poster Cotton144 CryosatNA - TUM
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Motivation Improved Oceanographic Measurements from SAR Altimetry: Results and Scientific Roadmap from the ESA CryoSat Plus for Oceans Project Cotton, D. 2 , Martin, F. 3 , Nilo2Garcia, P. 4 , Cipollini, P. 5 , Naeije, M. 6 , Moreau, T. 7 , Passaro, M. 8 , Fernandes, M.J. 9 , Anderson, O. 10 , Cancet, M. 11 , Benveniste, J. 1 , Restano, M. 12 , Lucas, B. 13 (1) ESA, (2) SatOC , (3) Starlab, (4) isardSAT, (5) NOC, (6) TU Delft, (7) CLS, (8) TU München (9) Porto University, (10) DTU, (11) Noveltis, (12) ESA, Serco, (13) ESA, Deimos BACKGROUND NEW PRODUCTS DEVELOPMENT AND VALIDATION The core of the CryoSat Plus for Oceans project was the development and validation of algorithms and processing schemes for new ocean products, based on CryoSat>2 data. 7 new experimental altimeter data sets and 3 new geophysical correction data sets were created, and are listed below: IMPACT ASSESSMENT CLS carried out independent assessments of the demonstration data sets. Key findings were: o RDSAR: It was confirmed that the two schemes (TU Delft RADS, and CNES/CLS CPP) provided continuity across the transition from LRM to SAR mode, though some small discrepancies remained between ascending and descending tracks. Analysis of a longer data set is recommended to provide improved statistics and to identify any possible drifts o SAR: Agreement between the full implementation of the SAMOSA echo model and the numerical model in CPP is near perfect with both well suited to derive accurate SAR altimeter measurements. o Geophysical Corrections: The U Porto Wet Troposphere correction showed an improvement over the currently available model. The COMAPI regional tide model provides an improvement on North> Western European shelf at scales of 50>200 km. No improvement could be detected through the use of the new ionosphere model, but the area studied (Europe) is not the most dynamic region. SCIENTIFIC ROAD MAP The results of the project were used to define an agreed Scientific Roadmap to support the transfer the results into scientific and operational activities. • The CryoSat Plus for Oceans (CP4O) project was dedicated to the exploitation of CryoSat>2 data over the open and coastal ocean. • CP4O was supported by the ESA Support to Science Element (STSE) Programme and by CNES CONCLUSIONS CP4O has demonstrated that CryoSat>2 data provide users with significantly improved measurements over the ocean, and has developed and evaluated a series of demonstration products intended to exploit this capability. This work has required some in>depth studies and innovative technical developments, helping to build a better technical understanding of SAR altimetry over the oceans. Figure 2: SAR mode (red) can resolve scales from 10-100km, not observable by conventional altimetry (Jason-2: Black, CryoSat-2 “Pseudo” LRM: blue) Credits: CNES/CLS • CryoSat reprocessing • S-3, Jason CS • Advancing SAR alt knowledge R &D Science Exploit’n • Specular waveforms • Doppler processing • Windowing • RDSAR statistics • Wet Tropo Corr • Iono Model • Regional Tides • CryoSat re-processing • Application to other missions • High res and regional applications – coast, polar • Coastal processors • Sea ice retracker • Bathy processing • Coastal alt products • Polar: MSS, MDT, tide model • Higher res bathymetry • Modify / enhance existing operational processors • Link to end uses • RADS, DUACS,.. • NWF, Hurricane monitoring,… • Climate studies SAR / RDSAR Processing Geophys. corrns Application specific processing User Exploit’n Integration into operational use Figure 1: Time series of LRM – RDSAR- LRM data near St Helena in the South Atlantic, demonstrating consistency across the products. The blue sector represents the RDSAR coverage, the white LRM. Credits TU Delft Figure 3 Wet Troposphere Correction from Dcomb algorithm estimated for CryoSat-2 sub-cycle 35, using data from GNSS stations, MWR satellite data and the ERA interim model. Credits University of Porto Figure 4: Regional Tide Model: Improvement in SLA variance (cm^2) between COMAPI (tide model used in CP4O) and GOT4.8 tidal model. Credits CLS. Open Ocean RDSAR and SAR −0.4 −0.4 −0.3 −0.2 −0.2 −0.2 −0.1 −0.1 −0.1 −0.1 0 0 0 0 0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 DTU13MDT −180˚ −150˚ −120˚ −90˚ −60˚ −30˚ 0˚ 30˚ 60˚ 90˚ 120˚ 150˚ −0.6 −0.4 −0.2 0.0 0.2 0.4 m Figure 5: CryoSat-2 data provide important improvements to maps of Mean Dynamic Topography for the Arctic Ocean, and so support analysis of key ocean circulation features. Credits DTU Space Figure 6: The retrieved residual bathymetry signal relative to a pre CryoSat-2 bathymetry (DTU10). There are some clear indications in the marked circle of a bathymetric / tectonic feature that could be an improved mapping of an existing sea mount or a mapping of an unknown sea mount. Credits DTU Space Polar Ocean SAR SAR for Sea Floor Mapping Improved Geophysical Corrections CP4O CCN1 Additional work was supported under a CCN, under the themes: 1. SIRAL coastal processing 2. A new Arctic Tidal Atlas using CryoSatP2 data 3. Improved estimates of thermal noise in the SAMOSA echo model 4. An extended evaluation of CryoSatP2 SAR mode data in the coastal zone The objectives of CP4O were: • To build a sound scientific basis for new scientific and operational applications of CryoSat>2 data over the open ocean, polar ocean, coastal seas and for sea>floor mapping. • To generate and evaluate new methods and products that will enable the full exploitation of the capabilities of the CryoSat>2 SIRAL altimeter, and extend their application beyond the initial mission objectives. • To ensure that the scientific return of the CryoSat>2 mission is maximised. Improved Geophysical Corrections: 1. Wet troposphere (U Porto) 2. Ionosphere (Noveltis) 3. Regional tide model (Noveltis) New Experimental Altimeter Data Sets 1. LRM for Open Ocean (TUDelft) 2. SAR for Open Ocean (Starlab, CLS) 3. SAR for Sea Floor Mapping (DTU Space) 4. SAR for Coastal Ocean (NOC) 5. SAR for Polar Ocean (DTU Space) 6. RDSAR for Open Ocean (CLS, TU Delft) 7. SARIn for Coastal Ocean (isardSAT) Algorithm Theoretical Basis Documents and Product Validation Reports are available for each of these products at www.satoc.eu/projects/CP4O. CryoSatP2 SAR mode data in the coastal zone −12 −10 −8 −6 −4 −2 0 2 4 48 50 52 54 56 58 60 62 Across−track distance from coast Distance (km) 0 5 10 15 20 25 30 10 0 0.5 1 1.5 2 2.5 3 3.5 4 SWH (m) GPOD DATA Nov12 to Oct13; SWH (misfit<4) samples mean+1std mean 0 2 4 6 8 10 0 0.5 1 1.5 2 2.5 3 3.5 4 Distance from closest coastline (km) SWH (m) GPOD DATA Nov12 to Oct13; SWH (misfit<4) samples mean+1std mean mean−1std 0 10 20 30 40 50 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Search radius (km) RMS (m) RMS difference Aberdeen Alt v TG TWLE SIRAL Coastal Processing A detailed analysis of the performance of Cryosat>2 data in the coastal zone was carried out. It was concluded that, under favourable conditions, measurements at 2 km from the coast can display the same level of noise as over the open ocean Adoption of specific processing configuration (Hamming filter, Zero padding) improves the noise characteristics especially in the “last few kms” Results from validation against tide gauges are encouraging > with fine tuning of search radius (and sometimes outlier removal) we can get RMS < 10 cm with search radii around ~20 km An improved coastal processing scheme was developed and tested for SARIN mode data over the Cuban Coast The approach that was developed analysed window delay, and fitted a smoothed model to avoid jumps. This was used to identify the ocean surface tracking point, truncate waveform and re>track. This approach can also be used in SAR mode and LRM data. Analysis of one full year of data demonstrated isardSAT retrievals were much less noisy than ESA standard product, giving a 60% improvement in performance in terms of reduction of SSH Standard Deviation Improved Estimates of Thermal Noise in SAMOSA The objective of this work was to improve the performance of the “SAMOSA” Open Ocean Re>tracker, by optimising the estimation of the thermal noise. An empirical approach identified the optimum position and window for estimating the thermal noise This improved approach used to generate evaluation data set with Cryosat>2 SAR mode data for the NE Atlantic, through comparison against the CPP SAR mode data set and Jason>2 (LRM) Improved SAMOSA has best performance in terms of lowest 1Hz noise, both SAMOSA and CPP (SAR mode) much better than Jason>2 (LRM) There remains a need to develop more robust re>tracker to improve proportion of data successfully re>tracked. Waveform misfit is a good parameter to use in flagging SAR altimeter data. A further investigation into performance at low wave heights is needed. New Arctic Tidal Atlas The Arctic Ocean is a challenging region for tidal modelling. The accuracy of the global tidal models decreases by several cm in the Polar Regions, impacting on the quality of the satellite altimeter sea surface heights and the altimetry> derived products. NOVELTIS and DTU Space developed a regional, high>resolution tidal atlas in the Arctic Ocean. In particular, this atlas benefits from the assimilation of Envisat data up to 82°N and CryoSat>2 data between 82°N and 88°N. The combination of these satellite altimetry missions gives the best possible coverage of altimetry> derived tidal constituents. The available tide gauge data were also used for data assimilation and validation. A key development was the application of a high resolution unstructured mesh for the underlying hydrodynamic model. This work is being continued under a further CCN 0 20 40 60 80 100 120 140 0 50 100 150 200 250 300 Lags Amplitude [A.U] Waveform [SWH = 1.59, 2012-01-04 [22:13:57]] Waveform New Approach [Margin 16 lags] Conventioanl [Lags 11-21] −20 −15 −10 −5 0 5 35 40 45 50 55 60 65 62029 62081 62105 64045 62001 62163 0 2 4 6 8 10 −0.1 −0.05 0 0.05 0.1 SWH CPP(m) SSH CPP − SSH STARLAB (m) MEAN BIAS (cm):−0.35 % STD (cm):1.20 % SLOPE (cm/m):−0.33 0 2 4 6 8 10 −0.5 0 0.5 SWH CPP(m) SWH CPP − SWH STARLAB (m) MEAN BIAS (cm):−1.46 % STD (cm):16.15 % SLOPE (cm/m):−0.54 0 1 2 3 4 5 6 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 SWH BUOY (m) 1 Hz noise at 2 m; CPP=0.012344 STARLAB=0.012214 JASON 2=0.016133 CPP Jason 2 STARLAB
Transcript of poster Cotton144 CryosatNA - TUM
Motivation
Improved.Oceanographic.Measurements.from.SAR.Altimetry:.Results.and.Scientific.Roadmap.from.the.ESA.CryoSat Plus.for.Oceans.Project
Cotton,&D.2,&Martin,&F. 3,&Nilo2Garcia,&P.4,&Cipollini,&P.5,&Naeije,&M. 6,&Moreau,&T. 7,Passaro,&M.8 ,&Fernandes,&M.J.&9,&Anderson,&O.10,&Cancet,&M.&11,&Benveniste,&J.1,&Restano,&M.12,&Lucas,&B.13
(1)&ESA,&(2)&SatOC ,&(3)&Starlab,&(4)&isardSAT,&(5)&NOC,&&(6)&TU&Delft,&(7)&CLS,&(8)&TU&München(9)&Porto&University,&(10)&DTU,&(11)&Noveltis,&(12)&ESA,&Serco,&(13)&ESA,&Deimos
BACKGROUND NEW.PRODUCTS.DEVELOPMENT.AND.VALIDATIONThe$core$of$the$CryoSat Plus$for$Oceans$project$was$the$development$and$validation$of$algorithms$and$processing$schemes$for$new$ocean$products,$based$on$CryoSat>2$data.$7$new$experimental$altimeter$data$sets$and$3$new$geophysical$correction$data$sets$were$created,$and$are$listed$below:
IMPACT.ASSESSMENTCLS$carried$out$independent$assessments$of$the$demonstration$data$sets.$Key$findings$were:o RDSAR:$$It$was$confirmed$that$the$two$schemes$(TU$Delft$RADS,$and$CNES/CLS$CPP)$provided$
continuity$across$the$transition$from$LRM$to$SAR$mode,$though$some$small$discrepancies$remained$between$ascending$and$descending$tracks.$Analysis$of$a$longer$data$set$is$recommended$to$provide$improved$statistics$and$to$identify$any$possible$drifts
o SAR:$$Agreement$between$the$full$implementation$of$the$SAMOSA$echo$model$and$the$numerical$model$in$CPP$is$near$perfect$with$both$well$suited$to$derive$accurate$SAR$altimeter$measurements.$
o Geophysical$Corrections:$The$U$Porto$Wet$Troposphere$correction$showed$an$improvement$over$the$currently$available$model.$The$COMAPI$regional$tide$model$provides$an$improvement$on$North>Western$European$shelf$at$scales$of$50>200$km.$No$improvement$could$be$detected$through$the$use$of$the$new$ionosphere$model,$but$the$area$studied$(Europe)$is$not$the$most$dynamic$region.$
SCIENTIFIC.ROAD.MAPThe results of the project were used to define an agreed Scientific Roadmap to support thetransfer the results into scientific and operational activities.
• The �CryoSat Plus for Oceans� (CP4O) project was dedicated tothe exploitation of CryoSat>2 data over the open and coastal ocean.
• CP4O was supported by the ESA Support to Science Element (STSE)Programme and by CNES
CONCLUSIONSCP4O has demonstrated that CryoSat>2 data provide users with significantly improved measurements overthe ocean, and has developed and evaluated a series of demonstration products intended to exploit thiscapability. This work has required some in>depth studies and innovative technical developments, helping tobuild a better technical understanding of SAR altimetry over the oceans.
Figure 2: SAR mode (red) can resolve scales from 10-100km, not observable by conventional altimetry (Jason-2: Black, CryoSat-2 “Pseudo” LRM: blue)Credits: CNES/CLS
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• CryoSat reprocessing • S-3, Jason CS • Advancing SAR alt
knowledge
R &D Science Exploit’n
• Specular waveforms • Doppler processing • Windowing • RDSAR statistics
• Wet Tropo Corr • Iono Model • Regional Tides
• CryoSat re-processing • Application to other
missions • High res and regional
applications – coast, polar
• Coastal processors • Sea ice retracker • Bathy processing
• Coastal alt products • Polar: MSS, MDT, tide
model • Higher res bathymetry
• Modify / enhance existing operational processors
• Link to end uses
• RADS, DUACS,.. • NWF, Hurricane
monitoring,… • Climate studies
SAR / RDSAR
Processing
Geophys. corrns
Application specific
processing
User Exploit’n
Integration into
operational use
Figure 1: Time series of LRM – RDSAR- LRM data near St Helena in the South Atlantic, demonstrating consistency across the products. The blue sector represents the RDSAR coverage, the white LRM. Credits TU Delft
Figure 3 Wet Troposphere Correction from Dcomb algorithm estimated for CryoSat-2 sub-cycle 35, using data from GNSS stations, MWR satellite data and the ERA interim model. Credits University of Porto
Figure 4: Regional Tide Model: Improvement in SLA variance (cm^2) between COMAPI (tide model used in CP4O) and GOT4.8 tidal model. Credits CLS.
Open.Ocean.RDSAR.and.SAR
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Figure 5: CryoSat-2 data provide important improvements to maps of Mean Dynamic Topography for the Arctic Ocean, and so support analysis of key ocean circulation features. Credits DTU Space
Figure 6: The retrieved residual bathymetry signal relative to a pre CryoSat-2 bathymetry (DTU10). There are some clear indications in the marked circle of a bathymetric / tectonic feature that could be an improved mapping of an existing sea mount or a mapping of an unknown sea mount. Credits DTU Space
Polar.Ocean.SAR SAR.for.Sea.Floor.Mapping
Improved.Geophysical.Corrections
CP4O.CCN1
Additional work was supported under a CCN, under the themes:1. SIRAL coastal processing2. A new Arctic Tidal Atlas using CryoSatP2 data3. Improved estimates of thermal noise in the SAMOSA echo model4. An extended evaluation of CryoSatP2 SAR mode data in the coastal zone
The objectives of CP4O were:
• To build a sound scientific basis for new scientific and operational applications of CryoSat>2 data overthe open ocean, polar ocean, coastal seas and for sea>floor mapping.• To generate and evaluate new methods and products that will enable the full exploitation of thecapabilities of the CryoSat>2 SIRAL altimeter, and extend their application beyond the initial missionobjectives.• To ensure that the scientific return of the CryoSat>2 mission is maximised.
Improved.Geophysical.Corrections:.
1. Wet$troposphere$(U$Porto)2. Ionosphere$(Noveltis)3. Regional$tide$model$(Noveltis)
New.Experimental.Altimeter.Data.Sets1. LRM$for$Open$Ocean$(TUDelft)$2. SAR$for$Open$Ocean$(Starlab,$CLS)$3. SAR$for$Sea$Floor$Mapping$(DTU$Space)4. SAR$for$Coastal$Ocean$$(NOC)5. SAR$for$Polar$Ocean$(DTU$Space)6. RDSAR$for$Open$Ocean (CLS,$TU$Delft)7. SARIn for$Coastal$Ocean$(isardSAT)
Algorithm.Theoretical.Basis.Documents.and$Product.Validation.Reports.are$available$for$each$of$these$products$at$www.satoc.eu/projects/CP4O.
CryoSatP2.SAR.mode.data.in.the.coastal.zone
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SIRAL.Coastal.Processing
A$detailed$analysis$of$the$performance$of$Cryosat>2$data$in$the$coastal$zone$was$carried$out.$It$was$concluded$that,$under$favourable conditions,$measurements$at.2.km.from.the.coast.can.display$the$same$level$of$noise$as$over$the$open$oceanAdoption$of$specific$processing$configuration$(Hamming$filter,$Zero$padding)$improves$the$noise$characteristics$especially$in$the$“last$few$kms”Results$from$validation$against$tide$gauges$are$encouraging$> with$fine$tuning$of$search$radius$$(and$sometimes$outlier$removal)$we$can$get$RMS.<.10.cm.with.search.radii.around.~20.km
An improved coastal processing scheme was developed andtested for SARIN mode data over the Cuban Coast
The approach that was developed analysed window delay,and fitted a smoothed model to avoid jumps. This wasused to identify the ocean surface tracking point,truncate waveform and re>track. This approach can alsobe used in SAR mode and LRM data.
Analysis of one full year of data demonstrated isardSATretrievals were much less noisy than ESA standard product,giving a 60% improvement in performance in terms ofreduction of SSH Standard Deviation
Improved.Estimates.of.Thermal.Noise.in.SAMOSA
The objective of this work was to improve the performanceof the “SAMOSA” Open Ocean Re>tracker, by optimisingthe estimation of the thermal noise.
An empirical approach identified the optimum position andwindow for estimating the thermal noise
This improved approach used to generate evaluation dataset with Cryosat>2 SAR mode data for the NE Atlantic,through comparison against the CPP SAR mode data setand Jason>2 (LRM)Improved$SAMOSA$has$best$performance$in$terms$of$lowest$1Hz$noise,$both$SAMOSA$and$CPP$(SAR$mode)$much$better$than$Jason>2$(LRM)
There$remains$a$need$to$develop$more$robust$re>tracker$to$improve$proportion$of$data$successfully$$re>tracked.$Waveform$misfit$is$a$good$parameter$to$use$in$flagging$SAR$altimeter$data.A$further$investigation$into$performance$at$low$wave$heights$is$needed.$
New.Arctic.Tidal.AtlasThe Arctic Ocean is a challenging region fortidal modelling. The accuracy of the global tidalmodels decreases by several cm in the PolarRegions, impacting on the quality of the satellitealtimeter sea surface heights and the altimetry>derived products.
NOVELTIS and DTU Space developed aregional, high>resolution tidal atlas in the ArcticOcean. In particular, this atlas benefits from theassimilation of Envisat data up to 82°N andCryoSat>2 data between 82°N and 88°N. Thecombination of these satellite altimetry missionsgives the best possible coverage of altimetry>derived tidal constituents. The available tidegauge data were also used for data assimilationand validation.
A key development was the application of ahigh resolution unstructured mesh for theunderlying hydrodynamic model.
This work is being continued under a furtherCCN
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