Shana Mattoo

The MODIS Aerosol Algorithm, Products, and Validation

The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA’s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.41–15 m). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 m. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of 0.03 0.05 over ocean and 0.05 0.15 over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within reff 0.11 m. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances

Spectral radiances measured at the top of the atmosphere in a wide spectral range (0.55–2.13 μm) are used to monitor the aerosol optical thickness and the aerosol size distribution (integrated on the vertical column) of the ambient (undisturbed) aerosol over the oceans. Even for the moderate resolution imaging spectrometer (MODIS) wide spectral range, only three parameters that describe the aerosol loading and size distribution can be retrieved. These three parameters are not always unique. For instance, the spectral radiance of an aerosol with a bilognormal size distribution can be simulated very well with a single lognormal aerosol with an appropriate mean radius and width of distribution. Preassumptions on the general structure of the size distribution are therefore required in the inversion of MODIS data. The retrieval of the aerosol properties is performed using lookup table computations. The volume size distribution in the lookup table is described with two lognormal modes: a single mode to describe the accumulation mode particles (radius 1.0 μm). Note that two accumulation modes may be present, one dominated by gas phase processes and a second dominated by cloud phase processes. The coarse mode can also be split into several partially overlapping modes describing maritime salt particles and dust. The aerosol parameters we expect to retrieve are η, the fractional contribution of the accumulation mode to scattering; τ, the spectral optical thickness; and rm, the mean particle size of the dominant mode. Additional radiative quantities such as asymmetry parameter and effective radius are derived subsequently. The impact of the surface conditions, wind speed and chlorophyll content on the retrieval is estimated, the impact of potential sources of error like the calibration of the instrument is also tested. The algorithm has been applied successfully to actual data sets provided by the Thematic Mapper on Landsat 5 and by the MODIS airborne simulator on the ER-2 and tested against ground and airborne measurements. A first estimate of the general accuracy is Δτ = ±0.05±0.05τ (at 550 nm), Δrm = 0.3rm, Δη = ±0.25.

Global aerosol climatology from the MODIS satellite sensors

The recently released Collection 5 MODIS aerosol products provide a consistent record of the Earths aerosol system. Comparison with ground-based AERONET observations of aerosol optical depth (AOD) we find that Collection 5 MODIS aerosol products estimate AOD to within expected accuracy more than 60% of the time over ocean and more than 72% of the time over land. This is similar to previous results for ocean, and better than the previous results for land. However, the new Collection introduces a 0.01 5 offset between the Terra and Aqua global mean AOD over ocean, where none existed previously. Aqua conforms to previous values and expectations while Terra is high. The cause of the offset is unknown, but changes to calibration are a possible explanation. We focus the climatological analysis on the better understood Aqua retrievals. We find that global mean AOD at 550 nm over oceans is 0.13 and over land 0.19. AOD in situations with 80% cloud fraction are twice the global mean values, although such situations occur only 2% of the time over ocean and less than 1% of the time over land. There is no drastic change in aerosol particle size associated with these very cloudy situations. Regionally, aerosol amounts vary from polluted areas such as East Asia and India, to the cleanest regions such as Australia and the northern continents. In almost all oceans fine mode aerosol dominates over dust, except in the tropical Atlantic downwind of the Sahara and in some months the Arabian Sea.

A spatio-temporal approach for global validation and analysis of MODIS aerosol products

[1] With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are beingretrieved, andneedto bevalidated andanalyzed. Asystem has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MODIS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols andparticles(0345,4801);1610GlobalChange:Atmosphere(0315, 0325); 1640 Global Change: Remote sensing; 0394 Atmospheric Composition and Structure: Instruments and techniques

MODIS Cloud screening for remote sensing of aerosols over oceans using spatial variability

] A cloud masking algorithm based on the spatial variability ofreflectances at the top of the atmosphere in visible wavelengths wasdeveloped for the retrieval of aerosol properties by MODIS. It isshown that the spatial pattern of cloud reflectance as observed fromspace, is very different from that of aerosols. Clouds show a veryhigh spatial variability in the scale of hundred meters to fewkilometers, whereas aerosols in general are very homogeneous. Theconcept of spatial variability of reflectances at the top of theatmosphere is mainly applicable over the ocean where the surfacebackground is sufficiently homogeneous for the separation betweenaerosols and clouds. Aerosol retrievals require a particular cloudmasking approach since a conservative mask will screen out strongaerosol episodes and a less conservative mask could allow forcloud contamination that tremendously affect the retrieved aerosoloptical properties (e.g. aerosol optical depth and effective radii). Adetailed study on the effect of cloud contamination on aerosolretrievals is performed and parameters are established determiningthe threshold value for the MODIS aerosol cloud mask (3X3-STD)over the ocean. The 3X3-STD algorithm discussed in this paper isthe operational cloud mask used for MODIS aerosol retrievals overthe ocean. I

A critical examination of the residual cloud contamination and diurnal sampling effects on MODIS estimates of aerosol over ocean

Observations of the aerosol optical thickness (AOT) by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard Terra and Aqua satellites are being used extensively for applications to climate and air quality studies. Data quality is essential for these studies. Here we investigate the effects of unresolved clouds on the MODIS measurements of the AOT. The main cloud effect is from residual cirrus that increases the AOT by 0.015/spl plusmn/0.003 at 0.55 /spl mu/m. In addition, lower level clouds can add contamination. We examine the effect of lower clouds using the difference between simultaneously measured MODIS and AERONET AOT. The difference is positively correlated with the cloud fraction. However, interpretation of this difference is sensitive to the definition of cloud contamination versus aerosol growth. If we consider this consistent difference between MODIS and AERONET to be entirely due to cloud contamination we get a total cloud contamination of 0.025/spl plusmn/0.005, though a more likely estimate is closer to 0.020 after accounting for aerosol growth. This reduces the difference between MODIS-observed global aerosol optical thickness over the oceans and model simulations by half, from 0.04 to 0.02. However it is insignificant for studies of aerosol cloud interaction. We also examined how representative are the MODIS data of the diurnal average aerosol. Comparison to monthly averaged sunphotometer data confirms that either the Terra or Aqua estimate of global AOT is a valid representation of the daily average. Though in the vicinity of aerosol sources such as fires, we do not expect this to be true.

Retrieval of aerosol optical thickness and size distribution over ocean from the MODIS airborne simulator during TARFOX

Radiation and in-situ measurements collected during the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) are used to test the method for remote sensing of aerosol properties and loading from the MODIS instrument. MODIS, a Moderate Resolution Imaging Spectroradiometer, will be launched in 1999 aboard the first EOS (Earth Observing System). Following the MODIS procedure [Tanre et al., 1997], the spectral radiance at the top of the atmosphere (TOA) measured over the ocean in a wide spectral range (0.55-2.13 μm) is used to derive the aerosol optical thickness (proportional to the aerosol total loading) and the aerosol size distribution (integrated over the vertical column) of the ambient (undisturbed) aerosol by comparing measured radiances with values in look-up table (LUT). The LUT includes the gas-phase oxidation accumulation mode, cloud-phase accumulation mode, and a coarse mode that represents maritime particles (salt) and dust. In each inversion, one accumulation and one coarse mode can be retrieved. The inversion retrieves the ratio of the contribution to the optical thicknesses of the two particle modes and the mean particle size that best fits the measurements. This algorithm is successfully applied to the data sets acquired during TARFOX. The MODIS airborne simulator (MAS) aboard the NASA ER-2 aircraft flew several times during the experiment above the University of Washington C-131A research aircraft on which the six-channel Ames Airborne Tracking Sun Photometer (AATS-6) was mounted. It flew also above surface-based Sun photometers. Optical thicknesses (at λ = 550 nm) as well as the spectral dependence from the various data sets compare very well.

Algorithm for atmospheric and glint corrections of satellite measurements of ocean pigment

An algorithm is developed to correct satellite measurements of ocean color for atmospheric and surface reflection effects. The algorithm depends on taking the difference between measured and tabulated radiances for deriving water-leaving radiances. The tabulated radiances are related to the measured radiance where the water-leaving radiance is negligible (670 nm). The tabulated radiances are calculated for rough surface reflection, polarization of the scattered light, and multiple scattering. The accuracy of the tables is discussed. The method is validated by simulating the effect of different wind speeds than that for which the lookup table is calculated, and aerosol models different from the maritime model for which the table is computed. The derived water-leaving radiances are accurate enough to compute the pigment concentration with an error of less than ±15% for wind speeds of 6 and 10 m/s and an urban atmosphere with aerosol optical thickness of 0.20 at A443 nm and decreasing to 0.10 at A670 nm. The pigment accuracy is less for wind speeds less than 6 m/s and is about 30% for a model with aeolian dust. On the other hand, in a preliminary comparison with coastal zone color scanner (CZCS) measurements this algorithm and the CZCS operational algorithm produced values of pigment concentration in one image that agreed closely.

Snow and ice mask for the MODIS aerosol products

Atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua spacecraft. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-infrared channels centered near 0.86 and 1.24 /spl mu/m and a thermal emission channel near 11 /spl mu/m to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

Evaluation and Wind Speed Dependence of MODIS Aerosol Retrievals Over Open Ocean

The Maritime Aerosol Network (MAN) data set provides high-quality ground truth to validate the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the prelaunch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R = 0.85 for Terra and 0.83 for Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier collections. Prior analysis noted an offset between Terra and Aqua ocean AODs, without concluding which sensor was more accurate. The simple linear regression reported here is consistent with other anecdotal evidence that Aqua agreement with the Aerosol Robotic Network is marginally better. However, we cannot claim based on the current study that the better Aqua comparison is statistically significant. A systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependence enters the retrieval when winds deviate from the 6-m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependence in the results can be mitigated by using auxiliary National Centers for Environmental Prediction wind speed information in the retrieval process.