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Understanding Retrieval Algorithm Uncertainties in Atmospheric Remote Sensing

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22 diapositives · 368 Views · Jul 30, 2014

This workshop presentation by Dave Turner and Ulrich Löhnert at the DOE/EU Retrieval workshop discusses the various types of uncertainties in retrieval algorithms used in atmospheric remote sensing. The presentation addresses the origins of these uncertainties, including systematic and random errors, and their impact on retrieval coefficients such as ice water content (IWC). Statistical methods, the interpretation of Bayesian error estimates, and the significance of in-situ observations are explored to enhance understanding and minimize retrieval uncertainties in measurements from instruments like radars, MWRs, and lidars.

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  1. (Getting a grip on)Retrieval algorithm uncertainties DOE/EU Retrievalworkshop Köln, 13.5.2013 Dave Turner Ulrich Löhnert • What types of uncertainties exist? • Where do retrieval uncertainties originate from? • How do we handle the origin of retrieval uncertainties in the retrieval algorithm? • Interpretation of Bayesian error estimates

  2. Systematic Random What types of uncertainties exist? Temperatureprofilesfrom MWR

  3. systematic measurement error: Microwave TBs in V band Where do retrieval uncertainties originate from?

  4. quasi bias-free Correct for systematic offsets on average …

  5. random measurement error: Microwave TBs in V band Where do retrieval uncertainties originate from? constantlook on hotload: ~0.5 K 12 hours

  6. random measurement error covariances: TBs in V band Where do retrieval uncertainties originate from? fromconstantlook on hotload instrumentspecific!

  7. Limited information content of measurement (“smoothing error”) Where do retrieval uncertainties originate from?

  8. Forward model (systematic & random) Where do retrieval uncertainties originate from? Humidity retrieval: Optimal estimation using two different water vapor absorption models OE uncertainty prior uncertainty bias against sondes using different absorption models

  9. ... OE Prior information Measurements How do we handle the origin of retrieval uncertainties in the algorithm? Limited information content of measurement (“smoothing error”) Forward model

  10. Forward model uncertainties: Sbmatrix Sensitivity of IWC = aZb Retrievals • Power law relationships used frequently • Use in-situ observations to determine the retrieval coefficients a,b by computing Z based upon observed size distribution, habit, etc. • There is always scatter in derived a and b • “Random” error (i.e., unknown what causes the scatter) • Correlated error (variables depend on some other variable such as cloud temperature) • What is the impact of the uncertainties in retrieval coefficients on the retrieved IWC?

  11. In Situ Ice Cloud Obs From 2000 ARM Cloud IOPCoefficients b(T) and a(T) b = 2.0 σb = 0.15 Log10(a) = -2.3 σlog10(a) = 0.2 Will simulate IWC using mean a,b values as truth, and investigate the impacts of uncertainties in these coefs

  12. IWC Sensitivity to Retrieval Coefficients

  13. IWC Sensitivity to Retrieval Coefficients

  14. IWC Sensitivity to Retrieval Coefficients

  15. IWC Sensitivity to Retrieval Coefficients

  16. IWC Sensitivity to Retrieval Coefficients

  17. IWC Sensitivity to Retrieval Coefficients

  18. ... OE Prior information Measurements How do we handle the origin of retrieval uncertainties in the algorithm? onlyrandom!!! Limited information content of measurement (“smoothing error”) Forward model

  19. Interpretation of A and S

  20. Interpretation of the S and A matrix • What should we be providing to the end user? • Do we need a general (easy-to-understand) documentation for the interpretation of Bayesian algorithms?

  21. Breakout groups on Sε determination for different instruments? Radar MWR Lidar

  22. How to determine diagonal and off-diagonal elements of Sy for the different instruments? (Radar, MWR, Lidar) • How can we better describe the uncertainties of the the forward model parameters included in Sb? Need to take a detailed look at forward models for the different instruments. • What kind of measurements are needed to improve or better characterize forward model uncertainties? • Sεdoes NOT include systematic errors!How do we check for systematic errors in the different instruments? Consistent bias correction procedures? Questions for break-out groups?