% on the NIC
nic_mizYYYYDDD‐nc_pl_a map, to the edge of
concentration of 13‐46% on the AARI
aari_bar_YYYYMMDD_pl_a map and to edge of
concentrationof11‐44%ontheIFREMER map.Itwas
assumedthattheNICMASIEmapsandicelimitson
theIFREMER andIUPmapsreflecttheconcentration
limits of the ice floe of 30‐40% due to the weather
filtersapplied.Fullscaleof
iceconcentrationonboth
oftheabovementionedmapsmaybemisleading.All
threemapscannotbeusedforrouteingofthelowest
ice class vessels in the ice or in the vicinity of ice.
However,theyappeartobeusefulforvesselsofthe
lowestclassesofice(see
Table1)astheyindicatethe
limits of the region with average 30‐40%
concentrationoficefloe.Thesevesselscannavigatein
this area with icebreaker assistance. The use of
IFREMER and IUP maps for vessels with higher ice
classes routing does not seem to be appropriate
because they do
not reflect the real concentration of
icefloe.
7 EVALUATIONOFUSEFULNESSOFREMOTE
SENSINGDATAFORVESSEL’SSPEED
ESTIMATION
Accuracy of scale of sea ice concentration and ice
thickness,whichwereusedinanalyzeddatasources,
isimportantforestimationofvessel’smaximumsafe
speed.Itisdifficultto
comparethequalityofscalesof
individualsources.
Itwasfoundthatscalesofdatasourcesarediscrete
ofvarioussteps:NIS–irregularsteps0‐10,10‐40,40‐
70,70‐90and90‐100%,NIC(barnw)‐variablesteps
10‐30, 20‐40, 30‐50, 40‐60, 50‐70,
60‐80, 70‐90, 80‐100
and 90‐100 %, AARI – few steps only of 13, 46, 78,
91%,NIC(MIZ)–largestepsfor18%and81%only,
NCEP – 0.5%, OSISAF (concentration) – continuous
scalebutinpracticediscreteoneat0.1%concentration
and after taking into
account weather filter 35%
concentration,IFREMER(concentration)–continuous
scalebutinpracticediscreteoneat0.1%concentration
and after taking into account weather filter 15%
concentration, IUP‐0.5% step after taking into
account the weather filter 40% concentration of ice
floes,OSISAF (simplifiedconcentration scale) – only
fewstepsof
0,35 and70%after takinginto account
weather filter of 35% concentration, NIC (MASIE) –
onlyone edge butafter taking into account weather
filter of 40% concentration and being the result of
summaryofmanyvariousdatasources,OSISAF(ice
type/age)–fewstepsonlylikeuncertain(ambiguous),
244
1
st
year,uncertain(ambiguous),multiyearice,NSIDC‐
CCAR – few steps only like 1
st
year, uncertain
(ambiguous),2
nd
yearandsoon.
ItshouldbeemphasizedthatESIMOdistinguished
followingintervalsofyoungicethickness:Nilas(<10
cm), gray (10‐15 cm) and a gray‐white (15‐30 cm).
First‐year ice was divided into thin (30‐70 cm),
medium (70‐120 cm) and thick (120‐200 cm).
First‐
yeariceisseaicethathasnotsurvivedmorethanone
winter. It was also assumed that multiyear ice (old)
hasathicknessof200cmandmore.Theappliedscale
seems to be a detailed and satisfying the needs of
assessmentofasafespeedofthevessel
inicebased
on Arikaynen (1979) criteria. However, it is not
entirelyconsistentwiththescaleoftheiceagesused
byRMRS(2015).
Debatable issue is the interpretation of discrete
scale on OSISAF ice type (age) maps. The scale
containsedgesofthe1
st
yeariceandmultiyearicebut
the edge is determined by a complex filter that is
reducingfalseiceandisaddingtheextentoficecover
upto50NmfollowingNSIDCiceextentfromtheday
before.Inthiscasethe1
st
yearicemeanscurrentyear
young ice. The multiyear ice means that have
survived at least one summer season (Eastwood
2014).
The discrete scale on NSIDC‐CCAR ice age of
everyoneyearsteprepresentsmeanthicknessofice
equal149cm,202cm,228cm,247cm,268cm.
Inthis
case the first‐year sea ice means “young” ice
according to ESIMO classification or of the current
winterorthatnotsurvivedanymeltingseason.Itis
equivalent of “current year young ice” according to
OSISAF ice type scale. The second‐year sea ice
survived one melting season and
so on. In this case
the NSIDC‐CCAR lowest value of ice thickness is
related to high thickness around 149 cm that
responding to medium and thick ice according to
ESIMOscale. The NSIDC‐CCAR scale looks like not
containing equivalency of ice thickness from 0 to 70
cmof
ice.
Aseparateissueislandfilterusedinthemajority
ofanalyseddata sources.It limitsmuchinformation
near the shore and in the straits, archipelagos and
narrow passages. Scales of ice ages do not reflect
decayofice.AARIchangesmapsfromconcentration
typetothicknesstypeandback
on1.VIand30..IX.It
suggest that decay of is substantial enough that
makes ice thickness is not critical for safe speed of
vessel. The provisions of RMRS (2015) apply
additionalcriteriaforthesafenavigationofvesselsof
different ice classes in ice‐covered areas. The
possibility of
completion of voyage depends on the
area(ofthesea)andthedifficultiesoficeconditions
(extreme,hard,medium,easy).
Theanalysisofaveragespeedofvesselofspecified
ice class in particular segments along the ice
boundaryfoundthatrelativestandarddeviationRSD
of ice concentration was 34%. It was
related to
average concentration of all data sources along 180
Nm of distance. Were only two examined data
sources related to ice thickness. NSIDC‐CCAR data
sourcesgavehighervaluesofthicknessthanOSISAF
datasources.Discrepancyofaverageicethicknessof
both sources affected the high RSD. It was
equal
92%.RSDofspeedforbothiceclassesofvesselswas
higher in case of NSIDC‐CCAR data than in case of
OSISAF data. It was due to significantly greater
variabilityinthedirectionofNSIDC‐CCARiceedge
thanincaseofOSISAFdatasources.
Thereasonseemsto
bethemethodofdetermining
theiceedgeonOSISAFmap(seechapter3.11).Itwas
observedthatthelowericeclassofvessel,thehigher
speeddeviationtowardslowervalues(Table5).
Local speed reduction occurred due to ice
conditionsmayreachupto32%oftheaveragespeed
expectedforiceclassL1andL3.Variationsinvelocity
toward smaller values are more significant than can
be seen from the calculated standard deviation
(Tabela5)
Table5. Speed of defined ice class vessel in relation to
averageiceconcentrationandaverage icethicknessofdata
sources along the line of ice limit during voyage from
KinnvikatoLongyearbyenfollowingequation2.
_______________________________________________
Data30NmdistancesegmentsAver.RSD
Source1 2 3 4 5 6 [kn][%]
_______________________________________________
Av. CT[%] 45 15 33 38 41 52 37 34
Av. H[cm] 15 0 15 116 90 116 59 92
NC‐L3 V[kn] 5.8 6.0 6.0 3.8 4.0 2.8 4.7 29
NC‐L3σ[kn] 0.4 0.1 0.2 1.6 1.4 2.5 1.4
NC‐L1 V[kn] 11.6 12.1 12.0
7.7 7.9 5.7 9.5 29
NC‐L1σ[kn] 1.2 0.0 0.5 0.7 0.8 1.3 2.7
OSI‐L3 V[kn] 4.9 5.9 5.4 5.2 5.1 4.6 5.2 9
OSI‐L3σ[kn] 1.2 0.0 0.5 0.7 0.8 1.3 0.4
OSI‐L1 V[kn] 9.3 11.2 10.2 9.9 9.7 8.8 9.9 8
OSI‐
L1σ[kn] 2.9 1.9 2.1 2.3 2.3 3.0 0.8
_______________________________________________
NC‐NSIDC‐CCAR,OSI–OSISAF,CT–totalconcentration,
H–icethickness,σ–average,RSD–relativestandard
deviation
Mean concentration values for individual data
sourceswerehighlyvariableintherangebetween0%
and77%.Theaveragevalueforallsourceswas37%.
Relative standard deviation of average value of
concentrationforexaminedsourceswasequal72%in
relations to average concentration. The highest
averagevaluesofvessel’sspeed
ofdefinediceclasses
L3andL1arerelatedtoAARI,NCEP,IFREMERand
IUP data sources. They were assumed to be too
optimisticscenario.Therewereiceboundarieslocated
the most Northward. This can be explained by the
high value of weather filter equal 40% of ice
concentration or
because the information about ice
occurrencebegin athigh concentration values above
40%. The lowest speed values fall on the OSISAF
(EDGE) data sources. They were assumed too
pessimistic scenario. This can be explained by high
threshold of weather filter, high value of ice
concentrationlimitonmapandhighstep
inbetween
concentration thresholds of 35% and 70%. The
intermediatespeed values fall on NIS, NIC(barnw),
NIC(MIZ),OSISAF(CONC) and NIC(MASIE)data
sources.Theywereassumedmostprobablescenario.
Table6.Averagespeedofdefinediceclassvessel inknots
inrelationtoiceconcentrationandicethicknessforvarious
data sources during voyage from Kinnvika to
LongyearbyenfollowingEquation2.
_______________________________________________
Data CTCCAR‐L3 CCAR‐L1OSI‐L3 OSI‐L1
Source [%] Av.St.D. Av. St.D. Av.St.D. Av.St.D.
_______________________________________________
NIS 52 4.1 2.3 8.3 4.5 5.3 0.5 10.6 1.1
NIC 38 4.9 1.3 9.7 2.6 5.7 0.1 11.2 0.3
245
(barnw)
AARI0 5.8 0.1 11.6 0.3 6.1 0.1 12.1 0.2
NICMIZ 77 3.3 2.7 6.5 5.4 4.9 0.5 4.9 0.5
NCEP 35 5.2 1.0 10.5 2.1 5.1 0.5 10.2 0.9
IFREMER 8 5.8 0.3 11.5 0.6 5.5 0.2 11.0 0.3
OSICONC51 4.2 2.1 8.5 4.2 4.5 0.8
9.1 1.7
IUP 0 5.8 0.1 11.6 0.3 6.1 0.1 12.1 0.2
MASIE 60 4.2 2.4 8.4 4.9 4.1 1.7 8.3 3.3
OSIEDGE53 4.2 2.1 8.4 4.3 4.6 0.9 9.1 1.7
Aver.CT 37 4.8 0.9 9.5 1.8 5.2 2.7 9.9 2.2
[%]
RSD[%] 72 18.0 18.0
13.0 22.0
_______________________________________________
CT–totalconcentration,CCAR–NSIDC‐CCAR,OSI–
OSISAF,Av.–averagespeed[kn],St.D. –atandard
deviation[kn],RSD–relativestandarddeviation[%]
AveragespeedofL3iceclassvesselrangedfrom
3.3knotstill5.8knotsataverage4.8knotsforNSIDC‐
CCAR ice thickness data and from 4.1 knots till 6.1
knots at average 5.2 knots for OSISAF ice thickness
data. Average speed of L1 ice class vessel ranged
from6.5knots
till11.6knotsataverage9.5knotsfor
NSIDC‐CCAR ice thickness data and from 4.9 knots
till 12.1 knots at average 9.9 knots for OSISAF ice
thickness data. Relative standard deviation of
averaged speed for both ice class vessels was equal
18%. Higher volatility were found for OSISAF data
sources. The highest relative deviations were found
upto50%belowtheaveragespeedvalue.Sametime
thehighestrelativedeviations wereequal22%above
theaveragespeedvalue.
Abovementionedrelativedeviationsfromaverage
speed of the vessel are the result of discrepant data
fromthesourcesservedforthis
evaluation.Itmeans
that the most important for evaluation of vessel’s
speedduringvoyageinice‐coveredareasdependson
datasources used forevaluation. That wasassumed
that the NIS, NIC (barnw), NIC (MIZ), OSISAF
(CONC) i NIC (MASIE) data sources indicating
most probable average values of speed should
be
goodforlowandmediumiceclassvesselsforvessel’s
speed evaluation during voyage planning process.
Distance inbetween points of beginning and end of
the voyage with vessel speed corresponds with the
timeofthevoyage.
Let’s take above values into consideration for
transit voyage planning on Northern Sea
Route of
total distanceequal 3,032.8 Nm. The vessel of ice
classL3withaveragespeed5knotsrequire50.5,25.3
or 20.7 days for the voyage in pessimistic, most
probable or optimistic scenarios respectively in case
ofextreme deviations weretaken intoconsideration.
ThevesseloficeclassL1
withaveragespeed9.7knots
require 26.1, 13.0 or 10.7 days for the voyage in
pessimistic, most probable or optimistic scenario
respectively in case extreme deviations were taken
intoconsideration.
Averagetechnicalspeedof“NorilskSA‐15”ULA
classvesselwas equal 12,6knots (Mulherin 1996).It
was assumed this speed
corresponding well with
speedofL1andL3iceclassvesselsestimatedinthis
study. It means the appropriate assumptions have
been adopted in the work. The standard deviation
valuesmaybeusedforvoyagetimeplanninginstead
of extreme relative deviation values. In any case a
widerangeof
datasourcesandscenariostobetaken
carefullyintoconsideration.
8 CONCLUSIONS
The spatial range of whole analysed path of 0‐90%
concentration area covered by ice identified by
variousdatasourceswasabout50Nm(Figures6and
7).Incaseof40%concentrationdatathespatialrange
wasabout
40Nm. Itcanberelatedtodistancepassed
byvesselswithfullseaspeed10‐15 knots.Thenthis
analysedzonewasinside2.5‐5hoursofsailingincase
of0‐90%concentrationdataand 2‐4hours of sailing
incaseof40%concentrationdiscrepanciesonly.
The
resultsofanalysesofdifferentmapsobtained
by remote sensing methods showed that the
informationpresentedisnotthesame.Anexampleof
the edges and limits of the concentration of ice floe
thatareclosetoconcentrationof40%foreachmapis
showninFigure7.Discrepanciesamongthe
analysed
data on the maps certainly arise from error of the
measurementmethod.AccordingtoRodrigues(2009)
basedonComiso(1999)theerrormaybeupto5‐10%
and even 15% of the concentration of ice floe. This
error depends on the remote sensing measurement
methodused. Theerror
ofthemeasurementmethod
shouldbetakenintoaccountwhenplanningtheroute
of the vessel in ice‐covered areas. It should also be
borneinmindthatthemoregeneralizedinformation
aboutthestateoftheicecover,thelesslikelybecomes
detectionoficefloepatchesofhighconcentration
and
theirs spatial extent. It should also be taken into
accountthatthevessel maybetrappedintheicefloe
of a high concentration while overcoming larger ice
floefield.Thenicebreakerassistancewillberequired.
In both these cases, the vessel will be able to sail at
very
low speed and thus lose a lot of time to go
through the ice and the travel time becomes
significantly longer. Thus, the current schedule and
thenextexpeditionschedulewillbedisrupted.
Now the question should be answered which
maps may be used to assess the ice conditions from
the
navigationpoint ofview. TheMASIE, IFREMER
andUIPmapsseemtobeuselessforvesselswithlow
ice class, as they relate to concentration of 30‐40%.
Suchconcentrationedgesmightbeusefulformedium
ice class ships. Low ice class vessels are looking for
concentration limit of 15%.
The NCEP maps also
appeartobeuselessforlowiceclassvessels,because
they may mislead the user during the preliminary
voyageplanningandschedulingthenextexpedition.
The NIC (MIZ) and AARI maps seem to meet the
needsofpreliminaryvoyageplanningandscheduling
thenextexpeditionofvessels
withlowiceclassesas
these maps depict the lower limits of 13‐18%
concentration. NIS maps named c_map3 and NIC
maps named barnwYYMMDDcolor have a
satisfactory scale concentration and precision to
present the edge of each concentration. They allow
planningtherouteingofthevesselandavoidingareas
with
higherconcentrationoficefloe.Whenanalysing
theicefloeconcentration onamap forplanningthe
routeandscheduleofthevessel,theerrorsofremote
sensingmethodsusedtoestimateconcentrationofice
floeshouldalwaysbetakenintoconsideration.
246
Figure7.Thespatialdistributionofedges orborders close
to 40% ice floe concentration for individual maps for the
day15August2009:
───edgeof40‐70%concentrationon
the NIS map, • • • edge of 30‐50% concentration on the
NIC (EGG) map,
▬ • • ▬ edge of 46% or 91%
concentration on the AARI map,
▬ ▬ ▬ edge of 40%
concentrationon the NIC (MASIE),
─┼─ edge of
concentration 40% on the NCEP map,
edge of 0%
concentration on OSISAF map,
edge of 35%
concentration on OSISAF ice edge map
─●─iceedge on
NSIDC‐CCAR ice age map,
─ ─ ambiguous ice edge
fromOpenWatersideonOSISAFicetypemap,
─╫─edge
of0%or81%concentrationonNIC(MIZ)map,
▬▬▬edge
of25‐65%concentrationoficefloefieldobservedfromthe
vessel.
─◄─routeofthevessel.
Finally,wemustanswerthequestionwhetherthe
above mentioned vessel of L2 (L1) class could
determinemorefavourablerouteataninitialstageof
routeing. The answer is positive. At the initial stage
the crew could follow data on reliable daily NIS
maps.TheNICbarnwYYMMDDcolormapswerenot
available
for required day. The NIC (MIZ) maps
could be used but their content does not advise the
vesselabouthigherconcentrationoficepatches.Thus
the vessel proba bly would follow standard route to
encounterice floepatches of high concentrationand
makeroutearoundtheicefield.
Anotherdiscussionrequire
usefulnessofanalysed
ice age maps for route planning. First, we should
understand,thattheirscaleisverygeneralisedforice
thickness interpretation. Following the definition we
candivide thescale ofthickness of ice presented by
these maps as young ice of thickness from 0 cm to
30 cm, first
year ice of thickness from 30 to 200 cm
and second year ice of thickness from 200 cm
upwards.
The minimum ice floe concentration of 35% is
identifiedbyOSISAFicetypemap.Thisis“areatobe
avoided” for vessels of ice class lower than L1
(Arikaynen1987).OSISAF
icetypemapsaresensitive
formeltingperiodandwidestripeofambiguousarea
is indicated instead of clear ice age data. This
ambiguous area may be interpreted as area of
younger ice then 1
st
ice age below 200cm high and
also as deteriorated ice of lower resistance and
hardness,easier to overcome by vessel, despite
considerable thickness. The location of edge in
between ambiguous and open water area should be
treated with caution because are determined by
indirectremotesensinginterpretation.
Ice edges
courses included on NSIDC‐CCAR ice
agemaparemorereliableindetailsthenOSISAFice
type map. The minimum ice floe concentration of
40% is identified by this map. This is “area to be
avoided” for vessels of ice class lower than L1
(Arikaynen 1987). The user should expect ice
thicknessbelow149cmoutoftheicefields.However
this thickness is available for icebreakers and the
highest ice class Arc7 (ULA) vessels only. The ice
fieldsofanyageshownonNSIDC‐CCARmapshould
beinterpretedas“areastobeavoided”foranylower
iceclassvessel
thenULA.TheNSIDC‐CCARicetype
mapsarealsosensitiveformeltingice.Duetoabove
largest uncertainties should be expected during
meltingperiodandintheMarginalIceZone.Itmay
begeneralized,thatallseaicefieldspresentedondata
sourcesthataredevelopedonbasis ofweather
filter
related to 30‐40% of sea ice concentration should be
consideredas“areastobeavoided”byvesselsofice
classlowerthanL1.
Theresultsoftheworkallow to estimate general
correlationsinbetweenvariouskindsofseaiceedges
in relation to the distance from sea
ice extent line.
They are located in the sequence of the following
distances:centerof“ambiguous”zonepresentedon
OSISAF ice age maps‐21 Nm, center of 30‐40% ice
floe concentration (IUP product excluded)‐24.1
Nm,centerof70‐81‐91%icefloeconcentration‐ 30.6
Nm. As the maximal average
distance of analysed
lines(IUPproductexcluded)wasequal37.2Nm,then
relativedistancesinrelationtotheseaiceextentline
were: center of“ambiguous” zone presented on
OSISAFiceagemaps–37%,centerof30‐40%icefloe
concentration(IUPproductexcluded)‐65%,center
of70‐81‐
91%icefloeconcentration‐ 82%.
Tendencies of distance changes were very well
correlated. The lowest distancefor line of 30‐40% of
concentration of sea ice pack was very close to
“ambiguous”fieldlimitfromOpenWaterside.Next,
the“ambiguous”fieldlimitfrom1
st
yearicewasvery
close to lowest distance for lines 70‐81‐91% of
concentration limit of various sources. Finally, the
highestdistanceforlineof30‐40%ofconcentrationof
sea ice pack was very close to highest distance for
lines 70‐81‐91% of concentration limit of various
sources.Incaseofshortageofdatasourcesthesepairs
couldbeusedforestimationofseaicepacklocation
as equivalency‐one line instead of other one. The
limit of high concentration ice pack isgenerally in
sameposition.Discrepancyoflocationinbetween30‐
40% and 70‐81‐91%
concentrationlooks be
negligible. The width of ice field inbetween 30‐40%
and 70‐81‐91% concentrationis higher than 3 Nm
only in places of higher volatility of analysed lines,
especially where the general course of ice limit
directionisconsiderablychangedonlongerdistances.
Detailed average distances
of various analysed
lines from external line of ice data in relation to
maximalicedatavalueswerefoundasfollow:8.4Nm
(23%)forNSIDC‐CCARiceage,12.3Nm(33%)for
247
minimal distance of 30‐40% ice concentration, 15.4
Nm (41%) for OSISAF ice type “ambiguous” zone
from Open Water side, 25 Nm (67%) for minimal
distance of 70‐81‐91% ice concentration 26.6 Nm
(72%)forOSISAFicetype“ambiguous”zonefrom1
st
yeariceage,35.9Nm(97%)formaximaldistanceof
30‐40% ice concentration and 36.3 Nm (98%) for
maximal distance of 70‐81‐91% ice concentration. In
the parentheses placed relative distances in between
first ice data and highest data including IUP 40%
concentrationisolines.
Depending on the sources
of information used
the estimated speed of L3 ice class vessel from 3.3
knots till 5.2 knots at average speed 5.0 knots was
received. Estimated speed of L1 ice class vessel
rangedfrom6.5knotstill12.1knotsataveragespeed
9.7 knots.Relative standard deviation of averaged
speedforeach
ofL3andL1iceclassvesselwasequal
18%.Thehighestrelativedeviationswerefoundupto
50% below the average speed value. The highest
relativedeviationsupwardwereequal22%.
Theresultsoftheworkarenotintendedtobeused
for decision making on spot, “on‐scene”,
during
direct guiding vessel in ice. It should be useful for
initial voyage planning. Results of analysis allow
decision‐makersto identifythe bestdata sourcesfor
consideredvoyageandvesselofdefinediceclass;to
understand advantages and limitations of freely
available in the internet data sources; to estimate
vessel’s
maximal safe speed in encountered ice
conditions and to estimate spatial distribution and
correlations in between various levels of sea ice
concentrationandthickness.
ACRONYMS
AARI‐Arctic and Antarctic Research Institute in
St.Petersburg
ALOS‐AdvancedLandObservingSatellite
AMSR‐E‐AdvancedMicrowaveScanningRadiometer‐
EarthObservingSystem
AMSR2‐ AdvancedMicrowaveScanningRadiometer2
AMSU‐ AdvancedMicrowaveSoundingUnit
ASA‐ AdvancedSyntheticApertureRadar
ASI‐ARTISTSeaIce
AVHRR‐ VIS Advanced Very High Resolution
Radiometer
AVHRR‐VIS
‐ Advanced Very High Resolution
Radiometer‐VisibleBand
CCAR–ColoradoCenterofaerodynamicsResearch
CDAS‐ClimateDataAssimilationSystem
CDOP‐ContinuousDevelopmentandOperationsPhase
byMeteo‐France
CERSAT‐FrenchERSProcessingandArchivingFacility
CIS‐CanadianIceService
CT‐ ConcentrationTotal
DMI‐ DanishMeteorologicalInstitut
DMSP‐DefenseMeteorologicalSatellite
Program
DMSPOLS‐DefenseMeteorologicalSatelliteProgam–
OperationalLinescanSystem
ENVISAT‐ ENVIronmentalSATellite
ESIMO‐ЕСИМО,Единaя Системa Информации об
обстановкевМировомОкеане
EUMETSAT‐EUropean Organisation for the
ExploitationofMETeorologicalSATellites
GDSIDB‐GlobalDigitalSeaIceDataBank
GMM‐GeometricalMathematicalModel
GOES‐Geostationary Operational Environmental
Satellite
IAPB‐InternationalArcticBuoyProgram
IFREMER‐ Institut
Français de Recherche pour
lʹexploitationdelaMer
IMS‐ Interactive Multisensor Snow and Ice Mapping
System
IUP‐ InstitutfürUmweltphysik,UniversitätBremen
MASIE‐ MultisensorAnalyzedSeaIceExtent
Met.no‐ NorwegianMeteorologicalInstitute
MIZ‐ MariginalIceZone
MMAB‐ MarineModelingandAnalysisBranch
MODIS‐ Moderate Resolution Imaging
Spectroradiometer
MTSAT‐ Multi‐functional
TransportSatellite
NAVO‐ NavalOceanographicOffice
NCAR‐ NationalCenterforAtmosphericResearch
NCEP‐NationalCentersforEnvironmentalPrediction
NESDIS‐ National Environmental Satellite, Data, and
InformationService
NGDC‐ NationalGeophysicalDataCenter
NIC‐ National Ice Center, US National Ice Service, US
NavalIceService
NIS‐NorwegianIceServices
NOAA‐ National Oceanic
and Atmospheric
Administration
NOMADS‐ National Operational Model Archive &
DistributionSystem
NSIDC‐ NationalSnowandIceDataCenter
NWP‐ NumericalWeatherPrediction
NWS‐ NationalWeatherService
OSISAF‐ OceanAndSeaIceSatelliteApplicationFacility,
HighLatitudeCentre
PALSAR‐PhasedArraytypeL‐bandSyntheticAperture
Radar
QUIKSSCAT‐ ʺquick recoveryʺ mission from
the NASA
Scatterometer
RADARSAT‐ RADARSATellitesystemequippedwitha
powerfulsyntheticapertureradar
RGB‐ additiveRed,Green,Bluecolormodel
SAF‐ SatelliteApplicationFacilities
SAR‐ SyntheticApertureRadar
SEVIRI‐ SpinningEnhancedVisibleandInfraredImager
SMHI‐Swedish Meteorological and Hydrological
Institute
SMMR‐ScanningMultichannelMicrowaveRadiometer
SSM/I‐SpecialSensor
MicrowaveImager
SMMIS‐SpecialSensorMicrowaveImagerSounder
UKHO‐ UnitedKingdomHydrographicOffice
URL‐ UniformResourceLocator
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