NASA Technical Reports Server (NTRS) 20140008935: Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

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IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012 3
Validation of Airborne FMCW Radar Measurements
of Snow Thickness Over Sea Ice in Antarctica
NataliaGalin,AnthonyWorby,ThorstenMarkus,CarlLeuschen,andPrasadGogineni,Fellow,IEEE
Abstract—Antarctic sea ice and its snow cover are integral naturaloranthropogenic.Itisgenerallyconsideredthatchanges
components of the global climate system, yet many aspects of in the climate will be most pronounced at these two remote
their vertical dimensions are poorly understood, making their
parts of our planet [1]. The sensitivity of the poles is mainly
representation in global climate models poor. Remote sensing is
duetothepresenceofseaice,anditsimportanceisrecognized
thekeytomonitoringthedynamicnatureofseaiceanditssnow
cover.Reliableandaccuratesnowthicknessdataarecurrentlya in its inclusion as one of the three key components in climate
highlysoughtafterdataproduct.Remotelysensedsnowthickness models:ocean–seaice–atmosphere[2].Inaddition,seaicehas
measurements can provide an indication of precipitation levels, a major impact on the Earth’s heat budget, ocean–atmosphere
predicted to increase with effects of climate change in the polar
interaction,andoceancirculation.
regions. Airborne techniques provide a means for regional-scale
The addition of snow to the surface of sea ice com-
estimationofsnowdepthanddistribution.Accurateregional-scale
snowthicknessdatawillalsofacilitateanincreaseintheaccuracy pounds many of the climate and biological processes that
of sea ice thickness retrieval from satellite altimeter freeboard sea ice influences. Having an even higher albedo and lower
estimates.Theairbornedatasetsareeasiertovalidatewithinsitu thermal conductivity than sea ice [3], snow increases the
measurements and are better suited to validating satellite algo-
reflection of solar radiation back into space and strongly
rithmswhencomparedwithinsitutechniques.Thisisprimarily
affects ocean–ice–atmosphere heat exchange. Consequently,
duetotwofactors:betterchanceofgettingcoincidentinsituand
airbornedatasetsandthetractabilityofcomparisonbetweenan snowcovercandrasticallyretardthegrowthofseaiceinwinter
insitudatasetandtheairbornedatasetaveragedoverthefoot- anddelaymeltinsummertime[4].
printoftheantennas.A2–8-GHzfrequencymodulatedcontinuous Inordertounderstandtheeffectsandfeedbackmechanisms
wave(FMCW)radarloanedbytheCenterforRemoteSensingof
of the changing climate on the extent and thickness of sea ice
IceSheetstotheAustralianAntarcticDivisionisusedtomeasure
anditssnowcoverandtheirseasonalvariability,itisimperative
snowthicknessoverseaiceinEastAntarctica.Providedwiththe
radar design parameters, the expected performance parameters togloballymonitoriceandsnowpropertiesonacontinuousba-
of the radar are summarized. The necessary conditions for un- sis.Onlysatelliteremotesensingcanprovidethisinformation.
ambiguous identification of the air/snow and snow/ice layers for Anumberofmethodshavealreadybeendevelopedtomeasure
theradararepresented.Roughnessesofthesnowandicesurfaces
seaiceelevationandfreeboardofseaiceusingeitherlaser[5],
are found to be dominant determinants in the effectiveness of
[6] or radar satellite altimetry [7] data which are then used to
layeridentificationforthisradar.Finally,thispaperpresentsthe
first in situ validated snow thickness estimates over sea ice in estimatethetotalseaicethickness.Knowledgeofsnowcoveris
Antarctica derived from an FMCW radar on a helicopterborne recognizedascriticaltoextractingaccurateicethicknessfrom
platform. altimeterdata.
Index Terms—Airborne, Antarctica, frequency modulated Other than model output, climatologies, and the extensive
continuouswave(FMCW),seaice,snow. compilation of ship-based observations in Antarctica [8], the
only existing large-scale snow depth product comes from
the passive AMSR-E instrument on National Aeronautics and
I. INTRODUCTION
Space Administration’s Aqua satellite [9], [10], but recent
THEPOLARregionsplayakeyroleintheEarth’sclimate studies have shown problems, particularly over rough sea ice
system, considered amplifiers of climate events, be they [11].Worbyetal.[12]andMassometal.[13]describeresults
fromanextensivesetofexperimentsconductedduringavoyage
intotheEastAntarcticzonein2003tovalidatesatelliteseaice
Manuscript received May 27, 2010; revised December 14, 2010 and
March 20, 2011; accepted May 1, 2011. Date of publication July 12, 2011; dataproducts.ItwasfoundthatAMSR-Esignificantlyunderes-
dateofcurrentversionDecember23,2011. timatesthesnowthicknessanditsperformanceisdramatically
N.GaliniswiththeCentreforPolarObservationandModelling,University
affectedbytheroughnessoftheunderlyingseaice.
CollegeLondon,WC1E6BTLondon,U.K(e-mail:[email protected]).
A. Worbyis with the Australian Antarctic Division, Kingston, Tas. 7050, Large-scale satellite data are hard to validate satisfactorily
Australia(e-mail:[email protected]).
with in situ data considering that not only it is difficult to
T. Markus is with the Cryospheric Sciences Branch, Hydrospheric and
Biospheric Sciences Laboratory, Goddard Space Flight Center, National achieve coincident measurements with satellite overpasses but
Aeronautics and Space Administration, Greenbelt, MD 20771 USA (e-mail: also the methodology of combining the large pixel size aver-
[email protected]).
ages (the order of tens of meters, for example) of a highly
C. Leuschen and P. Gogineni are with the University of Kansas,
Lawrence, KS 66045-7621USA (e-mail: [email protected]; gogineni@ heterogeneoussnowcoverdistributiontothatofasingleinsitu
cresis.ku.edu). (centimeter-size pixel) measurement is unknown. To address
Colorversionsofoneormoreofthefiguresinthispaperareavailableonline
this drawback, research has been directed to the development
athttp://ieeexplore.ieee.org.
DigitalObjectIdentifier10.1109/TGRS.2011.2159121 ofsled(averagepixelsizesofmeters)and/orairborne(average
0196-2892/$26.00©2011IEEE
4 IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012
pixels sizes of tens of meters) remote sensing investigation TABLE I
techniqueswhicharethemselveseasiertovalidatewithinsitu RADARDESIGNPARAMETERS
dataandarecapableofcoveringalargeareawhich,inturn,can
thenbeusedforvalidatingsatellitedata.
A strong case for the use of radar, together with laser, al-
timetryforsnowthicknessextractionisprovidedin[14].How-
ever, using separate radar and laser systems requires precise
calibration of the instruments and compensation of footprint
differences. Ultrawideband frequency modulated continuous
wave (FMCW) radars are able to extract both the air/snow
and snow/ice interfaces simultaneously and have been used
extensivelyforsnowdepthstudies[15].Theyprovidetheideal
meansformedium-scalenondisruptiveestimatesofsnowcover.
However,onlyafewhavebeenairborne,andevenfewerhave
beenemployedforresearchoverseaiceinAntarctica.
Until now, FMCW radar operation has been conclusively
demonstrated to work from a sled-based platform [16]–[18],
and airborne experiments have been performed over ice
TABLE II
sheets, lake ice, or mountain regions [19]–[22]. However, to
RADARPERFORMANCEPARAMETERS
date, results of snow thickness estimation over sea ice from
airborne radar are not currently available in the published
literature. The difficulty in achieving this has been the strin-
gent requirement imposed on the FMCW radar during higher
altitude operation, a problem not present in handheld or sled-
operatedradar.Thisrequirementtoafirstordermanifestsitself
inthelinearityperformanceoftheradar;thehigherthealtitude
oftheradar,thelesstolerancethereistononlinearitiesthatare
necessarilypresentinapracticalsystem.
Thispaperprovidesthefirstvalidationeffortofsnowthick-
ness retrievals from airborne FMCW radar over sea ice in
Antarctica. First,a description of the radar system is provided (AAD)forfittingandoperationfromahelicopterplatform.The
in terms of the design and performance parameters. Based on designparametersoftheradarsuppliedarepresentedinTableI.
these values, the minimum backscattering coefficient that the Ascanbeseenfromthesummaryprovidedinthetable,thean-
radarissensitivetoispresented.Thisallowsforthelimitations tennaalong-trackbeamwidthisquitelarge,andadmittedly,this
of the radar performance to be gauged in terms of detection isadesignshortcoming.Suchalargebeamwidthisessentially
sensitivityingeneralandsensitivitytolayeringwithinthesnow an inefficient use of transmitted power; however, due to the
pack. Provided with the performance parameters of the radar, pulselimitedoperationoftheradar,itdoesnotaffecttheradar
the following section describes the necessary conditions for resolution performance. Due to time and logistical resource
unambiguousidentificationoftheair/snowandsnow/icelayers. constraints,theseweretheonlyantennascertifiedforoperation
Theflightsandinsitucollectionproceduresarethendescribed, fromthehelicopter.Infutureexperiments,improvementofthe
andthevalidationprocedureispresented.Finally,erroranalysis antennasisafirstpriority.
is performed to characterize the confidence in snow thickness
retrievals.
A. RadarSystemDescription
The interpretation of the performance parameters based on
II. OVERVIEWOFFMCWRADAR
the design parameters and adjustments to helicopterborne op-
TheprincipalideaofFMCWrestsonthefactthattheproduct erationissummarizedinTableII.Duetothealmostunlimited
of two harmonics is equivalent to the sum of two sinusoidal beamwidthoftheradarinthealong-trackdimension,theradar
signals whose frequency values are the difference and sum of illuminatesalargeareaonthegroundwithatransmittedchirp
the two harmonics. Whereas pulse radar systems use the time signal every 1.25 ms. However, due to the nature of the post-
between transmission and reception of the pulse for detection processing of the FMCW radar data, where a pseudomatched
and ranging, in FMCW systems, the delay in time of the filtering operation takes place in the fast Fourier transform
transmitted signal is mapped into a difference frequency, and filter bank, the pixel on the ground (i.e., active area) from
it is the value of the difference frequency which carries the which all returns are integrated into a single range bin is
detection/ranginginformation.Brooker[23]providesadetailed calculated to be approximately 24 m2 (at a nominal operating
overviewofthebasicsoftheradardesignandcomponents. altitude of 100 m). Provided that the detection probability
A2–8-GHzFMCWradarwasloanedbytheCenterforRe- of the radar is set to 0.5 and the false-alarm rate is set at
moteSensingofIceSheetstotheAustralianAntarcticDivision 10−3, the minimum backscattering coefficient that the radar is
GALINetal.:VALIDATIONOFAIRBORNEFMCWRADARMEASUREMENTSOFSNOWTHICKNESSOVERSEAICE 5
Fig.2. Returnpowerrequirementsfortheair/snowandsnow/iceinterfaces
forunambiguousidentification.
Fig. 1. Possible ambiguity condition in returns from the air/snow and
snow/iceinterfaces.
sensitive to is approximately −107 dB. The usable bandwidth
oftheradarenablesittounambiguouslydistinguishreturnsthat
are vertically spaced further than 37.5 mm apart. The usable
bandwidth in this case was measured to be 4 GHz; hence, it
followsthattheverticalresolutionis(c/BW)≈3×108/(2×
4×109)=0.0375m.
In the case of a smooth (low spatial frequency) surface, it Fig. 3. Reflection and refraction/transmission at air/snow and snow/ice
wouldbeelementarytodistinguishthesurfacereturnfromthe interfaces.
subsurface. The radar in this case would be receiving close to
Fig.3,thereflectedpowersattheair/snowinterface(P )and
specularreflections,andthereisthennoambiguitywithrespect a/s
thesnow/iceinterface(P )areexpressedas
toasubsequentreturnarrivingfromadifferentoff-nadirrange s/i
cellorduetothesubsurface(i.e.,snow/iceinterfacereflection).
P =(R )2P (2)
Ifthesurfaceisrough,ambiguityintheidentificationofthe s/a (cid:2) a/s in(cid:3)c (cid:2) (cid:3)
snow/ice from the air/snow may occur. Fig. 1 shows a likely P = 1−R2 P R2 1−R2 (3)
s/i a/s inc s/i a/s
conditionwherebyareturnfromthesurfaceair/snowinterface
comingfromanadjacentrangecelloccursinthesamerangebin
where P is the power incident at the air/snow interface and
inc
asthereturnfromthesnow/iceinterface.Duetotherelatively
R and R are the Fresnel reflection coefficients (at nadir
shallow(≈100mm)snowcoveroverAntarcticseaice,which a/s s/i
incidence)attheair/snowandsnow/iceinterfaces,respectively.
isalsoquitefrequently subject todeformation and, hence, has
Using(1)andsubstitutingforP andP from(2)and(3),
s/a s/i
anuneven surface,thechance ofanoff-anglefacetmayresult
theconditionforunambiguousidentificationofthereturnfrom
inashorterpathdelaywhencomparedtothenadirpathlength.
thesnow/iceinterfacebecomes
Underthesecircumstances,toachieveunambiguousidentifica- (cid:2) (cid:3) (cid:2) (cid:3)
tion of the air/snow and snow/ice interfaces, itis required that R2 P < 1−R2 P R2 1−R2 (4)
a/s inc a/s inc s/i a/s
the power level of the air/snow (P ) interface be lower than
a/s
thatcomingfromthesnow/ice(P )interface or
s/i
(cid:2) (cid:3) (cid:2) (cid:3)
P <P (1) R2 P =K 1−R2 P R2 1−R2 (5)
a/s s/i a/s inc a/s inc s/i a/s
whichisshowninFig.2.Ifthisconditionisnotmet,thereturn whereK istherelativepowerfactor,introducedheretomodel
fromthesnow/iceinterfacewillnotbeidentifiablefromtheoff- thedegreetowhichthepowerisdividedattheinterfaces.Pro-
nadirreturnsfromtheair/snowinterface(seealso[24]). vided that K <1, this relationship summarizes the conditions
necessaryforunambiguousidentificationoftheinterfaces.
Quantifyingthisrelationshipallowsforanassessmentofthe
III. MODELINGTHECONDITIONSFORSNOW
likelihoodofthisconditiontobesatisfied.Therefractiveindex
INTERFACEIDENTIFICATION
of air is conventionally equal to unity, and the literature [25]–
Provided that the refractive index is the sole parameter [27],[29]summarizestherangeoflikelyvaluesforns (snow)
affectingthedistributionofpowerbetweenreflectionandtrans- andni(seaice)tobe
missionofincidentelectromagneticradiationattheinterfaceof
n :1.2→2.0
two media, the upper bound on the reflected power from the s
air/snow and snow/ice interfaces can be derived. Referring to n :3.1→3.5.
i
6 IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012
terfaces assuming smooth surface conditions. However, this
is unlikely to be the case for sea ice and its snow cover,
and it is the surface backscattering coefficient which is the
most appropriate for capturing the amount of reflected power
from these rough surfaces. The generally quoted empirical
model for the backscattering coefficient of snow covered ice
is[25]
(cid:4) (cid:5)
1
σ0(θ)=σ0 (θ)+T2 (θ) σ0 (θ(cid:4))+ ·σ0 (θ(cid:4))
a/s a/s sv L2(θ(cid:4)) s/i
(6)
with ice volume scattering neglected and where σ0 (θ) is
a/s
the backscattering coefficient for the snow surface, i.e., the
Fig.4. Snowrefractiveindexasafunctionoficerefractiveindexrequiredto air/snow interface, σs0v(θ(cid:4)) is the backscattering coefficient for
satisfyunambiguousrelativepowerrequirements. the snow volume, σ0 (θ(cid:4)) is the backscattering coefficient
s/i
for the ice surface, i.e., the snow/ice interface, T (θ) is
a/s
the Fresnel transmission coefficient at the air/snow interface,
L(θ(cid:4)) is the one-way propagation loss through the snow, θ
is the incidence angle, and θ(cid:4) is the refraction angle in the
snow. In the aforementioned equation, signal attenuation in
the snow pack is neglected, and only the dry snow case is
considered.
However, the aforementioned equation aggregates the sur-
faceandvolumescatteringcontributionsintoasinglebackscat-
teringcomponentandrepresentsthetotalbackscatteredpower
thatisreceivedattheradaroverthewholechirpduration.This
radar, however, is sensitive to the time delay of the backscat-
ter during the chirp. Incorporating this time dependence, the
Fig.5. Icerefractiveindexasafunctionofsnowrefractiveindexrequiredto backscatteringcoefficientisrewrittenas
⎧
satisfyunambiguousrelativepowerrequirements.
wairhC/isconhnosweidxaeanrmidningsenthotewhme/icocedaesinletceowrnfhadecinteisotnahsreeofpeoKqwuae=lra1rn.e0dtuawrnnhdseKnfrto=hmer0e.t1hi5es σ0(θ,τ)=⎪⎪⎪⎨⎪⎪⎪⎩τσ(cid:10)=τa03/τs1T,a2/(cid:13)s(θ,τsv)(cid:11)(cid:14)σs0v(τsv)(cid:12), ττ11≤≤tt<<TTpp−−ττ31
T2 (θ) σ0 (θ(cid:4)) , τ ≤t<T −τ
approximately an 8-dB difference, Fig. 4 shows the range of a/s s/i 3 p 3
the refractive index of snow given the range of the refractive (7)
index of ice that satisfies these conditions. The results in the
where t varies over the chirp duration 0<t<T , τ corre-
figureindicatethatitisnotunrealistictoassumeahigherpower p 1
spondstothedelayinthesignalduetotheseparationbetween
returnfromthesnow/iceinterfacecomparedtothereturnfrom
the radar and air/snow interface, τ corresponds to the delay
the air/snow interface. However, it should be noted that this sv
in the signal due to volume scattering events (that can occur
modelalsoexposesthehighsensitivitytosmallchangesinthe
anywhere between τ and τ , as is indicated by the sum), and
refractiveindexofsnow,asmallchangewhichcannecessitate 1 3
τ corresponds to the delay in the signal due to the separation
an unrealistically high refractive index for ice to maintain 3
between the radar and ice/snow interface (incorporating the
unambiguous detection ability, shown in Fig. 5. Furthermore,
changeinpropagationvelocity).
the two figures together provide a picture of the range of the
The purpose of the radar is to find the snow thickness and
refractive index for snow which will allow the underlying sea
thereby find the time separation between the air/snow inter-
ice to be detected by the radar. Admittedly, these calculations
face component (σ0 ) and the snow/ice interface component
are only applicable under dry snow conditions. If the snow a/s
(σ0 ).Aspreviouslydemonstrated,forunambiguousdetection
is wet, attenuation of the signal may limit or prevent signal s/i
of the air/snow and snow/ice interfaces, it is imperative that
penetration and reflection. In cases of flooding of the sea ice,
the snow/ice interface has a higher backscattering component
itsreflectioncoefficientwillincrease;however,subsequentand
relativetotheair/snowinterface.
likely wicking of the salty brine into the snow cover could
In the sections to follow, the roughness conditions of
prevent penetration of the radar signal into the snow cover
the air/snow and snow/ice interfaces will be found, and
completely.
the approximate backscattering coefficient for the two in-
terfaces will be calculated, demonstrating that the radar
A. BackscatteringCoefficientEstimation
under the presented experimental conditions was indeed
The previous section considered the upper bound on the able to unambiguously identify the air/snow and snow/ice
power distribution between the air/snow and snow/ice in- interfaces.
GALINetal.:VALIDATIONOFAIRBORNEFMCWRADARMEASUREMENTSOFSNOWTHICKNESSOVERSEAICE 7
Fig.8. Insitumeasuredsnowdepthdistributionmapoftheexperimentalarea.
Fig.6. SchematicoftheRadar-AeiralPhotography-Pyrometer-LaserScanner
helicopterinstrumentarrangement.CourtesyofJ.Lieser. schematicofthemarkedareaindicatingtheflightlines(Aand
B),andbelowthat(Fig.8)isamapoftherecordedsnowdepth
inmillimeters.Theaverageairtemperaturerecordedacrossthis
areais−10◦C;consequently,itisassumedthatthesnowpack
haslowmoisture[30].
A. ExperimentalDescription
The radar was flown over the lines marked A and B, at two
different altitudes, and three times over at each altitude. This
wasdoneinordertominimizethepossibilitythattheextracted
snowthicknesssamplesfromtheradardatawerecorruptedby
biases,duetosystematicand/orotherwiserandomerrorinthe
data, and any postprocessing algorithms. The data presented
here will be for flight line A where the maximal variability in
snow thickness is measured by the in situ results. This is for
thereasonthatthesnowvariabilityisquitesmall(maximumof
300 mm), which indicates, at most, an eight-range-bin distri-
bution, and in line B, there is no clear snow thickness pattern
as that present in line A. The comparison between 50- and
Fig.7. Schematicoftheareaneartheshipwhereinsituandflightexperiments 100-m altitudes is made to gauge the relative contribution of
wereperformed.
possible (probable) errors in the helicopter operation (such as
off-nadirpointing,off-trackflightline,andvibration),aswellas
IV. EXPERIMENTALSETUP
tomakeacomparisonbetweenthecontributionsofthedifferent
Theradar,togetherwithalaseraltimeterdifferentialinertial roughnessscalesofthesnowandicesurfaces.
navigation system and a camera, was installed into an instru- An estimate of the roughness conditions of the overflown
mentation helicopter operated by the AAD. Fig. 6 shows a surfaces is provided by the laser altimeter. The laser range
schematic of the helicopter (Eurocopter AS-350 BA “Squir- measurementsareusedforapproximatingtheaveragestandard
rel”), illustrating the location of the equipment. The addition deviation of the surface height at the operating altitudes of 50
of a laser and a digital camera to the radar data allows for and100m.Atthesealtitudes,thelaserspotsizesare0.23and
a multifaceted survey of the surface conditions to be made. 0.06m2,respectively;consequently,thereturnsareconsidered
The helicopter was taken on board the first voyage of the point measurements of the surface height. The difficulty with
2008AuroraAustralisRSVresupplyduringthe2008seasonto the laser sampling of the surface is that, due to the variation
EastAntarctica,visitingtheAustralianAntarcticStationDavis, in speed of the helicopter, the spatial frequency (distance) of
situated68◦35(cid:4) S,77◦58(cid:4) E.Only24hwasallocatedtoscience sampling is not constant—consequently, it is not possible to
during the voyage, and flights were planned over the pack ice directly retrieve the correlation length. However, calculating
as the ship approached the Davis Station. However, due to the standard deviation of the surface height across increasing
logistical difficulties, flight time was only available once we distances(asshowninFig.9)allowsforanindirect/first-order
hadapproachedthefast-icezone. measureofthecorrelationlengthofthesurfacetobeestimated.
Experimental flights conducted with the helicopterborne The reason that the altitude must be specified in deriving the
radar were made over a marked out area of 200 m × 80 m, standard deviation values is that the active area of the radar at
approximately 100 m away from the ship. In situ snow thick- thesealtitudesundersamplesthesurfaceroughnessofthesnow.
ness measurements were taken every 2 m, snow temperature ThisfactisalsoshowninFig.9,wherethehelicopteroperating
every10m,andsnowdensityevery20m.Fig.7showsabasic altitudeplacestheactiveareaoftheradaratthechangingslope
8 IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012
Fig.9. Fast-iceexperimentallyderivedstandarddeviationvaluesofsurface
roughness. Fig.10. Calculatedσ0forfastice.
of the curve. Using this figure, the average expected standard
deviationisfoundtobe9.5and10.5mmforthe50-and100-m
operatingaltitudes,respectively.
These values are used to approximate the backscattering
coefficientbasedonthesurfaceroughnessparameters[28],[29]
σ0 =|R|2e(−2g) (8)
wheregisknownasthespecularreflectioncoefficientreduction
factorandgivenin[28]as
√ σ
g ≡2π (9)
λ
Fig.11. Echogramofrawradardatacollectedovertheinsitustudiedarea.
whereσisthestandarddeviationofsurfaceheightandλisthe
wavelengthoftheemployedradiation.Fromthisapproximation
for the backscattering coefficient, it is likely that roughness
properties of the air/snow and snow/ice interfaces will play
a significant role in the ability of the radar (particularly at
the wavelengths used, i.e., 50–150 mm, due to the fact that
they are comparable with the roughness features themselves)
tounambiguouslydetectair/snowandsnow/iceinterfaces.
Fortunately, it can be asserted that, under similar roughness
conditions,theinterfacewiththegreatestdielectriccontrastwill
lead to greater degree of scattering [31], [32]. Consequently,
the condition for the air/snow interface to have a lower power
return than the snow/ice interface is not unrealistic. Provided
that the flights were conducted over the fast-ice zone, it was
consideredappropriatetospecifytheroughnessofthesnow/ice Fig.12. Echogramofradardataoverinsitustudiedareaafterapplicationof
linearizingalgorithm.
interface as less than that recorded for the air/snow interface.
Fig.10showstheapproximateexpectedbackscattercoefficient can be inverted. The principle behind the algorithm written to
fortheair/snowandsnow/iceinterfaces,demonstratingthatitis undotheeffectsofthenonlinearitiesistousethephasehistory
likelythatthesnow/icebackscatterisgreaterthantheair/snow of a fixed target (a copper coaxial delay line) inserted into
backscatter. the system between the transmit and receive paths to linearize
Threeflightsforthelineatthe50-maltitudeandthreeflights thephasehistoryofthereceivedreflectionsfromtheunknown
at the 100-m altitude were identified as the flights suitable for targets.Metaetal.[34]andVossieketal.[35]describesimilar
validationpurposes.Fig.11showstherawradarechogramfor nonlinearitycorrectingalgorithmsforFMCWradar.Themain
a flight at the 50-m altitude, approximately over the in situ point to note is that the nonlinearities are systematic and their
sampled area. It is very difficult to identify the air/snow and effect is range dependent; consequently, the same radar may
snow/icereflectionlineswithfineresolution.Thecauseofthis workfromasledplatformwhentherangebetweenthetransmit
has been identified to be the frequency generator which pro- and receive antennas is less than 2 m but fail to work from a
duces the 2–8-GHz sweep and is a common cause of problem helicopterplatformwhentherangetothetargetexceeds50m.
in wideband FMCW radar [33]. Fortunately, this also means Fig.12showsthesameradardataafterapplicationofalineariz-
thattheerrorismostlysystematicinnatureand,consequently, ingalgorithm.
GALINetal.:VALIDATIONOFAIRBORNEFMCWRADARMEASUREMENTSOFSNOWTHICKNESSOVERSEAICE 9
Fig.15. Insitumeasuredtemperatureprofileovertheline.
Fig.13. Insituandradardatacomparison,forthreepassesat50-maltitude.
Plottedasafunctionofdistancealongthe200-mtransect.
Fig.16. Insitumeasuredsnowdensityprofileovertheline.
the similar locations of two sections where very little snow
Fig.14. Insituandradardatacomparison,forthreepassesat100-maltitude. thickness is observed in the middle of the prominent snow
Plottedasafunctionofdistancealongthe200-mtransect.
moundpresentalongthelinearebetween90,110,and125m.
Toextracttheair/snowandsnow/icedata,asimpleautomatic This could be explained by the presence of icy/hard surfaces
peakpickingalgorithmisapplied.Thefirstpeakisfoundasthe of the wind-packed snow. The presence of these features can
oneoflargestamplitude,andthen,localizationofthesecondis perhaps just be identified in Fig. 12 at times of 3 and 4 s.
made to the left of the first one, no less than 10 dB below in Thesesignificantlylimitthepenetrationoftheradarsignalinto
amplitude[36].Then,aconditionisappliedthatthepeakmust thesnowpack,hencetheabsenceofadistinctsecondsurface.
remaininthesamelocationforaslongastheradarfootprintis It is likely that icy layers are the cause of the fading, as the
samplingasimilarsurface.Inthisparticularcase,thiscondition dataarecollectedoverfastice,whereinsitumeasurementsde-
leads to the expectation that the peaks will maintain the same tectedmanyhardandwind-packedsurfaces.Overall,thedirect
location for three consecutive radar returns. The radar travel correlation coefficients calculated at the two altitudes are 0.53
timethusderivedisconvertedintosnowdepthusinganaverage and 0.57, respectively, which are statistically significant (p≤
snowdensityof300kg/m3.Thiswasjustifiedbystudieswhich 0.0005). The differences between the results from the flights
showedthat,withashallowsnowpack,alargeerrorindensity at different altitudes are very little, and this can be explained
canbetoleratedwithouttheradarreturnmovingbyarangebin. by the fact that the operating conditions of the radar change
little, with the active area not changing substantially enough
for a significant change in surface roughness characteristics.
V. RESULTS
Additionally, it points to the fact that it is probable that the
Figs. 13 and 14 show a comparison of the averaged snow helicopterinstabilityisthedominantcontributortotheerror.
thicknessvaluesoverthethreepassesfor50and100m,withthe Applyingafive-pointmovingaveragefiltertotheradardata
in situ values over the 200-m transect. (Figs. 15 and 16 show increases the correlation with the in situ data to 0.8 in both
the temperature and density profiles measured over the line.) cases. Results from a linear regression analysis are shown in
The substantial deviation between the in situ results and the Fig.17.Thegradientoftheregressioncouldbeexpectedtobe
radardataforthe50-maltitudereturnsfrom120monwardto 1.0, and it is seen to deviate from this value. The main reason
theendofthe200-mtransectmaybeaproductofgeolocation for this could be due to an incorrect selection of the mapping
error, due to the fact that this is present in all of the three coefficientbetweenrange-binvaluesintheradarandtheactual
passes. Additionally, it is interesting to observe the consistent measured snow thickness values. However, if this coefficient
presenceofthreepeaksinbothfiguresinthemiddlesectionof is changed to force the gradient to be 1.0, the residual norm
the transect at approximately 90 and 130 m. Correspondingly, increases from 0.168 to 0.182, possibly indicating that the
10 IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012
Fig.18. Estimatedroughness(asrmsheight)derivedfromtheradardatafor
theair/snowandsnow/iceinterfaces.
Fig.17. Linearregressionanalysisoftheradarandinsitudata.
copterborne platform has not been demonstrated. The reason
gradientdeviationisageneralbiasintheradartowardsmaller forthisisaproductoftwoprimarydifficulties:
range-bin selection. This bias could be explained by the fact 1) geophysicalfeaturesofseaiceanditssnowcover;
that the radar is unable to penetrate the frequently present icy 2) instrumentationdifficulties.
orslushlayerattheinterfacebetweenthesnowandice,which
Thefirstproblemcapturesthesuiteofdifficultiespresented
apersonwitharulerstickisunlikelytodetect.
by particular conditions of sea ice and its snow cover in the
Antarctic where it is frequently wet, icy, rough, and relatively
A. ErrorAnalysis thin (order of tens of centimeters), hence requiring a small
viewingaperture,highresolution,andhighincidentpower.The
The availability of in situ data for the flights allows for
second problem refers to the difficulties in obtaining a high-
accuracy analysis of the radar system to be estimated, under
resolution instrument and, then, the subsequent difficulties in
the assumption that the correct (accurate) snow thickness was
validating helicopterborne data which are a highly unstable
providedbytheinsitudata.Thepercentageerrorbetweenthe
platform, particularly when aiming for centimeter-scale ver-
insituandradarderivedsnowthicknesses(withthesmoothing
tical resolution. Overcoming these difficulties, this paper has
applied) was calculated over the transect length and averaged
presentedastep-by-stepanalysisofthecompleteradarsystem
over the active area, and it was found to be approximately
and a validation process of the radar and in situ derived snow
±17%.Itmustbequalifiedthatthiserroristhecompletesystem
thicknessdata,witharadarsystemofaccuracyof17%.
error incorporating in itself all the possible sources of error
Given the large beamwidth of the radar, coupled with the
in both the instrument and subsequent analysis, including the
large bandwidth (for high vertical resolution), the necessary
following: vibration, off-nadir attitude, residual nonlinearities,
condition for unambiguous identification of the air/snow and
clutter,andprocessingerror.
snow/ice layers is presented. The condition is strongly sensi-
Inthefuture,itwouldbedesirabletoperformananalysisinto
tive to the surface roughness features; however, the laser data
thesensitivityoftheinstrumenttothemainerrorsources;how-
and simple approximation calculations for the backscattering
ever,atthisstage,itwasnotfeasible.Additionally,ananalysis
coefficient demonstrate that, at least, over the site chosen for
intothenatureoftheaveragingorintegrationperformedbythe
study, the condition is satisfied. However, extension to further
radaroftheair/snowandsnow/icesignalsovertheactivearea
areas, and particularly into the pack ice zone, where rough-
footprint into a single value should be conducted in order to
ness is expected to be much greater, requires improvement of
determinethemaincontributingfeaturesofthemedia.
the instrument performance, namely, decreasing the antenna
Itshouldalsobementionedthatacorrelationof1.0between
beamwidth.
theinsituandradardata,infact,shouldnotbeaimedforand
AnextensionoftheutilizationoftheFMCWradardatasetis
could, in practice, rarely be achieved. The reasons for this are
exploitingthefactthattheradarreceivesreturnssimultaneously
that the radar’s view of the world and a ruler measurement of
and independently from the air/snow and snow/ice interfaces.
snow thickness could not even theoretically be in one-to-one
Hence, the relative roughness features of the snow cover and
correspondence. The radar signal may be affected by an icy
underlyingseaicecanbeextracted.Thisisnotcurrentlyavail-
layer and increased wetness or salinity within the snow pack,
able in any other remote sensing data set and provides much
whichahumanmaynotobserve.
needed insight into the hypothesized relationship between ice
roughnessandsnowthickness,aswellasfurtherstudyintothe
AMSR-Esnowthicknessextractionalgorithm,anditssensitiv-
VI. SUMMARYANDDISCUSSION
itytoroughness.Fig.18showsthecalculatedrelativeestimates
To date, while it is theoretically assumed possible, snow oftheroughnessasafunctionofincreasingintegrationlength,
thickness extraction over sea ice in Antarctica from a heli- showing that the air/snow interface is rougher than that of the
GALINetal.:VALIDATIONOFAIRBORNEFMCWRADARMEASUREMENTSOFSNOWTHICKNESSOVERSEAICE 11
underlyingice,whichisinagreementwiththeobservationsof [17] P.Kanagaratnam,T.Markus,V.I.Lytle,B.Heavey,P.Jansen,G.Prescott,
thisfast-icearea. andS.P.Gogineni,“Ultra-widebandradarmeasurementsofthicknessof
snowoverseaice,”Trans.Geosci.RemoteSens.,vol.45,no.9,pp.2715–
Futureengineeringworkontheradarwillbeaddressingthe
2724,Sep.2007.
antenna design and mounts in order to increase their stability, [18] J. Holmgren, M. Sturm, N. E. Yankielun, and G. Koh, “Extensive
as well as the linearity of the frequency modulation from 2 to measurements of snow depth using FM-CW radar,” Cold Regions Sci.
Technol.,vol.27,no.1,pp.17–30,Feb.1998.
8 GHz, and increasing the number of chirps transmitted per
[19] T. Rink, P. Kanagaratnam, D. Braaten, T. Akins, and S. P. Gogineni,
second in order to improve the radar accuracy and precision “A wideband radar for mapping near-surface layers in snow,” in Proc.
ofthecoupledradar–helicoptersystem. IGARSS,Denver,CO,2006,pp.3655–3657.
[20] H.P.Marshall,K.Birkeland,K.Elder,andT.Meiners,“Helicopter-based
microwaveradarmeasurementsinalpineterrain,”inProc.Int.SnowSci.
Workshop,2008.
ACKNOWLEDGMENT [21] N.E.Yankielun,“Anairbornemillimeter-waveFM-CWradarforthick-
nessprofilingoffreshwaterice,”CRREL1992.
The authors would like to thank J. L. Lieser (Antarctic [22] R.Willyard,“AirborneRadarforMeasuringSnowThicknessOverSea
Climate and Ecosystems Cooperative Research Centre) and Ice,”M.S.thesis,Univ.Kansas,Lawrence,KS,2006.
[23] G.M.Brooker,“UnderstandingmillimeterwaveFMCWradars,”inProc.
P. Jansen for collection and processing of the LiDAR data set
ICST,2005,pp.152–157.
andthekindreleaseforthisstudy. [24] S.P.GogineniandG.E.Prescott,“ValidationofAMSR-Esnowdepthon
seaiceretrievalsusinganairbornepulseradar,”RadarSyst.RemoteSens.
Lab.,2001.
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[13] R. Massom, A. P. Worby, V. I. Lytle, T. Markus, D. Yi, K. Tateyama,
H.Enomoto,A.Steer,andJ.Zwally,“Earlyspringtimesnowcoveron
EastAntarcticseaice,ARISE2003:Variabilityandsatellitevalidation,”
Ann.Glaciology,vol.44,no.1,pp.288–296,2003. NataliaGalinreceivedtheB.Eng.degreeinelectri-
[14] C. J. Leuschen, R. N. Swift, J. C. Comiso, R. K. Raney, calengineeringfromTheUniversityofNewSouth
R.D.Chapman,W.B.Krabill,andJ.G.Sonntag,“Combinationoflaser Wales,Sydney,Australia,in2006.HerPh.D.work
andradaraltimeterheightmeasurementstoestimatesnowdepthduring wasaimedatmeasuringsnowthicknessonseaice
the2004AntarcticAMSR-ESeaIcefieldcampaign,”J.Geophys.Res., over Antarctica from a helicopterborne frequency
vol.113,no.C4,p.C04S90,2008. modulatedcontinuouswaveradar.
[15] H. P. Marshall and G. Koh, “FMCW radars for snow research,” Cold She is currently a Postdoctoral Research Fellow
RegionsSci.Technol.,vol.52,no.2,pp.118–131,Apr.2008. with the Centre for Polar Observation and Mod-
[16] G.Koh,N.E.Yankielun,andA.I.Baptista,“Snowcovercharacterisa- elling, University College London, London, U.K.,
tionusingmultibandFMCWradars,”Hydrol.Process.,vol.10,no.12, wheresheisworkingonCryoSat-2data,measuring
pp.1609–1617,Dec.1996. changesinice-sheetmassbalance.
12 IEEETRANSACTIONSONGEOSCIENCEANDREMOTESENSING,VOL.50,NO.1,JANUARY2012
Anthony Worby received the B.Sc.(Hons.) degree CarlLeuschenreceivedtheB.S.andM.S.degrees
inoceanographyandmeteorologyfromtheFlinders in electrical engineering from The University of
University of South Australia, Adelaide, Australia, Kansas,Lawrence,in1995and1997,respectively.
and the Ph.D. degree from the University of Since 1995, he has been with the Radar Sys-
Tasmania,Hobart,Australia. temsandRemoteSensingLaboratory,Universityof
He is currently the Program Leader for Climate Kansas, where he was a Graduate Teaching Assis-
Processes and Change theme with the Australian tantfortheSensorDesignLaboratory.Hisresearch
AntarcticDivision,Kingston,Australia.Hisparticu- interests include ground-penetrating radar, numer-
larinterestincludestheroleofseaiceintheclimate ical electromagnetics, and signal processing with
systemandthethicknessdistributionofseaiceand emphasisonwavemigrationandsyntheticaperture
snowcoveraroundAntarctica. radar.
PrasadGogineni(M’84–SM’92–F’99)receivedthe
Ph.D.degreeinelectricalengineeringfromtheUni-
ThorstenMarkusreceivedtheM.S.andPh.D.de- versityofKansas,Lawrence,in1984.
grees in physics from the University of Bremen, HeiscurrentlyaDeaneAckersDistinguishedPro-
Bremen,Germany,in1992and1995,respectively. fessor with the Department of Electrical Engineer-
He is currently the Head of the Cryospheric ing and Computer Science, University of Kansas,
Sciences Branch, Hydrospheric and Biospheric Lawrence,whereheisalsocurrentlytheDirectorof
SciencesLaboratory,GoddardSpaceFlightCenter, theNationalScienceFoundationScienceandTech-
National Aeronautics and Space Administration, nologyCenterforRemoteSensingofIceSheets.He
Greenbelt,MD.Hisresearchinterestsincludesatel- hasbeeninvolvedwithradarsoundingandimaging
lite and airborne remote sensing of cryospheric, oficesheetsformorethan15yearsandcontributed
oceanic,andatmosphericprocesses.HeistheProject tothefirstsuccessfuldemonstrationofsyntheticapertureradarimagingofthe
ScientistforICESat-2. icebedthroughmorethan3-km-thickice.