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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Path Radiance Technique for Retrieving Aerosol Optical Thickness Over Land

The key issue in retrieving aerosol optical thickness over land from shortwave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a Landsat TM (Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Department of Energy's Atmospheric Radiation Measurement) program on September 27,1997, a very clear day (aerosol optical thickness of 0.07 at 0.5 microns) during the first Landsat Intensive Observation Period (IOP). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 micron and band 3 at 0.66 micron agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Tsay, S.-C.↗
NASA NTRS1999

Path Radiance Technique for Retrieving Aerosol Optical Thickness over Land

The key issue in retrieving aerosol optical thickness over land from short-wave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a Landsat TM (Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Department of Energy's Atmospheric Radiation Measurement) program on September 27, 1997, a very clear day (aerosol optical thickness of 0.07 at 0.5 pm) during the first Landsat IOP (Intensive Observation Period). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 pm and band 3 at 0.66 pm agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Tsay, S.-C.↗
NASA NTRS2001

Validation of MODIS Aerosol Optical Depth Retrieval Over Land

Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.

Chu, D. A.↗
NASA NTRS2000

Dust in the Sky: Atmospheric Composition. Modeling of Aerosol Optical Thickness

Aerosol is any small particle of matter that rests suspended in the atmosphere. Natural sources, such as deserts, create some aerosols; consumption of fossil fuels and industrial activity create other aerosols. All the microscopic aerosol particles add up to a large amount of material floating in the atmosphere. You can see the particles in the haze that floats over polluted cities. Beyond this visible effect, aerosols can actually lower temperatures. They do this by blocking, or scattering, a portion of the sun's energy from reaching the surface. Because of this influence, scientists study the physical properties of atmospheric aerosols. Reliable numerical models for atmospheric aerosols play an important role in research.

Chin, Mian↗
NASA NTRS1999

Path Radiance Techniques for Retrieving Aerosol Optical Thickness over Land

The key issue in retrieving aerosol optical thickness over land from shortwave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a TM (Landsat Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Atmospheric Radiation Measurement) program on September 27, 1997, a very clear day during the first Landsat IOP (Intensive Observation Period). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 micrometers and band 3 at 0.66 micrometers agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness (such as 0.07 at 0.5 micrometers as in the example considered here) makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Wen, Guoyong↗
DOE OSTI2022

Quantifying the effects of mixing state on aerosol optical properties

Abstract. Calculations of the aerosol direct effect on climate rely on simulated aerosol fields. The model representation of aerosol mixing state potentially introduces large uncertainties into these calculations, since the simulated aerosol optical properties are sensitive to mixing state. In this study, we systematically quantified the impact of aerosol mixing state on aerosol optical properties using an ensemble of 1800 aerosol populations from particle-resolved simulations as a basis for Mie calculations for optical properties. Assuming the aerosol to be internally mixed within prescribed size bins caused overestimations of aerosol absorptivity and underestimations of aerosol scattering. Together, these led to errors in the populations' single scattering albedo of up to −22.3 % with a median of −0.9 %. The mixing state metric χ proved useful in relating errors in the volume absorption coefficient, the volume scattering coefficient and the single scattering albedo to the degree of internally mixing of the aerosol, with larger errors being associated with more external mixtures. At the same time, a range of errors existed for any given value of χ. We attributed this range to the extent to which the internal mixture assumption distorted the particles' black carbon content and the refractive index of the particle coatings. Both can vary for populations with the same value of χ. These results are further evidence of the important yet complicated role of mixing state in calculating aerosol optical properties.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Comparison of Coincident Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depths over Land and Ocean Scenes Containing Aerosol Robotic Network Sites

The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), launched on 18 December 1999 aboard the Terra spacecraft, are making global observations of top-of-atmosphere (TOA) radiances. Aerosol optical depths and particle properties are independently retrieved from these radiances using methodologies and algorithms that make use of the instruments corresponding designs. This paper compares instantaneous optical depths retrieved from simultaneous and collocated radiances measured by the two instruments at locations containing sites within the Aerosol Robotic Network (AERONET). A set of 318 MISR and MODIS images, obtained during the months of March, June, and September 2002 at 62 AERONET sites, were used in this study. The results show that over land, MODIS aerosol optical depths at 470 and 660 nm are larger than those retrieved from MISR by about 35% and 10% on average, respectively, when all land surface types are included in the regression. The differences decrease when coastal and desert areas are excluded. For optical depths retrieved over ocean, MISR is on average about 0.1 and 0.05 higher than MODIS in the 470 and 660 nm bands, respectively. Part of this difference is due to radiometric calibration and is reduced to about 0.01 and 0.03 when recently derived band-to-band adjustments in the MISR radiometry are incorporated. Comparisons with AERONET data show similar patterns.

Moderate Resolution Imaging Spectroradiometer (MOD↗
DOE OSTI2025

NeuralMie (v1.0): an aerosol optics emulator

The direct interactions of atmospheric aerosols with radiation significantly impact the Earth's climate and weather and are important to represent accurately in simulations of the atmosphere. This work introduces two contributions to enable a more accurate representation of aerosol optics in atmosphere models: (1) NeuralMie, a neural network Mie scattering emulator that can directly compute the bulk optical properties of a diverse range of aerosol populations and is appropriate for use in atmosphere simulations where aerosol optical properties are parameterized, and (2) TAMie, a fast Python-based Mie scattering code based on the Toon and Ackerman (1981) Mie scattering algorithm that can represent both homogeneous and coated particles. TAMie achieves speed and accuracy comparable to established Fortran Mie codes and is used to produce training data for NeuralMie. NeuralMie is highly flexible and can be used for a wide range of particle types, wavelengths, and mixing assumptions. It can represent core-shell scattering and, by directly estimating bulk optical properties, is more efficient than existing Mie code and Mie code emulators while incurring negligible error compared to existing aerosol optics parameterization schemes (0.08 % mean absolute percentage error).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

BOREAS Aerosol Optical Depth Measurements and Atmospheric Correction

Aerosol optical depth measurements were conducted during all three Intensive Field Campaigns of BOREAS in 1994 by both groundbased and airborne tracking sun photometers. These measurements documented the highly variable aerosol loadings in the BOREAS study areas: very clear days with optical depths at 525 nm of 0.05 alternated with very hazy days (due to smoke from extensive western forest fires) with optical depths greater than 0.5. The airborne sun photometer showed the aerosol layer extended up to 3.5-4 km. Remote sensing missions were largely constrained to clear days, but some occurred under less optimum conditions. The spectral aerosol optical depths were used to derive aerosol size distributions and other aerosol optical properties useful for atmospheric correction of satellite and aircraft remote sensing imagery. Aerosol scattering phase functions and aerosol single scattering albedoes were calculated from Mie scattering theory using reasonable assumptions for the index of refraction for the aersols. Our atmospheric correction procedure Imagecor used the aerosol optical properties to derive surface radiances at each pixel from Landsat Thematic Mapper data of the southern study area on July 25, 1994. Similar efforts under FIFE showed close agreement between atmospherically corrected surface radiances and helicopter measurements of surface radiance of the same sites. Recently we incorporated calculations of the total downwelling irradiance from the 6S radiative transfer program (which vary little over the entire Landsat scene) to derive surface reflectances from the atmospherically corrected surface radiances. Tests using this procedure with both FIFE and HAPEX data sets show good agreement with ground-measured surface reflectances. Surface reflectances derived from the atmospherically corrected radiances of the July 25th Landsat scene will be compared to surface measurements made in BOREAS'southern study area.

Wrigley, R. C.↗
NASA NTRS2007

3D Radiative Aspects of the Increased Aerosol Optical Depth Near Clouds

To characterize aerosol-cloud interactions it is important to correctly retrieve aerosol optical depth in the vicinity of clouds. It is well reported in the literature that aerosol optical depth increases with cloud cover. Part of the increase comes from real physics as humidification; another part, however, comes from 3D cloud effects in the remote sensing retrievals. In many cases it is hard to say whether the retrieved increased values of aerosol optical depth are remote sensing artifacts or real. In the presentation, we will discuss how the 3D cloud affects can be mitigated. We will demonstrate a simple model that can assess the enhanced illumination of cloud-free columns in the vicinity of clouds. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from the enhanced Rayleigh scattering due to presence of surrounding clouds. A stochastic cloud model of broken cloudiness is used to simulate the upward flux.

Marshak, Alexander↗
NASA NTRS2000

Aerosol Radiative Forcing Derived From SeaWIFS - Retrieved Aerosol Optical Properties

To understand climatic implications of aerosols over global oceans, the aerosol optical properties retrieved from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are analyzed, and the effects of the aerosols on the Earth's radiation budgets (aerosol radiative forcing, ARF) are computed using a radiative transfer model. It is found that the distribution of the SeaWiFS-retrieved aerosol optical thickness is distinctively zonal. The maximum in the equatorial region coincides with the Intertropical Convergence Zone, and the maximum in the Southern Hemispheric high latitudes coincides with the region of prevailing westerlies. The minimum aerosol optical thickness is found in the subtropical high pressure regions, especially in the Southern Hemisphere. These zonal patterns clearly demonstrate the influence of atmospheric circulation on the oceanic aerosol distribution. Over global oceans, aerosols reduce the annual mean net downward solar flux by 5.4 W m-2 at the top of the atmosphere and by 6.1 W m-2 at the surface. The largest ARF is found in the tropical Atlantic, Arabian Sea, Bay of Bengal, the coastal regions of Southeast and East Asia, and the Southern Hemispheric high latitudes. During the period of the Indonesian big fires (September-December 1997), the cooling due to aerosols is greater than 15 W m-2 at the top of the atmosphere and greater than 30 W m(exp -1) at the surface in the vicinity of the maritime continents. The atmosphere receives extra solar radiation by greater than 15 W m(exp -1) over a large area. These large changes in radiative fluxes are expected to have enhanced the atmospheric stability, weakened the atmospheric circulation, and augmented the drought condition during that period. It would be very instructive to simulate the regional climatic. The model-calculated clear sky solar flux at the top of the atmosphere is compared with that derived from the Clouds and the Earth's Radiant Energy System (CERES). The net downward solar flux of CERES is systematically larger than the model calculations by -3 W M-2. In the equatorial region, the CERES-derived net downward solar flux is even larger than the model calculations without including aerosols. It is possible that the CERES incorrectly identified regions of high humidity and high aerosol concentration as being cloud contaminated and, hence, overestimated the clear sky net downward solar flux.

Chou, Mong-Dah↗
NASA NTRS2017

Developing and Diagnosing Climate Change Indicators of Regional Aerosol Optical Properties

Given the importance of aerosol particles to radiative transfer via aerosol-radiation interactions, a methodology for tracking and diagnosing causes of temporal changes in regional-scale aerosol populations is illustrated. The aerosol optical properties tracked include estimates of total columnar burden (aerosol optical depth, AOD), dominant size mode (Ångström exponent, AE), and relative magnitude of radiation scattering versus absorption (single scattering albedo, SSA), along with metrics of the structure of the spatial field of these properties. Over well-defined regions of North America, there are generally negative temporal trends in mean and extreme AOD, and SSA. These are consistent with lower aerosol burdens and transition towards a relatively absorbing aerosol, driven primarily by declining sulfur dioxide emissions. Conversely, more remote regions are characterized by increasing mean and extreme AOD that is attributed to increased local wildfire emissions and long-range (transcontinental) transport. Regional and national reductions in anthropogenic emissions of aerosol precursors are leading to declining spatial autocorrelation in the aerosol fields and increased importance of local anthropogenic emissions in dictating aerosol burdens. However, synoptic types associated with high aerosol burdens are intensifying (becoming more warm and humid), and thus changes in synoptic meteorology may be offsetting aerosol burden reductions associated with emissions legislation.

Ryan C Sullivan↗
NASA NTRS2014

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from τMI [basic algorithm] = 0.41τAERONET + 0.16 to τMI [new algorithm] = 0.70τAERONET + 0.01.

aerosols↗
NASA NTRS2012

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results.

Petrenko, Mariya↗
NASA NTRS2013

Assessment of Error in Aerosol Optical Depth Measured by AERONET Due to Aerosol Forward Scattering

We present an analysis of the effect of aerosol forward scattering on the accuracy of aerosol optical depth (AOD) measured by CIMEL Sun photometers. The effect is quantified in terms of AOD and solar zenith angle using radiative transfer modeling. The analysis is based on aerosol size distributions derived from multi-year climatologies of AERONET aerosol retrievals. The study shows that the modeled error is lower than AOD calibration uncertainty (0.01) for the vast majority of AERONET level 2 observations, ~99.53%. Only ~0.47% of the AERONET database corresponding mostly to dust aerosol with high AOD and low solar elevations has larger biases. We also show that observations with extreme reductions in direct solar irradiance do not contribute to level 2 AOD due to low Sun photometer digital counts below a quality control cutoff threshold.

AERONET↗
DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Effect of Wind Speed on Aerosol Optical Depth over Remote Oceans, Based on Data from the Maritime Aerosol Network

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (approx. 0.004 - 0.005), even for strong winds over 10m/s. The relationships show significant scatter (correlation coefficients typically in the range 0.3 - 0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used

Smirnov, A.↗