Presentation is loading. Please wait.

Presentation is loading. Please wait.

REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Retrieval of aerosol optical properties for clear-sky.

Published byJanel Gilbert Modified over 9 years ago

Similar presentations

Presentation on theme: "REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Retrieval of aerosol optical properties for clear-sky."— Presentation transcript:

1 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Retrieval of aerosol optical properties for clear-sky and partially cloudy scenes from METOP sensors M. Grzegorski, G. Poli, A. Holdak, R. Lang and R. Munro

2 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Overview The Metop/GOME-2 polarisation measurement devices (PMDs) PMAp: Polar Multi-sensor Aerosol product developed at EUMETSAT – A multi-sensor Metop product  AOD over ocean & cloud products: operational in Q1 2014 Examples and Verifications Work in progress & future plans First results: AOD over land (PMAp second generation)

3 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN METOP instrument level-1 data used by PMAp Instru ment Spatial resolution Spectral rangecomments GOMEMain science channel 80 x 40 km240nm -800nm, res. 0.25-0.5nm AAI, low spatial resolution Polarization Monitoring Device 10 x 40 km Metop-B 5 x 40 km Metop-A 311nm-803nm, 15 bands AOD, aerosol type, AAI AVHRR-1.08 x 1.08 km580nm-12500nm, 5 bands Clouds, scene heterogeneity, desert dust IASI-12km (circular)3700–15500nm, resolution 0.5 cm -1 Coarse mode aerosols (desert dust, volcanic ash) Auxiliary data ECMWF wind speed (forecasting) Temporal interpolation necessary -Required for retrievals over ocean surface albedo, Surface elevation --Required for land surface retrievals Target spatial resolution

4 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN The GOME-2 Polarization Monitoring Devices Band-S No.pix1pixw.wav1wav2 1225311.709314.207 2304316.762318.720 33712321.389329.139 4506330.622334.443 5576336.037340.161 68417360.703377.873 71024380.186383.753 811719399.581428.585 913827434.083492.066 1016518494.780548.756 111832552.474556.262 1218711568.070612.869 131989617.867661.893 142184744.112768.269 152242794.080803.072 Radiances & stokes fraction better spatial resolution stokes fraction s = Q/I

5 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN The Polarization Monitoring Devices q-fraction Q-Stokes fraction V-LIDORT GOME-2

6 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp: Very accurate co-location of AVHRR and IASI to the GOME-2 PMD pixel footprints Slide: 6 AVHRR collocation: an AVHRR pixel is collocated to a GOME-2 PMD pixel if it is inside the GOME-2 pixel IASI collocation: a IASI pixel may span up to 6 GOME-2 PMD pixels. Which GOME-2 pixel should it be collocated to? Spatial aliasing due to read-out timing of detectors is taken into account! 2011

7 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp: AOD retrieval algorithm I Three step retrieval: Step1: Pre-classification by AVHRR. Detection of clouds, cloud fraction Strong dust/ash events Pre-classification of possible aerosol types (depending on BTD – T4-T5 tests plus VIS/NIR wavelength dependency) no dust / fine mode, dust, ash, no classification Step2: Retrieval of a subset or all 28 AODs plus chlorophyll correction based on max. 28 aerosol models from LUT provided by O. Hasekamp (O3MSAF) using three alternative retrievals based on cloud, wind-speed/surface and geometry conditions Step3: Selection of the best fit out of the max. 28 AODs using least-square minimization to all wavelength (between 400 and 800 nm)

8 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp: AOD retrieval algorithm Geometry dependent test with intercomparison of: calculated surface signal calculated wind speed dependence calculated aerosol signa l Criterion: impact on TOA not too large w.r.t expected clear-sky conditions Cloud filter: AVHRR/VIS AVHRR/IR Use of reflectance or Stokes fractions Use of reflectance Use of corrected reflectance

9 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Best case: Retrieval clear sky & dark surface Step 2: A set of AODs (for the pre-selected models) and chlorophyll corrections is estimated using three channels: UV [380 nm], VIS/green [520 nm], red edge [800 nm; main AOD band] using least-square minimization. AOD retrieved from 800 nm. Step 3: Selection of a aerosol type / chlorophyll / AOD set using least-square minimization of measured and modelled reflectance in all PMD channels. Stokes fractions are used in addition if applicable. (East part of the swath and close to sun-glint) aerosol model number PMD reflectance SZA=40, cos(RAZI)=-1, VZA=45, AOD= 4 SZA=40, nadir, aerosol model 3 PMD reflectance AOD LUT by O. Hasekamp (SRON/O3MSAF)

10 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Alternate retrieval Combining reflectances & stokes fractions under conditions with large surface contribution Guess an AOD using one channel (reflectance or stokes fraction) using different aerosol models and a priori surface Check reliability: Stokes fraction PMD reflectance AOD LUT by O. Hasekamp (SRON/O3MSAF)

11 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Partially cloudy conditions: Cloud radiance correction by AVHRR AVHRR cloud tests: Albedo test T4 test Uniformity test T4T5 test Retrieval for partly cloudy pixels: Limited to PMD 13/15 Corrected for cloud reflectance ChannelCentral wave- length[μm] Wavelength range [μm] 10.6300.580 - 0.680 20.8650.725 - 1.000 3A1.6101.580 - 1.640 3B3.7403.550 - 3.930 410.80010.300- 11.300 512.00011.500- 12.500 Geometric cloud fraction: Use regular retrieval on corrected reflectances

12 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp results: Aerosol Optical Depth (23/05/2011)

13 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp results: AOD clear sky cases (23/05/2011)

14 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Volcanic ash flag: Identifying pixels misclassified as cloud Orange: Strong ash test positive, cloud tests ignored Blue: cloud fraction < 0.3, AOD retrieved White: no retrieval or cloud fraction > 0.3 and negative ash test Aerosol optical depth Volcanic ash flag: Brightness temperature difference T4-T5 (10 μm – 12 μm) Thresholds in VIS and NIR (e.g. AVHRR CH3A/CH2)

15 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Initial Verification of PMAp Comparison to MODIS Overpass difference: 1.0h MODIS / Terra and METOP Main retrieval R = 0.89 AOD (MODIS) AOD (PMAp) Alternate retrieval R = 0.83 AOD (MODIS) AOD (PMAp) Cloudy pixels R = 0.71 AOD (MODIS)

16 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp Cloud products PMAp: cloud fraction PMAp: cloud optical depth FRESCO (www.temis.nl)www.temis.nl Effective cloud fraction

17 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp tandem operations: AOD Metop A & Metop B (30/08/2013)

18 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp AOD Metop (Mid December 2013 to end January 2014)

19 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp AOD Metop vs AERONET (Mid January 2014 to February 2014)

20 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp AOD Metop vs AERONET (Mid January 2014 to February 2014)

21 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN The PMAp product operational implementation Product features Product features: Near real time 3 minutes granules, maximum 3 hours after sensing time Available via EUMETCast in EPS native and netcdf4. Full orbit offline data. Available from the EUMETSAT archive http://archive.eumetsat.int AOD, COD, volcanic ash flag Planned start of pre-operational dissemination: March 2014

22 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN The PMAp product test-data Product test and trail dissemination phase PMAp runs in EUMETSATs core ground segment #1 in operational mode since 16 th of January 2014 Test data is available to interested users on an offline basis (best effort) on an operational NRT EUMETCast test-dissemination basis (6 th February 2014) Want to be a test user? early access to data early access to al relevant documentation ruediger.lang@eumetsat.int, or ops@eumetsat.int

23 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN The PMAp product Product phase – schedule summary 16 th January 2014:Implementation on Core ground segment #1 6 th February 2014:Start of EUMETCast NRT test dissemination stream 17 th February 2014:Product Validation Board meeting – pre-operational product quality status 4 th March 2014:Start of trail-dissemination to all EUMETCast users 25 th March 2014: Operations Readiness Review (ORR) 26 th March 2014:Start of pre-operational status dissemination Q1 – Q3/2014:Extensive product validation and quality update campaign 20 th August 2014 (TBC):Product Validation Board meeting – operational product quality status

24 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Future algorithm developments Extension of the AOD retrieval to pixels over land (preliminary land retrieval available on prototype level) AOD interpolation for different aerosol types at 460 nm AOD type selection using different aerosol indices between 370-460nm Corrections for partly cloudy pixels combining GOME and AVHRR around 630 nm A dedicated volcanic ash retrieval is currently being developed using the same framework: Temperature differences & NDVI (AVHRR) Shape of the IASI spectra (e.g. concept of Lieven Clarisse) GOME-2 UV ratio Online calibration of AVHRR channels 1, 4 and 5 using GOME-2 and IASI (development for PMAp and in the frame of GSICS)

25 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN PMAp AOD over land First result (30/08/2013) from Metop-A and B

26 REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Conclusions A new aerosol product over ocean from METOP instruments (PMAp) will be provided to users (operational in Q1/2014) The aerosol product is developed using a multi-instrument approach combining GOME, AVHRR and IASI AOD will be retrieved for clear-sky and partly cloudy scenes Cloud fraction, cloud optical depth and limited information on aerosol type like volcanic ash is provided in addition Verifications of the algorithms show promising results The second generation will provide AOD over land and an improved multi-sensor retrieval of volcanic ash

Download ppt "REMOTE SENSING OF ATMOSPHERIC AEROSOL, CLOUDS, AND AEROSOL-CLOUD INTERACTION 16/12-19/12/2013, BREMEN Retrieval of aerosol optical properties for clear-sky."

Similar presentations

GOME-2 polarisation data and products L.G. Tilstra (1,2), I. Aben (1), P. Stammes (2) (1) SRON; (2) KNMI GSAG #42, EUMETSAT, 14-10-2008.

GOME-2 polarisation data and products L.G. Tilstra (1,2), I. Aben (1), P. Stammes (2) (1) SRON; (2) KNMI GSAG #42, EUMETSAT,
Atmospheric Correction Algorithm for the GOCI Jae Hyun Ahn* Joo-Hyung Ryu* Young Jae Park* Yu-Hwan Ahn* Im Sang Oh** Korea Ocean Research & Development.

Atmospheric Correction Algorithm for the GOCI Jae Hyun Ahn* Joo-Hyung Ryu* Young Jae Park* Yu-Hwan Ahn* Im Sang Oh** Korea Ocean Research & Development.
GOME-2 FM3 (Metop-A) Instrument Review, EUMETSAT, Darmstadt, June 2012 Slide: 1 Rűdiger Lang, Rose Munro, Antoine Lacan, Richard Dyer, Marcel Dobber, Christian.

GOME-2 FM3 (Metop-A) Instrument Review, EUMETSAT, Darmstadt, June 2012 Slide: 1 Rűdiger Lang, Rose Munro, Antoine Lacan, Richard Dyer, Marcel Dobber, Christian.
Summary of GEO-CAPE Aerosol Working Group Progress Members: Mian Chin, Pubu Ciren, Hiren Jethva, Joanna Joiner, Shobha Kondragunta, Alexei Lyapustin, Shana.

Summary of GEO-CAPE Aerosol Working Group Progress Members: Mian Chin, Pubu Ciren, Hiren Jethva, Joanna Joiner, Shobha Kondragunta, Alexei Lyapustin, Shana.
 nm)  nm) PurposeSpatial Resolution (km) 317.51Ozone, SO 2, UV8 3251Ozone8 3403Aerosols, UV, and Volcanic Ash8 3883Aerosols, Clouds, UV and Volcanic.

 nm)  nm) PurposeSpatial Resolution (km) Ozone, SO 2, UV8 3251Ozone8 3403Aerosols, UV, and Volcanic Ash8 3883Aerosols, Clouds, UV and Volcanic.
What’s new in MODIS Collection 6 Aerosol Deep Blue Products? N. Christina Hsu, Rick Hansell, MJ Jeong, Jingfeng Huang, and Jeremy Warner Photo taken from.

What’s new in MODIS Collection 6 Aerosol Deep Blue Products? N. Christina Hsu, Rick Hansell, MJ Jeong, Jingfeng Huang, and Jeremy Warner Photo taken from.
MCST – MODLAND Eric F. Vermote –MODLAND representative.

MCST – MODLAND Eric F. Vermote –MODLAND representative.
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.

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.
Constraining aerosol sources using MODIS backscattered radiances Easan Drury - G2

Constraining aerosol sources using MODIS backscattered radiances Easan Drury - G2
Menghua Wang NOAA/NESDIS/ORA E/RA3, Room 102, 5200 Auth Rd.

Menghua Wang NOAA/NESDIS/ORA E/RA3, Room 102, 5200 Auth Rd.
Quantifying aerosol direct radiative effect with MISR observations Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,

Quantifying aerosol direct radiative effect with MISR observations Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,
Page 1 1 of 19, OCO STM 2006 OCO Science Team Meeting March 22, 2006 Vijay Natraj (Caltech), Hartmut Bösch (JPL), Yuk Yung (Caltech) A Two Orders of Scattering.

Page 1 1 of 19, OCO STM 2006 OCO Science Team Meeting March 22, 2006 Vijay Natraj (Caltech), Hartmut Bösch (JPL), Yuk Yung (Caltech) A Two Orders of Scattering.
Page 1 1 of 100, L2 Peer Review, 3/24/2006 Level 2 Algorithm Peer Review Polarization Vijay Natraj.

Page 1 1 of 100, L2 Peer Review, 3/24/2006 Level 2 Algorithm Peer Review Polarization Vijay Natraj.
Page 1 1 of 21, 28th Review of Atmospheric Transmission Models, 6/14/2006 A Two Orders of Scattering Approach to Account for Polarization in Near Infrared.

Page 1 1 of 21, 28th Review of Atmospheric Transmission Models, 6/14/2006 A Two Orders of Scattering Approach to Account for Polarization in Near Infrared.
ESTEC July 2000 Estimation of Aerosol Properties from CHRIS-PROBA Data Jeff Settle Environmental Systems Science Centre University of Reading.

ESTEC July 2000 Estimation of Aerosol Properties from CHRIS-PROBA Data Jeff Settle Environmental Systems Science Centre University of Reading.
Satellite Imagery ARSET Applied Remote SEnsing Training A project of NASA Applied Sciences Introduction to Remote Sensing and Air Quality Applications.

Satellite Imagery ARSET Applied Remote SEnsing Training A project of NASA Applied Sciences Introduction to Remote Sensing and Air Quality Applications.
Visible Satellite Imagery Spring 2015 ARSET - AQ Applied Remote Sensing Education and Training – Air Quality A project of NASA Applied Sciences Week –

Visible Satellite Imagery Spring 2015 ARSET - AQ Applied Remote Sensing Education and Training – Air Quality A project of NASA Applied Sciences Week –
GOME-2 Polarisation Study — Final Presentation L.G. Tilstra (1,2), I. Aben (1), P. Stammes (2) (1) SRON; (2) KNMI EUMETSAT, Darmstadt, 28-11-2008.

GOME-2 Polarisation Study — Final Presentation L.G. Tilstra (1,2), I. Aben (1), P. Stammes (2) (1) SRON; (2) KNMI EUMETSAT, Darmstadt,
Rutherford Appleton Laboratory Remote Sensing Group Ozone Profile Retrieval from MetOp R. Siddans, G. Miles, B. Latter A. Waterfall, B. Kerridge Acknowledgements:

Rutherford Appleton Laboratory Remote Sensing Group Ozone Profile Retrieval from MetOp R. Siddans, G. Miles, B. Latter A. Waterfall, B. Kerridge Acknowledgements:
WP 3: Absorbing Aerosol Index (AAI) WP 10: Level-1 validation L.G. Tilstra 1, I. Aben 2, and P. Stammes 1 1 Royal Netherlands Meteorological Institute.

WP 3: Absorbing Aerosol Index (AAI) WP 10: Level-1 validation L.G. Tilstra 1, I. Aben 2, and P. Stammes 1 1 Royal Netherlands Meteorological Institute.

Similar presentations

Ads by Google