Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

Coddington, O.; Vukićević, Tomislava; Schmidt, S.; Platnick, S.

doi:10.1002/2017jd026493

Cited by 12 publications

(9 citation statements)

References 54 publications

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“…The GENRA technique (Vukicevic et al (2010)) is attractive because it does not make the same assumptions of forward model linearity and the Gaussian nature of uncertainty. Developed for the assessment of cloud remote sensing (Coddington et al (2012); Coddington et al (2013); Coddington et al (2017), GENRA is similar to Bayesian inference in its treatment of all components of the retrieval system as stochastic with associated PDFs. The result is a posterior which represents the best understanding of the expected parameter PDF for a synthetic measurement.…”

Section: Genramentioning

confidence: 99%

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Knobelspiesse¹,

Ibrahim²,

Franz³

et al. 2020

Preprint

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Abstract. Since early 2000, NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument has been performing remote sensing retrievals of aerosol optical properties from the polar orbiting Terra spacecraft. A noteworthy aspect of MISR observations over the ocean is that, for much of the Earth, some of the multi-angle views have contributions from solar reflection by the ocean surface (glint, or glitter), while others do not. Aerosol retrieval algorithms often discard these glint influenced observations because they can overwhelm the signal and are difficult to predict without knowledge of the (wind speed driven) ocean surface roughness. However, theoretical studies have shown that multi-angle observations of a location at geometries with and without reflected sun glint can be a rich source of information, sufficient to support simultaneous retrieval of both the aerosol state and the wind speed at the ocean surface. We are in the early stages of creating such an algorithm. In this manuscript, we describe our assessment of the appropriate level of parameterization for simultaneous aerosol and ocean surface property retrievals using sun glint. For this purpose, we use Generalized Nonlinear Retrieval Analysis (GENRA), an information content assessment (ICA) technique employing Bayesian inference, and simulations from the Ahmad-Fraser iterative radiative transfer code. We find that four parameters are suitable: aerosol optical depth (τ), particle size distribution (expressed as the fine mode fraction f of small particles in a bimodal size distribution), surface wind speed (w), and relative humidity (r, to define the aerosol water content and complex refractive index). None of these parameters define ocean optical properties, as we found that the aerosol state could be retrieved with the nine MISR near-infrared views alone, where the ocean body is black in the open ocean. We also found that retrieval capability varies with observation geometry, and that as τ increases so does the ability to determine aerosol intensive optical properties (r and f, while it decreases for w). Increases in wind speed decrease the ability to determine the true value of that parameter, but have minimal impact on retrieval of aerosol properties. We explored the benefit of excluding the two most extreme MISR view angles for which radiative transfer with the plane parallel approximation is less certain, but found no advantage in doing so. Finally, the impact of treating wind speed as a scalar parameter, rather than as a two parameter directional wind, was tested. While the simpler scalar model does contribute to overall aerosol uncertainty, it is not sufficiently large to justify the addition of another dimension to parameter space. An algorithm designed upon these principles is in development. It will be used to perform an atmospheric correction with MISR for coincident ocean color (OC) observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on the NASA Terra spacecraft. Unlike MISR, MODIS is a single view angle instrument, but it has a more complete set of spectral channels ideal for determination of ocean optical properties. The atmospheric correction of MODIS OC data can therefore benefit from MISR aerosol retrievals. Furthermore, higher spatial resolution data from coincident MISR observations may also improve glint screening.

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Section: Genramentioning

confidence: 99%

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Knobelspiesse¹,

Ibrahim²,

Franz³

et al. 2020

Preprint

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“…In addition, the 1.38 µm channel may offer possibilities for "correction" rather than blunt masking by removing the net radiative effect of the cirrus in an adjustment of the measured top-of-atmosphere radiances, and then using those previously cirrus-affected pixels to derive information about the aerosol and/or surface beneath. Furthermore, the pair of SWIR channels centered at 2.135 and 2.25 µm will provide information on cloud thermodynamic phase unavailable from previous sensors (Coddington et al, 2017).…”

Section: Masking and Other Preliminary Necessitiesmentioning

confidence: 99%

Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument

et al. 2019

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“…This leap in technology will enable improved understanding of aquatic ecosystems and biogeochemistry, as well as provide new information on phytoplankton community composition and improved detection of algal blooms (see, e.g., Bracher et al, 2009;Torecilla et al, 2011;Catlett and Siegel, 2018). OCI will also continue and advance many atmospheric aerosol, cloud, and land capabilities from heritage satellite instrumentation (Coddington et al, 2017;Platnick et al, 2018;Remer et al, 2019a), which in combination with its ocean measurements, will enable improved assessment of atmospheric and terrestrial impacts on ocean biology and chemistry (PACE Science Definition Team, 2018 and references within).…”

Section: Introductionmentioning

confidence: 99%

Test Results From the Prelaunch Characterization Campaign of the Engineering Test Unit of the Ocean Color Instrument of NASA’s Plankton, Aerosol, Cloud and Ocean Ecosystem (PACE) Mission

Meister¹,

Knuble²,

Chemerys³

et al. 2022

Front. Remote Sens.

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This paper summarizes the results from the system level test campaign of the Engineering Test Unit (ETU) of the ‘Ocean Color Instrument’ (OCI), the primary payload of NASA’s ‘Plankton, Aerosol, Cloud and ocean Ecosystem’ (PACE) mission. The main goals of the test campaign were to optimize characterization procedures and evaluate system level performance relative to model predictions. Critical performance parameters such as radiometric gain, signal-to-noise ratio, polarization, instantaneous field-of-view, temperature sensitivity, relative spectral response and stability were evaluated for wavelengths from 600 to 2,260 nm and are in line with expectations. We expect the OCI flight unit to meet the PACE mission performance requirements. Building and testing the ETU has been extremely important for the development of the OCI flight unit (e.g. improved SNR by increasing the aperture, optimized thermal design), and we strongly recommend the inclusion of an ETU in the development of future spaceborne sensors that rely on novel technological designs. ETU testing led to the discovery of a hysteresis issue with the SWIR bands, and a correction algorithm was developed. Also, the coregistration of the SWIR bands relative to each other is worse than expected, but this was discovered too late in the schedule to remediate.

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Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

Cited by 12 publications

References 54 publications

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument

Test Results From the Prelaunch Characterization Campaign of the Engineering Test Unit of the Ocean Color Instrument of NASA’s Plankton, Aerosol, Cloud and Ocean Ecosystem (PACE) Mission

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