Glint from scenarios to global scale
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Glint – from Scenarios to Global Scale. Hartmut Boesch University of Leicester. Initial Glint CO 2 Retrieval Tests (TN3b1). Simulations with OCO algorithm One atmosphere for all simulations Aerosol: AOD = 0.03, 0.1, 0.2, 0.4; only BL aerosol

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Glint – from Scenarios to Global Scale

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Glint from scenarios to global scale

Glint – from Scenarios to Global Scale

Hartmut Boesch

University of Leicester


Glint from scenarios to global scale

Initial Glint CO2 Retrieval Tests (TN3b1)

  • Simulations with OCO algorithm

    • One atmosphere for all simulations

    • Aerosol: AOD = 0.03, 0.1, 0.2, 0.4; only BL aerosol

    • Cirrus: COD = 0.02, 0.1, 0.2, 0.3; Height 8 and 12 km

    • SZA: 5o, 50o, 70o

    • Windspeed: 1, 5, 10 m/s (1 parameter only to describe surface)

  • Instrument:

  • Retrieval setup:

    • A priori as truth except for aerosols/cirrus profiles

    • Aerosol and cirrus type as in simulations

  • Retrieval experiments:

  • 3-band CO2 and CH4 retrieval with increased window in SWIR-2

  • 3-band CO2 and CH4 retrieval with increased window in SWIR-2 with continuum scaling in SWIR-1 and SWIR-2 (to describe whitecaps and other band-to-band uncertainties)


  • Glint from scenarios to global scale

    Summary Glint CO2 Retrieval

    • A priori setup is as truth except vertical profiles of aerosols and cirrus

      • -> biases are only interference errors !

    • More soundings but larger spread of biases with continuum scaling

    • Quality Filter

    • 2 < 0.8 per band

    • Dof > 1.8

    • AOD < 0.2


    Glint from scenarios to global scale

    Glint CO2 Retrieval – Aerosols and Cirrus

    Retrieval with continuum scaling

    • Much improved retrieval of AOD compared to nadir retrievals

    • Continuum scaling has little effect on AOD and COD retrieval but XCO2 biases couple with cirrus

    Retrieval without continuum scaling


    Glint from scenarios to global scale

    Glint CO2 Retrieval with Continuum Scaling – Correlation Matrix

    COD = 0.2

    COD = 0.02

    Correlations between cirrus and continuum scaling

    SV Elements:

    1-27: CO2

    28: H2O

    29: CH4

    30: T

    31: AOD

    32: haerosol

    33: waerosol

    34: COD

    35: hice

    36: wice

    37: ws

    38: cont (SWIR1)

    39: cont (SWIR2)

    (SZA = 50o, ws = 5m/s)


    Glint from scenarios to global scale

    Error Parameterization - Glint CO2 Retrieval

    • Full set (640) of simulations for error parameterization to create error tables to obtain global distribution of errors

      • SZA: 5o, 25o, 50o, 60o, 70o

      • Windspeed: 1, 5, 7.5, 10 m/s

  • Retrieval experiments:

  • 3-band CO2 and CH4 retrieval with increased window in SWIR-2 without continuum scaling

  • Mean Precision: 0.52 ppm

    Mean bias: 0.27 ppm +/- 0.25 ppm

    258 converged soundings and 83 pass filter


    Glint from scenarios to global scale

    Converged and Filtered Soundings

    windspeeds

    filtered

    Largely reduction of number of soundings with increasing SZA


    Glint from scenarios to global scale

    Characteristics of Sunglint Retrieval

    Windspeed is highly non-linear retrieval parameter

    Cox-Munk BRDF

    Lots of correlations between state vector elements

    Windspeed Correlation Coefficient

    CO2

    iaerosol

    T, H2O

    CO2

    iaerosol

    T, H2O

    ws

    ws

    ice

    ice

    Low windspeed:

    Correlations with ice

    High windspeed:

    Correlations with aerosols


    Glint from scenarios to global scale

    XCO2 Bias as function of AOD and COD

    AOD

    COD

    • Biases show clear increase with AOD and COD but depends also on SZA and windspeed

    • Threshold:

      • AOD < 0.1

      • COD < 0.1

      • AOD+COD < 0.2.

    AOD + COD


    Glint from scenarios to global scale

    Regression of XCO2 Biases

    • Regression of XCO2 biases against wind speed, AOD, COD and cirrus height (and constant) for each SZA

    • Polynomial interpolation of regression parameters with SZA to account for non-linearity


    Glint from scenarios to global scale

    XCO2 Error Parameterization

    Filtered and converged ConvergedNot converged

    Calculated Biases

    Regressed Biases

    Calculated Random Error

    Regressed Random Error


    Glint from scenarios to global scale

    Aerosol and Cirrus Parameters

    High windspeed

    Low windspeed

    Aerosol

    Cirrus

    Windspeed

    Filtered and converged ConvergedNot converged


    Glint from scenarios to global scale

    Glint - Summary and Conclusions

    • Sunglint retrievals are important as they provide a constraint of CO2 and CH4 over distribution oceans which will help with surface flux inversions over land.

    • Sunglint retrievals tend to behave differently compared to nadir-land retrievals

      • High non-linearity of windspeed parameter

      • Using one parameter (windspeed) to describe surface reflectance results in large information content for aerosol retrieval

      • More freedom might be required to deal with whitecaps, calibration uncertainties, etc

    • Overall, good performance with mean XCO2 bias of 0.27 ppm +/- 0.25 ppm and estimated precision of 0.5 ppm

    • A regression for bias, precision and kernels is available to map global error distribution and that can be used in OSSEs.


    Glint from scenarios to global scale

    Glint - Summary and Conclusions

    • Sunglint studies so far look promising but further work is needed to

      • Resolve remaining issues

        • how to best deal with correlations between windspeed and aerosols/cirrus

        • investigate best method to deal with whitecaps

        • extent error parameterizations with aerosol type

        • use of more advanced aerosol/cirrus filters

      • Develop global error files (L2e-files) using more realistic geometries (viewing angle  solar angle). This might need inputs from ESA on expected observational scenarios

      • Develop full error budget for sunglint observations

      • Consider specific case studies for localized sources over ocean


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