How Long should the MISR Record Be when Evaluating Aerosol Optical Depth Climatology in Climate Models?

Lee, Huikyo; Garay, M. J.; Калашникова, О. В.; Yu, Yan; Gibson, Peter B.

doi:10.3390/rs10091326

Cited by 14 publications

(7 citation statements)

References 42 publications

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“…They found that in and downwind of some strong aerosol source regions (including the biomass burning sampled at Alta Floresta), upward of a decade could be required. Although spatial patterns were similar between their MODIS and MISR results, Lee et al () found that MODIS‐based estimates of needed record length were often 1–3 years higher than those from MISR, perhaps due to differences in treatment and sampling of high‐AOD events between these data sets. Further study on this topic would be worthwhile for the future.…”

Section: Intercomparisons Of Aod Time Series Between Modis Viirs Anmentioning

confidence: 84%

“…An implication of this is that climatologies of AOD generated from satellite products in these regions may be sensitive to exactly which years are used to generate the climatology. Recently, Lee et al () attempted to quantify the role of interannual variability by assessing the record length needed to obtain a stable (to within 0.01) annual or seasonal mean AOD field from Multiangle Imaging Spectroradiometer (MISR) or MODIS data. They found that in and downwind of some strong aerosol source regions (including the biomass burning sampled at Alta Floresta), upward of a decade could be required.…”

Section: Intercomparisons Of Aod Time Series Between Modis Viirs Anmentioning

confidence: 99%

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VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

et al. 2019

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A primary goal of the Deep Blue (DB) project is to create consistent long‐term aerosol data records, suitable for climate studies, using multiple satellite instruments. In order to continue Earth Observing System (EOS)‐era aerosol products into the Joint Polar Satellite System era, we have successfully ported the DB algorithm to process data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Although the basic structure of the VIIRS algorithm is similar to that for the Moderate Resolution Imaging Spectroradiometer (MODIS), many enhancements have been made compared to the MODIS collection 6 (C6) version. Most have also been implemented in the latest MODIS Collection 6.1 (C6.1). For example, a new smoke mask was developed based on the spectral curvature of measured reflectance to distinguish biomass burning smoke from weakly absorbing urban/industrial aerosols. Consequently, a new aerosol‐type flag was added into the VIIRS DB data set. In addition, new dust models have been developed to account for the nonsphericity of mineral dust. As a result, a discontinuity in the retrieved aerosol optical depth (AOD) of Saharan dust plumes seen in MODIS C6 products near the boundary between North Africa and the Atlantic has been much reduced. We have also evaluated the VIIRS and MODIS Terra/Aqua C6.1 AOD against Aerosol Robotic Network data. VIIRS and MODIS retrievals show similar performance; around 80% of matchups agree with Aerosol Robotic Network within the expected error of ±(0.05 + 20)%, indicating that DB can provide consistent AOD through the historical EOS and present Joint Polar Satellite System eras.

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Section: Intercomparisons Of Aod Time Series Between Modis Viirs Anmentioning

confidence: 84%

Section: Intercomparisons Of Aod Time Series Between Modis Viirs Anmentioning

confidence: 99%

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

et al. 2019

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“…This does mean that interannual variations could influence the composites for these two sensors. However, recently, Lee et al () used MODIS and MISR data to evaluate how many years were required to define a climatology of AOD within a sampling uncertainty (relative to full mission) of less than 0.01. They found that over the bulk of the open ocean, 2 years appeared sufficient, while in coastal outflow regions (e.g., dust/smoke belts) the time period was more often 4–12 years, dependent on region and distance from aerosol source.…”

Section: Comparison To Other Over‐water Satellite Data Setsmentioning

confidence: 99%

Validation of SOAR VIIRS Over‐Water Aerosol Retrievals and Context Within the Global Satellite Aerosol Data Record

et al. 2018

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This study validates aerosol properties retrieved using a Satellite Ocean Aerosol Retrieval (SOAR) algorithm applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements, from Version 1 of the VIIRS Deep Blue data set. SOAR is the over-water complement to the over-land Deep Blue algorithm and has two processing paths: globally, 95% of pixels are processed with the full retrieval algorithm, while the 5% of pixels in shallow or turbid (mostly coastal) waters are processed with a backup algorithm. Aerosol Robotic Network (AERONET) data are used to validate and compare the midvisible (550 nm) aerosol optical depth (AOD), Ångström exponent (AE), and fine mode fraction of AOD at 550 nm (FMF). AOD uncertainty is shown to be approximately ±(0.03 + 10%) for the full and ±(0.03 + 15%) for the backup algorithms, with a small positive median bias around 0.02. When AOD is below about 0.2, the AE and FMF have small negative offsets from AERONET around −0.15 and −0.04, respectively. For higher AOD, AE is less offset and the magnitudes of differences versus AERONET are about ±0.2 and ±0.14, respectively. Aerosol-type classifications provided by SOAR are found to be reasonable, matching optical-based classifications from AERONET over 80% of the time. Spatial and temporal patterns of AOD and AE are also compared with those of other contemporary over-water satellite aerosol data sets; dependent on region, the satellite data sets show varying levels of consistency, with SOAR broadly in-family, and the largest discrepancies in regions with persistent heavy cloud cover.Plain Language Summary Aerosols are small particles in the atmosphere like desert dust, volcanic ash, smoke, industrial haze, and sea spray. Understanding them is important for applications such as hazard avoidance, air quality and human health, and climate studies. Satellite instruments provide an important tool to study aerosol loading over the world. However, individual satellites do not last forever and newer satellites often have improved capabilities compared to older ones. This paper evaluates an extension of an algorithm, originally designed to monitor aerosols from an older satellite instrument, to a new satellite instrument called Visible Infrared Imaging Radiometer Suite. The evaluation is performed by comparing to ground truth data which are part of the National Aeronautics and Space Administration's global Aerosol Robotic Network, as well as to other satellite-based aerosol data sets from different spaceborne instruments.

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“…To assess their consistency, the products should be compared during overlapping periods, because interannual and shorterterm variability can be significant in some parts of the world (e.g. Lee et al 2018). In the current study, AOD monthly aggregates from different products were evaluated with ground-based measurements such as those from the Aerosol Robotic Network (AERONET, Holben et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Merging regional and global AOD records from 15 available satellite products

Sogacheva

Popp

Sayer

et al. 2019

Preprint

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Abstract. Satellite instruments provide a vantage point to study aerosol loading consistently over different regions of the world. However, the typical lifetime of a single satellite platform is on the order of 5&#8211;15 years; thus, for climate studies the usage of multiple satellite sensors should be considered. This paper assesses some options for creating merged products from an ensemble of 15 individual aerosol optical depth (AOD) data records produced from a broad range of institutions, sensors, and algorithms. Discrepancies exist between AOD products due to differences in their information content, spatial and temporal sampling, calibration, retrieval algorithm approach, as well as cloud masking and other algorithmic assumptions. Users of satellite-based regional AOD time-series are often confronted with the challenge of choosing the appropriate dataset for the intended application. In this study AOD products from different sensors and algorithms are discussed with respect to temporal and spatial differences. Several approaches are investigated to merge AOD records from different satellites, based on evaluation and inter-comparison results. Global and regional comparison of AOD monthly aggregates with ground-based AOD from the Aerosol Robotic Network (AERONET) indicates that different products agree qualitatively for major aerosol source regions on annual, seasonal and monthly time scales, but have regional offsets. All merged regional AOD time series show highly consistent temporal patterns illustrating the evolution of regional AOD. With few exceptions, all merging approaches lead to similar results, reassuring the usefulness and stability of the merged products. Here, we introduce a monthly AOD merged product for the period 1995&#8211;2017, which provides a long-term perspective on AOD changes over different regions of the world. We show that the quality of the merged product is as good as that of individual products. Optimal agreement of the AOD merged product with the AERONET further demonstrates the advantage of the merging of multiple products.

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How Long should the MISR Record Be when Evaluating Aerosol Optical Depth Climatology in Climate Models?

Cited by 14 publications

References 42 publications

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

Validation of SOAR VIIRS Over‐Water Aerosol Retrievals and Context Within the Global Satellite Aerosol Data Record

Merging regional and global AOD records from 15 available satellite products

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