ALBERT

Description: The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

Description: To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1∘×1∘ daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1∘×1∘ grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Description: For reflected sunlight observed from space at visible and near-infrared wavelengths, particles suspended in Earth’s atmosphere provide contrast with vegetation or dark water at the surface. This is the physical motivation for the Dark Target (DT) aerosol retrieval algorithm developed for the Moderate Resolution Imaging Spectrometer (MODIS). To extend the data record of aerosol optical depth (AOD) beyond the expected 20-year lifespan of the MODIS sensors, DT must be adapted for other sensors. A version of the DT AOD retrieval for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar-Orbiting Partnership (SNPP) is now mature enough to be released as a standard data product, and includes some upgraded features from the MODIS version. Differences between MODIS Aqua and VIIRS SNPP lead to some inevitable disagreement between their respective AOD measurements, but the offset between the VIIRS SNPP and MODIS Aqua records is smaller than the offset between those of MODIS Aqua and MODIS Terra. The VIIRS SNPP retrieval shows good agreement with ground-based measurements. For most purposes, DT for VIIRS SNPP is consistent enough and in close enough agreement with MODIS to continue the record of satellite AOD. The reasons for the offset from MODIS Aqua, and its spatial and temporal variability, are investigated in this study.

Description: We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15%) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

Description: Long-term measurements of global aerosol loading and optical properties are essential for assessing climate-related questions. Using observations of spectral reflectance and radiance, the dark-target (DT) aerosol retrieval algorithm is applied to Moderate Resolution Imaging Spectroradiometer sensors on both Terra (MODIS-T) and Aqua (MODIS-A) satellites, deriving products (known as MOD04 and MYD04, respectively) of global aerosol optical depth (AOD at 0.55 µm) over both land and ocean, and an Ångström exponent (AE derived from 0.55 and 0.86 µm) over ocean. Here, we analyze the overlapping time series (since mid-2002) of the Collection 6 (C6) aerosol products. Global monthly mean AOD from MOD04 (Terra with morning overpass) is consistently higher than MYD04 (Aqua with afternoon overpass) by ∼ 13 % (∼ 0.02 over land and ∼ 0.015 over ocean), and this offset (MOD04 – MYD04) has seasonal as well as long-term variability. Focusing on 2008 and deriving yearly gridded mean AOD and AE, we find that, over ocean, the MOD04 (morning) AOD is higher and the AE is lower. Over land, there is more variability, but only biomass-burning regions tend to have AOD lower for MOD04. Using simulated aerosol fields from the Goddard Earth Observing System (GEOS-5) Earth system model and sampling separately (in time and space) along each MODIS-observed swath during 2008, the magnitudes of morning versus afternoon offsets of AOD and AE are smaller than those in the C6 products. Since the differences are not easily attributed to either aerosol diurnal cycles or sampling issues, we test additional corrections to the input reflectance data. The first, known as C6+, corrects for long-term changes to each sensor's polarization sensitivity and the response versus the scan angle and to cross-calibration from MODIS-T to MODIS-A. A second convolves the detrending and cross-calibration into scaling factors. Each method was applied upstream of the aerosol retrieval using 2008 data. While both methods reduced the overall AOD offset over land from 0.02 to 0.01, neither significantly reduced the AOD offset over ocean. The overall negative AE offset was reduced. A collection (C6.1) of all MODIS Atmosphere products was released, but we expect that the C6.1 aerosol products will maintain similar overall AOD and AE offsets. We conclude that (a) users should not interpret global differences between Terra and Aqua aerosol products as representing a true diurnal signal in the aerosol. (b) Because the MODIS-A product appears to have an overall smaller bias compared to ground-truth data, it may be more suitable for some applications. However (c), since the AOD offset is only ∼ 0.02 and within the noise level for single retrievals, both MODIS products may be adequate for most applications.

Description: We have developed a Bayesian Dark Target (BDT) algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrieval over land. In the BDT algorithm, we simultaneously retrieve all pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 550 nm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (466, 550, 644, and 2100 nm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BDT significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BDT was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05 + 15 %) expected error envelope increased from 55 % to 76 %. In addition to retrieving the values of AOD, FMF and surface reflectance, the BDT also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BDT algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

Description: Long-term measurements of global aerosol loading and optical properties are essential for assessing climate-related questions. Using observations of spectral reflectance and radiance, the dark-target (DT) aerosol retrieval algorithm has been applied to Moderate-resolution Imaging Spectroradiometer sensors on both Terra (MODIS-T) and Aqua (MODIS-A) satellites, deriving products (known as MOD04 and MYD04, respectively) of global aerosol optical depth (AOD at 0.55 μm) over both land and ocean, and Angstrom Exponent (AE derived from 0.55 and 0.86 μmm) over ocean. Here, we analyse the overlapping time series (since mid-2002) of the Collection 6 (C6) aerosol products. Global monthly mean AOD from MOD04 (Terra with morning overpass) is consistently higher than MYD04 (Aqua with afternoon overpass) by ~13 % (~0.02 over land and ~0.015 over ocean), and this offset (MOD04 – MYD04), has seasonal as well as long-term variability. Focusing on 2008, and deriving yearly gridded mean AOD and AE, we find that over ocean, the MOD04 (morning) AOD is higher and the AE is lower. Over land, there is more variability, but only biomass-burning regions tend to have AOD lower for MOD04. Using simulated aerosol fields from the Goddard Earth Observing System (GEOS-5) Earth system model, and sampling separately (in time and space) along each MODIS-observed swath during 2008, the magnitudes of morning versus afternoon offsets of AOD and AE are smaller than those in the C6 products. Since the differences are not easily attributed to either aerosol diurnal cycles or sampling issues, we test additional corrections to the input reflectance data. The first, known as C6+, corrects for long-term changes to each sensors' polarization sensitivity, response-versus-scan angle, and to cross-calibration from MODIS-T to MODIS-A. A second convolves the de-trending and cross-calibration into scaling factors. Each method was applied upstream of the aerosol retrieval, using 2008 data. While both methods reduced the overall AOD offset over land from 0.02 to 0.01, neither significantly reduced the AOD offset over ocean. The overall negative AE offset was reduced. A Collection (C6.1) of all MODIS-atmosphere products was released, but we expect that the C6.1 aerosol products will maintain similar overall AOD and AE offsets. We conclude that: a) users should not interpret global differences between Terra and Aqua aerosol products as representing a true diurnal signal in the aerosol. b) Because the MODIS-A product appears to have overall smaller bias compared to ground-truth, it may be more suitable for some applications, however c) since the AOD offset is only ~0.02 and within noise level for single retrievals, both MODIS products may be adequate for most applications.

Description: MODIS-DT Collection 6 - Aqua/Terra level 2, 3; entire record processed - "Trending" issues reduced - Still a 15% or 0.02 Terra vs Aqua offset. - Terra/Aqua convergence improved with C6+, but bias remains. - Other calibration efforts yield mixed results. VIIRS-DT in development - VIIRS is similar, yet different then MODIS - With 50% wider swath, VIIRS has daily coverage - Ensures algorithm consistency with MODIS. - Currently: 20% NPP vs Aqua offset over ocean. - Only small bias (%) over land (2012-2016) - Can VIIRS/MODIS create aerosol CDR? Calibration for MODIS - VIIRS continues to fundamentally important. It's not just Terra, or just Aqua, or just NPP-VIIRS, I really want to push synergistic calibration.

Description: No abstract available