An optimization approach for aerosol retrievals using simulated MISR radiances

Diner, David J.; Hodos, Rachel; Davis, Anthony B.; Garay, M. J.; Martonchik, John V.; Sanghavi, S.; Allmen, Paul von; Kokhanovsky, Alexander A.; Zhai, Peng-Wang

doi:10.1016/j.atmosres.2011.05.020

Cited by 25 publications

(13 citation statements)

References 28 publications

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“…(Although the MISR Research algorithm used for these studies offers great flexibility in defining algorithm assumptions, it comes at the cost of setup effort and slower throughput that make regional but not global‐scale processing feasible.) Simulation studies suggest that with the look‐up table retrieval approach, retrieval error can also occur if the aerosol mixture proportions are quantized at insufficiently fine intervals [ Diner et al ., ], so having a richer aerosol‐type climatology in the algorithm could require a significantly expanded look‐up table.…”

Section: Discussionmentioning

confidence: 99%

An analysis of global aerosol type as retrieved by MISR

2015

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In addition to aerosol optical depth (AOD), aerosol type is required globally for climate forcing calculations, constraining aerosol transport models and other applications. However, validating satellite aerosol-type retrievals is more challenging than testing AOD results, because aerosol type is a more complex quantity, and ground truth data are far less numerous and generally not as robust. We evaluate the Multiangle Imaging Spectroradiometer (MISR) Version 22 aerosol-type retrievals by assessing product self-consistency on a regional basis and by making comparisons with general expectation and with the Aerosol Robotic Network aerosol-type climatology, as available. The results confirm and add detail to the observation that aerosol-type discrimination improves dramatically where midvisible AOD exceeds about 0.15 or 0.2. When the aerosol-type information content of the observations is relatively low, increased scattering-angle range improves particle-type sensitivity. The MISR standard, operational product discriminates among small, medium, and large particles and exhibits qualitative sensitivity to single-scattering albedo (SSA) under good aerosol-type retrieval conditions, providing a categorical aerosol-type classification. MISR Ångström exponent deviates systematically from ground truth where particle types missing from the algorithm climatology are present, or where cloud contamination is likely to occur, and SSA tends to be overestimated where absorbing particles are found. We determined that the number of mixtures passing the algorithm acceptance criteria (#SuccMix) represents aerosol-type retrieval quality effectively, providing a useful aerosol-type quality flag.

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Section: Discussionmentioning

confidence: 99%

An analysis of global aerosol type as retrieved by MISR

2015

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“…For example, the MISR retrievals use a LUT containing 74 aerosol mixtures [ Kahn et al ., ]. The main disadvantage of LUT approach is that the predetermined aerosol models might not fully represent the global and temporal variations of aerosol properties found in nature, and lack of the correct model can bias the retrievals [ Diner et al ., ]. To overcome this limitation, various types of optimization algorithms have been developed [cf.…”

Section: Introductionmentioning

confidence: 99%

Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

Harten

Diner

et al. 2017

JGR Atmospheres

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The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER‐2 high‐altitude aircraft since October 2010. In step‐and‐stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from nine viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov‐chain/adding‐doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI data sets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI preengineering test flight. The retrieval results including aerosol optical depth, single‐scattering albedo, aerosol size and refractive index are compared with Aerosol Robotic Network reference data. We identify the best angular combinations for 2, 3, 5, and 7 angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements and target revisits in constraining aerosol property and surface reflection retrieval.

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“…A consistent implementation of such an approach is not straightforward since aerosol models are defined as prior knowledge of the observed medium but uncertainties cannot Figure 1. Aerosol dual-mode models based on Govaerts et al (2010b) in the {g, ω 0 } space derived from the aggregation of aerosol single-scattering properties retrieved from AERONET observations (Dubovik et al, 2006). Classes 1 to 3 are dominated by the fine mode and 4 to 6 by the coarse one.…”

Section: Introductionmentioning

confidence: 99%

Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 1: theoretical concept

Govaerts

Luffarelli

2018

Atmos. Meas. Tech.

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Abstract. This paper presents a new algorithm for the joint retrieval of surface reflectance and aerosol properties with continuous variations of the state variables in the solution space. This algorithm, named CISAR (Combined Inversion of Surface and AeRosol), relies on a simple atmospheric vertical structure composed of two layers and an underlying surface. Surface anisotropic reflectance effects are taken into account and radiatively coupled with atmospheric scattering. For this purpose, a fast radiative transfer model has been explicitly developed, which includes acceleration techniques to solve the radiative transfer equation and to calculate the Jacobians. The inversion is performed within an optimal estimation framework including prior information on the state variable magnitude and regularisation constraints on their spectral and temporal variability. In each processed wavelength, the algorithm retrieves the parameters of the surface reflectance model, the aerosol total column optical thickness and single-scattering properties. The CISAR algorithm functioning is illustrated with a series of simple experiments.

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An optimization approach for aerosol retrievals using simulated MISR radiances

Cited by 25 publications

References 28 publications

An analysis of global aerosol type as retrieved by MISR

An analysis of global aerosol type as retrieved by MISR

Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 1: theoretical concept

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