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

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

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 μm Spatial resolution 1 x 1 km Two viewing angles allow to account for surface effects on TOA radiation Over land the dual view aerosol retrieval algorithm (ADV) is used AATSR has two viewing angles; forward at 55°, and nadir

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, , 1998

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

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

Test for August 10 th 2004 Comparison with MODIS Cloud Protocol : 4 tests BT 12µm R 659 R 865nm /R 659 BT 12µm – BT 11µm Not always used Agreement: % Disagreement: % Non conclusive: 4.91 % AATSR CLOUD MASK CLEAR CLOUD AATSR CLOUD MASK CLEAR Cloud Screening

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): 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: /2005JD Levy et al. 2007: Global aerosol optical properties and application to Moderate Resolution Imaging Spectroradiometer aerosol retrieval over land. J. Geophys. Res., 112, D13210.

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

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

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

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

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

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

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

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

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)

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

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

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 >) Problems: AATSR swath limits coverage Clouds Snow

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 km 2 or larger) Selection appropriate aerosol model