ALBERT

Description: Author(s): V. Baru, A. A. Filin, C. Hanhart, Yu. S. Kalashnikova, A. E. Kudryavtsev, and A. V. Nefediev [Phys. Rev. D 84, 074029] Published Thu Oct 20, 2011

Description: Author(s): C. Hanhart, Yu. S. Kalashnikova, A. E. Kudryavtsev, and A. V. Nefediev [Phys. Rev. D 85, 011501] Published Fri Jan 06, 2012

Description: The Multi-angle Imaging SpectroRadiometer (MISR) provides a unique, independent source of data for studying dust emission and transport. MISR's multiple view angles allow the retrieval of aerosol properties over bright surfaces, and such retrievals have been shown to be sensitive to the non-sphericity of dust aerosols over both land and water. MISR stereographic views of thick aerosol plumes allow height and instantaneous wind derivations at spatial resolutions of better than 1.1 km horizontally and ~200m vertically. We will discuss the radiometric and stereo-retrieval capabilities of MISR specifically for dust, and demonstrate the use of MISR data in conjunction with other available satellite observations for dust property characterization and climate studies.First, we will discuss MISR non-spherical (dust) fraction product over the global oceans. We will show that over the Atlantic Ocean, changes in the MISR-derived non-spherical AOD fraction illustrate the evolution of dust during transport. Next, we will present a MISR satellite perspective on dust climatology in major dust source regions with a particular emphasis on the West Africa and Middle East and discuss MISR's unique strengths as well as current product biases. Finally, we will discuss MISR dust plume product and climatological applications.

Description: In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) fine mode fraction and Multi-angle Imaging SpectroRadiometer (MISR) nonspherical fraction data are used to derive dust and smoke aerosol optical thickness (T(sub dust) and T(sub smoke)) over the tropical Atlantic in a complementary way: due to its wider swath, MODIS has 3-4 times greater sampling than MISR, but MISR dust discrimination is based on particle shape retrievals, whereas an empirical scheme is used for MODIS. MODIS and MISR show very similar dust and smoke winter climatologies. T(sub dust) is the dominant aerosol component over the tropical Atlantic, accounting for 40-70 percent of the total aerosol optical thickness (AOT), whereas T(sub smoke) is significantly smaller than T(sub dust). The consistency and high correlation between these climatologies and their daily variations lends confidence to their use for investigating the relative dust and smoke contributions to the total AOT variation associated with the Madden-Julian Oscillation (MJO). The temporal evolution and spatial patterns of the dus anomalies associated with the MJO are consistent between MODIS and MISR: the magnitude of MJO-realted T(sub dust) anomalies is comparable to or even larger than that of the total T, while the T(sub smoke) anomaly represents about 15 percent compared to the total, which is quite different from their relative magnitudes to the total T on the climatological time scale. This suggests that dust and smoke are not influenced by the MJO in the same way. Based on correlation analysis, dust is strongly influenced by the MJO-modulated trade wind and precipitation anomalies, and can last as long as one MJO phase, whereas smoke is less affected.

Description: To determine a plausible range of mass extinction efficiencies (MEE) of terrestrial atmospheric dust from the near to thermal IR, sensitivity analyses are performed over an extended range of dust microphysical and chemistry perturbations. The IR values are subsequently compared to those in the near-IR, to evaluate spectral relationships in their optical properties. Synthesized size distributions consistent with measurements, model particle size, while composition is defined by the refractive indices of minerals routinely observed in dust, including the widely used OPAC/Hess parameterization. Single-scattering properties of representative dust particle shapes are calculated using the T-matrix, Discrete Dipole Approximation and Lorenz-Mie light-scattering codes. For the parameterizations examined, MEE ranges from nearly zero to 1.2 square meters per gram, with the higher values associated with non-spheres composed of quartz and gypsum. At near-IR wavelengths, MEE for non-spheres generally exceeds those for spheres, while in the thermal IR, shape-induced changes in MEE strongly depend on volume median diameter (VMD) and wavelength, particularly for MEE evaluated at the mineral resonant frequencies. MEE spectral distributions appear to follow particle geometry and are evidence for shape dependency in the optical properties. It is also shown that non-spheres best reproduce the positions of prominent absorption peaks found in silicates. Generally, angular particles exhibit wider and more symmetric MEE spectral distribution patterns from 8-10 micrometers than those with smooth surfaces, likely due to their edge-effects. Lastly, MEE ratios allow for inferring dust optical properties across the visible-IR spectrum. We conclude the MEE of dust aerosol are significant for the parameter space investigated, and are a key component for remote sensing applications and the study of direct aerosol radiative effects.

Description: An initial comparison of aerosol optical thickness over North Africa for year 2007 was performed between the Deep Blue and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms complimented with MISR and OMI data. The new MAIAC algorithm has a better sensitivity to the small dust storms than the DB algorithm, but it also has biases in the brightest desert regions indicating the need for improvement. The quarterly averaged AOT values in the Bodele depression and western downwind transport region show a good agreement among MAIAC, MISR and OMI data, while the DB algorithm shows a somewhat different seasonality.

Description: Talks presented by Dr. Ralph Kahn at the 16th AeroCom and 5th AeroSat Workshops, held October 9-13, 2017 in Helsinki, Finland.

Description: We are creating a new algorithm that combines observations from MISR and MODIS (both on the NASA Terra spacecraft) to improve atmospheric correction and coverage for ocean color data products. The algorithm utilizes information rich, multi-angle MISR observations for atmospheric correction, applied to MODIS. Our goal is to produce atmospherically corrected Remote Sensing Reflectance from MODIS with enhanced coverage and accuracy, for input to downstream bio-optical ocean parameter retrieval algorithms.An important aspect of this work is the utilization of multi-angle views of the reflected ocean surface sun glint. Usually, such observations are avoided, since the intensity of the glint overwhelms any contribution from the ocean body. However, MISR's multi-angle observations see varying degrees of glint, which means they can be used to better determine aerosol optical properties (Kaufman et al., 2002, Ottaviani et al., 2013), and to identify surface wind speeds that govern the glint pattern. The latter could be utilized to replace the wind speeds taken from ancillary sources that are currently used to conservatively mask potential glint contamination in MODIS observations.To assess this capability, and to identify the appropriate parameterization, we present an analysis using the Generalized Nonlinear Retrieval Analysis (GENRA, Vukicevic et al., 2009) information content assessment. This technique is also easily modified to act as a Bayesian retrieval algorithm, for which initial results are discussed. Finally, we describe the status of integrating MISR data into the processing capabilities of the Ocean Biology Processing Group (OBPG) at NASA, and show the first ocean color vicarious calibration (Franz et al., 2007) of the MISR instrument.

Description: This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify and understand the differences between current algorithms, and hence improve future retrieval algorithms. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as as20 sumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, at least as significant as these differences are sampling issues related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset.