Articles | Volume 18, issue 11
https://doi.org/10.5194/amt-18-2447-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-2447-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jun 2025
Research article |
| 11 Jun 2025
| 11 Jun 2025
HARP2 pre-launch calibration: dealing with polarization effects of a wide field of view
Noah Sienkiewicz
CORRESPONDING AUTHOR
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
J. Vanderlei Martins
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
Brent A. McBride
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
Xiaoguang Xu
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
Anin Puthukkudy
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
Rachel Smith
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
Roberto Fernandez-Borda
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD, USA
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Cited articles
Barsi, J. A., McCorkel, J. T., McAndrew, B., Shuman, T., Sushkov, A., Rodriguez, M., and Reed, N.: Spectral and radiometric performance of the Goddard laser for absolute measurement of radiance, in: Proceedings Earth Observing Systems XXVIII, San Diego, California, USA, 20–25 August 2023, SPIE, 12685, 126850A, https://doi.org/10.1117/12.2678195, 2023.
Chellappa, R. and Theodoridis, S. (Eds.): Academic Press Library in Signal Processing: Image and Video Processing and Analysis and Computer Vision, Academic Press, 435 pp., https://doi.org/10.1016/C2016-0-00726-X, 2017.
Ding, L., Kowalewski, M. G., Cooper, J. W., Smith, G. R., Barnes, R. A., Waluschka, E., and Butler, J. J.: Development and performance of a filter radiometer monitor system for integrating sphere sources, Opt. Eng., 50, 113603, https://doi.org/10.1117/1.3646532, 2011.
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J. F., Sorokin, M., and Slutsker, I.: Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res.-Atmos., 111, D11208, https://doi.org/10.1029/2005JD006619, 2006.
Dubovik, O., Li, Z., Mishchenko, M. I., Tanré, D., Karol, Y., Bojkov, B., Cairns, B., Diner, D. J., Espinosa, W. R., Goloub, P., Gu, X., Hasekamp, O., Hong, J., Hou, W., Knobelspiesse, K. D., Landgraf, J., Li, L., Litvinov, P., Liu, Y., Lopatin, A., Marbach, T., Maring, H., Martins, V., Meijer, Y., Milinevsky, G., Mukai, S., Parol, F., Qiao, Y., Remer, L., Rietjens, J., Sano, I., Stammes, P., Stamnes, S., Sun, X., Tabary, P., Travis, L. D., Waquet, F., Xu, F., Yan, C., and Yin, D.: Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives, J. Quant. Spectrosc. Ra., 224, 474–511, https://doi.org/10.1016/j.jqsrt.2018.11.024, 2018.
Fougnie, B., Braceo, G., Lafrance, B., Ruffel, C., Hagolle, O., and Tinel, C.: PARASOL in-flight calibration and performance, Appl. Optics, 46, 5435–5451, https://doi.org/10.1364/AO.46.005435, 2007.
Fu, G., Hasekamp, O., Rietjens, J., Smit, M., Di Noia, A., Cairns, B., Wasilewski, A., Diner, D., Seidel, F., Xu, F., Knobelspiesse, K., Gao, M., da Silva, A., Burton, S., Hostetler, C., Hair, J., and Ferrare, R.: Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm, Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, 2020.
Hamill, P., Piedra, P., and Giordano, M.: Simulated polarization as a signature of aerosol type, Atmos. Environ., 224, 117348, https://doi.org/10.1016/j.atmosenv.2020.117348, 2020.
Hansen, J. E. and Travis, L. D.: Light Scattering in Planetary Atmospheres, Space Sci. Rev., 16, 527–610, 1974.
Harmel, T. and Chami, M.: Estimation of the sunglint radiance field from optical satellite imagery over open ocean: Multidirectional approach and polarization aspects, J. Geophys. Res.-Oceans, 118, 76–90, https://doi.org/10.1029/2012JC008221, 2013.
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020.
Hasekamp, O. P. and Landgraf, J.: Retrieval of aerosol properties over the ocean from multispectral single-viewing-angle measurements of intensity and polarization: Retrieval approach, information content, and sensitivity study, J. Geophys. Res.-Atmos., 110, 1–16, https://doi.org/10.1029/2005JD006212, 2005.
Hasekamp, O. P. and Landgraf, J.: Retrieval of aerosol properties over land surfaces: capabilities of multiple-viewing-angle intensity and polarization measurements, Appl. Optics, 46, 3332, https://doi.org/10.1364/ao.46.003332, 2007.
Hasekamp, O. P., Fu, G., Rusli, S. P., Wu, L., Di Noia, A., Brugh, J. aan de, Landgraf, J., Martijn Smit, J., Rietjens, J., and van Amerongen, A.: Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities, J. Quant. Spectrosc. Ra., 227, 170–184, https://doi.org/10.1016/j.jqsrt.2019.02.006, 2019.
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007.
Iniesta, D. T. and Collados, M.: Demodulation Matrices for Solar Polarimetry, Appl. Opt., 39, 1637–1642, 2000.
Kelley, N. E., McCorkel, J., Wanzek, E., Georgiev, G., Barsi, J., McAndrew, B., and Efremova, B.: GSFC Calibration Laboratory capabilities and future plans overview, in: Earth Observing Systems XXVIII, San Diego, California, USA, 20–25 August 2023, SPIE, 12685, 126850B, https://doi.org/10.1117/12.2681380, 2023.
Knobelspiesse, K., Cairns, B., Mishchenko, M., Chowdhary, J., Tsigaridis, K., van Diedenhoven, B., Martin, W., Ottaviani, M., and Alexandrov, M.: Analysis of fine-mode aerosol retrieval capabilities by different passive remote sensing instrument designs, Opt. Express, 20, 21457–21484, https://doi.org/10.1364/OE.20.021457, 2012.
Li, D., Chen, F., Zeng, N., Qiu, Z., He, H., He, Y., and Ma, H.: Study on polarization scattering applied in aerosol recognition in the air, Opt. Express, 27, A581–A595, https://doi.org/10.1364/OE.27.00a581, 2019.
Martins, J. V., Marshak, A., Remer, L. A., Rosenfeld, D., Kaufman, Y. J., Fernandez-Borda, R., Koren, I., Correia, A. L., Zubko, V., and Artaxo, P.: Remote sensing the vertical profile of cloud droplet effective radius, thermodynamic phase, and temperature, Atmos. Chem. Phys., 11, 9485–9501, https://doi.org/10.5194/acp-11-9485-2011, 2011.
Martins, J. V., Fernandez-borda, R., McBride, B., Remer, L., and Barbosa, H. M. J.: The HARP Hyperangular Imaging Polarimeter and The Need for Small Satellite Payloads with High Science Payoff for Earth Science Remote Sensing, in: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22–27 July 2018, IEEE, 6304–6307, https://doi.org/10.1109/IGARSS.2018.8518823, 2018.
McBride, B. A., Martins, J. V., Barbosa, H. M. J., Birmingham, W., and Remer, L. A.: Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements, Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020, 2020.
McBride, B. A., Martins, J. V., Cieslak, J. D., Fernandez-Borda, R., Puthukkudy, A., Xu, X., Sienkiewicz, N., Cairns, B., and Barbosa, H. M. J.: Pre-launch calibration and validation of the Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) instrument, Atmos. Meas. Tech., 17, 5709–5729, https://doi.org/10.5194/amt-17-5709-2024, 2024.
McClain, C. R.: A decade of satellite ocean color observations, Annu. Rev. Mar. Sci., 1, 19–42, https://doi.org/10.1146/annurev.marine.010908.163650, 2009.
McClain, S. C., Bartlett, C., Pezzaniti, J. L., and Chipman, R. A.: Depolarization measurements of an integrating sphere, Appl. Optics, 34, 152, https://doi.org/10.1364/oam.1993.tuv.3, 1995.
Miller, D. J., Zhang, Z., Platnick, S., Ackerman, A. S., Werner, F., Cornet, C., and Knobelspiesse, K.: Comparisons of bispectral and polarimetric retrievals of marine boundary layer cloud microphysics: case studies using a LES–satellite retrieval simulator, Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, 2018.
Mishchenko, M. I. and Travis, L. D.: Satellite retrieval of aerosol properties over the ocean using polarization as well as intensity of reflected sunlight, J. Geophys. Res., 102, 16989–17013, 1997.
Mishchenko, M. I., Cairns, B., Hansen, J. E., Travis, L. D., Burg, R., Kaufman, Y. J., Martins, J. V., and Shettle, E. P.: Monitoring of aerosol forcing of climate from space: Analysis of measurement requirements, J. Quant. Spectrosc. Ra., 88, 149–161, https://doi.org/10.1016/j.jqsrt.2004.03.030, 2004.
Puthukkudy, A., Martins, J. V., Remer, L. A., Xu, X., Dubovik, O., Litvinov, P., McBride, B., Burton, S., and Barbosa, H. M. J.: Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017, Atmos. Meas. Tech., 13, 5207–5236, https://doi.org/10.5194/amt-13-5207-2020, 2020.
Ramos, A. A. and Collados, M.: Error propagation in polarimetric demodulation, Appl. Optics, 47, 2541–2549, https://doi.org/10.1364/AO.47.002541, 2008.
Remer, L. A. and Boss, E.: Polarimetry in the PACE Mission: Science Team Consensus Document, NASA Report No. 20190001717, PACE Tech. Rep. Ser., 3, https://ntrs.nasa.gov/citations/20190001717 (last access: 16 May 2025), 2018.
Remer, L. A., Davis, A. B., Mattoo, S., Levy, R. C., Kalashnikova, O. V., Coddington, O., Chowdhary, J., Knobelspiesse, K., Xu, X., Ahmad, Z., Boss, E., Cairns, B., Dierssen, H. M., Diner, D. J., Franz, B., Frouin, R., Gao, B.-C., Ibrahim, A., Martins, J. V., Omar, A. H., Torres, O., Xu, F., and Zhai, P.-W.: Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument, Front. Earth Sience, 7, 1–20, https://doi.org/10.3389/feart.2019.00152, 2019a.
Remer, L. A., Knobelspiesse, K., Zhai, P.-W., Xu, F., Kalashnikova, O. V., Chowdhary, J., Hasekamp, O., Dubovik, O., Wu, L., Ahmad, Z., Boss, E., Cairns, B., Coddington, O., Davis, A. B., Dierssen, H. M., Diner, D. J., Franz, B., Frouin, R., Gao, B.-C., Ibrahim, A., Levy, R. C., Martins, J. V., Omar, A. H., and Torres, O.: Retrieving Aerosol Characteristics From the PACE Mission, Part 2: Multi-Angle and Polarimetry, Front. Environ. Sci., 7, 1–21, https://doi.org/10.3389/fenvs.2019.00094, 2019b.
Schott, J. R.: Fundamentals of polarimetric remote sensing, Society of Photo-Optical Instrmentation Engineers (SPIE), Bellingham, Washington, 244 pp., https://doi.org/10.1117/3.817304, 2009.
Tyo, J. S., Goldstein, D. L., Chenault, D. B., and Shaw, J. A.: Review of passive imaging polarimetry for remote sensing applications, Appl. Optics, 45, 5453–5469, https://doi.org/10.1364/AO.45.005453, 2006.
Virtanen, P., Gommers, R., Oliphant, T. E., et al.: SciPy 1.0: fundamental algorithms for scientific computing in Python, Nat. Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020.
Werdell, P. J., Behrenfeld, M. J., Bontempi, P. S., Boss, E., Cairns, B., Davis, G. T., Franz, B. A., Gliese, U. B., Gorman, E. T., Hasekamp, O., Knobelspiesse, K. D., Mannino, A., Martins, J. V., McClain, C., Meister, G., and Remer, L. A.: The plankton, aerosol, cloud, ocean ecosystem mission status, science, advances, B. Am. Meteorol. Soc., 100, 1775–1794, https://doi.org/10.1175/BAMS-D-18-0056.1, 2019.
Wu, L., Hasekamp, O., van Diedenhoven, B., and Cairns, B.: Aerosol retrieval from multiangle, multispectral photopolarimetric measurements: importance of spectral range and angular resolution, Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, 2015.
Short summary
HARP2 (Hyper-Angular Rainbow Polarimeter) is a satellite remote sensing camera which was launched on the NASA PACE (Plankton Aerosol Cloud and Ocean Ecosystem) mission in early 2024. HARP2 uses image data of the Earth to allow scientists to measure natural processes. There exists interest in accurate polarimeter measurements of clouds and aerosols to understand climate change. In 2022, HARP2 underwent lab calibration evaluating its wide field-of-view characteristics. In doing so it was shown that key HARP2 calibration parameters possessed significant field-of-view variability.
HARP2 (Hyper-Angular Rainbow Polarimeter) is a satellite remote sensing camera which was...
