Correspondence: Xingming.liang @noaa, Tel: 301-763-8102 x149, Fax: 301-763-8572

1. The Aerosol Quality Monitor (AQUAM) XingMing Liang1,2 and Alexander Ignatov1 1NOAA/NESDIS/STAR, 2Colorado State University/CIRA 7. Time Series 1. Aerosol Products from AVHRR at NESDIS AOD geometric mean NOAA has been making aerosol retrievals over global oceans from AVHRR since 1991 using a single-channel algorithm (Rao et al., 1989). Currently, 3rd generation of this algorithm is in use, which makes three independent retrievals of aerosol optical depths (AOD) in AVHRR Ch1 (0.63µm), Ch2 (0.86µm) and Ch3a (1.61µm), (Ignatov et al., 2004). In 2008, a new Advanced Clear-Sky Processor over Oceans (ACSPO) system became operational. It uses the same 3rd generation aerosol algorithm, in conjunction with an improved cloud screening and sampling. Also, this aerosol algorithm was employed to generate a 30+ year time series of AOD data using the Pathfinder Atmosphere Extended (PATMOS-x) system, which uses different cloud screening and recalibrated AVHRR reflectances (Heidinger, 2011). • MODIS AOD1 data are centered at ~0.17 and show significant seasonal cycle. • Geometric mean of AVHRR AODs are smaller than MODIS, due to over-screening in low AODs domain for MODIS QC3. • Geometric SD is larger than MODIS, indicating the need for improved QC in ACSPO AOD product. • The AOD minimum (including negatives) is a useful indicator of sensor calibration (Ignatov, 2002). (Note that negative values were truncated by the QC flag in MODIS L2 product.) • AVHRR AODs show better cross-platform consistency relative to MODIS but are more noisy. • The cross-platform inconsistency for MODIS likely due to deficient calibration in Terra, and has been fed-back to MODIS Team. • The number of aerosol pixels is ~×3 larger for AVHRR than MODIS QC3, but consistent with QC1, further indicated over-screening in QC3 AOD minimum 2. The Aerosol Quality Monitor (AQUAM) www.star.nesdis.noaa.gov/sod/sst/AQUAM AQUAM was established to monitor ACSPO and PATMOS-x aerosol products in near-real time (NRT) for temporal stability, self- and cross-consistency, and comparisons with MODIS, AERONET, GOCART, and NAAPS data. Currently, ACSPO retrievals from NOAA-16, -17, -18, -19 and Metop-A, and MO(Y)D04 retrievals from Terra and Aqua in AVHRR-like bands, Ch1 (0.65µm), Ch2 (0.86µm) and Ch6 (1.64µm), are monitored in AQUAM. Our ultimate goal is accurate modeling of TOA radiances, using community radiative transfer model in conjunction with first guess aerosol fields (NAAPS, GOCART), and aerosol correction to SST. 5. AVHRR vs. MODIS consistency AOD geometric standard deviation 3. Selection of MODIS data Number of pixels (x 10000) NOAA-19 AOD1 (0.63μm), 2011-07-03 QC=1 Global histogram of AOD for N19 Global histogram of log(AOD) for N19 QC=3 8. Conclusion and Future Work • AQUAM is a NRT web-based tool employed to monitor AVHRR AOD for quality, stability, self- and cross-consistency, including consistency with MODIS AOD from Terra & Aqua. • MO(Y)D04 C5 AOD products are used in AQUAM, The “best ocean AOD” field, with cloud mask and QC3 flag applied, are initially selected. • MODIS QC3 shows more stable and smaller SD than QC1, but over-screening in low AOD domain. The over-screening in QC3 will be resolved in C6. • The ocean AERONET AODs are unstable and inadequate for sensor AODs VAL. • AVHRR retrieval domain and number of pixels is larger than MODIS, but global mean AOD is smaller. • Global standard deviation of AVHRR AODs is larger than MODIS, likely due to suboptimal QC in AVHRR AOD. • AVHRR scattergrams are noisier indicating the need for improved QC in AVHRR. • The cross-platform inconsistency for MODIS likely due to deficient calibration in Terra, and has been fed-back to MODIS Team. • Using CRTM simulation in conjunction with GOCART and NAAPS fields to simulate TOA reflectances and brightness temperatures, and aerosol correction to SST, are underway. • Using accurate simulations of reflectances and brightness temperatures will improve ACSPO cloud mask and AOD QC, and SST and aerosol retrievals algorithms. • AQUAM analyses will be extended to include VIIRS aerosol retrievals. Aqua AOD1 (0.65μm), 2011-07-03 Global histogram of log(AOD) for Aqua Global histogram of AOD for Aqua • AVHRR retrieval domain is larger than MODIS and mean AODs are smaller, partly due to MODIS QC3 screening out large low AODs domain. • The AOD distributions are close to lognormal (O’Neill et al, 2000). • Global maximum AVHRR AODs are smaller than MODIS. • AVHRR SDs are larger, likely indicating the need for improved QC in AVHRR AOD. • MO(Y)D_04 aerosol products Collection 5 (C5) are selected for AVHRR validation. The “best ocean AOD” field, with cloud mask and QC flag applied, are used. • Two typical QCs (QC=1 and QC=3) are analyzed. The case of QC=3 is more stable and smaller SD than QC=1, though the global coverage is smaller. • The global mean AODs in QC=3 is persistent larger than QC=1, indicates that the larger low AODs domain are screened out in QC=3. • Based on discussion with MODIS Team, this issue is due to suboptimal in C5, and will be updated in C6. • Thus, AQUAM conservatively select QC=3 for AVHRR AODs validation. 6. AVHRR AOD need improved QC 4. AERONET inadequate for ocean AODs validation AOD1 vs AOD2 AE12 vs AOD1 Matchup in 1°x1° and 2hr • “logAOD vs logAOD” scattergrams are more regular and preferred over “AOD vs AOD” • “AOD vs AOD” and “AE vs AOD” show excessive noise and outliers in AVHRR, indicates the need for improved QC for AVHRR AOD. • MODIS AODs are behaved better, due to smoothing nature of multi-channel retrievals • Noise in AE’s increases towards low AODs, in both products (Ignatov et al., 1998). Acknowledgement This work is conducted under the Algorithm Working Group funded by GOES-R Program Office, NPOESS Ocean Cal/Val funded by IPO, and Polar PSDI, NDE and ORS Programs funded by NOAA. CRTM is provided by NESDIS JCSDA. Thanks go to Istvan Laszlo, Shobha Kondragunta, Lorraine Remer, Andrew Heidinger, Mian Chin, Arlindo da Silva, Peter Colarco, Sarah Lu, Jianglong Dong, Ed Hyer, Doug Westphal, Yury Kihai, Boris Petrenko, Mark Liu, Yong Han, Yong Chen, Paul Van Delst, Fuzhong Weng, John Sapper, Changyong Cao, Likun Wang, Fred Wu and Nick Nalli for advice and help. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official NOAA or U.S. Government position, policy, or decision. • AERONET L1.5 data was tested in AQUAM, and the preliminary result show that there are only about 20 ocean (coast or inland-water) sites. • The ocean AERONET AODs are unstable and inadequate for sensor AODs VAL. IAMA Conference, Nov 30 - Dec 2, 2011, UC Davis, CA Correspondence: Xingming.liang@noaa.gov, Tel: 301-763-8102 x149, Fax: 301-763-8572