UV Aerosol Indices from (TROP)OMI An investigation of viewing angle dependence 28.11.2013, Marloes Penning de Vries and Thomas Wagner Max Planck Institute.

Slides:



Advertisements
Similar presentations
Validation of SCIA’s reflectance and polarisation (Acarreta, de Graaf, Tilstra, Stammes, Krijger ) Envisat Validation Workshop, Frascati, 9-13 December.
Advertisements

Products from the OMPS Limb Profiler (LP) instrument on the Suomi NPP Satellite Pawan K. Bhartia Earth Sciences Division- Atmospheres NASA Goddard Space.
WP 5 : Clouds & Aerosols L.G. Tilstra and P. Stammes Royal Netherlands Meteorological Institute (KNMI) SCIAvisie Meeting, KNMI, De Bilt, Absorbing.
 nm)  nm) PurposeSpatial Resolution (km) Ozone, SO 2, UV8 3251Ozone8 3403Aerosols, UV, and Volcanic Ash8 3883Aerosols, Clouds, UV and Volcanic.
A New A-Train Collocated Product : MODIS and OMI cloud data on the OMI footprint Brad Fisher 1, Joanna Joiner 2, Alexander Vasilkov 1, Pepijn Veefkind.
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.
Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 Institute.
Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 Institute.
GEOS-5 Simulations of Aerosol Index and Aerosol Absorption Optical Depth with Comparison to OMI retrievals. V. Buchard, A. da Silva, P. Colarco, R. Spurr.
Envisat Symposium, April 23 – 27, 2007, Montreux bremen.de SADDU Meeting, June 2008, IUP-Bremen Cloud sensitivity studies.
Retrieval of SO 2 Vertical Columns from SCIAMACHY and OMI: Air Mass Factor Algorithm Development Chulkyu Lee, Aaron van Dokelaar, Gray O’Byrne: Dalhousie.
1 Global Observations of Sulfur Dioxide from GOME Xiong Liu 1, Kelly Chance 1, Neil Moore 2, Randall V. Martin 1,2, and Dylan Jones 3 1 Harvard-Smithsonian.
METO 621 Lesson 27. Albedo 200 – 400 nm Solar Backscatter Ultraviolet (SBUV) The previous slide shows the albedo of the earth viewed from the nadir.
ANTHROPOGENIC AND VOLCANIC CONTRIBUTIONS TO THE DECADAL VARIATIONS OF STRATOSPHERIC AEROSOL Mian Chin, NASA Goddard Space Flight Center Plus: Thomas Diehl,
Development of GEMS Cloud Data Processing Algorithm Yong-Sang Choi 1, Bo-Ram Kim 1, Heeje Cho 2, Myong-Hwan Ahn 1 (Former COMS PI), and Jhoon Kim 3 (GEMS.
Gloudemans 1, J. de Laat 1,2, C. Dijkstra 1, H. Schrijver 1, I. Aben 1, G. vd Werf 3, M. Krol 1,4 Interannual variability of CO and its relation to long-range.
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.
1. The MPI MAX-DOAS inversion scheme 2. Cloud classification 3. Results: Aerosol OD: Correlation with AERONET Surface extinction: Correlation with Nephelometer.
EARLINET and Satellites: Partners for Aerosol Observations Matthias Wiegner Universität München Meteorologisches Institut (Satellites: spaceborne passive.
Quality of the official SCIAMACHY Absorbing Aerosol Index (AAI) level-2 product L.G. Tilstra and P. Stammes Royal Netherlands Meteorological Institute.
M. Van Roozendael, AMFIC Final Meeting, 23 Oct 2009, Beijing, China1 MAXDOAS measurements in Beijing M. Van Roozendael 1, K. Clémer 1, C. Fayt 1, C. Hermans.
EUMETSAT METEOROLOGICAL SATELLITE CONFERENCE 15/09/2013 – 20/09/2013, VIENNA EUMETSAT METEOROLOGICAL SATELLITE CONFERENCE 15/09/2013 – 20/09/2013, VIENNA.
1 Remote Sensing of Tropospheric Constituents by OMI on EOS Aura Satellite Pawan K Bhartia NASA Goddard Space Flight Center, Greenbelt, MD, USA Split Antarctic.
SO 2 Retrievals in the UV from Space Caroline Nowlan Atomic and Molecular Physics Division Harvard-Smithsonian Center for Astrophysics Collaborators: Kelly.
1 Aerosol information from the UV-visible spectrometer GOME-2 Piet Stammes, KNMI, De Bilt, The Netherlands 7 November 2012.
OMI Aerosol Products: A tutorial ARSET Applied Remote SEnsing Training A project of NASA Applied Sciences.
A. Bracher, L. N. Lamsal, M. Weber, J. P. Burrows University of Bremen, FB 1, Institute of Environmental Physics, P O Box , D Bremen, Germany.
GE0-CAPE Workshop University of North Carolina-Chapel Hill August 2008 Aerosols: What is measurable and by what remote sensing technique? Omar Torres.
POLAR MULTI-SENSOR AEROSOL PROPERTIES OVER LAND Michael Grzegorski, Rosemary Munro, Gabriele Poli, Andriy Holdak and Ruediger Lang.
Optical properties Satellite observation ? T,H 2 O… From dust microphysical properties to dust hyperspectral infrared remote sensing Clémence Pierangelo.
The Second TEMPO Science Team Meeting Physical Basis of the Near-UV Aerosol Algorithm Omar Torres NASA Goddard Space Flight Center Atmospheric Chemistry.
UV Aerosol Product Status and Outlook Omar Torres and Changwoo Ahn OMI Science Team Meeting Outline -Status -Product Assessment OMI-MODIS Comparison OMI-Aeronet.
Satellite group MPI Mainz Investigating Global Long-term Data Sets of the Atmospheric H 2 O VCD and of Cloud Properties.
Kenneth Pickering (NASA GSFC), Lok Lamsal (USRA, NASA GSFC), Christopher Loughner (UMD, NASA GSFC), Scott Janz (NASA GSFC), Nick Krotkov (NASA GSFC), Andy.
Intercomparison of OMI NO 2 and HCHO air mass factor calculations: recommendations and best practices A. Lorente, S. Döerner, A. Hilboll, H. Yu and K.
MAX-DOAS observations and their application to validations of satellite and model data in Wuxi, China 1) Satellite group, Max Planck institute for Chemistry,
Comparison of OMI NO 2 with Ground-based Direct Sun Measurements at NASA GSFC and JPL Table Mountain during Summer 2007 George H. Mount & Elena Spinei.
SATELLITE OBSERVATIONS OF ATMOSPHERIC CHEMISTRY Daniel J. Jacob.
Synergy of MODIS Deep Blue and Operational Aerosol Products with MISR and SeaWiFS N. Christina Hsu and S.-C. Tsay, M. D. King, M.-J. Jeong NASA Goddard.
Evaluation of OMI total column ozone with four different algorithms SAO OE, NASA TOMS, KNMI OE/DOAS Juseon Bak 1, Jae H. Kim 1, Xiong Liu 2 1 Pusan National.
Trace gas algorithms for TEMPO G. Gonzalez Abad 1, X. Liu 1, C. Miller 1, H. Wang 1, C. Nowlan 2 and K. Chance 1 1 Harvard-Smithsonian Center for Astrophysics.
Retrieval of Vertical Columns of Sulfur Dioxide from SCIAMACHY and OMI: Air Mass Factor Algorithm Development, Validation, and Error Analysis Chulkyu Lee.
C. Lerot 1, M. Koukouli 2, T. Danckaert 1, D. Balis 2, and M. Van Roozendael 1 1 BIRA-IASB, Belgium 2 LAP/AUTH, Greece S5P L2 Verification Meeting – 19-20/05/2015.
 4-azimuth MAX-DOAS measurements in Mainz  Characterisation of the information content using 3D RTM MAXDOAS horizontal (averaging) effects MPI for Chemistry.
TOMS Ozone Retrieval Sensitivity to Assumption of Lambertian Cloud Surface Part 1. Scattering Phase Function Xiong Liu, 1 Mike Newchurch, 1,2 Robert Loughman.
Update on TROPOMI instrument and status Pepijn Veefkind, Diego Loyola, Andreas Richter, Ilse Aben, Michel van Roozendael, Isabelle De Smedt, Richard Siddans,
Retrieval of biomass burning aerosols with combination of near-UV radiance and near -IR polarimetry I.Sano, S.Mukai, M. Nakata (Kinki University, Japan),
Comparisons of LER/MLER Cloud Pressures with a Model of Mie Scattering Plane-Parallel Cloud Alexander Vasilkov 1, Joanna Joiner 2, Pawan K. Bhartia 2,
Monitoring volcanic haze from space: the Bárðarbunga fissure eruption OMI Science Team Meeting 31 August – 2 September 2015, KNMI, de Bilt Image: VIIRS.
Evaluation of model simulations with satellite observed NO 2 columns and surface observations & Some new results from OMI N. Blond, LISA/KNMI P. van Velthoven,
OMI Soft Calibration P. K. Bhartia, Glen Jaross, Steve Taylor, Xiong Liu, Tom Kelly, Changwoo Ahn, Dave Haffner NASA GSFC, Maryland, USA.
Satellite Products Aerosols and Trace Gases Introduction to Remote Sensing for Air Quality Applications Richard Kleidman
Challenge the future Corresponding author: Delft University of Technology Collocated OMI DOMINO and MODIS Aqua aerosol products.
1 SO 2 Air Mass Factors for pollution and volcanic emissions OMI Science Team Meeting De Bilt, June 2006 Pieter Valks, Werner Thomas, Thilo Ebertseder,
Fourth TEMPO Science Team Meeting
DOAS workshop 2015, Brussels, July 2015
Carbon monoxide from shortwave infrared measurements of TROPOMI: Algorithm, Product and Plans Jochen Landgraf, Ilse Aben, Otto Hasekamp, Tobias Borsdorff,
N. Bousserez, R. V. Martin, L. N. Lamsal, J. Mao, R. Cohen, and B. R
Near UV aerosol products
Absolute calibration of sky radiances, colour indices and O4 DSCDs obtained from MAX-DOAS measurements T. Wagner1, S. Beirle1, S. Dörner1, M. Penning de.
Comparison of GOME-2 and OMI surface UV products
Need for TEMPO-ABI Synergy
Kelly Chance Smithsonian Astrophysical Observatory
Chris Sioris Kelly Chance
Retrieval of SO2 Vertical Columns from SCIAMACHY and OMI: Air Mass Factor Algorithm Development and Validation Chulkyu Lee, Aaron van Dokelaar, Gray O’Byrne:
MEASUREMENT OF TROPOSPHERIC COMPOSITION FROM SPACE IS DIFFICULT!
MAXDOAS horizontal (averaging) effects
CALIPSO Total Attenuated Backscatter 532 nm 7 June 2006 Volcanic plume
Cloud trends from GOME, SCIAMACHY and OMI
Presentation transcript:

UV Aerosol Indices from (TROP)OMI An investigation of viewing angle dependence , Marloes Penning de Vries and Thomas Wagner Max Planck Institute for Chemistry, Mainz, Germany

Indices determined at two wavelengths in the UV [1,2] Available from TOMS, GOME(-2), SCIAMACHY, OMI, OMPS,... Most-used wavelength pair: 340/380 nm UVAI≥ 0: Absorbing Aerosol Index (AAI) UVAI≤ 0: SCattering Index (SCI) [3] Advantages UVAI are determined even for cloudy pixels and over highly reflective surfaces No a priori input required (aside from surface pressure) UVAI are very sensitive to elevated UV-absorbing particles Absorbing (UVAI≥ 0) and non-absorbing (UVAI≤ 0) particles can be easily distinguished Disadvantages Quantitative interpretation difficult Sensitive to calibration errors Reminder – UV Aerosol Indices Torres et al., JGR 1998; 2 de Graaf et al., JGR 2005; 3 Penning de Vries et al., ACP, 2009

Calculation of UVAI Determine the measured reflectance at reference wavelength λ 0 : R meas (λ 0 ) Model R Rayl (λ) for Rayleigh atmosphere with R meas (λ 0 ) = R Rayl (λ 0 ) Calculate UVAI using: UVAI = -100* 10 log(R meas /R Rayl ) λ λ0λ0 λ SCI = 1.12 (UVAI = -1.12) AAI = 3.13 (UVAI = 3.13)

UVAI Examples Non-absorbing aerosols (new colorscale!) – Sec. Organic Aerosols over S.E. USA – Volcanic sulfate aerosols (Nabro, 2011) Aug 9 Aug 10 Aug GOME-2 UVAI JJA 2007 OMI UVAI June 13, 2011 GOME-2 PMD UVAI SCIAMACHY Aug 31 July 30 July Absorbing aerosols – Desert dust ( ) – Biomass burning smoke (Russia, 2010) – Volcanic ash (Kasatochi, 2008)

Angle dependence of UVAI Angle dependence was studied theoretically in de Graaf et al., JGR 2005: – Model calculations using DAK – Aerosol layer (SSA = 0.9, AOT = 1, g = 0.7) at 3-4 km, surface albedo 0.05 Viewing angle dependence is moderate for GOME(-2) and SCIAMACHY viewing geometries, but is substantial for (TROP)OMI Rel. azimuth angle 0 Rel. azimuth angle 180 SCIAMACHY GOME-2 (TROP)OMI

OMI UVAI measurements of Nabro eruption Explosive eruption with high-altitude sulfate plume on June 12, 2011 OMI detected the aerosol plume on June 13 (one overpass) and 14 (two overpasses) SO 2 VCD (K.Yang) OMI pixels affected by row anomaly removed June 13 UVAI (NASA) SO 2 VCD (K.Yang) UVAI (NASA) June 14

OMI UVAI measurements of Nabro eruption (2) Same section of plume measured twice within 100 minutes Pixels selected with SO 2 VCD>1 DU to pick out volcanic plume First overpass: negative UVAI; second overpass: positive UVAI?! SO 2 VCD (K.Yang) UVAI (NASA) OMI

RTM study – reflectances Calculations by Steffen Dörner using McArtim3 (SZA 20) Rayleigh phase function causes viewing angle dependence of reflectance Aerosols and clouds have different phase functions JJA Surface albedo 0 1 Layer top altitude: 19 km 15 km 11 km 7 km 3 km Clouds COT 50 Aerosols AOT 1.2 SSA 1.0, g 0.6

RTM study – UVAI from aerosols Viewing angle dependence most pronounced for highest AOT and highest altitude RTM settings: – SZA 20, albedo 0.1 – Angs. coeff. = 1.5, g = 0.6 – Homog. layer, 1 km thick - 9 -

RTM study – UVAI from clouds Viewing angle effect much less pronounced for clouds – Possibly not present at all; g was set to 0.6 by mistake!

Application to Nabro plume Radiative transfer modeling of UVAI of elevated sulfate plume – Plume at km – Non-absorbing aerosols with AOT (depending on SO 2 ) Viewing angle effect reproduced by model This is direct evidence for high-altitude aerosol layer (>11 km) with high single- scattering albedo (>0.97) – Note: shown calculations were performed with a version of SCIATRAN that has issues with large viewing angles orbit 36772orbit Modeled UVAIOMI UVAI

Final words Viewing-angle dependence of UVAI for high-altitude plumes very strong – For Nabro’s sulfate plume, change of UVAI sign was observed and modeled – From UVAI alone, we can say that the plume was at high altitude (>11 km) and was nearly non-absorbing (SSA>0.97) Exploit this for other plumes stretching over the complete OMI/TROPOMI swath, or for plumes caught twice by the instrument (like in the presented case) These findings imply that RT becomes complicated for large viewing angles, which may also affect trace gas retrievals