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LIDAR DATA VALIDATION DURING MOHAVE 2009

This study evaluates the performance and accuracy of lidar data collected during the Mohave 2009 campaign. The results show good agreement between lidar and balloon measurements, with some variations depending on integration time and altitude ranges. The study concludes that the H2O Raman lidar technique shows promising results for UTLS measurements.

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LIDAR DATA VALIDATION DURING MOHAVE 2009

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  1. LIDAR DATA VALIDATION DURING MOHAVE 2009 Thierry Leblanc NASA/JPL Thanks to Tony Grigsby and Stuart McDermid, who contributed to obtain a very valuable JPL lidar dataset

  2. JPL H2O LIDAR MOHAVE 2009 DATASET TMW: 12 nights, total 75 hours Data details (11-27 Oct.) Oct. 11: 2.0 hours (1 CFH, 1 MLS coinc.)Oct 12-13: Ø StormOct 14-15: Ø Lidar Synch TestsOct. 16: 6.0 hours (1 FPH, 1 MIPAS coinc.)Oct. 17: 9.3 hours Full night (1 CFH)Oct. 18: 4.0 hours (1 FPH+1 CFH)Oct. 19: 9.5 hours Full night (1 CFH, MIPAS coinc.)Oct. 20: 6.1 hours Cloudy half-night (2 CFH+1 FPH)Oct. 21: 9.0 hours Full night (2 CFH)Oct. 22: 9.9 hours Full night (2 CFH)Oct 23: Ø RestOct. 24: 5.1 hours (1 CFH)Oct. 25: 5.0 hours (2 CFH)Oct 26: Ø Laser failureOct. 27: 9.7 hours Full night, high clouds (1 CFH, 1 MLS coinc.) ----------------------------------------------------------------------------TOTAL: 75 hours to compare with 13 CFH, 3 FPH, 31 PTU

  3. Lidar vs. balloon 1-hr coincidences: match well All lidars:1-hr integration Good matchwith balloonup to 12 km

  4. Lidar vs. balloon 6-hr integ.: match well… sometimes All lidars:all-night integration sometimes match well in the LT

  5. Lidar vs. balloon …but not all the time All lidars:all-night integration sometimes does NOT match well in the LT 09:25 UT 6:08 UT

  6. Lidar vs. balloon … and depends on integration time All lidars:all-night integration integration timesometimes an issue 2 different time windows

  7. Lidar vs. RS92 correc. Lidar and RS92 correc. match up to 18 km Within 5%(calibration at bottom using RS92 corrected)

  8. Lidar vs. CFH 1-hr Lidar and CFH match up to 14 km Within 5% for z<14 km

  9. TMF Lidar vs. CFH All-night Lidar and CFH match up to 20 km Within 5% for z<20 km Within 10% for z>20 km

  10. TMF Lidar vs. STROZ lidar STROZ plagued with Fluorescence Both lidars:1-hr integrationdatasets STROZ: Wet bias for z>10 km STROZ error bars over-estimated?

  11. TMF Lidar vs. STROZ lidar STROZ plagued with Fluorescence Both lidars:all-night integrationdatasets STROZ: Wet bias for z>10 km STROZ error bars over-estimated?

  12. TMF Lidar vs. ALVICE lidar ALVICE plagued with Fluorescence Both lidars:1-hr integrationdatasets ALVICE: Wet bias for z>10 km ALVICE error bars under-estimated?

  13. TMF Lidar vs. ALVICE lidar ALVICE plagued with Fluorescence Both lidars:all-night integrationdatasets ALVICE: Wet bias for z>10 km ALVICE error bars under-estimated?

  14. Effect of Fluorescence for ALVICEtoo wet by 25% ALVICE vs. ALVICE Both datasets:all-night integrationdatasets

  15. LT: all within 10% Summary 5 km<z<9 kmAll within 5% 3 km<z<5 km All within 10%

  16. LT: all within 10% Summary 9 km<z<13 km Effect of fluorescencebecomessignificant

  17. H2O Raman Lidar technique is promising CONCLUSION (lidar)

  18. H2O Raman Lidar technique is promising CONCLUSION (lidar) Deviations from CFHnear +/- 3%up to 20 km

  19. JPL TROPO. O3 LIDAR Overall: Lidar has 6% high bias vs. ECC 1D view of the 10/20 Intrusion

  20. Overall: Agreement with ECC good JPL TROP. O3 LIDAR 6-7% lidar high bias in troposphere

  21. Poor Wet Rich Dry Poor Wet MOHAVE 2009 = Nice O3/H2O correlation JPL H2O LIDAR Xtras Nice anti-correlation between O3 and H2O O3 H2O

  22. Rich Poor Dry Wet MOHAVE 2009 = Nice 2D timeseries JPL H2O LIDAR Xtras Observation of fast transitions between regimes… O3 H2O

  23. H2O and O3 variability point towards nice case studies  will be shown on Thursday Morning(see poster display as well) CONCLUSION 1. The JPL/TMF Lidars have very well performed during MOHAVE 2009 2. H2O Lidar showed no systematic bias with CFH • H2O lidar technique is ready for UTLSWhat’s next?…

  24. THANK YOU

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