A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

Reid, Jeffrey S.; Gumber, Amanda; Zhang, Jianglong; Holz, Robert E.; Rubin, Juli I.; Xian, Peng; Smirnov, A.; Eck, T. F.; O’Neill, Norman T.; Levy, Robert C.; Reid, Elizabeth A.; Colarco, Peter R.; Benedetti, Angela; Tanaka, Taichu Y.

doi:10.3390/rs14132978

Cited by 10 publications

(5 citation statements)

References 78 publications

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“…Shown also in Figure 2 are the total and speciated AOD differences between the individual RA and the MRC. For total AOD, CAMSRA is apparently higher than the other three RAs over the ocean, which is consistent with the findings on its operational counterpart of high biased FM AOD verified with Maritime Aerosol Network over the ocean in Reid et al (2022). This high bias is attributed to its universally higher OA/smoke AOD compared to other RAs, and suggests that CAMSRA may have higher BB emissions and/or less efficient removals compared to the other RAs.…”

Section: Total and Speciated Aod Climatologysupporting

confidence: 86%

“…It is also noted that all the RAs have slightly higher AOD (on the order of 0.02) over the ocean than MODIS QAed product here. MODIS AOD products are well known to low bias significant aerosol events (e.g., Reid et al, 2022;Gumber et al, 2023), which could lower the mean state of AOD. The slightly lower MODIS AOD compared to the RAs could also be related to clear-sky and contextual bias (Zhang et al, 2009), as MODIS AOD retrieval is only available under clear-sky conditions, while all the RAs include all-sky conditions.…”

Section: Analysis Methodsmentioning

confidence: 99%

“…Those 6-hour-averaged MODIS AOD data were then binned into monthly means. Note that MODIS AOD products are well known to low bias significant aerosol events (Reid et al, 2022;Gumber et al, 2023), which could result in a slightly low AOD climatology, especially in source regions.…”

Section: Modis Aodmentioning

confidence: 99%

“…In recent years, global aerosol reanalyses have been developed by major operational and research centers, owing to the availability of long-record satellite remote sensing aerosol products and advancements in aerosol data assimilation and modeling. These reanalyses are based on their operational counterparts that are included in the "Core Four" members of the International Cooperative for Aerosol Prediction Multi Model Ensemble (ICAP-MME C4C; Sessions et al, 2016;Xian et al, 2019;Reid et al, 2022). The reanalyses include the Copernicus Atmosphere Monitoring Service ReAnalysis (CAMSRA; Inness et al, 2019) produced by the European Centre for Medium-Range Weather Forecasts (ECMWF); the Japanese Reanalysis for Aerosol (JRAero) (Yumimoto et al, 2017) developed by the Japan Meteorological Agency (JMA); the NASA Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2; Randles et al, 2017); and the Navy Aerosol Analysis and Prediction System reanalysis (NAAPS-RA; Lynch et al, 2016) developed by the U.S.…”

Section: Introductionmentioning

confidence: 99%

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Intercomparison of Aerosol Optical Depths from four reanalyses and their multi-reanalysis-consensus

Xian,

Reid,

Ades

et al. 2023

Preprint

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Abstract. The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of Aerosol Optical Depth (AOD) trends and attribution over multi-decadal timescales. Notable aerosol reanalyses currently available include NAAPS-RA from the U.S. Naval Research Laboratory; the NASA MERRA-2; JRAero from the Japan Meteorological Agency (JMA); and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, and data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where diversity and challenges are prominent. Regions with high pollution and often mixed fine-coarse mode aerosol environments such as South Asia, East Asia, Southeast Asia, and the Maritime Continent pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions, and remote oceans exhibit large relative differences in speciated AODs and fine-mode vs coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis-consensus (MRC) approach was developed similar to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAP-MME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments.

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Section: Total and Speciated Aod Climatologysupporting

confidence: 86%

Section: Analysis Methodsmentioning

confidence: 99%

Section: Modis Aodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Intercomparison of Aerosol Optical Depths from four reanalyses and their multi-reanalysis-consensus

Xian,

Reid,

Ades

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…However, since the most-severe aerosol events occur near their terrestrial sources over land, statistics are developed that define severe events locally. While many aerosol product evaluation studies have been conducted (Remer et al, 2008;Levy et al, 2010;Hyer et 120 al., 2011;Sayer et al, 2013;Li et al, 2014;Bilal et al, 2018;Lyapustin et al, 2018;Wei et al, 2019;Reid et al, 2022), this study deviates in that it does not strictly compare products against AERONET, or even between each other, but rather an assessment of differences in the probability distribution functions of AOD with a focus on the relative differences between the aerosol retrieval algorithms. Section 2 describes each of the satellite data products, the ground based AERONET observation, and the software used to grid and aggregate the data.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Severe Aerosol Events from NASA MODIS and VIIRS Aerosol Products for Data Assimilation and Climate Continuity

Gumber

Reid²,

Holz³

et al. 2022

Preprint

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Abstract. While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm’s ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar orbiting satellite algorithms to monitor and characterize significant events a Level 3 (L3) product has been developed, using a consistent aggregation methodology, for four years of observations (2016–2019). Included in this product is AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS “baseline algorithms” are compared to NASA’s recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher percentile AOD regions of the world by product, identified those with the highest measured AODs, and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range-in particular for higher AOD events. Most notable are differences in Boreal biomass burning and Saharan dust. Significant percentile biases that must be accounted for when data is used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions on lower boundary condition and aerosol optical models.

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Global trends in the aerosol optical, physical, and morphological properties obtained using multi-sensor measurements

Gupta

Ratnam

Madhavan

et al. 2023

Atmospheric Environment

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A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

Cited by 10 publications

References 78 publications

Intercomparison of Aerosol Optical Depths from four reanalyses and their multi-reanalysis-consensus

Intercomparison of Aerosol Optical Depths from four reanalyses and their multi-reanalysis-consensus

Assessment of Severe Aerosol Events from NASA MODIS and VIIRS Aerosol Products for Data Assimilation and Climate Continuity

Global trends in the aerosol optical, physical, and morphological properties obtained using multi-sensor measurements

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