Retrieval of aerosol properties using AATSR

1. Retrieval of aerosol properties using AATSR Gerrit de Leeuw1,2,3, Larisa Sogacheva1,Pekka Kolmonen1, Anu-Maija Sundström2, Edith Rodriguez1 1 FMI, Climate Change Unit, Helsinki, Finland 2Univ. of Helsinki, Dept. of Physics, Helsinki, Finland 3 TNO, Utrecht, Netherlands

2. Along Track Scanning Radiometer - ATSR ATSR-2 (ERS-2) : 1995 – 2002+AATSR (ENVISAT) : 2002 – 2009+ SLST (Sentinel 3) : 2013 – > 0.555, 0.659, 0.865,1.6, 3.7, 11, 12 μm > 1 x 1 km2 > 500 km swath (global in ~5 days) Aerosols/types; clouds ‘High’ resolution

3. Sun synchronous • Equator overpass time 10:00 • Swath 500km • Spectral Channels • IR: 1.6, 3.7, 10.85, and 12 μm • VIS: 0.555, 0.67, and 0.865 μm • Spatial resolution 1 x 1 km • AATSR has two viewing angles; forward at 55° , and nadir • Two viewing angles allow to account for surface effects on TOA radiation • Over land the dual view aerosol retrieval algorithm (ADV) is used

4. Basic concepts of the DV-algorithm • TOA-reflectance for an underlying Lambertian surface • Spectral and Directional information of ATSR-2 • Shape of the BRDF independent of the wavelength • Effects of aerosols small at 1.6 µm • Bi-modal aerosol model • Veefkind et al., GRL vol 25, no. 16, 3135-3138, 1998

5. Schematic representation of DV- and SV- algorithms SV:Over ocean • Radiative Transfer Model : DAK (Double Adding KNMI) • Optical properties aerosol • Meteorology • Satellite observation: • Instrument characteristics • Calibration • Cloud and surface effects Actual retrieval

6. Crucial steps in aerosol retrieval • Cloud screening: any residual cloud in a scene results in high AOD • Surface contributions: • Eliminate: multiple view • Dark surface over ocean, with Ocean surface reflectance model • Radiative transfer model • Compare modeled reflectance at top of atmosphere with measurement • ’Best fit’ provides desired aerosol parameters

7. AATSR CLOUD MASK AATSR CLOUD MASK CLOUD CLEAR CLEAR Cloud Screening • Cloud Protocol : 4 tests • BT12µm • R659 • R865nm/R659 • BT12µm – BT11µm Not always used Test for August 10th 2004Comparison with MODIS Agreement: 83.03 % Disagreement: 12.05 % Non conclusive: 4.91 %

8. Aerosol models in ADV: • based on AERONET observations • Dubovik et al. 2002: Variability of absorption and optical properties of key aerosol types observed in worldwide locations. J ATMOS SCI, 59 (3): 590-608. • Robles-Gonzalez et al. 2002, Aerosol properties over the Indian Ocean Experiment (INDOEX) campaign area retrieved from ATSR-2, J. Geophys. Res., 111, D15205, doi:10.1029/2005JD006184. • Levy et al. 2007: Global aerosol optical properties and application to Moderate Resolution Imaging Spectroradiometer aerosol retrieval over land. J. Geophys. Res., 112, D13210.

9. ADV Aerosol Remote Sensing Applications Europe: 2003, 2006, 2008 2003, yearly avarage (Pekka Kolmonen)

10. ADV Aerosol Remote Sensing Applications Europe: forest fires Iberian Peninsula, 11 August 2003 (Anu-Maija Sundström)

11. ADV Aerosol Remote Sensing Applications Europe: focus on Po Valley (TEMIS) 0.9 2003, yearly average 2003, July-August average (Pekka Kolmonen)

12. ADV Aerosol Remote Sensing Applications Europe: clean air over Finland 04 June 2008 02 May 2006 (Larisa Sogacheva)

13. 3.0 ADV Aerosol Remote Sensing Applications Focus on China Variability (0.55 m): March 2008 0.55 m; 25 July 2008 (Anu-Maija Sundström)

14. ADV Aerosol Remote Sensing Applications Focus on China (Anu-Maija Sundström)

15. ADV Aerosol Remote Sensing Applications Focus on China Single overpass: 19Oct2008 Zoom over Beijing area (Anu-Maija Sundström)

16. 3 Aerosol Remote Sensing Applications 0.2 Regional: Europe 0.7 Finland:clean air China, Beijing Note scales 1.8 0.7 Po Valley Smoke Iberian Peninsula CONCLUSION: ADV works for very low AOD over Finland (~0.05) to very high AOD over China (~3)

17. Data sets • Available: • Europe 2003, 2006, 2008 • Zoom on Po-Valley • China 8 months in 2008, more to come • Amazone: work in progress • Africa, India, Brazil, Beijing: EUCAARI Development Countries: work in progress • Ocean: AMARSI algo tested (AATSR / MERIS) and ready for use • Global: MACC: 2 years, work in progress • All AATSR data received on LTO tape (7/2002 – 4/2009)

18. Conclusions • The AATSR Dual view algorithms works over land in a variety of conditions • No a priori info on surface needed, but could improve the results • Aerosol models through LUT approach; could be improved • Some reasonable results have been obtained over the desert over the UAE (bright surface), but little or no dust • Cloud screening reasonable, but may be further improved • Dust detection often fails, a dust detection algorithm developed for SEVIRI over ocean (Bennouna et al., 2009, in press) is tested for AATSR

19. SEVIRI: Dust Retrieval over Ocean Cloud Dust Bennouna et al., 2009, JGR Atmospheres, in press

20. Conclusions • AATSR data archive (7/2002-4/2009) received and read • NRT under development: • Uses rolling archive • Long time series: ATSR-2 – AATSR – SLSTA (1995 – present .. 2013 >) • Problems: • AATSR swath limits coverage • Clouds • Snow

21. Use of AATSR data in GLOBemissions • Data assimilation: data interval too long (3 days at mid latitudes or more when clouds) • Hotspot detection • Localized sources, such as: • Forest fire emissions • Power plants • (needed for inventories) • Inversion? • Advantage with respect to ’operational’ products: • Choice of pixel size (1x1 km2 or larger) • Selection appropriate aerosol model