1 / 34

Cloud Properties Retrieved by MIDAS from Near-Infrared Scattered Sunlight Spectra

This workshop presentation discusses the retrieval of cloud properties using differential optical absorption spectroscopy (DOAS) from near-infrared scattered sunlight spectra. It includes information on the impact of scattering, instrumentation, theoretical approach, intercomparison, and applications for liquid and ice observations.

georgiat
Télécharger la présentation

Cloud Properties Retrieved by MIDAS from Near-Infrared Scattered Sunlight Spectra

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Cloud Properties Retrieved by MIDAS from Near-Infrared Scattered Sunlight Spectra John S. Daniel NOAA Aeronomy Laboratory ICARTT J31 Data Workshop 9, 10 March 2005 Boulder

  2. Outline • Background: Differential Optical Absorption Spectroscopy II. Gulf of Maine - July 9, 2004 III. Barrow - September 14, 2004

  3. DOAS Direct and optically thin diffuse e.g., NO2, OClO, BrO foreground

  4. Additional Considerations • scattering affects the amount of absorber in cloud “seen” by transmitted and reflected photons • intensity observations reflect the impact of the absorber amount and the effective path length through the cloud Optically Thick Clouds Equivalence Theorem Photon Path Distribution

  5. Simple DOAS No Longer

  6. Zenith-Looking Summary45° SZA Cloud Path Cloud Path

  7. Instrumentation 7 Fixed-Grating Spectrometers fiber optically fed coverage ~290 - 1680 nm resolution ~0.3 - 6 nm FOV: ~10°

  8. Liquid and Ice Sensitivity Liquid Ice Vapor

  9. O4 CO2, CH4 O2, O4 CO2

  10. Theoretical Approach Optimal Inversion Spectra Forward Model Disort 2.0 Liquid- and mixed-phase Absorbers/scatters Vapor, liquid, ice, CO2, O2, O4, CH4 Intercomparison Path-Integrated Quantities Rodgers

  11. Effect of Random Noise - Liquid Cloud weak medium strong Medium Weak Standard Deviation/Correct Value Strong

  12. Field Campaigns ARM SGP, Oklahoma October, 2003 New England Summer, 2004 ARM NSA, Barrow, Alaska Sept/Oct, 2004

  13. July 9, 2004 Gulf of Maine Latitude GOES EAST, 9 July 17:45 UT Longitude

  14. P-LWP Retrievals Preliminary Time

  15. Preliminary Liquid Results Arbitrarily Scaled FSSP vs MIDAS (Reff)

  16. Cloud Retrievals: P-3 Courtesy: P. Pilewskie

  17. ICARTT Plans P-3 Ron Brown Remote Sensing Observations Microwave Radiometer Radar MIDAS SSFR FSSP In Situ Provide a Liquid Water Path / Effective Radius Comparison

  18. ICARTT Plans P-3 Ron Brown Remote Sensing Observations Microwave Radiometer Radar MIDAS SSFR FSSP In Situ Provide a Liquid Water Path / Effective Radius Comparison

  19. Barrow, AK, Installation 2004ARM NSA Facility MWR/AERI comparison M-PACE

  20. Comparison to Microwave Radiometer Barrow, AK, 14 September 2004 preliminary LWP (g/m2) Time (ADT)

  21. preliminary LWP (g/m2) Time (ADT)

  22. What About Ice? Millimeter-Wavelength Cloud Radar

  23. Qualitative Ice Comparison - Spectral vs. Radar14 Sept 2004, Barrow AK preliminary Radar IWC = a Zb Sheba Matt Shupe PIWP, IWP (g/m2) Time (ADT)

  24. Ice Retrievals preliminary PIWP (g/m2) Time (ADT)

  25. Example Spectra

  26. Typical Fit Quality PLWP: ~33 g/m2 PIWP: ~83 g/m2

  27. No Ice In Retrieval

  28. No Liquid in Retrieval

  29. Acknowledgments Summary Excellent liquid and ice comparisons to microwave radiometer and radar provide us with the confidence to apply our technique to retrieve LWP and effective radius Susan Solomon, Robert Portmann, Henry Miller Ping Yang Dave Turner, Matt Shupe

  30. Applications for Liquid and Ice Observations • SAR - “The single largest uncertainty in determining the climate sensitivity to either natural or anthropogenic changes is clouds and their effects on radiation and their role in the hydrological cycle.” • TAR - “… there has been no apparent narrowing of the uncertainty range associated with cloud feedbacks in current climate change simulations.” • Climate research and monitoring - prevalence of cloud liquid and ice - effects on radiation field - photon path distribution for liquid => processes and parameterizations for climate models • Weather forecasting - ground-based model initialization - liquid/ice partitioning • Evaluation of RT models • Aviation

More Related