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Retrieval of Atmospheric Ozone Concentrations from Satellite Based Limb Data Sheng Bo Chen

Retrieval of Atmospheric Ozone Concentrations from Satellite Based Limb Data Sheng Bo Chen College of Geoexploration Science and Technology, Jilin University chensb@jlu.edu.cn. Outline 1. Introduction

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Retrieval of Atmospheric Ozone Concentrations from Satellite Based Limb Data Sheng Bo Chen

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  1. Retrieval of Atmospheric Ozone Concentrations from Satellite Based Limb Data Sheng Bo Chen College of Geoexploration Science and Technology, Jilin University chensb@jlu.edu.cn

  2. Outline 1. Introduction 2. SCHIMACHY Data 3. Inversion Method 4. Inversion Error Analysis 5. Inversion Validation 6. Conclusions

  3. 1. Introduction Atmospheric Sounding experienced ground-based detection, balloon soundings and rockets and other space technology , since the satellite-based atmospheric sounding instruments there. • Ground-based Measurement • Invented in 1924 Dobson detector • 1973 Brewer foundation VIS spectrometer NO2 • Balloon Soundings • Detect height 30-35 km • 1988 McElroy limb spectrometer NO2 • Plane and Rockets • 70 s the stratosphere and interface layer • Satellite-based Measurement • Worldwide

  4. Satellite Measurement • Observatory Geometry • Nadir Measurements • Occultation Measurements • Limb Measurements

  5. Limb Based Instruments • Limb Measurements • 1973 Cunnold step one proposed limb scattering techniques, used in aircraft. Wavelength UV-VIS 6. • 2010 CAS Changchun Institute of Optics, limb imaging spectrometer prototype. UV 270-390 nm and VIS 540-780 nm

  6. 2. SCIAMACHY Data SCIAMACHY is one of 10 instruments equipped with the ESA satellite ENVISAT. It is used to observe UV-VIS-NIR-SWIR range of passive remote sensing of solar radiation absorption spectrum of atmosphere.

  7. SCIAMACHY is designed to a double imager and divided into eight channels, the instrument records the reflection and scattering of solar radiation spectrum range through 214-2386 nm wavelength, with moderate spectral resolution 0.24-1.48 nm.

  8. < 1000 nm, 2350 nm • Select data：Determine the wavelength

  9. 3. Inversion Algorithm Atmospheric limb-scattering inversion • Vector of inversion + Inversion of concentration

  10. Inversion algorithm • Newton iterative • Simple • Each iteration needed to calculate weight function • A large amount of calculation • Optimal estimation • Wide range • Easy to estimate error covariance • Improved Onion-peeling • May not need a priori contour line and not needed to calculate information weight function • The same concentration of fixed value, the local horizontal uniform • Chahine relaxation iteration • Simple and easy to implement • Weighted multiplicativealgebraic reconstruction technique (WMART) • The simultaneous use of multiple wavelength and multiple tangent height data for the inversion of concentration at a height

  11. According to the meteorological data assuming an initial target of ozone profiles, using SCIATRAN model to simulate the limb radiation and compared with SCIAMACHY satellite radiation.The radiation difference value is feedback information to adjusting the ozone profile. Then we use this profile simulation new radiation value in order to better to match the observed value iteration processing.The result is the ozone profile. Weighted multiplicative algebraic reconstruction inversion method （WMART）

  12. Radiation normalization The limb radiation normalization to the reference tangent height • Wavelength pair In order to make the aerosol scattering effect be minimized, the inversion will be multiple wavelength normalization radiation value combinations instead of the direct radiation value as the amount of reflection. Ozone inversion parameters

  13. Wavelength pairs effect cloud Surface albedo aerosol

  14. Aerosol sensitivity The radiation relative deviation under the influence of aerosol The inversion vector relative deviation under the influence of aerosol 1. Before processing: Hartley band along with the change ofSZA ↑↑;Chappuis band is insensitive to SZA, but depend on TH and in 21 km reach the maximum peak. 2. After processing: Two bands are not sensitive to SZAandalong with rising TH reduced↑↓. 0 influence lines, negative influence

  15. Cloud sensitivity The radiation value relative deviation under the influence of cloud The inversion vectorrelative deviation under the influence of cloud 1. Before processing : <300 nm no effect ,SZA ↑↓ 2. After processing :TH ↑↓, negative effect; HPV negative peak around SZA 60， CTV Negative peak in SZA 80

  16. Surface albedo sensitivity The radiation relative deviation under the influence of surface albedo without processing The inversion vectorrelative deviation under the influence of surface albedo 1. Before processing：SZA↑↓ 2. After processing：HPV with SZA↑↓ , dependent on TH； CTV along with rising SZA and TH reduced ↑↓

  17. Sensitivity summary After processing: The influence of three factors are reduced to a lower magnitude The influence degree of the value of radiation Aerosol> cloud > surface albedo

  18. WMART • A number of bands and tangent radiation tangent height bands i – inversion height，k – Wavelength combination，j – tangent height radiation step1 Band correction factor step2 Height correction factor step3 Density correction

  19. Band combination weight factors • Ozone weight factors • Weight function has a different range and has different combinations at different height. • Smooth • Start 0 ,end 0

  20. Inversion Implementation • SCIA_JLU Automatic batch processing multi-track SCIAMACHY data O3（30 min/26prf）and NO2（15min/104prf）

  21. 4. Inversion Error Analysis • The main error source • Tangent positioning • Aerosol Boundary layer visibility Stratospheric aerosol load Extinction coefficient • Surface albedo • Cloud parameters Cloud height Cloud optical thickness • Analysis method • Parameters deviation，SCIATRAN

  22. 4.1 Tangent height positioning error dTH∈{0.25, 0.5, 1} km • dTH↑error↑ ，0.25 km (10 %) • positive and negative,58 km maximum error • SZA haveLittle effect,SZA=70 maximum error Ozone inversion error

  23. 4.2 Aerosol - stratospheric aerosol load • STAER∈{BK, MOD, HIG, EXT} • STAER↑error↑ 。MOD AER SZA<60 (15 %),70-90°(20 %,30 % and 45 %); higher than 20 km(15 %), higher than 40 km (1 %) • Height↑error↓ • SZA ↑ error ↑ Ozone inversion error

  24. 4.3 Aerosol-extinction coefficient Ozone inversion error Multiple∈{2, 3, 4} ●Multiple↑error↑ ●2 times,10-68 km(12 %); higher than22 km (5 %) ●Height↑error first↑ then↓ ●SZA ↑error↑

  25. 4.4 Surface albedo Ozone inversion error • ALB∈{0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1} • dALB↑error↑,Symmetric distribution • dALB=0.1，35-68 km(0.5 %), under 35 km (3 %) • height↑error↓ • SZA ↑error↓

  26. 4.5 Cloud height • CLD∈{[2.4-3], [0.6-3], [0.3-1], [5-10], [8-15]} km • Troposphere cloud small( within 2 %); stratosphere cloud error is the largest (50 %) • height ↑error↓ • Insensitive to SZA Ozone inversion error

  27. 4.6 Cloud optical thickness • TAU∈{0.05, 1, 2, 3} • dTAU↑error↑ 4 %, higher than 40 km (0.4 %) • height ↑error↓ • SZA ↑error first ↑ then ↓ Ozone inversion error

  28. Error summary Ozone inversion error

  29. 5. Inversion Validation • Ozone inversion contrast • Inversionozone（JLU ozone） • -Bremen University SCIAMACHY ozoneV2.3（BU ozone） • -Saskatchewan University OSIRIS ozone V3.0 • -MLS ozone

  30. Inversion validation • SCIAMACHY • Period of time： 3 days, 37 tracks • Location and time： Exact correspondence • Comparison • Middle latitude:the highest point is the difference • Low latitude have good consistency; 10-68 km: average deviation 15 % 10-50 km and 55-63 km: average deviation 10 %

  31. Inversion validation • OSIRIS Period of time: 3 days Latitude:±5°Longitude:±10° Height range: 18-46 km • Comparison structure , peak height and size is good 18-39 km: average deviation is less than 10% Higher than 40 km: much more than20 %

  32. Inversion validation • MLS • Period of time: 3 days • Latitude:±5°Longitude:±10 • Height range: 18-46 km • Comparison • More than 20 km consistency is good , following 20 km have obvious difference • 20-46 km，average deviation 10 %

  33. Inversion validation • Comparison summary Ozone deviation

  34. 6. Conclusions • Global measurements by satellite • Limb based measurements will improve the vertical resolution of ozone concentrations • China will launch a satellite based limb ozone measurement instruments • Ground measurements will validate the satellite results. They should be integrated

  35. Thank You!

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