Vicarious calibration of GLI by global datasets. Calibration 5th Group Hiroshi Murakami (JAXA EORC)

Transcription

1 Vicarious calibration of GLI by global datasets Calibration 5th Group Hiroshi Murakami (JAXA EORC) ADEOS-2 PI workshop March

2 0. Contents 1. Background 2. Operation flow 3. Results 4. Temporal change 5. Mirror-angle dependency 6. Possibility of this scheme 7. Summary 8. Future works 9. Lessons learned ADEOS-2 PI workshop March

3 1. Background Ground observation may be better for the vicarious calibration, but has problems; In the early phase, we cannot obtain enough number of ground observations. Ground measurement error (surface and atmospheric) can be one of the serious problem. Sub-pixel spatial structure can be an serious error source. As a kind of provisional adjustment, we tried to derive vicarious coefficients using global GLI L TOA, SeaWiFS nlw (8 days mean), and GLI atmospheric correction look-up tables (Rayleigh, ozone, solar irradiance, aerosol by RSTAR5b). Each grid may have large error, but the large number (more than 100,000) can be reduce it statistically. ADEOS-2 PI workshop March

4 2. Operation flow Processed 16 days; 02/06, 03/20, 04/06, 04/22, 05/08, 05/24, 06/09, 06/25, 07/11, 07/27, 08/12, 08/28, 09/13, 09/29, 10/15, 10/24 in day L1B L TOA and geometry Fix two NIR bands for aerosol optical thickness (τ a ) and model selection LUTs Aerosol model selection by GLI atmos corr. Look Up Table (τa L TOA ) SeaWiFS 8-day binned nlw interpolated to GLI bands through an in-water model (Tanaka et al.) Pressure (and water vapor) by JMA objective analysis Column ozone by TOMS Simulated L TOA Derive correction coefficients by comparison between GLI L1B and simulated L TOA. ADEOS-2 PI workshop March

5 2. Operation flow Selected aerosol models We can use several model patterns; CH19-13 or CH19-29 are used in this analysis, because CH13 is used in the ocean color atmospheric correction and longer wavelength looks temporally stable. 2003/03/20 around Japan ADEOS-2 PI workshop March

6 2. Operation flow Comparison between simulated CH01 and observed GLI CH01 L TOA in 2003/07/11 (by CH13-19) Simulation by GLI NIR & GANAL & SeaWiFS GLI L TOA Compare Vicarious coefficients GLI/Simulation Distribution by mirror incident angle ADEOS-2 PI workshop March

7 An example in 2003/07/11 Water vapor and airmass dependency for absorption bands 2. Operation flow scatter diagram used for aerosol estimation in this case ADEOS-2 PI workshop March

8 2. Operation flow; nlw confirmation We checked the operation by comparing outputs of ocean algorithm and simulation inputs. Calculated nlws, CHLA and Tau are agree with the input SeaWiFS (bandinterpolated) ones. nlw, CHLA and Tau in 2003/07/11 Atmospheric correction by CH16-19 ADEOS-2 PI workshop March

9 3. Results; vicarious coefficients Coefficients based on CH13A-19A About 5% change at CH01. Unrealistic large scatter on SWIR channels CH global avg CH global avg NA Temporal change of the model selection NA NA ADEOS-2 PI workshop March

10 4. Temporal change (1) Coefficients based on CH19B-29B On-board calibration and stripe noise correction indicated A-side is changed during the mission period. New candidate for bright targets Scatter on SWIR can be small. Temporal change of the model selection can be stable ADEOS-2 PI workshop March

11 4. Temporal change (2) CH13A and 19A changes based on the CH19B -29B (19B and 29B are tuned to be agree with the results of 13A and 19A) CH13A and 19A are about 5% decreased (coefficients are increased) during eight months. This is consistent with A/B side difference in the stripenoise analysis in dark areas. (maybe caused by the stray light) 5% ADEOS-2 PI workshop March

12 5. Mirror-angle dependency (1) Scan-mirror incident angle dependency based on CH13A - 19A (considering temporal changes of CH13A and 19A) CH1-3 show angle dependencies. Only mirror-side difference is changed (no mirror angle dependency) in other channels. We can identify the angle dependency by the large sample number in this scheme. ADEOS-2 PI workshop March

13 5. Mirror-angle dependency (2) Example for Level-2 operation: MOBY & GLI nlw By considering the mirror incident angle dependency, nlw estimation can be improved in UV and blue bands. ADEOS-2 PI workshop March

14 6. Possibility of this scheme (1) MODIS Level-1B This scheme can apply to other satellite data Terra/ MODIS CH01-03 Due to the MODIS algorithm version up in Nov 2003 Aqua/ MODIS CH01-03 ADEOS-2 PI workshop March

15 6. Possibility of this scheme (2) GLI thermal channels Similar scheme can be used to GLI thermal infrared channels (Reynolds SST instead of SeaWiFS nlw) Thermal infrared simulated by LOWTRAN-7, Reynolds SST and atmospheric profile by JMA objective analysis data Coefficients in Apr, May, Jun, Aug, Oct, 2003 ADEOS-2 PI workshop March

16 7. Summary 1) We could derive vicarious coefficients, which have enough accuracy for Level-2 processing, (for dark target) using global data sets and radiative transfer model. 2) The coefficients show, Band characteristics for all VNIR and SWIR channels except for strong absorption channels. Scan-angle dependency and its temporal change for CH Scan-mirror side difference and its temporal change for the mirror-side A. 3) We set the coefficients to 1.0 in Ver.1, and recommend the CH13A-19A-base ones for level-2 applications. Candidates: ADEOS-2 PI workshop March

17 8. Future works 1) Set calibration table for considering mirrorangle, mirror-side, and their temporal changes in the level-1 (or 2) processing 2) Integrate all results of this analysis, ground match-up, stripe noise, and onboard calibrations 3) Investigate the reasons of the above characteristics ADEOS-2 PI workshop March

18 9. Lessons learned 1) We should better to have the way to know the NIR bands, which are used for aerosol estimation, by some independent ways, e.g., ground observation, global statistics, moon observation, or on-orbit calibrations. 2) One (or some) well-calibrated sensor(s) should be operated continuously. (we hope our future sensor to be one of them.) 3) After all, we should better to re-evaluate solar irradiance data set, especially from UV to blue bands. ADEOS-2 PI workshop March

19 10. Acknowledgement This work is doing in JAXA GLI calibration team and GLI calibration working group. MOBY data used in 5. is provided by Dr. Dennis Clark and Dr. Stephanie Flora of MODIS, NOAA. SeaWiFS level-3 8-day binned data is provided by NASA Goddard Space Flight Center. Objective analysis data and Earth Probe TOMS ozone data used in the L TOA calculation is provided by Japan Meteorological Agency and NASA Goddard Space Flight Center, respectively. Ocean-color atmospheric correction algorithm is provided by Prof. Hajime Fukushima. RSTAR5b making the look-up table is constructed by Prof. Teruyuki Nakajima and his laboratory. In-water algorithm for the channel interpolation is provided by Dr. Akihiko Tanaka. We thank very much above data providers and collaborators. ADEOS-2 PI workshop March