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

Sayer, A. M.; Munchak, L. A.; Hsu, N. Christina; Levy, Robert C.; Bettenhausen, C.; Jeong, Myeong-Jae

doi:10.1002/2014jd022453

Cited by 584 publications

(549 citation statements)

References 113 publications

Supporting

Mentioning

497

Contrasting

Order By: Relevance

“…Sayer et al, 2014). These are the root mean square error (RMSE), mean absolute error (MAE), median bias (BIAS), the Pearson linear correlation coefficient (R), the number of coincident MODIS and sun photometer cases (cases) and the fraction (f ) of the MODIS/AERONET AOD retrievals in agreement within the expected uncertainty.…”

Section: Statisticsmentioning

confidence: 83%

“…Usually referred to as expected error (EE), it was applied in accordance with Eq. (3) (Sayer et al, 2014).…”

Section: Statisticsmentioning

confidence: 99%

“…Another approach, the most commonly used for comparison (Bennouna et al, 2011;Sayer et al, 2014), involves averaging all the AOD SP values in the interval of ±30 min and comparing them to the MODIS instrument overpass time (note that AOD t and AOD a averages are really the daily values of MODIS) located in a radius of 25 km around the sun photometer. At least two single AOD SP and two single AOD t (AOD a ) observations were required to calculate the spatio-temporal average.…”

Section: Coincidence Criteria For Modis and Sun Photometer Observationsmentioning

confidence: 99%

“…The aim is to compare the performance of the DB and DT algorithms directly (Sayer et al, 2014). All of these statistical indicators were evaluated for the whole set of collocated AOD t , AOD a , AOD ta with AOD SP , and BAOD; AE t , AE a , AE ta with AE SP ; as well as time frequencies (Fig.…”

Section: Statisticsmentioning

confidence: 99%

“…This comparative analysis does not aim to be a validation study of the MODIS sensor since many works during the long history of the MODIS sensor on the Terra and Aqua platforms have sought to improve its features (these include Kaufman et al, 1997a, b;Tanré et al, 1997;Remer et al, 2002Remer et al, , 2005Remer et al, , 2006Hsu, et al, 2004Hsu, et al, , 2006Hsu, et al, , 2013Levy et al, 2007Levy et al, , 2009Levy et al, , 2010Levy et al, , 2013Levy et al, , 2015Sayer et al, 2013Sayer et al, , 2014 https://darktarget.gsfc.nasa.gov/atbd/overview, last access: 9 April 2018). However, compared to other areas of the world, no studies have been reported in the Caribbean region and in Cuba in particular (Papadimas et al, 2009;Mishchenko et al, 2010;Kahn et al, 2011;Bennouna et al, 2011Bennouna et al, , 2013Witte et al, 2011;Gkikas et al, 2013Gkikas et al, , 2016Levy et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Marrero¹,

Revilla

Parrado³

et al. 2018

Atmos. Meas. Tech.

View full text Add to dashboard Cite

Abstract. In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AOD t ) and Aqua (AOD a ) satellites and those measured using a sun photometer (AOD SP ) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AOD ta ) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AOD t , AOD a , AOD ta compared to AOD SP . For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AOD ta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AOD t , AOD a , AOD ta vs. AOD SP , with a slight overestimation of satellite data compared to AOD SP , (f ). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AOD ta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AOD SP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS-sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

show abstract

Section: Statisticsmentioning

confidence: 83%

“…Usually referred to as expected error (EE), it was applied in accordance with Eq. (3) (Sayer et al, 2014).…”

Section: Statisticsmentioning

confidence: 99%

Section: Coincidence Criteria For Modis and Sun Photometer Observationsmentioning

confidence: 99%

Section: Statisticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Marrero¹,

Revilla

Parrado³

et al. 2018

Atmos. Meas. Tech.

View full text Add to dashboard Cite

show abstract

Spatial boundaries of Aerosol Robotic Network observations over the Mediterranean basin

Mishra

Rudich

Koren

2016

Geophysical Research Letters

View full text Add to dashboard Cite

Accurate knowledge of aerosol variability on a relatively high spatiotemporal scale is needed for better assessment of aerosol radiative effects and aerosol‐climate interactions. We investigated the spatial boundaries of the Aerosol Robotic Network (AERONET) observations over the Mediterranean basin using a statistical approach. We used 13 years (2002–2014) of aerosol optical depth (AOD) measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) and 15 AERONET sites around the Mediterranean basin. The gridded correlation maps show moderate to high correlations (R > 0.5) around each AERONET site up to ~200–500 km radius depending on location. Such analyses provide information on the spatial domain in which the AERONET measurements can be reliably used per site. The statistical model provides a better daytime AOD product on finer temporal resolution with higher spatial coverage as compared to using AERONET/MODIS observations separately. The findings from this study can be useful for the assimilation‐based model forecasting of aerosol properties.

show abstract

Comparison and evaluation of the MODIS Collection 6 aerosol data in China

et al. 2015

View full text Add to dashboard Cite

Several important improvements have been made in recent Moderate Resolution ImagingSpectroradiometer (MODIS) Collection 6 aerosol retrievals, but few regional validations are conducted. We compared Deep Blue (DB) and Dark Target (DT) retrievals over China and evaluated their performance with ground observations. Sampling frequency of DB was much higher than that of DT, which was mainly caused by unavailable retrieval of DT in bright surface and heavy pollution conditions. It is found that merged aerosol optical depth (AOD) will miss some cases if it was determined only by vegetation density. Collocated comparison shows that DT AOD was substantially higher than DB with seasonal difference exceeding 0.3-0.4 over eastern China. However, when all available retrievals were considered, DT AOD was obviously lower than DB in all the seasons except spring due to their large difference in spatial coverage in high-AOD conditions. DB can well reveal spatial extent of the widespread haze pollution while there were few values in DT. More than one half of the situations with AOD > 1.0 was missed by DT, which largely underestimated the common regional haze pollution in eastern China. Ground validations show that DT tended to overestimate the aerosol loading by underestimation of the surface contribution and single scattering albedo of aerosols. DB performed generally well with higher accuracy in northern China but exhibited obvious underestimation in northwestern and southern China. Despite of slight decrease in accuracy, DB retrievals with all quality enable a large increase in spatial coverage, especially when dense haze clouds existed.

show abstract

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

Cited by 584 publications

References 113 publications

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Spatial boundaries of Aerosol Robotic Network observations over the Mediterranean basin

Comparison and evaluation of the MODIS Collection 6 aerosol data in China

Contact Info

Product

Resources

About