The multi-viewing multi-channel multi-polarisation imager – Overview of the 3MI polarimetric mission for aerosol and cloud characterization

Fougnie, Bertrand; Marbach, T.; Lacan, Antoine; Lang, Ruediger; Schlüssel, Peter; Poli, Gabriele; Munro, Rosemary; Couto, André B.

doi:10.1016/j.jqsrt.2018.07.008

Cited by 112 publications

(64 citation statements)

References 18 publications

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“…In this paper we investigate an alternative method for the estimation of the COT and cloud effective radius from satellite multi-angle polarimetric measurements, based on artificial neural networks (NNs). NNs have been widely applied to cloud remote sensing problems, including cloud detection and classification (Miller and Emery, 1997;Aires et al, 2011;Taravat et al, 2015), retrieval of cloud properties based on traditional, plane-parallel radiative transfer assumptions (Cerdeña et al, 2007;Loyola et al, 2007Loyola et al, , 2010Loyola et al, , 2018Håkansson et al, 2018), and threedimensional retrievals (Cornet et al, 2004;Cornet et al, 2005;Evans et al, 2008;Okamura et al, 2017). Among the attractive features of NN-based retrieval schemes are their high speed and their modest memory demand (at least after the training phase is completed), which make them suitable for processing large amounts of measurements in very little time.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach

et al. 2019

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Abstract. This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument aboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization and has been applied to the processing of 1 year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) products show that the neural network algorithm has a low bias of around 2 in cloud optical thickness (COT) and between 1 and 2 µm in the cloud effective radius. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval, at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.

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Section: Introductionmentioning

confidence: 99%

Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach

et al. 2019

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“…Driven by the need for daily global coverage for the Copernicus Atmospheric Monitoring Service (CAMS, https:// atmosphere.copernicus.eu/), the POLDER design also forms the blueprint for the 3MI instruments (Fougnie et al, 2018), to be flown on METOP-SG in the time frame ∼2020-2035. 3MI uses the same filter-wheel technology -with the corresponding DoLP accuracy -but has more spectral bands than POLDER, including bands in the Short Wave Infra-Red (SWIR), albeit with reduced angular range.…”

Section: Introductionmentioning

confidence: 99%

Aerosol retrievals from the ACEPOL Campaign

Hasekamp

Rietjens

et al. 2019

Preprint

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Abstract. In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – Netherlands Institute for Space Research. The campaign took place in October-November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high altitude aircraft, including four Multi-Angle Polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar -2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land but also some cases with higher AOD were observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the Aerosol Optical Depth (AOD) (Mean Absolute Error (MAE) between 0.014–0.024 at 440 nm). For the fine mode effective radius the MAE ranges between 0.021–0.028 micron. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona and Nevada (26 October) and a flight with high AOD (including measurements with AOD > 1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAE in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume also a reasonable agreement in AOD between the MAPs and HSRL-2 was found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. Also a good comparison is found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure for particles sphericity) with MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume.

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“…A limited number of satellite missions carrying polarimetric payloads have been launched (Dubovik et al, 2019), including the Polarization and Directionality of the Earth's Reflectances (POLDER) instrument that was hosted on Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL;2004 and on the short-lived ADEOS and ADEOS-II missions (Tanré et al, 2011). Several more satellite missions with MAP instruments are planned to be launched in the time frame of 2022-2023, such as the European Space Agency (ESA)'s Multi-viewing Multi-channel Multi-polarisation Imager (3MI) on Meteorological Operational Satellite -Second Generation (MetOp-SG) (Fougnie et al, 2018), and the National Aeronautics and Space Administration (NASA) Multi-Angle Imager for Aerosols (MAIA) (Diner et al, 2018), and the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission (Werdell et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Inversion of multi-angular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals

Meng¹,

Zhai²,

Franz³

et al. 2020

Preprint

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Abstract. NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in the timeframe of late 2022 to early 2023, will carry the Ocean Color Instrument (OCI), a hyperspectral scanning radiometer, and two multi-angle polarimeters (MAP), the UMBC Hyper-Angular Rainbow Polarimeter (HARP2) and the SRON Spectro-Polarimeter for Planetary EXploration one (SPEXone). One purpose of the PACE MAPs is to better characterize aerosols properties, which can then be used to improve atmospheric correction for the retrieval of ocean color in coastal waters. Though this is theoretically promising, the use of MAP data in the atmospheric correction of collocated hyperspectral ocean color measurements has not yet been well demonstrated. In this work, we performed aerosol retrievals using the MAP measurements from the Research Scanning Polarimeter (RSP), and demonstrate its application to the atmospheric correction of hyperspectral radiometric measurements from SPEX Airborne. Both measurements were collected on the same aircraft from the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign in 2017. Two cases over ocean with small aerosol loading (aerosol optical depth ∼ 0.04) are identified including collocated RSP and SPEX Airborne measurements and Aerosol Robotic Network (AERONET) in-situ observations. The aerosol retrievals are performed and compared with two options: one uses reflectance only and the other use both reflectance and polarization. It is demonstrated that polarization information helps reduce the uncertainties of aerosol microphysical and optical properties. The retrieved aerosol properties are then used to compute the contribution of atmosphere and ocean surface for atmospheric correction over the discrete bands from RSP measurements and the hyperspectral SPEX Airborne measurements. The water leaving signals determined this way are compared with both AERONET and Moderate Resolution Imaging Spectroradiometer (MODIS) Ocean Color products with good agreement. The results and lessons-learned from this work will provide a basis to fully exploit the information from the unique combination of sensors on PACE for aerosol characterization and ocean ecosystem research.

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The multi-viewing multi-channel multi-polarisation imager – Overview of the 3MI polarimetric mission for aerosol and cloud characterization

Cited by 112 publications

References 18 publications

Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach

Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach

Aerosol retrievals from the ACEPOL Campaign

Inversion of multi-angular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals

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