SPEX airborne spectropolarimeter calibration and performance

J. Martijn Smit; Jeroen H. H. Rietjens; Gerard van Harten; Antonio Di Noia; Wouter Laauwen; Brian E. Rheingans; David J. Diner; Brian Cairns; Andrzej Wasilewski; Kirk D. Knobelspiesse; Richard Ferrare; Otto P. Hasekamp

doi:10.1364/AO.58.005695

Applied Optics
Vol. 58,
Issue 21,
pp. 5695-5719
(2019)
•https://doi.org/10.1364/AO.58.005695

SPEX airborne spectropolarimeter calibration and performance

J. Martijn Smit, Jeroen H. H. Rietjens, Gerard van Harten, Antonio Di Noia, Wouter Laauwen, Brian E. Rheingans, David J. Diner, Brian Cairns, Andrzej Wasilewski, Kirk D. Knobelspiesse, Richard Ferrare, and Otto P. Hasekamp

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J. Martijn Smit, Jeroen H. H. Rietjens, Gerard van Harten, Antonio Di Noia, Wouter Laauwen, Brian E. Rheingans, David J. Diner, Brian Cairns, Andrzej Wasilewski, Kirk D. Knobelspiesse, Richard Ferrare, and Otto P. Hasekamp, "SPEX airborne spectropolarimeter calibration and performance," Appl. Opt. 58, 5695-5719 (2019)

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Abstract

To improve our understanding of the complex role of aerosols in the climate system and on air quality, measurements are needed of optical and microphysical aerosol. From many studies, it has become evident that a satellite-based multiangle, multiwavelength polarimeter will be essential to provide such measurements. Here, high accuracy ( $\sim 0.003$ ) on the degree of linear polarization (DoLP) measurements is important to retrieve aerosol properties with an accuracy needed to advance our understanding of the aerosol effect on climate. SPEX airborne, a multiangle hyperspectral polarimeter, has been developed for observing and characterizing aerosols from NASA’s high-altitude research aircraft ER-2. It delivers measurements of radiance and DoLP at visual wavelengths with a spectral resolution of 3 and 7–30 nm, respectively, for radiance and polarization, at nine fixed equidistant viewing angles from $- 56 °$ to $+ 56 °$ oriented along the ground track, and a swath of 7° oriented across-track. SPEX airborne uses spectral polarization modulation to determine the state of linear polarization of scattered sunlight. This technique has been developed in the Netherlands and has been demonstrated with ground-based instruments. SPEX airborne serves as a demonstrator for a family of space-based SPEX instruments that have the ability to measure and characterize atmospheric aerosol by multiangle hyperspectral polarimetric imaging remotely from a satellite platform. SPEX airborne was calibrated radiometrically and polarimetrically using Jet Propulsion Laboratory (JPL) facilities including the Polarization Stage Generator-2 (PSG-2), which is designed for polarimetric calibration and validation of the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI). Using the PSG-2, the accuracy of the SPEX airborne DoLP measurements in the laboratory setup is found to be 0.002–0.004. Radiometric calibration is realized with an estimated accuracy of 4%. In 2017, SPEX airborne took part in the “Aerosol Characterization from Polarimeters and Lidar” campaign on the ER-2 that included four polarimeters and two lidars. Polarization measurements of SPEX airborne and the coflying Research Scanning Polarimeter (RSP), recorded during the campaign, were compared and display root-mean-square (RMS) differences ranging from 0.004 (at 555 nm) up to 0.02 (at 410 nm). For radiance measurements, excellent agreement between SPEX airborne and RSP is obtained with an RMS difference of $\sim 4 %$ . The lab- and flight-performance values for polarization are similar to those recently published for AirMSPI, where also an intercomparison with RSP was made using data from field campaigns in 2013. The intercomparison of radiometric and polarimetric data both display negligible bias. The in-flight comparison results provide verification of SPEX airborne’s capability to deliver high-quality data.

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VP	1	6	3	8	5	2	7	4	9
$θ_{VP}$	−55.9	−42.1	−27.8	−13.9	$+ 0.1$	$+ 14.4$	$+ 28.1$	$+ 42.4$	$+ 56.2$

		Ocean	Cloud	Land	All
# Flight tracks		8	7	20	35
# Data points		10,336	6973	18,693	36,002
410 nm	DoLP fit slope	0.986	0.965	0.958	0.977
	DoLP fit offset	0.002	−0.002	0.003	−0.001
	$Δ {DoLP}_{random}$	0.007	0.005	0.007	0.008
	$Δ {DoLP}_{sys}$	0.005	0.008	0.013	0.009
	$Δ {DoLP}_{rms}$	0.008	0.010	0.015	0.012
	Rad fit slope	0.966	0.955	0.934	0.957
	Rad fit offset	−0.0004	0.0005	0.0015	0.0001
	$Δ I_{random} / ⟨ I ⟩$	2%	2%	2%	2%
	$Δ I_{sys} / ⟨ I ⟩$	4%	5%	5%	5%
	$Δ I_{rms} / ⟨ I ⟩$	4%	5%	5%	6%
470 nm	DoLP fit slope	0.983	0.976	0.979	0.985
	DoLP fit offset	0.003	0.0003	0.002	0.0007
	$Δ {DoLP}_{random}$	0.005	0.003	0.003	0.004
	$Δ {DoLP}_{sys}$	0.004	0.003	0.005	0.005
	$Δ {DoLP}_{rms}$	0.006	0.004	0.006	0.006
	Rad fit slope	0.981	0.964	0.952	0.966
	Rad fit offset	−0.0003	0.0008	0.0011	0.0005
	$Δ I_{random} / ⟨ I ⟩$	2%	2%	1%	2%
	$Δ I_{sys} / ⟨ I ⟩$	3%	4%	3%	4%
	$Δ I_{rms} / ⟨ I ⟩$	3%	4%	4%	5%
555 nm	DoLP fit slope	0.993	0.989	0.993	0.994
	DoLP fit offset	0.0008	0.0001	0.0007	0.0004
	$Δ {DoLP}_{random}$	0.003	0.002	0.002	0.002
	$Δ {DoLP}_{sys}$	0.003	0.001	0.001	0.002
	$Δ {DoLP}_{rms}$	0.004	0.003	0.002	0.003
	Rad fit slope	0.994	0.982	0.977	0.982
	Rad fit offset	0	0.0004	0.0003	0.0004
	$Δ I_{random} / ⟨ I ⟩$	2%	1%	1%	2%
	$Δ I_{sys} / ⟨ I ⟩$	0%	2%	2%	2%
	$Δ I_{rms} / ⟨ I ⟩$	2%	2%	2%	3%
670 nm	DoLP fit slope	0.989	0.977	0.985	0.992
	DoLP fit offset	0.002	−0.0003	0.001	0.0002
	$Δ {DoLP}_{random}$	0.008	0.002	0.004	0.006
	$Δ {DoLP}_{sys}$	0.004	0.002	0.001	0.005
	$Δ {DoLP}_{rms}$	0.008	0.003	0.005	0.006
	Rad fit slope	0.990	1.003	0.998	1.006
	Rad fit	0.0002	0.0007	0.0005	0.0001
	$Δ I_{random} / ⟨ I ⟩$	4%	1%	2%	2%
	$Δ I_{sys} / ⟨ I ⟩$	1%	1%	0%	1%
	$Δ I_{rms} / ⟨ I ⟩$	4%	2%	2%	2%
	$Δ {DoLP}_{rms}$	0.007	0.005	0.007	0.006
	$Δ I_{rms} / ⟨ I ⟩$	3%	3%	3%	4%

VP	1	6	3	8	5	2	7	4	9
$θ_{VP}$	−55.9	−42.1	−27.8	−13.9	$+ 0.1$	$+ 14.4$	$+ 28.1$	$+ 42.4$	$+ 56.2$

		Ocean	Cloud	Land	All
# Flight tracks		8	7	20	35
# Data points		10,336	6973	18,693	36,002
410 nm	DoLP fit slope	0.986	0.965	0.958	0.977
	DoLP fit offset	0.002	−0.002	0.003	−0.001
	$Δ {DoLP}_{random}$	0.007	0.005	0.007	0.008
	$Δ {DoLP}_{sys}$	0.005	0.008	0.013	0.009
	$Δ {DoLP}_{rms}$	0.008	0.010	0.015	0.012
	Rad fit slope	0.966	0.955	0.934	0.957
	Rad fit offset	−0.0004	0.0005	0.0015	0.0001
	$Δ I_{random} / ⟨ I ⟩$	2%	2%	2%	2%
	$Δ I_{sys} / ⟨ I ⟩$	4%	5%	5%	5%
	$Δ I_{rms} / ⟨ I ⟩$	4%	5%	5%	6%
470 nm	DoLP fit slope	0.983	0.976	0.979	0.985
	DoLP fit offset	0.003	0.0003	0.002	0.0007
	$Δ {DoLP}_{random}$	0.005	0.003	0.003	0.004
	$Δ {DoLP}_{sys}$	0.004	0.003	0.005	0.005
	$Δ {DoLP}_{rms}$	0.006	0.004	0.006	0.006
	Rad fit slope	0.981	0.964	0.952	0.966
	Rad fit offset	−0.0003	0.0008	0.0011	0.0005
	$Δ I_{random} / ⟨ I ⟩$	2%	2%	1%	2%
	$Δ I_{sys} / ⟨ I ⟩$	3%	4%	3%	4%
	$Δ I_{rms} / ⟨ I ⟩$	3%	4%	4%	5%
555 nm	DoLP fit slope	0.993	0.989	0.993	0.994
	DoLP fit offset	0.0008	0.0001	0.0007	0.0004
	$Δ {DoLP}_{random}$	0.003	0.002	0.002	0.002
	$Δ {DoLP}_{sys}$	0.003	0.001	0.001	0.002
	$Δ {DoLP}_{rms}$	0.004	0.003	0.002	0.003
	Rad fit slope	0.994	0.982	0.977	0.982
	Rad fit offset	0	0.0004	0.0003	0.0004
	$Δ I_{random} / ⟨ I ⟩$	2%	1%	1%	2%
	$Δ I_{sys} / ⟨ I ⟩$	0%	2%	2%	2%
	$Δ I_{rms} / ⟨ I ⟩$	2%	2%	2%	3%
670 nm	DoLP fit slope	0.989	0.977	0.985	0.992
	DoLP fit offset	0.002	−0.0003	0.001	0.0002
	$Δ {DoLP}_{random}$	0.008	0.002	0.004	0.006
	$Δ {DoLP}_{sys}$	0.004	0.002	0.001	0.005
	$Δ {DoLP}_{rms}$	0.008	0.003	0.005	0.006
	Rad fit slope	0.990	1.003	0.998	1.006
	Rad fit	0.0002	0.0007	0.0005	0.0001
	$Δ I_{random} / ⟨ I ⟩$	4%	1%	2%	2%
	$Δ I_{sys} / ⟨ I ⟩$	1%	1%	0%	1%
	$Δ I_{rms} / ⟨ I ⟩$	4%	2%	2%	2%
	$Δ {DoLP}_{rms}$	0.007	0.005	0.007	0.006
	$Δ I_{rms} / ⟨ I ⟩$	3%	3%	3%	4%

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Applied Optics