Corey Bettenhausen

MODIS Collection 6 aerosol products: Comparison between Aqua's e-Deep Blue, Dark Target, and “merged” data sets, and usage recommendations

The Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheres data product suite includes three algorithms applied to retrieve midvisible aerosol optical depth (AOD): the Enhanced Deep Blue (DB) and Dark Target (DT) algorithms over land, and a DT over-water algorithm. All three have been refined in the recent “Collection 6” (C6) MODIS reprocessing. In particular, DB has been expanded to cover vegetated land surfaces as well as brighter desert/urban areas. Additionally, a new “merged” data set which draws from all three algorithms is included in the C6 products. This study is intended to act as a point of reference for new and experienced MODIS data users with which to understand the global and regional characteristics of the C6 DB, DT, and merged data sets, based on MODIS Aqua data. This includes validation against Aerosol Robotic Network (AERONET) observations at 111 sites, focused toward regional and categorical (surface/aerosol type) analysis. Neither algorithm consistently outperforms the other, although in many cases the retrieved AOD and the level of its agreement with AERONET are very similar. In many regions the DB, DT, and merged data sets are all suitable for quantitative applications, bearing in mind that they cannot be considered independent, while in other cases one algorithm does consistently outperform the other. Usage recommendations and caveats are thus somewhat complicated and regionally dependent.

Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

The Deep Blue (DB) algorithms primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terras gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

Cross-Calibration of S-NPP VIIRS Moderate Resolution Reflective Solar Bands Against MODIS Aqua over Dark Water Scenes

The Visible Infrared Imaging Radiometer Suite (VIIRS) is being used to continue the record of Earth Science observations and data products produced routinely from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. However, the absolute calibration of VIIRSs reflected solar bands is thought to be biased, leading to offsets in derived data products such as aerosol optical depth (AOD) as compared to when similar algorithms are applied to different sensors. This study presents a cross-calibration of these VIIRS bands against MODIS Aqua over dark water scenes, finding corrections to the NASA VIIRS Level 1 (version 2) reflectances between approximately +1 % and -7 % (dependent on band) are needed to bring the two into alignment (after accounting for expected differences resulting from different band spectral response functions), and indications of relative trending of up to ^0.35 % per year in some bands. The derived calibration gain corrections are also applied to the VIIRS reflectance and then used in an AOD retrieval, and are shown to decrease the bias and total error in AOD across the midvisible spectral region compared to the standard VIIRS NASA reflectance calibration. The resulting AOD bias characteristics are similar to those of NASA MODIS AOD data products, which is encouraging in terms of multisensor data continuity.

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

This study extends the application of the previously developed Aerosol Single-scattering albedo and layer Height Estimation (ASHE) algorithm, which was originally applied to smoke aerosols only, to both smoke and dust aerosols by including nonspherical dust properties in the retrieval process. The main purpose of the algorithm is to derive aerosol height information over wide areas using aerosol products from multiple satellite sensors simultaneously: aerosol optical depth (AOD) and Angstrom exponent from the Visible Infrared Imaging Radiometer Suite (VIIRS), UV aerosol index from the Ozone Mapping and Profiler Suite (OMPS), and total backscatter coefficient profile from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The case studies suggest that the ASHE algorithm performs well for both smoke and dust aerosols, showing root-mean-square error of the retrieved aerosol height as compared to CALIOP observations from 0.58 to 1.31 km and mean bias from −0.70 to 1.13 km. In addition, the algorithm shows the ability to retrieve single-scattering albedo to within 0.03 of Aerosol Robotic Network inversion data for moderate to thick aerosol loadings (AOD of ~1.0). For typical single-layered aerosol cases, the estimated uncertainty in the retrieved height ranges from 1.20 to 1.80 km over land and from 1.15 to 1.58 km over ocean when favorable conditions are met. Larger errors are observed for multilayered aerosol events, due to the limited sensitivities of the passive sensors to such cases.

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S‐NPP VIIRS as Part of the “Deep Blue” Aerosol Project

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectro-radiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASAs VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASAs S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine mode AOD fraction are also well-correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.