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Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE)

CarbonSat L1L2 Study Final Presentation , 3-Jul-2013 . Universität Bremen, FB1 Physik und Elektrotechnik. Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE). Mission Requirement Consolidation: Spectral requirements, Gain-Matrix, Pseudo-Noise (PN)

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Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE)

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  1. CarbonSat L1L2 Study Final Presentation, 3-Jul-2013 Universität Bremen, FB1 Physik und Elektrotechnik Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE) • Mission Requirement Consolidation: • Spectral requirements, Gain-Matrix, Pseudo-Noise (PN) • ESA Study CarbonSat Earth Explorer 8 Candidate Mission • “Level-2 and Level-1B Requirements Consolidation Study“ • ESA Contract No4000105676/12/NL/AF M. Buchwitz, H. Bovensmann Institute of Environmental Physics (IUP) / Institute of Remote Sensing (IFE), University of Bremen (UB), Bremen, Germany 1

  2. Overview • This presentationcoversthefollowingtopicsrelatedtoLevel 1 Mission RequirementsConsolidation: • Gainmatrixapproachforrequirementformulation & verification • Illustratedfor „Relative SpectralRadiometricAccuracy“ (RSRA) requirement • Pseudo-Noisedue toinhomogeneousspectrometerentranceslitillumination • Spectralrequirements • Note thatseveralitemsrelatedtorequirementsconsolidationhavealreadybeenpresentedunder Agenda Item 3. • Other aspectsseefollowingpresentations: • RadiometricRequirements (UoL) • Spatial / temporal co-registration (SRON) • High spatialresolutionsamplingfor C&A correction/flagging (IUP) 2

  3. Gain Matrix (GM) approach Gain Matrix (GM) approach forrequirement formulationandverification 3

  4. Gain Matrix (GM) approach: The issue • The initial (e.g., MRD v1.1) Relative SpectralRadiometricAccuracy (RSRA) requirement • formulation was „simple“ („< 0.05% (T) withineach band“) but • verydifficulttobemetand • includedspectralregions, where relaxed valueswould also beappropriate („overspecification“) • Itthereforehasbeeninvestigatedifthe RSRA requirementcanbereformulatedusing a Gain Matrix (GM) formulation 4

  5. Gain Matrix (GM) approach • GM approach (detailssee TN-4b): • ComputeGain Matrix G (how?: via L1->L2 retrievalalgorithm) • ComputeΔx = G Δy, where • G = Sx KT Sy-1 , withSx = (KT Sy-1 K + Sxa-1)-1 • Δyisthemeasurementerror#) (a spectrum = a vector) and • Δxisthesystematicerror (vector) ofretrievedgeophysicalparameters, whichcanbeconverted (using simple formulas) totheerrors (biases) oftheparametersofinterest, i.e., ΔXCO2andΔXCH4 • Finally, onehastocomparetheresultingΔXCO2and ΔXCH4valueswiththepermittedmaximumerrorfortheerrorsourceforwhichΔyhasbeencomputedtodetermineifthecorrespondingrequirement (e.g., RSRA) ismetornot. • #) relative errorofthemeasuredreflectance, or, moreprecisely: in thecorresponding TN, Δyisdefinedastheratioof an „erroneous“ reflectanceandthecorrespondingerror-freereflectance; however, adding +1.0 hasessentiallynoeffectbecauseofthepolynomialused in theretrievalalgorithm 5

  6. GM: Status TN-4b • TN-4b describes GM approach & GMs asdeliveredto ESA • GM approachusedfor MRD v1.2 • But: Refinements still ongoing: Latestdeliveryof IUP->ESA: Gs + correspondingreflectancesfor so-calledLdarkandLbrightscenes 6

  7. Pseudo Noise Pseudo-Noise (PN) due toinhomogeneousspectrometerentranceslitillumination 7

  8. Pseudo noise (PN): Approach • A PN datasethasbeenprovidedby ESA: Contains PN spectrafor 7 scenarios (IH0..IH6) • Foreach band and all 7 scenariosreflectanceratio „errorspectra“ (Δy) havebeengeneratedcontaining INHOM / HOM reflectanceratios: Δy SWIR-1 NIR SWIR-2 All y-scales: +/- 2% Reflectanceratios: upto +/-2% for NIR & SWIR-2; muchsmallerfor SWIR-1 8

  9. PN: Error estimates:Worstcasefor XCO2 Δy 9

  10. PN: Error estimates:Worstcasefor XCH4 Δy 10

  11. Pseudo noise (PN): Summary andconclusions • Resultsarebased on simulatedretrievalsappliedtoreflectancespectraperturbedby „typical“ PN errors: • Findings: • Withoutanycorrectiontheerrorscanbequitelarge • Using SHIFT & SQUEEZE theerrorsaresignificantlyreduced • These errorvaryfromgroundpx-to-pxandaretherefore „noise“ ratherthanspatio-temporallycoherentbiases on the relevant spatio-temporal scales-> Impact on precision (= randomerror) • Analyzing~1400 scenariosthefollowinghasbeenfound: • The largestsinglescenarioerrorsfoundare1.3 ppm for XCO2and9 ppb for XCH4. Forthisworstcase: • XCO2precisiondegradation: 1 ppm (T) -> 1.6 ppm (=√(12+1.32)) • XCH4precisiondegradation: 10 ppb (T) -> 13.5 ppb ((=√(102+92)) 11

  12. SpectralRequirements SpectralRequirements 12

  13. Spectralstability / knowledge Spectralstability / knowledge MRDv1.1 MRDv1.1 • T: 0.05 SSI = SSI/20 = FWHM/60*): • NIR: FWHM = 0.1 nm -> 0.002 nm • SW1: FWHM = 0.3 nm -> 0.005 nm • SW2: FWHM = 0.55 nm -> 0.009 nm • *) assuming: SSR=3 Welljustifiedorisitpossibleto relax thisrequirement? 13

  14. Spectralerrors: Case 3: Squeezeerrorwithin FWHM/10 Biases • Ifusing SH&SQ anditeration: • XCO2: OK • XCH4: OK 14

  15. Spectralerrors: Case 6: Quadraticerrorwithin FWHM/20 Biases • Ifusing SH&SQ anditeration: • XCO2: large errors • XCH4: large errors 15

  16. Spectralerrors: Summary & conclusions • Withoutcorrection XCO2and XCH4biasescanexceed (violate) theaccuracyrequirementifspectralerrorsreachorexceedthe T req. (< 0.05 SSI = FWHM/60) • With „shift & squeeze“ correctionerrorsaresignificantlyreduced • However, errorsareonly „small“ if „shift & squeeze“ is a goodmodelforthespectralerrors (in thiscase larger spectralerrorsareacceptable, e.g., FWHM/30, possiblyeven FWHM/20; thisrequireshoweverseveraliterations); ifthisis not true, e.g., becauseof „quadraticerrors“ ormorecomplexspectraldependencies, thebiasesmaybe larger thanrequired. • Iftheerroriswelldescribedby „shiftandsqueeze“, therequirementcanbe relaxed by (at least) a factorof 2. Ifthisis not true, therequirementcannotbe relaxed. • Not discussed but „obvious“: In-flightstabilityisveryimportant(evenmorethanknowledge) becausewavelengthcalibrationcanbeimprovedwith L1-2 tools (bycarefullyinvestigating sub-sets oftheobs.) andiftheerrorsarestable „all“ datacanbereliablyprocessedusingtheimprovedcalibration – otherwiseveryfrequentspectralcalibrationisneeded. 16

  17. Summary andConclusions • Specificconclusions: • See „Summary andConclusions“ givenforeachtopic • General conclusion: • Initial requirements (e.g., MRD v1.1) canbejustified – at least for „worstcase“ situations • Not clearhoweverhowrealistictheassumederrorsare !? • Itisthereforeimportanttorepeatthisanalysiswithrealistic instrumental / residual calibrationerrors • The resultshavebeenusedtoreformulatethecorrespondingrequirements (-> MRD v1.2) 17

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