Multi-sensor Aerosol Products Sampling System (MAPSS)

Petrenko, Maksym; Ichoku, Charles; Leptoukh, G.

doi:10.5194/amt-5-913-2012

Cited by 101 publications

(110 citation statements)

References 30 publications

(38 reference statements)

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“…The accuracy of satellite retrievals is generally assessed through comparison with the ground-based sunphotometer aerosol measurements from the Aerosol Robotic Network (AERONET; Holben et al, 1998), where the AERONET measurements are considered the "truth" with uncertainty of ±0.02 (Ichoku et al 2002;Petrenko et al, Atmos. Meas.…”

Section: C6 Comparison With Aeronetmentioning

confidence: 99%

Exploring systematic offsets between aerosol products from the two MODIS sensors

Levy¹,

Mattoo²,

Sawyer³

et al. 2018

Preprint

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Abstract. 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 15 land and ocean, and Angstrom Exponent (AE derived from 0.55 and 0.86 µm) 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 20 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 25 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 30 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.Atmos. Meas. Tech. Discuss., https://doi

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Section: C6 Comparison With Aeronetmentioning

confidence: 99%

Exploring systematic offsets between aerosol products from the two MODIS sensors

Levy¹,

Mattoo²,

Sawyer³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Figure 1 shows a cutout of a GIANT spreadsheet (top), a schematic of MAPSS sampling strategy (bottom left), map of AERONET sites circa 2001 (bottom center), and a plot taken from [7] (bottom right). MAPSS has evolved into the Multi-sensor Aerosol Products Sampling System [8]. In addition to regular comparison with AERONET, field experiment work characterized MODIS product performance on regional and local scales.…”

Section: Short Modis Historymentioning

confidence: 99%

Growing up MODIS: Towards a mature aerosol climate data record

Levy¹

2013

AIP Conference Proceedings

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“…We found that the reduc- tion can be 6-11 and 11-23 % for Brazil and Australia area in the new algorithm, respectively. Petrenko et al (2012) introduced a new method to validate satellite AOD with AERONET measurements. Following this method, we averaged MODIS AOD retrieval and AERONET measurement spatially and temporally.…”

Section: Cross Comparison Among Dt Aodsmentioning

confidence: 99%

Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction

Graaf

Menenti

2016

Atmos. Meas. Tech.

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Abstract. Aerosol optical depth (AOD) product retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) measurements has greatly benefited scientific research in climate change and air quality due to its high quality and large coverage over the globe. However, the current product (e.g., Collection 6) over land needs to be further improved. The is because AOD retrieval still suffers large uncertainty from the surface reflectance (e.g., anisotropic reflection) although the impacts of the surface reflectance have been largely reduced using the Dark Target (DT) algorithm. It has been shown that the AOD retrieval over dark surface can be improved by considering surface bidirectional distribution reflectance function (BRDF) effects in previous study. However, the relationship of the surface reflectance between visible and shortwave infrared band that applied in the previous study can lead to an angular dependence of the AOD retrieval. This has at least two reasons. The relationship based on the assumption of isotropic reflection or Lambertian surface is not suitable for the surface bidirectional reflectance factor (BRF). However, although the relationship varies with the surface cover type by considering the vegetation index NDVI SWIR , this index itself has a directional effect and affects the estimation of the surface reflection, and it can lead to some errors in the AOD retrieval. To improve this situation, we derived a new relationship for the spectral surface BRF in this study, using 3 years of data from AERONET-based Surface Reflectance Validation Network (ASRVN). To test the performance of the new algorithm, two case studies were used: 2 years of data from North America and 4 months of data from the global land. The results show that the angular effects of the AOD retrieval are largely reduced in most cases, including fewer occurrences of negative retrievals. Particularly, for the global land case, the AOD retrieval was improved by the new algorithm compared to the previous study and MODIS Collection 6 DT algorithm, with the increase of 2.0 and 4.5 % AOD retrievals falling within the expected accuracy envelope ±(0.05 + 15 %), respectively. This implies that the users can get more accurate data without angular bias, i.e., more meaningful AOD data.

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Multi-sensor Aerosol Products Sampling System (MAPSS)

Cited by 101 publications

References 30 publications

Exploring systematic offsets between aerosol products from the two MODIS sensors

Exploring systematic offsets between aerosol products from the two MODIS sensors

Growing up MODIS: Towards a mature aerosol climate data record

Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction

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