Light absorption by aerosols from A-Train satellite data and global model Modeling team: Mian Chin, Huisheng Bian, Tom Kucsera NASA GSFC OMI aerosol team: Hiren Jethva, Omar Torres POLDER/GRASP team: Oleg Dubovik, Pavel Litvinov, Tatyana Lapyonok, Fabrice Ducos, David Fuertes, Cheng Chen U. Lille GRASP Acknowledgements: AERONET site managers, scientists, engineers, and technicians Support from NASA Terra/Aqua Science Program, Aura Science Program, and Atmospheric Composition Modeling and Analysis Program, and the French Labex CaPPA Project

Introduction Aerosol absorption plays important roles in air quality, weather, and climate Through aerosol-radiaiton-cloud interaction, absorbing aerosols affect boundary layer depth, wind speed, and cloud formation Absorbing aerosols cause warming, partially offset the aerosol cooling effects Most important shortwave absorbing aerosols species: black carbon (BC), dust, and some organic aerosols (aka brown carbon, a part of OA) BC and OA are mainly from anthropogenic and biomass burning sources while dust is from arid and semi-arid land areas Global observations of aerosol absorption is sparse because of the limitation of satellite instrument capabilities and retrieval accuracy This study focuses on comparisons of AOD and AAOD from A-train satellite retrievals and global model simulations with AERONET data

A-train satellite retrievals of AOD and AAOD from the same instrument Aura PARASOL POLDER on PARASOL satellite: Visible to NIR wavelengths, multi-viewing angle with polarization. GRASP retrieval (U. Lille) Monthly average at 1°×1° Over Africa, Middle East, and parts of India and China: Data from the quality controlled products (“SLOW” production) by the GRASP group Over other parts of the world: Provisional data (“FAST” production) with unsophisticated filters to remove some anomalous/contaminated data OMI on Aura satellite: UV wavelengths (converted to 500 nm) OMAERUV retrieval version 1.7.4 (GSFC) Monthly average at 0.5°×0.5°

GEOS-5/GOCART model calculations of AOD and AAOD Aerosol species simulated: sulfate, nitrate, ammonium, BC, OA, dust, and sea salt Meteorology: Modern Era Reanalysis for Research and Applications, version 2 (MERRA2) Emissions: Anthropogenic, biomass burning, and natural (ocean, volcanoes, dust) Over Africa/Middle East region (40°S-40°N, 30°W-60°E), dust, BC, and OA emissions are replaced with the retrieved emissions based on POLDER/GRASP AOD with GEOS-Chem adjoint model (C. Chen et al., manuscript in preparation, 2017) Optical properties: OPAC refractive indices with parameterized particle size growth as f(RH)

AOD: 200802 and 200809 OMI/OMAERUV 500 nm POLDER/GRASP 565 nm GEOS5/GOCART 550 nm 200809 200802

AAOD: 200802 and 200809 OMI/OMAERUV 500 nm POLDER/GRASP 565 nm GEOS5/GOCART 550 nm 200809 200802

AERONET sites with ≥ 2 months of Almucantar AOD data in 2008 (191) Comparisons with AERONET Almucantar data of AOD and AAOD, monthly averages in 2008 AERONET sites with ≥ 2 months of Almucantar AOD data in 2008 (191) NAM = North America CAM = Central America SAM = South America EUR = Europe RBU = Russia/Belarus/Ukraine CAS = Central Asia EAS = East Asia SAS = South Asia SEA = Southeast Asia ANZ = Australia/New Zealand NAF = North Africa MDE = Middle East RAF = Rest of Africa OCN = Oceanic For comparisons with AERONET, AOD and AAOD data over all AERONET sites are converted to 550 nm values using the corresponding AERONET Angstrom Exponents

Polluted regions of South Asia and East Asia India China AOD 550 nm AAOD 550 nm AE 440-870 nm × AERONET Δ POLDER SU   BC OM Dust Seasalt GEOS-5/GOCART NI OMI

Less polluted regions of N America and Europe USA Spain AOD 550 nm AAOD 550 nm AE 440-870 nm × AERONET Δ POLDER SU   BC OM Dust Seasalt GEOS-5/GOCART NI OMI

Dust regions over North Africa and N Atlantic Nigeria Sal Island AOD 550 nm AAOD 550 nm AE 440-870 nm × AERONET Δ POLDER SU   BC OM Dust Seasalt GEOS-5/GOCART NI OMI

Biomass burning regions in South America and southern Africa Brazil Zambia AOD 550 nm AAOD 550 nm AE 440-870 nm × AERONET Δ POLDER SU   BC OM Dust Seasalt GEOS-5/GOCART NI OMI

Overall comparisons with AERONET: Land GEOS-5/GOCART NAM = North America CAM = Central America SAM = South America EUR = Europe RBU = Russia/Belarus/Ukraine CAS = Central Asia EAS = East Asia SAS = South Asia SEA = Southeast Asia ANZ = Australia/New Zealand NAF = North Africa MDE = Middle East RAF = Rest of Africa OCN = Oceanic POLDER/GRASP AERONET OMI/OMAERUV AERONET AERONET

Overall comparisons with AERONET: Coastal and Oceanic islands GEOS-5/GOCART NAM = North America CAM = Central America SAM = South America EUR = Europe RBU = Russia/Belarus/Ukraine CAS = Central Asia EAS = East Asia SAS = South Asia SEA = Southeast Asia ANZ = Australia/New Zealand NAF = North Africa MDE = Middle East RAF = Rest of Africa OCN = Oceanic POLDER/GRASP AERONET OMI/OMAERUV AERONET AERONET

Concluding remarks Preliminary comparisons of AOD and AAOD from two completely different A-Train satellite sensors (POLDER on PARASOL and OMI on Aura) and model: Over land: a broad consistency of AOD among them (mostly over land), although AAOD differing by a factor of 2 (with POLDER agree with AERONET retrieval better) Over coastal and oceanic islands: AOD from POLDER and OMI is overall 37% and 57% higher than AERONET, respectively. AAOD from OMI and model are 37% lower but that from POLDER is 50% higher than AERONET retrievals Over open ocean: POLDER and model have large difference in AAOD, but there is a lack of other datasets to verify Quantifying light absorption by aerosols still needs major effort, especially over oceans – better instrument sensitivity and more accurate optical properties for model calculations are needed [Using POLDER/GRASP posterior emissions over Africa/Middle East helps improve the model simulations (test in other models needed – contact Oleg Dubovik and Cheng Chen from U. Lille)]