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Open Access 3 Discussions The Cryosphere , and M. Davidson 2 1832 1831 , H. Skourup 1 , V. Helm 1 , S. Hendricks 1 This discussion paper is/has beenPlease under refer review to for the the corresponding journal final The paper Cryosphere in (TC). TC if available. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research,DTU Bremerhaven, Space, Copenhagen, Denmark ESTEC, Noordwijk, the Netherlands ties related to snow and ice properties. Our study shows that the choice of retracker ment. In this paper80 we % apply of a the first retrackercurrent algorithm maximum literature. of with For radar thresholds the echo oflies 40 % power, 40 at spanning %, threshold a the 50 we certain % range assumecoincident depth and of that CryoSat-2 between values the the and used main surface airborne in scattering andthe laser snow-ice horizon 50 altimetry % interface measurements. as and This verifiedscattering 80 % contrasts through horizon thresholds with similar where to otherevaluate we the published assume uncertainties studies. the of Using trends ice-snow thearise in selected interface from sea-ice retrackers as the freeboard we choice the and of higher main the level retracker products threshold that only, independently from the uncertain- the freeboard to thickness conversion.height Besides and uncertainties limited of knowledge thesignal of actual ice into sea-surface and the snow snowThis properties, cover has the and consequences penetration therefore in of the thethe the selection interpretation of radar main of retracker scattering algorithms radar which horizon echoes are and is used to crucial. assign track a range estimate to each CryoSat measure- satellite altimetry. In thisequipped context with the the CryoSat-2 Ku-band SAR satellitefreeboard radar was altimeter defined SIRAL, launched as which the in we height 2010text use of to and of the derive ice is quantifying sea-ice surface Arctic abovewas the ice-volume launched local decrease sea in at level. 2010 In globalwhich and the we scale, is con- use the to equipped derive CryoSat-2 with sea-icethe satellite the freeboard sea defined Ku-band as level. SAR the Accurate height radarsurface CryoSat-2 of altimeter in the range SIRAL, ice the measurements surface order above over of open centimeters water are and necessary the to ice achieve the required accuracy of Several studies have shown thatis there is thinning considerable during evidence that thetion the last of Arctic decades. sea-ice ice-covered When areasensing combined this technique with capable leads the of to observed quantifying a this rapid decline ice reduc- in volume sea-ice decrease at volume. global The scale only is remote 1 Germany 2 3 Received: 24 February 2014 – Accepted: 18Correspondence March to: 2014 R. – Ricker Published: ([email protected]) 2 AprilPublished 2014 by Copernicus Publications on behalf of the European Geosciences Union. Abstract Sensitivity of CryoSat-2 Arctic sea-ice volume trends on radar-waveform interpretation R. Ricker The Cryosphere Discuss., 8, 1831–1871,www.the-cryosphere-discuss.net/8/1831/2014/ 2014 doi:10.5194/tcd-8-1831-2014 © Author(s) 2014. CC Attribution 3.0 License. 5 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). The N was ◦ ). Together 2013 ). However, , ective retrack- ff 1999 2004 , , ), especially during ) used a half-power ) have been the first ects. There is already ff ). 2008 Laxon et al. 2013 ( , 2003 ; , 2011 , 2009 Rothrock et al. , Wingham et al. ). Therefore it is crucial to measure ). In order to map land ice elevations Laxon et al. N. A better coverage up to 86 Comiso et al. Laxon et al. ◦ 1992 , Willatt et al. 2014 , Kwok et al. ), the reduction of sea-ice volume in the Arctic 1834 1833 ected by clouds. The current satellite altimeter ff erent bursts by their doppler informations. The ff 2012 , Kurtz et al. Wadhams et al. ; erent retracker thresholds depending on seasonal properties ), however field experiments indicate that snow moisture and ff 2003 Stroeve et al. 1995 , , N. ◦ ) again focused on the lower part of the leading edge to minimize 2014 ( Laxon et al. Beaven et al. It has been suggested that Ku-Band radar waves do fully penetrate dry andThe cold main scattering horizon is estimated at the leading edge of the radar echo wave- CryoSat-2, a mission of the European Space Agency (ESA), was launched in April Basin-scale measurements of sea-ice thickness are currently carried out by satellite 2010 and isInterferometric equipped Radar with Altimeter). a Its rangeice Ku-Band retrieval freeboard, radar enables which the altimeter calculation issea-ice (SIRAL of the freeboard the – can height sea- be Synthetic of convertedlibrium Aperture the into ( sea-ice ice thickness, surface assuming hydrostatic above equi- the actual sea level. The possible with the ICESatsmaller mission, footprint which (70 m), featured but adedicated could laser be to altimeter a Cryospheric with science athe is significantly Arctic CryoSat-2, up which to provides 88 improved coverage of 10 km and an orbit coverage limited to 82.5 Sea-ice thickness is anin important its parameter seasonal cycle of maynotable the cause polar evidence significant negative cryosphere for feedback where thinning e changes of the Arctic sea-ice ( 2011 and November 2013. Furthermorefrom we March obtain 2013 a toGreenland significant and November increase the 2013 of Canadian freeboard in Archipelago.sumption that Since the applying this area di is for unlikelyof multi-seasonal it the gives snow sea-ice rise load north is to necessary the of in as- the future. 1 Introduction board, thickness and volume, butfected. that Specifically the we main find trends declines in10.9 of these % Arctic parameters (50 sea-ice % are volume less threshold) of af- 2013. 9.7 and % In 6.9 (40 % % contrast threshold), (80 to %threshold), that threshold) 25.71 % we between (50 find % March threshold) increases 2011 and in and 32.65 % Arctic March (80 % sea-ice threshold) volume between of November 27.88 % (40 % thresholds does have a non-negligible impact on magnitude estimates of sea-ice free- ing near the waveform peak ( retical considerations of SARlocated near altimetry the suggests peakthe that power case the and for main not conventional ata scattering the pulse-limited variety horizon half altimeters of is power assumptions ( point point is while on in used the a in leading recent literature. edge study as dedicated waveform fitting results in an e snow ( density layering may preventArctic a spring radar conditions over ranging multi-year through ice ( the snow toforms. In the synthetic ice aperture surface radarcollocated in (SAR) beams, altimetry, separated the waveform frommain consists di scattering of horizon a is stack obtained of old by a of retracker algorithm, the either an peak empirical power thresh- or an empirical approximation of the entire waveform. Theo- Helm et al. the main scattering horizon very accurately. spatial and temporal variations of the volume scattering contribution. The penetration with the rapid reductionthe summer of season ice-covered ( area ( can be used to calculate ice thickness ( ice volume are requiredimplications to for assess a current further changes reduction of of Arctic the sea-ice ice thickness cover. altimeter and its missions. Thements Altimetric of sea-ice freeboard, thickness the retrieval height is of based the on ice-surface measure- above the local water level, which might exceed the rate of ice extent decrease. Therefore, long term observations of sea- radar altimeters onboard thethat ERS were used missions for ( These Arctic pulse-limited sea-ice radar thickness retrieval, altimeters followed had by a the comparable EnviSat large mission. footprint of the order of 5 5 25 15 20 10 15 20 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) er- ff Helm 2014 ( erent ap- ff Kurtz et al. erent thresholds which span ect of the retracker threshold ff ff ). 2014 , ) to validation data from airborne experiments 1835 1836 Kurtz et al. 2013 erent altimetry sensor wavelengths we define the , ff ): 1 Laxon et al. erence of 12 cm between a 50 % threshold and a waveform fitting ff ). It involves an oversampling and a smoothing of the original waveform gives an outline of the steps in our data processing chain. To obtain radar 2 2014 ect of SAR waveform interpretation from other uncertainties in the freeboard to , from CryoSat-2 (hereafter called CS-2).snow But layer lower requires wave a propagation correction speed based in on the assumed snow depth and penetration. The ice freeboard refers to sea-ice freeboard asSnow defined freeboard: above. elevation of thetimetry. air/snow interface, which is sensed byRadar laser freeboard: since al- the main scatteringwith horizon the may ice not be freeboard, associated we directly use the term radar freeboard for range measurements ff Figure We obtain the two-way delay time of the averaged radar echoes (waveforms) by The conversion of freeboard to sea-ice thickness again depends on the correct Here, we present CryoSat-2 freeboard and thickness retrievals with the first consis- 1. 2. 3. terminology of freeboard (Fig. 2.1 Radar freeboard The term sea-iceabove freeboard the usually local refers sea to level. the With elevation di of the snow/ice interface 2 Data and methodology choice of the threshold or the empirical waveform fitting method. of the main scattering horizon below the snow surface depends significantly on the of the returning echo.the Since phase they information are are not discarded ( used in this study and to keep consistence, sides the SAR mode we alsoArctic use Ocean data and of in SARIn mode coastal for zones. a SARIn defined data area additionally in the contain western phase information freeboard it is necessarymain first scattering to relate surface. range We estimates use from geolocated the radar satellite echoes to provided locate by the the ESA. Be- applying a TFMRAet (Threshold-First-Maximum-Retracker-Algorithm) al. retracker ( and determines the first maximumstep by the derivative of leading the edgethreshold interpolated of of curve. In the the a maximum first second power. maximum We of choose the thresholds waveform of is 40 tracked % at (TFMRA40), a 50 % certain radar echo interpretation. We thereforerange investigate on the the e magnitude ofresulting Arctic trends. sea-ice volume in spring and autumn, but also on the of the local sea-surface elevation. knowledge of snow depthvery and well the constrained densities bysea-ice observations of thickness at data sea-ice ( basin-scale. and First snow, comparisons all of parameters CryoSat-2 not the e thickness conversion. We describe theborne datasets methodology and and other compare sea-iceent our remote uncertainty findings sensing sources products. to are weighted The air- andon contributions the of observable total di Arctic uncertainty sea-ice is analyzed volume for change its impact relative to assumptions to the CryoSat-2 found a mean di method with a nearthe peak choice scattering of retracker horizon addsdue during to the the to existing period increased uncertainty 2011–2013. of moisturearise physically Therefore or due limited penetration to ice variable lenses footprint in scale the surface snow roughness layer. and In inaccurate reconstruction addition, uncertainties and moorings show a goodison agreement reflect on the large residual scale,essential but uncertainties for scatter trend cited in estimates the above. insea-ice data Quantifying modeling sea-ice compar- these studies. and uncertainties the use is of CryoSat-2 data,tent for example uncertainty in estimates inproaches spring/autumn for 2011, waveform 2012 interpretation. and Wethe 2013, apply range using three of di di values2 found in Arctic literature sea-ice and volume access estimates. their The impact on goal trends of of our CryoSat- study is to isolate and quantify 5 5 10 15 20 25 10 25 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , (1) shows ) is sub- which is 3 Wingham K Laxon et al. 2010 , ) by a multipli- Wingham et al. ). We assume that 2013 ). We consider sev- ( 2014 Andersen usive radar returns over ( 1991 erent applied thresholds. the echo power at range ff ). It has to be noted that , ff i 2004 ( Laxon et al. Kurtz et al. Drinkwater -nadir reflections from leads can bias ; ff ) and ) of the power maximum of a waveform: nadir leads and hence are discarded. r ). O 1994 ff , cient accuracy. 1838 1837 2013 ffi ( 2006 , erent bursts. Specular reflections (narrow wave- gives an overview of these parameters and their ff Laxon 3 (2) 3 (3) 1 · Peacock and Laxon · ]) ]) ); 1 3 − + . The second parameter is the “stack kurtosis” max max Laxon et al. i i 2008 WF ( /N ,WF ,WF Wingham et al. WF erent notation of the pulse peakiness in contrast to 3 ) and on the “right” (PP 1 ff l N − + · max ). To identify echoes from the ocean we additionally consider the max erent shape of the radar waveforms. Radar echoes over open ocean i i ff i max(WF) max(WF) Giles et al. represents the number of range bins and WF 2012 WF ). It provides information about the “width” of the echo. Surface waves on , . Thus PP can be transferred to values in i WF max(WF) N 1 WF mean([WF = 1986 mean([WF i ): X N , ). Here the term “stack” refers to an assembly of beam echoes which steer to = = = l r For the coarse discrimination between ocean and sea-ice area (including leads) we Here This surface-type dependance of radar waveforms is traditionally used to automati- Then, by applying a lead detection algorithm, we automatically obtain the actual Second, the mean sea-surface height product DTU10 MSS ( Eastwood 2013 bin index tions in Helm et al. (2014), (TFMRA50) and 80 % (TFMRA80) of the first-maximum power to simulate the assump- “OCOG WIDTH”, which is derived from the algorithm of the OCOG retracker ( ination. Radar echoes that areor not “sea assigned ice” to are one assumed of the to surface be types biased “ocean”, by “lead” o PP use interpolated ice concentration( from the daily OSI SAF iceet concentration al. product the ocean cause a high OCOG WIDTH which can be used for the surface type discrim- refused by introducing abins modified on pulse the “left” peakiness (PP which considers only three range PP the range retrieval, since thewaveform. little Because area is those required echoes in do the not radar show footprint the to dominate typical the specular reflection they are PP assumed threshold values which“ocean”, “lead” are and used “sea to ice”.described We distinguish in use between the “pulse thewe peakiness” surface used PP types a that slightly has already di been ( echoes from sea-ice are defined bythe a “standard wider deviation” SSD shape provides and a thuswith measure a of incidence lower the peakiness. angle variation Further, in ( surface backscatter cation with a factor ofa 1 measure of peakiness2006 of range integrated stack powera distribution fixed ( point onforms) the from leads surface cause from a high di pulse peakiness as well as a small kurtosis. In contrast, eral waveform parameters that areputed either available from in the the raw waveforms. data Table files or can be com- ice floes usually havea far distinct mirror-like less specular surface reflection.snow waves On covered than the and other the roughened hand sea-icea open di surface significantly ocean lead di and to a thuswith wider higher feature angular significant distribution wave height and again show specific characteristics. cally classify leads in the ice pack ( tracted from the geo-located surface elevationsactual to sea-surface remove the height. main This contributionssea-surface of is cannot the be done obtained to with su reduce errors inelevation regions of where the sea the level in actual ice-free sections of the CS-2 ground tracks. Leads between the resulting range givesexemplary the CS-2 distance waveforms to for sea-ice theAs and main a leads scattering result and we horizon. the receive Figure geolocated di sea-ice. ellipsoidal elevations of CS-2 data for each orbit over 5 5 20 15 25 10 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) ). 3 (5) (6) (7) 2014 , 2m, since we < Matzler and Weg- R Kurtz et al. < F , which has not yet corrected ∗ is a seasonal function, taking R F , which were identified as sea-ice max L . The penetration is either the snow P ). Z 1 is obtained by a geometric correction cient retracking. For reasons of conve- ∗ of the CS-2 range retrievals depending R ffi F P ective scattering horizon is the ice freeboard ) and approximately 80 % ( ff 1840 1839 ). If the main scattering horizon is located in can be obtained by multiplying the uncorrected 3 − , depending on the retracker threshold. To make R F 2013 , max always to the local snow depth: P max P Laxon et al. max max may vary with season and region for reasons of density layering max P Z < P Z > P SSA) (4) : : P + · ), the correction can be applied by reducing the range below the snow/ice max 0.28 P Z P (MSS + + 1987 ( − ective scattering horizon of CS-2 range retrievals is the elevation that is obtained ( ∗ R R erent retracker thresholds and snow depths ff = F L F ff ) = = erent thresholds to track the ice freeboard as well as the actual local snow depth. In = Z We finally only allow freeboard values within the interval 0m We expect that Finally, the actual radar freeboard We therefore parametrize the penetration As the next step, the remaining anomaly from the mean sea-surface height (sea- ff ( ∗ S R R assume that those values originatenience and from comparison insu to freeboard retrievalthe from snow laser freeboard altimetry for (ICESat) further we compute conversion into sea-ice thickness: F rather wet snow. radar freeboard with a penetration correction factor for theF wave propagation: shallow snow cover, we limit P but also decreased permittivityinto of account wet the snow. winter Thus season with rather cold, dry snow and the melting season with fraction of penetration into the snow layer accordingly. on di depth or a maximum penetration sure that the penetration does not exceed the snow depth in areas or regions with a too low retracker threshold the snow propagation correction has to be reduced by the The surface-type classification parameters wereexemplary initialized CS-2 based ground on tracks manual where tuning coincident of aircraft validation data (see Sect. 2.1.1 Sea-surface anomaly interface by the ratio of(22 % vacuum speed for of a lightthe snow to snow density local layer, speed of either of 300 light to kgm in the the physical snow properties layer of the snow or due to the choice of In this case thefor uncorrected slower radar wave freeboard propagation speedmuller in the full snow layer. Regarding general earlier studies assume thatfor the thresholds e of 50 % ( were available.The ranges of theinterpolated retrieved open and water spots low-pass from filteredtrack, leads yielding over and the ocean a are sea-surface 25 anomaly kmelevation from (SSA), window. the the This mean deviation sea-surface is of height the done (Fig. actual for sea-surface each CS-2 F 2.1.2 Snow layer corrections The e by the various retracker thresholds whichagation have speed to be inside corrected the fordi the snow lower wave layer. prop- Thus we have to know the performance of the surface anomaly SSA) thatis is subtracted obtained from by the the retrackedin interpolated surface the elevations lead surface type and discrimination. oceanfor The elevations the radar lower freeboard wave propagation in the snow layer, is then yielded by: 5 5 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) (9) (8) 2012 Laxon , ): W ρ Wingham et al. ) with a resolu- Eastwood depending on the T 2012 , b shows the data mask 4 ). Furthermore a value of for first-year ice (FYI) and 3 − and the monthly mean thick- ) and sea water ( I ) suggest that though W99 is 2010 j ρ , c ) in the absence of year around a) Fig. 4 2011 Brodzik et al. ( 1999 , . ), sea-ice ( of 916.7 kgm W S I ρ ρ ρ n Bay (Fig. 1842 1841 ), we use the Warren snow climatology (W99) ffi Alexandrov et al. ) may have impacted the distribution of snow-depth Warren et al. 2013 ( Kurtz and Farrell 2007 , I ). Both snow depths and snow density are available as W ρ ρ ) can be converted into sea-ice thickness ), the sea-ice concentration − is also taken from the Warren snow-water equivalent clima- 2 − 7 1999 W S S , added up over the total number M of grid cells. The sea-ice ρ , ρ ρ j Laxon et al. · (Eq. N. Therefore we interpolate this region by applying a boxcar average Z S ◦ F + Nghiem et al. j I and the densities of snow ( ¯ T for multi-year ice (MYI) ( ρ · is taken for the water density Z 3 W − ) for CS-2 data processing. 3 A − · ρ − W j of grid cell ρ Warren et al. c j · 2013 1 ¯ T ( S = M j X F In order to estimate the Arctic sea-ice volume we need to fill the gap of the CS-2 data The snow density The snow freeboard to thickness conversion is applied for each individual CS-2 Corresponding to = = for one month are averaged on a EASE2.0 Grid ( Snow freeboard 2.2 Sea-ice thickness 2.4 Uncertainty of freeboard and thickness Besides the uncertainty arisingdent factors from impact the the accuracy choice of of freeboard and the thickness retracker retrieval. In thresholds, indepen- with the area Aness (625 km concentration c is afor re-gridded CS-2 product data of processing the along OSI the CS-2 SAF ground ice tracks. concentration that is used retrieval above 88 of the width of 375equal km area (15 projection, grid therefore cells) the to monthly the sea-ice thickness volume retrieval. V The can EASE2.0 be grid estimated isV as: an For the computation of sea-icesurface-type volume mask, of but the exclude Arctic theand Basin an Ba we exemplary apply monthly the averageclimatology ICESat/GLAS snow shows depth consistently field unrealistic snow from depths November in 2011, the where excluded the area. tion of 25 km, including radardata freeboard, products. snow depth, For sea-ice averaging thickness weprocessed and use data all points auxiliary the within arithmetic the meangrid boundaries which cell of is represents a calculated grid thethe from cell. mean open all For water value sea-ice fraction. thickness, of each data points classified2.3 as sea-ice only, Volume without estimates a monthly product. We use882.0 kgm ice densities ground track. We calculatea ice larger-scale thickness averaged snow fromcertainties freeboard an of in individual retrieved order thickness data after to point later allow spatial and estimation downsampling. not Only of after from individual that, un- data tology ( 1024 kgm recent decade ( in areas that arean now airborne more snow-depth often radar, still covered representable by for multi-year seasonal ice, sea-ice.regions but Based by snow depth 50 on %. has datamulti-year We to from be follow sea-ice reduced this using in approach first-year theand and ice daily apply classify ice the the snow-depth typeet ice reduction al. product cover accordingly. from in This first-year OSI step and SAF was ( introduced by snow-depth observations for the entireservations Arctic from Ocean. The drift climatologymulti-year stations is sea-ice. based in It on a is ob- period therefore likely were that the the Arctic reduction Ocean of was multi-year dominated sea-ice in by the for the estimation of snow depth ( snow depth T 5 5 20 15 10 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ), 3 (11) (10) ) and I ρ σ ): summarizes the 2007 2 , ). ), ice density ( Z 2 2013 σ ). Table ,  ects the freeboard retrieval Z ecting the thickness retrieval ff σ ff Giles et al. · 2012 )( , 8 ∂T ∂Z  SSA), a + + Laxon et al. ects the lead elevations as well as the 2 ff ) consider potential high level errors due  I ), snow depth ( ρ for an individual measurement is then ob- R σ F Kurtz et al. · T σ 1844 1843 I 2006 σ ( ∂T ∂ρ  ), the estimated speckle noise originating from in- + 1 m). However this was observed for pulse limited I + 2 ρ is computed by taking the standard deviation of the < 2 σ ·  2006 2 Z ( SSA + ρ  σ  σ · Z R that results from the potential radar penetration. Considering 2 · F S ) P σ Wingham et al. σ W ∂T + ∂ρ + ρ 2 2 P ) Z 2 I  Z 2 − ρ σ σ ρ ). For an uncertainty estimation of the sea-ice thickness we have to + σ  S · · · Z 2 − 2 ρ ρ 2 2 (   0.12 m for this contribution. It a W σ ). Furthermore there are contributions which arise from uncertainties in ). Finally   S I + Wingham et al. I I 2 F 6 SSA 8 ρ W ects the range measurements. Second, there is an uncertainty of the re- = ( ρ ρ ρ σ σ ff W ρ · − erent types of errors from CS-2 measurements over sea-ice have already W ρ − − l1b + − Z · S ff ρ σ W W W S S 2 l1b ∂T ρ ρ ρ F ρ ∂F σ ) di      = = = The uncertainty of sea-ice thickness Due to monthly averaging the uncertainties of the individual measurements are re- Regarding In this study we assume that these sources of uncertainty are independent ofThe re- uncertainty of radar freeboard is assumed to be governed by the radar speckle R 2 2 T F 2006 σ tained by applying propagation of uncertainty to Eq. ( individual radar freeboard measurement by adding the variances: ( snow density ( include the uncertainty comparisons between airborne laser and CS-2we radar altimeter assume measurements (Sect. an arcticvariability wide of uncertainty water of density 0.1 are m. neglected The ( contribution of errors due to the using uncertainties for radar freeboard ( σ contributions to the freeboard and thickness uncertainty estimates. duced, leading to the variance of grid cell of monthly mean freeboard and thickness only a first order approximationof resulting individual from error incomplete contributions. knowledge of the covariance and the accuracy ofdance the of actual detected sea leads,surface surface which anomaly. height. are The needed latter for depends an on accurate the interpolation abun- of the sea- mean sea surface heightdetected MSS. leads As along a a CS-2 consequence ground it track. rises We can with then decreasing estimate density the of uncertainty of an through Eq. ( tracker thresholds and uncorrelated in general. Though we acknowledge that this is value of ice floe elevations. The lead coveragetype. is The variable, depending SSA on season, uncertainty detected region lead and ice elevations within athe sliding moving 25 window km the window. uncertainty In is the given absence by of the leads deviation inside of the mean SSA from the been discussed. The first of whichnoise is and the instrument a system errorflection that occurs horizon as speckle dependinguncertainty on of the the physical actualthrough properties sea Eq. level of ( height the (MSS densities snow of the cover. sea-ice Third, layer and the snow loading, directly a strument system errorsmode is employed between (SAR 0.10 m or and SARin). In 0.14 m, this depending study on we the therefore use operating a constant average to limited recording ofradar altimetry thin and ice is still ( not clarified for CS-2 ( 5 5 15 10 20 15 10 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ∗ R F a). 5 (13) (12) , the of grid N M ) and assuming a sea- 9 1846 1845 0.05 for each grid cell, the Arctic sea-ice volume = 2   j 2 c ! j σ ! ¯ T j ¯ j σ T ¯ · T b originate from discarded CS-2 data that were biased by σ 5 j ¯ T

cient retracking and poor quality in the ALS data. Furthermore ∂V ∂ + ffi ). 2

of individual freeboard and thickness measurements and  i + T j , j 2 i c 2 F c 2002 σ i ! σ T , is obtained by: , j  i c 2 F V σ 2   shows ALS snow freeboard and CS-2 uncorrected radar freeboard σ σ · · 1 N j 2 5 = j N i V ∂V ∂c P 1 ) in a direct comparison, for which only valid data from coincident coverage are = M j X

4 = ¯ = = T , -nadir leads or insu In order to provide a consistent comparison with CS-2 measurements the ALS data Figure The laser scanner has been operated at an altitude of 300 m with around 370 shot In consistence with the CS-2 processing the geolocated ALS elevations have to be Airborne laser scanner (ALS) provide high-precision and high-resolution measure- Since 2005 the CryoSat Validation Experiment (CryoVex) is carried out over sea-ice ¯ 2 2 V F ff Forsberg et al. ( was mounted on board of the AWI aircraft “Polar 5”. ments and thus are capable toCryoSat-2. evaluate The measurements accuracy of for the the radar rangeitation altimeter measurements is SIRAL is due on about to a few GPS cm. positioning, The especially main lim- for a longer baseline of more than 100 km and two research aircraft were accomplished. Besides other sensors a laser scanner σ respectively : (Eq. considered. Gaps in Fig. o cover an area of 300the m by footprint 1000 m. geometry The andFinally averaging process therefore every is the averaged applied value coarser todata accommodate point. of resolution the of ALS CS-2 data measurements. is assigned to a corresponding CS-2 referenced to the actual sea surfacethe height. ALS Therefore elevation leads model. are picked Theshot manually sea-surface points out height by of is applying a thensubtracting spline determined the interpolation. sea-surface along height The the from snow center the freeboard geolocated is ALS then elevations. obtainedpoints by are weighted, depending onwe the assume distance to to the be respectivethe located CS-2 ALS in data data the point, are averaged that center over of the respective the CS-2 CS-2 Doppler Doppler cell, which cell. is In assumed the to following step points each scan linehas been and around a 1 m. point Intosections our spacing with analysis of a we include total around two lengthon 0.3 flights of m. 15 where about and we The 17 450 consider km spacing April profile in and along were coincidence operated track with from CS-2. the They Canadian took Forces Station place Alert (Fig. laser altimeter data to collocated CS-2 measurements. in the Northerncampaign Hemisphere in to the Lincoln directly Sea validate in spring CS-2 2011 products. the first During coincident the measurements by CryoVEx CS-2 In contrast to thefreeboard thresholds as the of main TFMRA50 scatteringinto and horizon, the we TFMRA80 have snow where toalways layer determine we referring the when assume to signal the the applying penetration snow ice the freeboard we TFMRA40 can retracker. accomplish Since that by laser comparing altimetry airborne is where the uncertainties of eachcells. grid cell are added up over the total number 3 Airborne validation ice concentration uncertainty uncertainty σ with variances number of measurements within a grid cell. Considering Eq. ( 5 5 25 15 20 10 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.31 m / ) of the entire er significantly 5 c. Here we use c (black dashed ff 5 6 b) shows a latitude- 6 erent thresholds (40 %, erent retracker thresh- ff ff 1 % in land-fast ice regions < shows some long scale agreement of summarizes the corresponding mean 5 3 results from the apparent penetration of the 0.3 m of FYI/MYI in March and 0.11 5 1848 1847 / set between snow and radar freeboard. This is ). We find a mean radar freeboard of 0.33 m in ff 3 0.18 m, that resulted from the direct comparison of CS- = we hence obtain the apparent penetration that also has to be max P ∗ R F c shows a monthly mean of MESOP ASCAT Backscatter from April 2011. d shows the lead detection map of April 2011. It illustrates the percentage shows the radar freeboard from March and November 2013 together with 6 6 set that we can observe in Fig. a shows the CS-2 mean radar freeboard retrieval from April 2011 using the ff 7 6 olds erences between ALS and CS-2 and obtain 0.225 m. Since we consider the uncor- Figure Figure The corresponding map of radar freeboard uncertainties (Fig. From simultaneous in-situ measurements on the ground we additionally know that The o ff dependent gradient. The mean uncertaintiesand for are FYI and around MYIthe 0.03 do m. Canadian not Archipelago Increased di and uncertainties land-fastcircle). ice of regions like up the to Laptev Sea 0.1 m (black dashed can be observed in mean radar freeboard of 0.21FYI m and for MYI seasonal we use ice a (FYI).OSI monthly For mean SAF the ice-type ice-type product. discrimination data During between are thefreeboard CS-2 interpolated data and along processing each thickness CS-2 retrieval groundEASE2.0 track. the grid As over interpolated for one the ice-type month. CS-2 data are averaged on the the multi-year ice (MYI) region north of Greenland and the Canadian Archipelago and ter contrast. The along track comparison in Fig. we additionally smoothed both data sets with a boxcar average of 10 km width for a bet- 4.2 Freeboard, thickness and volume retrievals from di Figure High backscatter indicatesbackscatter rather a indicates rather youngerserved in FYI. rough the East A surface Siberian slightly Sea.square), It and Increased occurs though as here freeboard higher hence this backscatter can in region MYI, Fig. be is slightly ob- whereas shifted to low of the leads west. within one gridof cell CS-2 as a measurements. fraction Fractions of ofSea lead-flagged up east waveforms to of of 15 the Svalbard. % total We canlike number also be the note found Laptev low in Sea lead (black the fractions dashed Barents of circle). and Kara the corresponding uncertainty maps,50 retrieved % and by 80 applying %) di forvalues the classified TFMRA retracker. into Table FYI andwe MYI. find Considering a the mean results radar of freeboard the of TFMRA40 0.17 retracker Arctic we used the value 2 and validation measurements (Sect. TFMRA40 retracker threshold. For the penetration parametrization (Eq. 4 Results 4.1 Radar freeboard retrieval Figure rected radar freeboard corrected for slower wave propagationthe in apparent snow penetration to by get 22 the % actual yields penetration. an Reducing actual penetrationthe of mean 0.18 m. snow depthTFMRA40 retracker exceeded the radar 0.3 m. doesface. not Therefore However penetrate it we the snow note is cover thatregion to also north this the clear of ice/snow comparison Alert inter- that might in be regarding spring. only the valid for the multi-year ice radar into the snowdi layer. To determine the penetration depth we average the mean between the mean snowtrack (ALS) 5399 and and 0.27 radar m (CS-2) along track freeboard 5428. we receive 0.18 m along a relative probability that reveals therepresents modal the freeboard level as ice. the peak The of tail the represents function the which fraction of deformed ice. As deviation the freeboard gradient, exemplary betweentrack 5428. 150 In and general 200 we km observealso track an shown distance o in on the ground corresponding probability density functions in Fig. 5 5 15 20 10 25 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3 × ± for km 3 3 4.82 2.22 m km / 10 ± 3 × 10 × 4.58 ± 4.28 0.16 m for FYI/MYI ± ). The TFMRA40 re- 0.79 m for FYI/MYI in − 4 / − . On the other hand the / 3 0.64 m in March 2013 and between March 2011 and 0.05 km / 3 − 0.61 3 0.05 m for FYI/MYI in Novem- the TFMRA80 retrieval shows − − 10 km 7 , not including the choice of the 0.26 / 3 3 × − 10 km 0.02 × 2.1 m in March 2013 and 1.25 3 − / for November. The uncertainties of the erent. For TFMRA40 the fraction of FYI 10 3 ff × 5.51 km ± 3 1850 1849 10 × er by less than 0.5 ff 4.79 ± the uncertainties of all products show increased values in 6 0.12 m for FYI/MYI in March and 0.22 m for FYI/MYI in March and . − 3 − / / km 3 0.08 0.81 . For TFMRA50 and TFMRA80 we find gradients with the same leading erent magnitudes. For TFMRA50 we observe a decline of 1.69 10 3 − − ff × shows the Arctic sea-ice volume estimates and corresponding uncertain- shows the sea-ice thickness from March and November 2013 together with km summarizes the volume estimates and the deviations relatively to the 2011 9 8 3 0.02 m for FYI/MYI in March 2013 and between March 2011 and 2013 and an increase of 2.62 4 − 0.12 m in November 2013. Conforming to Fig. 3 10 / / × km 3 Figure Table In conformance to Fig. Figure The TFMRA50 retrieval shows a higher contrast between MYI and FYI than it can We find a significant decrease of radar freeboard of TFMRA80 in comparison to For the TFMRA50 and TFMRA80 retrievals we assume that the ice/snow interface 0.23 0.03 for FYI/MYI between TFMRA50− and TFMRA40 are uncertainties in land-fast ice regions and a latitude dependent gradient. The deviations in November. Furthermorein the comparison TFMRA80 to uncertaintyremains. the map TFMRA40 shows and increased TFMRA50 values retrievals whilethe the land-fast ice general region pattern of the Laptev Sea as well as a latitude-dependent gradient. the TFMRA40 the TFMRA50lar patterns, radar in freeboard particular is− the slightly shape decreased, of butber the shows 2013. MYI The simi- region. TFMRA50 Theshow uncertainties the deviation are same to in pattern. TFMRA40 the is order of the TFMRA40the retrieval and TFMRA40 and TFMRA50deviations of retrievals. Between TFMRA80 and TFMRA40 we find increased radar freeboard north ofresponding Greenland uncertainties and generally the show Canadian an Archipelago. The increase cor- from March tois November. the mainfreeboard scattering and horizon. the In radar penetration this is case equal the to the radar full freeboard snow is depth. In equal comparison to to the ice of FYI/MYI in November. However in contrast to March the November retrieval shows 5 Discussion The comparison of theApril regional 2011 distribution with of ASCAT the backscatter data example CS-2 shows freeboard similar maps geographical of features. Since 2013 and an increasetotal of sea-ice 1.7 volume varyretracker between threshold. 2 and 3 total volume of the TFMRA80exceeds 10 is significantly lower than the other retrievals andretrievals. For never the TFMRA40 volume estimates webetween find March a 2011 decline of and 1.57 20134.11 while for November wesign observe but an of increase di of10 2.52 November and further a decline of 0.73 ties for March and Novemberthe 2011, chosen 2012 retracker and threshold 2013.TFMRA50 and They are are the very discriminated ice close regarding type. andratio The di between total FYI volumes and ofvolume MYI is TFMRA40 is always and significantly higher di than in both TFMRA50 and TFMRA80. We also note that the decreased sea-ice thickness compareddeviations to of TFMRA50 and TFMRA40.November Further between the we TFMRA80 find and TFMRA40 retrievals. be observed in thethe TFMRA40 same retrieval. features The again. uncertaintythickness In map comparison uncertainties for to both are the products increased corresponding shows freeboard by retrievals a the factor of around 10. Again we find high unrealistic snow depths weretrieval excluded reveals a by mean the sea-ice data thicknessin of mask November 1.97 2013. (Fig. The contrastis between rather low, the especially MYI in region March. north of Greenland and FYI the corresponding uncertainty maps. Areas where the climatology shows consistently 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | cient ffi . Increased ¯ T , ¯ 2 F σ erent retrack posi- ect ff ff ). d). The absence of leads 2013 over FYI, the parametriza- 6 , ) where we find similar vol- 9 max erent applied retracker reveals P ff Laxon et al. ), therefore orbit patterns may arise from ect on the thickness retrieval. While the ff 12 erent ratios between FYI and MYI volume. a) in both datasets and give confidence that ff 6 1852 1851 25 km grid cell. A higher number of measurements re- × ect of a higher than usual snow load in combination with ff ) has a significant e 5 erent numbers of data points per grid cell and thus a ff ). 3 ers in magnitude. Especially in November 2013 we observe a major increase of Considering the trends between 2011 and 2013 we find a decline of sea-ice volume The comparison of freeboard retrievals from the di In contrast to TFMRA50 and TFMRA80, we assume a partial penetration for Besides the freeboard and thickness data, we also calculated a first order estimation ff data and airborne and moored validation data ( in the sea-ice thickness retrievals is in the order of direct comparisons between CS-2 board should correlate. Local features like asea small are area visible of potentially (black MYI dashed in box the in Siberian Fig. MYI is usually associated with higher ASCAT backscatter both backscatter and free- can speculate that this ana limited e penetration of thevolume main scattering scattering caused surface by into ice the lenses snow due and to possibly non wet negligible snow in the beginning of the di radar freeboard in thecompared MYI to region previous north November ofthresholds. data This Greenland and can even and be March the consideredwinter 2013 Canadian as in season Archipelago unlikely freeboard and since maps March November of represents a all the period end shortly of the after beginning of the freeze up. We tion is always equalThis to is the also snow visibleumes depth in for which TFMRA40 the is and iceIn TFMRA50 done this volume but for study calculations di we TFMRA50 use (Fig. a andspatial simple constant TFMRA80. penetration values parametrization which which assumes canW99 temporal snow bias and depth, the depending thickness on result.period ice Furthermore and type limited classification, the area. might modified be only valid for a certain in March, but an increase in November. This counts for all applied thresholds and only the TFMRA40parametrization freeboard (Eq. andmodified thickness W99 snow retrieval. depth rarelytion The exceeds generates the only value nature a for partial radarto of penetration a of lower the the ratio snow load of penetration over MYI MYI. to This FYI can lead thickness compared to the assumption that the penetra- that despite variable thresholdsmean the values mean vary geographical with pattern changingtions the (Fig. is threshold preserved. as But a the result of the di are only weakly constrained bylimited observations, our mainly uncertainty in estimation Arctic to spring, a and first-order thus level. we But have the magnitude of uncertainty one grid cell, thefor uncertainty all contribution CS-2 data due pointsincluded to and within the not one lack reduced of month,melt by leads which and gridding. result would might Also in be temporal be visiblecovariances constant variations orbit-patterns significant are in between during the not uncertainty monthly freeze-up means. and contributions The summer temporal of and freeboard spatial and thickness retrievals duces the uncertainty of eachthe grid slightly cell di (Eq. uncertainties appear in land-fastof ice leads regions that like can theis be Laptev therefore seen the Sea in main because theof driver of extended lead of the land-fast detection the ice lack map regions. CS-2uncorrelated However (Fig. freeboard uncertainties we and do and acknowledge thus thickness that the uncertaintydescription the reduction of in by assumption certain averaging areas of might factors. be Foronly an example be insu the reduced uncertainty by of gridding sea-surface if anomaly enough can lead detections exist. If none are available within but it should be investigatedfreeboard in retrieval more in detail thin for ice a areas. potential improved lead detectionof their and uncertainties. The latitude dependentmeasurements gradient results within from a the 25km higher number of CS-2 is indeed ablecan to be capture seen actual inASCAT distribution backscatter the of in lead sea-ice a detectionleads. types. young map The Other FYI discussion in similarities region of the coincides the Barents with physical and higher relationship Kara fraction is Sea, of beyond where detected the higher scope of this paper, 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Willatt erent scientific ff -Band radar experi- u ). This coincides with recent work by 1854 1853 ). The main driver of their geographical pattern 2014 ). They show that the CS-2 range estimates may ( 2013 , 2011 ( ects the magnitude of ice/radar freeboard and the higher ). ff 3 Kurtz et al. Laxon et al. , resulting from our uncertainty estimates. They are not including 3 ) and Willatt et al. km 3 2013 ( ) and 10 × erent thresholds for the threshold first-maximum retracker algorithm (TFMRA). 3 ff 2010 ± ( Our first-order uncertainty estimates have magnitudes comparable to those obtained The choice of retracker thresholds mostly change the magnitude of the freeboard and Thus we can speculate how to accommodate the spatial and temporal variability of We note that due to the uncertainties which arise from the freeboard to thickness 2 to groups for CryoSat-2 data processing onthresholds Arctic gives sea-ice. confidence In that general the thetion application freeboard of of retrieval sea-ice all represents types. This theon is actual a shown distribu- local by scale direct as comparisons well with as airborne with laser ASCAT altimetry backscatterthrough data direct on comparisons a between basincraft CryoSat-2 scale. and data moorings and validation ( datasets from air- In this study wefirst calculate consistent CryoSat-2 uncertainty radar estimates freeboard inthree and spring/autumn di thickness 2011, retrievals 2012 with andThe the 2013, choice applying of the thresholds is based on current approaches by di 6 Conclusions are not penetrating theLaxon snow et completely al. in these conditions, which was assumed by freezing season. This further implies that retracker with 50 % and also a 80 % threshold is unlikely. It givesretracker (TFMRA80) rise the to radar does the not assumption penetrate that through the even snow by load applying completely. an 80 % threshold of 27.88 % (TFMRA40), 25.71 %2011 (TFMRA50) and to 32.65 % 2013. (TFMRA80)the from seasonal November focus bias of This futureNovember strong 2013 investigation, rise also retrievals of because showsnorth volume the an of in comparison increase Greenland November between of and should March radar the be and freeboard Canadian in in Archipelago the from MYI March region to November which are uncertainties in theof sea-surface anomaly CryoSat-2 due ground to tracks, absence intainty of patterns particular leads with for and a the latitude-dependent thewith gridded gradient density a products. and lack This increased of uncertainties causes leads in uncer- like areas land-fast-ice regions, e.g. Laptevhigher Sea. level products like sea-ice thicknessice and volumes volume. of We 9.7 find % declinesMarch (TFMRA40), of 10.9 2011 Arctic % sea- and (TFMRA50) and 2013. 6.9 In % contrast (TFMRA80) between to that we find increases in Arctic sea-ice volume the potential uncertainties thatthe ice/radar arise freeboard, due the toassumed choice penetration the of has choice a the significant of retrackerthreshold influence the threshold on choice the in retracker. mostly final Considering combination retrieval. a level with Nevertheless products the the while the main trends remain. et al. the usage of a low-threshold retracker, avoidingto volume scattering, track might the be snow reasonable freeboard.is On physically the possible, other ainclude hand, high-threshold in volume retracker case scattering might of be andis regions the where hypothetically thus better penetration at track choice. the thethreshold It is moment ice would not and freeboard. correctly timed may Such with result a the in actual parametrization snow significantconversion, conditions. biases the if absolute volume the± of choice Arctic of sea-ice is constrained to an uncertainty of (CryoVEx, see also Sect. radar penetration in regionsas or cold periods and where dry snow withoutnarios conditions significant where can internal the density not contrast main be by scattering considered ice horizon lenses. In is these not sce- penetrating the snow load completely only partially penetraterequired. into Their the findings snow arements based layer, and on thus aircraft controlled a validation ground-based penetration data K such correction as would from be the CryoSat-2 Validation Experiment 5 5 10 25 15 20 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1841 1833 , 2011. 1853 , 2008. , (last access: 28 10.5194/tc-4-373- http://osisaf.met.no 10.5194/tc-7-1035- 1839 , 1837 , erent thresholds depending on 1836 ff , 10.1029/2011GL049216 1835 10.1029/2007GL031972 , 1834 1841 1846 , 1856 1855 1834 1842 1838 , 2014. , 2002. 1837 1833 , 1995. 1837 , 2012. , remote Sensing of the Cryosphere Special Issue, available , 2008. , 2009. 1836 , 1991. , 1844 1860 The validation measurements in the framework of CryoVEx and PAMAR- 1834 , 10.5194/tcd-8-721-2014 1844 1841 10.3390/ijgi1010032 1837 , 2013. , 2010. http://www.sciencedirect.com/science/article/pii/S0034425707002817 10.1029/2009JC005312 10.1029/2008GL035710 10.1016/j.rse.2007.02.037 10.1109/IGARSS.2002.1026244 10.1029/90JC01954 10.1080/01431169508954448 Thus, for the future it would be useful to investigate di ation IceBridge, Geophys. 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Remote Sens., 15, 915– Laxon, S., Peacock, N., and Smith, D.: High interannual variability of sea ice thickness in the Stroeve, J., Serreze, M., Holland, M., Kay, J., Malanik, J., and Barrett, A.: The Arctic’s 5 5 10 15 30 10 25 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) ) 1999 ( ), radar penetra- 10 R F ) and snow density I 38 σ ρ left of the power max- ≥ σ l ) 5 70 70 ) Warren et al. IC (%) OCOG WIDTH ≤ ≥ ≥ ) 2010 ( 2006 r ( 30 15 ), ice density ( 1999 ( PP ≥ ≤ l1b σ ), radar freeboard ( Z l σ 40 ≥ 1860 1859 Estimation based on Wingham et al. Alexandrov et al. Warren et al. Waveform parameter 18.5 4 SSD≥ PP ≤ 3 − 3 ), speckle noise ( − 3 − 40 8 SSA σ K ≥ ≤ , standard deviation SSD, peakiness PP K 10 ≤ MYI: 23 kgm 100.0 kgm Variable0.1 mVariable0.10–0.14 m Radar freeboardFYI: uncertainty, 35.7 Eq. kgm ( Depending Measurements, on CryoVex lead 2011 coverage Variable right of the power maximum, sea-ice concentration IC and the width of PP r 40 ≤ ): uncertainties of snow depth ( ≥ 11 S I R ρ P SSA l1b ρ F Z σ σ σ σ σ σ Parameter Valueσ Reference/source Estimations of the individual uncertainties which contribute to the calculations in ) and ( Waveform parameter and ice concentration thresholds used in the CryoSat-2 process- ), sea-surface anomaly ( TypeOcean PP Lead 0 Sea ice P 10 σ ). S ρ σ ( tion ( Table 2. Eqs. ( imum, peakiness PP the OCOG box (OCOG WIDTH). Table 1. ing algorithm to discriminatepeakiness between PP, stack the kurtosis surface types “Ocean”, “Lead” and “Sea ice”: pulse Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | of f ) V V 3 ∆ σ km 3 of gridded (m) T T 6.91 5.51 10.19 6.18 − (m) (m) − I R F ) (%) (10 F V V f σ 3 are estimated following ∆ , discriminated between 0.73 1.08 km V 8 − − 3 σ (m) T and ) (10 V V 3 ∆ 7 σ km 3 (m) (m) I R F F 10.86 4.82 11.36 5.19 are obtained by adding of the individual un- − − (m) V and sea-ice thickness estimates ∆ T ) (%) (10 I V V f σ 3 σ F ∆ 1862 1861 1.69 1.78 km , − − 3 R F (m) (m) I R F ) (10 F V V erences 3 ∆ ff σ km 3 (m) March 2013 November 2013 T of March and November 2011 are used as a reference to calcu- FYI MYI FYI MYI 9.67 4.58 8.12 4.89 V − − (m) (m) TFMRA40 TFMRA50 TFMRA80 I ) (%) (10 R V V f σ 3 F from the same month in the following years, also given as fraction F ∆ 1.57 1.32 km V − − 3 ∆ (10 NovMar Nov 0.71 7.89 2.52 27.88 3.85 4.11 0.50 2.62 1.11 25.71 3.98 4.28 0.28 1.70 5.38 32.65 4.36 4.79 MarNov 16.27 9.04Mar 2.57 2.04 16.21 8.63 2.70 2.11 10.59 5.20 3.05 2.33 Arctic volumes Mean radar and ice freeboard erences ). Uncertainties of volume di TFMRA50TFMRA80 0.14 0.09 1.71 1.16 0.28 0.18 2.74 1.88 0.09 0.06 1.02 0.64 0.26 0.15 2.34 1.43 TFMRA40 0.17 1.97 0.30 2.10 0.11 1.25 0.31 2.22 ff 13 2013 2011 2012 the 2011 retrieval. This(TFMRA50) is and done 80 % forEq. (TFMRA80). the ( Absolute TFMRA volume retracker uncertainties certainty thresholds contributions. 40 % (TFMRA40), 50 % Table 4. late di Table 3. data for March andfirst-year ice November (FYI) 2013, and corresponding multi-year ice to (MYI). Figs. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1864 1863 Flowchart of the CryoSat-2 data processing algorithm. Schematic diagram of parameter regarding the CryoSat-2 freeboard and thickness pro- Fig. 2. Fig. 1. cessing. The actual sea-surface height isthe composed sea-surface of anomaly the (SSA). mean The sea-surfacesurface height radar from (MSS) freeboard the and is range obtainedradar retrieval by altimeter over subtracting of sea-ice. the CryoSat-2 In actual can contrast sea penetrate to the a snow laser cover, depending altimeter on (e. g. the IceSat), snow properties. the Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . The fitted (b) and leads (a) erent applied TFMRA (Threshold ff 1866 1865 Exemplary snow depth of November 2011 overlaid by the data mask (b) Data mask, which is applied to the thickness retrieval to calculate monthly volume Exemplary extractions of CryoSat-2 waveforms for sea-ice Fig. 4. (a) estimates. Only thickness datavolume within estimates. the dark(solid grey black line). area Thickness aredepth data fit used is in for not excluded the valid regions there. calculation are of discarded the because the W99 snow Fig. 3. waveform (grey) is a result ofform linear (black interpolation dots). and The smoothing of coloredfirst-maximum the retracker vertical algorithm) original lines thresholds CryoSat-2 represent in wave- this theand study: di 80 40 % % (TFMRA40), (TFMRA80). 50 % (TFMRA50) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). 5 (d) Probability ) from 15 and (c) 6 Corresponding (b) . (c) and (a) ) of CryoSat-2 and snow freeboard ∗ R F 1868 1867 METOP ASCAT mean backscatter for 04/2011. (c) . For the comparison only valid data from coincident coverage S F and ∗ R F Uncorrected TFMRA40 radar freeboard ( (b) CryoSat-2 mean radar freeboard of April 2011, retrieved by applying the TFMRA40 Area of coincident flights of CryoSat-2 and Polar-5 (black box in Fig. ) from airborne laser altimetry (Laser) along CryoSat-2 tracks 5399 and 5428. S F Fig. 6. (a) retracker. It shows the areaThe of coincident dashed validation black flights in dashed April box 2011 (black marks box,Detected a see leads Fig. common as feature fractiongrid of of cell. The the dashed totalan circle number increased marks uncertainty. of a CryoSat-2 land-fast ice point region measurements with within low one density of leads, resulting in uncertainties of the radar freeboard. Fig. 5. (a) 17 April 2011. The aircraftNorth surveyed West. the ascending CryoSat-2tracks from the South East to the ( are considered. density functions of Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | as a result of a pen- R F erent TFMRA (Threshold first- ff erent TFMRA (Threshold first-maximum ff ). 7 1870 1869 . I F CryoSat-2 sea-ice thickness retrieval with uncertainties of March and November 2013. CryoSat-2 freeboard retrieval with uncertainties of March and November 2013. The free- maximum retracker algorithm) retracker80 % thresholds: (TFMRA80). 40 % Furthermore (TFMRA40), weboard assume 50 to % a thickness (TFMRA50) maximum conversion, while radar and to for penetration be TFMRA50 of equal and to 0.18 TFMRA80 the for snow we the depth assume free- (see the also penetration Fig. Fig. 8. The thickness processing is accomplished applying three di etration of 0.18 m intobe equal snow, to while the for ice TFMRA50 freeboard and TFMRA80 we assume the freeboard to Fig. 7. board processing is accomplished applying three di retracker algorithm) retracker(TFMRA80). Furthermore for thresholds: TFMRA40 we 40 assume % the radar freeboard (TFMRA40), 50 % (TFMRA50) and 80 % Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1871 Arctic sea-ice volume of March and November 2011–2013 after applying TFMRA Fig. 9. (Threshold first-maximum retracker(TFMRA50) algorithm) and retracker 80 % thresholdscriminated (TFMRA80) between 40 of % first-year ice the (TFMRA40), (FYI) power and 50 of % multi-year ice the (MYI). first maximum of the waveforms, dis-