Articles | Volume 14, issue 10
https://doi.org/10.5194/amt-14-6561-2021
© Author(s) 2021. 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-14-6561-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Oct 2021
Research article |
| 12 Oct 2021
| 12 Oct 2021
Accuracy in starphotometry
Liviu Ivănescu
CORRESPONDING AUTHOR
Centre d'applications et de recherches en télédétection (CARTEL), Université de Sherbrooke, Sherbrooke, QC, Canada
Konstantin Baibakov
Centre d'applications et de recherches en télédétection (CARTEL), Université de Sherbrooke, Sherbrooke, QC, Canada
Canadian Space Agency, Agence spatiale canadienne, Saint-Hubert, QC, Canada
Norman T. O'Neill
Centre d'applications et de recherches en télédétection (CARTEL), Université de Sherbrooke, Sherbrooke, QC, Canada
Jean-Pierre Blanchet
Department of Earth and Atmospheric Sciences, Université du Québec à Montréal (UQÀM), Montréal, QC, Canada
Karl-Heinz Schulz
retired
formerly at: Dr. Schulz & Partner GmbH, Buckow, Germany (end of operations as of April 2016)
Related authors
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Yann Blanchard, Seyed Ali Sayedain, and Yasmin AboEl-Fetouh
Atmos. Chem. Phys., 25, 27–44, https://doi.org/10.5194/acp-25-27-2025, https://doi.org/10.5194/acp-25-27-2025, 2025
Short summary
Short summary
Dust from mid-latitude deserts or from local drainage basins is a weak component of atmospheric aerosols in the Arctic. Satellite-based dust estimates are often overestimated because dust and cloud measurements can be confused. Illustrations are given with an emphasis on the flawed claim that a classic indicator of dust (negative brightness temperature differences) is proof of the presence of airborne Arctic dust. Low-altitude warm-water plumes are the likely source of such negative values.
Liviu Ivănescu and Norman T. O'Neill
Atmos. Meas. Tech., 16, 6111–6121, https://doi.org/10.5194/amt-16-6111-2023, https://doi.org/10.5194/amt-16-6111-2023, 2023
Short summary
Short summary
The starphotometers' complex infrastructure prohibits calibration campaigns. On-site calibration procedures appear as the only practical solution. A multi-star approach overcomes site-specific sky transparency stability problems. Star selection strategies were proposed for mitigating some sources of errors. Data processing strategies and instrument design improvements appear necessary.
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Thomas F. Eck, Jeffrey S. Reid, David M. Giles, Daniel Pérez-Ramírez, and Jai Prakash Chaubey
Atmos. Meas. Tech., 16, 1103–1120, https://doi.org/10.5194/amt-16-1103-2023, https://doi.org/10.5194/amt-16-1103-2023, 2023
Short summary
Short summary
Aerosols are atmospheric particles that vary in size (radius) from a fraction of a micrometer (µm) to around 20 µm. They tend to be either smaller than 1 µm (like smoke or pollution) or larger than 1 µm (like dust or sea salt). Their optical effect (scattering and absorbing sunlight) can be divided into FM (fine-mode) and CM (coarse-mode) parts using a cutoff radius around 1 µm or a spectral (color) technique. We present and validate a theoretical link between the types of FM and CM divisions.
Simone Pulimeno, Angelo Lupi, Vito Vitale, Claudia Frangipani, Carlos Toledano, Stelios Kazadzis, Natalia Kouremeti, Christoph Ritter, Sandra Graßl, Kerstin Stebel, Vitali Fioletov, Ihab Abboud, Sandra Blindheim, Lynn Ma, Norm O’Neill, Piotr Sobolewski, Pawan Gupta, Elena Lind, Thomas F. Eck, Antti Hyvärinen, Veijo Aaltonen, Rigel Kivi, Janae Csavina, Dmitry Kabanov, Sergey M. Sakerin, Olga R. Sidorova, Robert S. Stone, Hagen Telg, Laura Riihimaki, Raul R. Cordero, Martin Radenz, Ronny Engelmann, Michel Van Roozendal, Anatoli Chaikovsky, Philippe Goloub, Junji Hisamitsu, and Mauro Mazzola
EGUsphere, https://doi.org/10.5194/egusphere-2025-2527, https://doi.org/10.5194/egusphere-2025-2527, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study analyzed aerosols optical properties over the Arctic and Antarctic to measure them even during long periods of darkness. It found that pollution in the Arctic is decreasing, likely due to European emission regulations, while wildfires are becoming a more important source of particles. In Antarctica, particle levels are higher near the coast than inland, and vary by season. These results help us better understand how air pollution and climate are changing at the Earth’s poles.
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Yann Blanchard, Seyed Ali Sayedain, and Yasmin AboEl-Fetouh
Atmos. Chem. Phys., 25, 27–44, https://doi.org/10.5194/acp-25-27-2025, https://doi.org/10.5194/acp-25-27-2025, 2025
Short summary
Short summary
Dust from mid-latitude deserts or from local drainage basins is a weak component of atmospheric aerosols in the Arctic. Satellite-based dust estimates are often overestimated because dust and cloud measurements can be confused. Illustrations are given with an emphasis on the flawed claim that a classic indicator of dust (negative brightness temperature differences) is proof of the presence of airborne Arctic dust. Low-altitude warm-water plumes are the likely source of such negative values.
Liviu Ivănescu and Norman T. O'Neill
Atmos. Meas. Tech., 16, 6111–6121, https://doi.org/10.5194/amt-16-6111-2023, https://doi.org/10.5194/amt-16-6111-2023, 2023
Short summary
Short summary
The starphotometers' complex infrastructure prohibits calibration campaigns. On-site calibration procedures appear as the only practical solution. A multi-star approach overcomes site-specific sky transparency stability problems. Star selection strategies were proposed for mitigating some sources of errors. Data processing strategies and instrument design improvements appear necessary.
Seyed Ali Sayedain, Norman T. O'Neill, James King, Patrick L. Hayes, Daniel Bellamy, Richard Washington, Sebastian Engelstaedter, Andy Vicente-Luis, Jill Bachelder, and Malo Bernhard
Atmos. Meas. Tech., 16, 4115–4135, https://doi.org/10.5194/amt-16-4115-2023, https://doi.org/10.5194/amt-16-4115-2023, 2023
Short summary
Short summary
We used (columnar) ground-based remote sensing (RS) tools and surface measurements to characterize local (drainage-basin) dust plumes at a site in the Yukon. Plume height, particle size, and column-to-surface ratios enabled insights into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modelers refine dust impacts in their climate change simulations. It is an important step since local dust is a key source of dust deposition on snow in the sensitive Arctic region.
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Thomas F. Eck, Jeffrey S. Reid, David M. Giles, Daniel Pérez-Ramírez, and Jai Prakash Chaubey
Atmos. Meas. Tech., 16, 1103–1120, https://doi.org/10.5194/amt-16-1103-2023, https://doi.org/10.5194/amt-16-1103-2023, 2023
Short summary
Short summary
Aerosols are atmospheric particles that vary in size (radius) from a fraction of a micrometer (µm) to around 20 µm. They tend to be either smaller than 1 µm (like smoke or pollution) or larger than 1 µm (like dust or sea salt). Their optical effect (scattering and absorbing sunlight) can be divided into FM (fine-mode) and CM (coarse-mode) parts using a cutoff radius around 1 µm or a spectral (color) technique. We present and validate a theoretical link between the types of FM and CM divisions.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
Short summary
Short summary
Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Outi Meinander, Pavla Dagsson-Waldhauserova, Pavel Amosov, Elena Aseyeva, Cliff Atkins, Alexander Baklanov, Clarissa Baldo, Sarah L. Barr, Barbara Barzycka, Liane G. Benning, Bojan Cvetkovic, Polina Enchilik, Denis Frolov, Santiago Gassó, Konrad Kandler, Nikolay Kasimov, Jan Kavan, James King, Tatyana Koroleva, Viktoria Krupskaya, Markku Kulmala, Monika Kusiak, Hanna K. Lappalainen, Michał Laska, Jerome Lasne, Marek Lewandowski, Bartłomiej Luks, James B. McQuaid, Beatrice Moroni, Benjamin Murray, Ottmar Möhler, Adam Nawrot, Slobodan Nickovic, Norman T. O’Neill, Goran Pejanovic, Olga Popovicheva, Keyvan Ranjbar, Manolis Romanias, Olga Samonova, Alberto Sanchez-Marroquin, Kerstin Schepanski, Ivan Semenkov, Anna Sharapova, Elena Shevnina, Zongbo Shi, Mikhail Sofiev, Frédéric Thevenet, Throstur Thorsteinsson, Mikhail Timofeev, Nsikanabasi Silas Umo, Andreas Uppstu, Darya Urupina, György Varga, Tomasz Werner, Olafur Arnalds, and Ana Vukovic Vimic
Atmos. Chem. Phys., 22, 11889–11930, https://doi.org/10.5194/acp-22-11889-2022, https://doi.org/10.5194/acp-22-11889-2022, 2022
Short summary
Short summary
High-latitude dust (HLD) is a short-lived climate forcer, air pollutant, and nutrient source. Our results suggest a northern HLD belt at 50–58° N in Eurasia and 50–55° N in Canada and at >60° N in Eurasia and >58° N in Canada. Our addition to the previously identified global dust belt (GDB) provides crucially needed information on the extent of active HLD sources with both direct and indirect impacts on climate and environment in remote regions, which are often poorly understood and predicted.
Peng Xian, Jianglong Zhang, Norm T. O'Neill, Travis D. Toth, Blake Sorenson, Peter R. Colarco, Zak Kipling, Edward J. Hyer, James R. Campbell, Jeffrey S. Reid, and Keyvan Ranjbar
Atmos. Chem. Phys., 22, 9915–9947, https://doi.org/10.5194/acp-22-9915-2022, https://doi.org/10.5194/acp-22-9915-2022, 2022
Short summary
Short summary
The study provides baseline Arctic spring and summertime aerosol optical depth climatology, trend, and extreme event statistics from 2003 to 2019 using a combination of aerosol reanalyses, remote sensing, and ground observations. Biomass burning smoke has an overwhelming contribution to black carbon (an efficient climate forcer) compared to anthropogenic sources. Burning's large interannual variability and increasing summer trend have important implications for the Arctic climate.
Peng Xian, Jianglong Zhang, Norm T. O'Neill, Jeffrey S. Reid, Travis D. Toth, Blake Sorenson, Edward J. Hyer, James R. Campbell, and Keyvan Ranjbar
Atmos. Chem. Phys., 22, 9949–9967, https://doi.org/10.5194/acp-22-9949-2022, https://doi.org/10.5194/acp-22-9949-2022, 2022
Short summary
Short summary
The study provides a baseline Arctic spring and summertime aerosol optical depth climatology, trend, and extreme event statistics from 2003 to 2019 using a combination of aerosol reanalyses, remote sensing, and ground observations. Biomass burning smoke has an overwhelming contribution to black carbon (an efficient climate forcer) compared to anthropogenic sources. Burning's large interannual variability and increasing summer trend have important implications for the Arctic climate.
Keyvan Ranjbar, Norm T. O'Neill, and Yasmin Aboel-Fetouh
Atmos. Chem. Phys., 22, 1757–1760, https://doi.org/10.5194/acp-22-1757-2022, https://doi.org/10.5194/acp-22-1757-2022, 2022
Short summary
Short summary
We argue that the illustration employed by Huang et al. (2015) to demonstrate the transport of Asian dust to the high Arctic was, in fact, largely a cloud event and that the actual impact of Asian dust was measurable but much weaker than what they proposed and had occurred a day earlier (in agreement with the transport model they had employed to predict the transport path to the high Arctic).
Konstantin Baibakov, Samuel LeBlanc, Keyvan Ranjbar, Norman T. O'Neill, Mengistu Wolde, Jens Redemann, Kristina Pistone, Shao-Meng Li, John Liggio, Katherine Hayden, Tak W. Chan, Michael J. Wheeler, Leonid Nichman, Connor Flynn, and Roy Johnson
Atmos. Chem. Phys., 21, 10671–10687, https://doi.org/10.5194/acp-21-10671-2021, https://doi.org/10.5194/acp-21-10671-2021, 2021
Short summary
Short summary
We find that the airborne measurements of the vertical extinction due to aerosols (aerosol optical depth, AOD) obtained in the Athabasca Oil Sands Region (AOSR) can significantly exceed ground-based values. This can have an effect on estimating the AOSR radiative impact and is relevant to satellite validation based on ground-based measurements. We also show that the AOD can marginally increase as the plumes are being transported away from the source and the new particles are being formed.
Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
Geosci. Model Dev., 13, 5737–5755, https://doi.org/10.5194/gmd-13-5737-2020, https://doi.org/10.5194/gmd-13-5737-2020, 2020
Cited articles
AiryLab: Measurement Report for Celestron C11 Telescope, Tech. rep., AiryLab, available at: https://www.airylab.com/contenu/mesures/astro/rapport 2012-10002-a.pdf (last access: 21 September 2021), 2012.
a
Albert, J. E.: Satellite-Mounted Light Sources as Photometric Calibration
Standards for Ground-Based Telescopes, Astron. J., 143, 8,
https://doi.org/10.1088/0004-6256/143/1/8, 2012. a
Alekseeva, G. A.: The determination of atmospheric extinction by the stellar
magnitude differences method in stellar spectrophotometry, Izvestiya Glavnoj
Astronomicheskoj Observatorii v Pulkove, 198, 18–21, available at: http://adsabs.harvard.edu/abs/1980IzPul.198...18A (last access: 21 September 2021), 1980. a
Alekseeva, G. A., Galkin, V. D., Nikanorova, I. N., and Novikov, V. V.: A
Spectrophotometric Catalogue of 60 Selected Southern Stars, Balt.
Astron., 3, 361, https://doi.org/10.1515/astro-1994-0405, 1994. a
Alekseeva, G. A., Arkharov, A. A., Galkin, V. D., Hagen-Thorn, E., Nikanorova, I., Novikov, V. V., Novopashenny, V., Pakhomov, V., Ruban, E., and Shchegolev, D.: The Pulkovo Spectrophotometric Catalog of Bright Stars in the Range from 320 TO 1080 NM, Balt. Astron., 5, 603–838,
available at: http://adsabs.harvard.edu/abs/1997BaltA...6..481A (last access: 21 September 2021), 1996. a, b, c, d
ASTM-G173-03: Standard Tables for Reference Solar Spectral Irradiances: Direct Normal and Hemispherical on 37∘ Tilted Surface, ASTM International, https://doi.org/10.1520/G0173-03R12, 2012. a
Baibakov, K., O'Neill, N. T., Firanski, B., and Strawbridge, K.: Preliminary
Analysis of Night-time Aerosol Optical Depth Retrievals at a Rural,
Near-urban Site in Southern Canada, AIP Conference Proceedings, 3–8 August
2008, Foz do Iguaçu, Brazil, 1100, 443, https://doi.org/10.1063/1.3117015, 2009. a
Baibakov, K., O'Neill, N. T., Ivanescu, L., Duck, T. J., Perro, C., Herber, A., Schulz, K.-H., and Schrems, O.: Synchronous polar winter starphotometry and lidar measurements at a High Arctic station, Atmos. Meas. Tech., 8, 3789–3809, https://doi.org/10.5194/amt-8-3789-2015, 2015. a
Baker, D. J.: Rayleigh, the Unit for Light Radiance, Appl. Optics, 13,
2160–2163, https://doi.org/10.1364/AO.13.002160, 1974. a
Baudat, G.: Full Frame Guiding and Focusing, in: Northeast Astro-Imaging
Conference, Crowne Plaza Conference Center, Suffern, NY, USA, 6 April 2017, available at: https://www.innovationsforesight.com/PDF/FullFrameGuidingandFocusing_NEAIC2017_2.pdf (last access: 21 September 2021),
2017. a
Baum, B. A., Yang, P., Heymsfield, A. J., Bansemer, A., Cole, B. H., Merrelli, A., Schmitt, C., and Wang, C.: Ice cloud single-scattering property models with the full phase matrix at wavelengths from 0.2 to 100 µm, J. Quant. Spectrosc. Ra., 146, 123–139,
https://doi.org/10.1016/j.jqsrt.2014.02.029, 2014. a
Bessell, M. S.: Standard Photometric Systems, Annu. Rev. Astron. Astr., 43, 293–336, https://doi.org/10.1146/annurev.astro.41.082801.100251,
2005. a
Bohlin, R. C.: Hubble Space Telescope CALSPEC Flux Standards: Sirius (and
Vega), Astron. J., 147, 127, https://doi.org/10.1088/0004-6256/147/6/127, 2014. a
Bohlin, R. C., Dickinson, M. E., and Calzetti, D.: Spectrophotometric
Standards from the Far-Ultraviolet to the Near-Infrared: STIS and NICMOS
Fluxes, Astron. J., 122, 2118–2128, https://doi.org/10.1086/323137,
2001. a
Bohlin, R. C., Gordon, K. D., and Tremblay, P.-E.: Techniques and Review of
Absolute Flux Calibration from the Ultraviolet to the Mid-Infrared,
Publ. Astron. Soc. Pac., 126, 711–732,
https://doi.org/10.1086/677655, 2014. a, b
Box, G. P. and Taha, G.: Reply to “Comment on: “New method for inferring total ozone and aerosol optical thickness from multispectral extinction
measurements using eigenvalue analysis” by G. Taha and G.P. Box” by Xia
Xiangao and Wang Mingxing, Geophys. Res. Lett., 28, 1999–2000,
https://doi.org/10.1029/2001GL013210, 2001. a
Bucholtz, A.: Rayleigh-scattering calculations for the terrestrial
atmosphere, Appl. Optics, 34, 2765–2773, https://doi.org/10.1364/AO.34.002765, 1995. a, b
Burki, G., Rufener, F., Burnet, M., Richard, C., Blecha, A., and Bratschi, P.: The atmospheric extinction at the E.S.O. La Silla observatory, Astron. Astrophys. Sup., 112, 383,
available at: http://adsabs.harvard.edu/abs/1995A&AS..112..383B (last access: 21 September 2021), 1995. a
Cachorro, V. E., Romero, P. M., Toledano, C., Cuevas, E., and de Frutos, A. M.: The fictitious diurnal cycle of aerosol optical depth: A new approach for “in situ” calibration and correction of AOD data series, Geophys.
Res. Lett., 31, L12106, https://doi.org/10.1029/2004GL019651, 2004. a
Cannon, A. J. and Pickering, E. C.: The Henry Draper catalogue, Annals of the Astronomical Observatory of Harvard College, v. 91-93,96, Astronomical Observatory of Harvard College, Cambridge, Mass., USA, 1918–1921,
available at: https://www.worldcat.org/oclc/230383766 (last access: 21 September 2021), 1918. a
Carlund, T., Landelius, T., and Josefsson, W.: Comparison and Uncertainty of
Aerosol Optical Depth Estimates Derived from Spectral and Broadband
Measurements, J. Appl. Meteorol., 42, 1598–1610, https://doi.org/10.1175/1520-0450(2003)042<1598:CAUOAO>2.0.CO;2, 2003. a
Carroll, B. W. and Ostlie, D. A.: An Introduction to Modern Astrophysics, 2nd edn., Pearson Education, Inc., Addison Wesley,
available at: https://www.worldcat.org/oclc/69020924 (last access: 21 September 2021), 2007. a
Cede, A., Herman, J., Richter, A., Krotkov, N., and Burrows, J.: Measurements of nitrogen dioxide total column amounts using a Brewer double
spectrophotometer in direct Sun mode, J. Geophys. Res., 111,
D05304, https://doi.org/10.1029/2005JD006585, 2006. a
Chattopadhyay, R. and Midya, S. K.: Airglow emissions: fundamentals of theory and experiment, Indian J. Phys., 80, 115–166,
available at: http://hdl.handle.net/10821/204 (last access: 21 September 2021), 2006. a
Chew, B. N., Campbell, J. R., Reid, J. S., Giles, D. M., Welton, E. J.,
Salinas, S. V., and Liew, S. C.: Tropical cirrus cloud contamination in sun
photometer data, Atmos. Environ., 45, 6724–6731,
https://doi.org/10.1016/j.atmosenv.2011.08.017, 2011. a
Chylek, P., Henderson, B., and Mishchenko, M.: Aerosol radiative forcing and
the accuracy of satellite aerosol optical depth retrieval, J.
Geophys. Res.-Atmos., 108, 4764, https://doi.org/10.1029/2003jd004044,
2003. a
Dempsey, J. T., Storey, J. W. V., and Phillips, A.: Auroral Contribution to
Sky Brightness for Optical Astronomy on the Antarctic Plateau, Publ. Astron. Soc. Aust., 22, 91–104, https://doi.org/10.1071/AS04036, 2005. a, b
Deustua, S., Kent, S., and Smith, J. A.: Absolute Calibration of Astronomical Flux Standards, in: Planets, Stars and Stellar Systems,
Springer Netherlands, Dordrecht, the Netherlands, 375–402, https://doi.org/10.1007/978-94-007-5618-2_8, 2013. a
DeVore, J., Kristl, J. A., and Rappaport, S. A.: Retrieving cirrus
microphysical properties from stellar aureoles, J. Geophys.
Res.-Atmos., 118, 1–18, https://doi.org/10.1002/jgrd.50440, 2013. a
Dubovik, O., Smirnov, A. V., Holben, B. N., King, M. D., Kaufman, Y. J., Eck,
T. F., and Slutsker, I.: Accuracy assessments of aerosol optical properties
retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance
measurements, J. Geophys. Res.-Atmos., 105, 9791–9806,
https://doi.org/10.1029/2000JD900040, 2000. a
Eyer, L. and Grenon, M.: Photometric Variability in the HR Diagram, in:
Proceedings of the ESA Hipparcos Symposium SP-402, Venice, Italy, 13–16 May 1997, vol.
402, edited by: Bonnet, R., Høg, E., Bernacca, P.,
Emiliani, L., Blaauw, A., Turon, C., Kovalevsky, J., Lindegren, L., Hassan,
H., Bouffard, M., Strim, B., Heger, D., Perryman, M., and Woltjer, L., p. 467–472, available at: https://ui.adsabs.harvard.edu/abs/1997ESASP.402..467E/abstract (last access: 21 September 2021),
1997. a
Forgan, B. W.: General method for calibrating Sun photometers, Appl.
Optics, 33, 4841–4850, https://doi.org/10.1364/AO.33.004841, 1994. a
Fried, D. L.: Limiting Resolution Looking Down Through Atmosphere, J. Opt.
Soc. Am., 56, 1380–1384, https://doi.org/10.1364/JOSA.56.001380, 1966. a
Galkin, V. D. and Arkharov, A. A.: Determination of Extra Atmospheric
Monochromatic Stellar Magnitudes in the Region of Telluric Bands, Sov.
Astron., 25, 361–366, available at: http://adsabs.harvard.edu/abs/1981SvA....25..361G (last access: 21 September 2021), 1981. a
Galkin, V. D., Leiterer, U., Alekseeva, G. A., Novikov, V. V., and Pakhomov,
V. P.: Accuracy of the Water Vapour Content Measurements in the Atmosphere
Using Optical Methods, arXiv [preprint], arXiv:1010.3669, 18 October 2010. a
Galkin, V. D., Immler, F., Alekseeva, G. A., Berger, F.-H., Leiterer, U., Naebert, T., Nikanorova, I. N., Novikov, V. V., Pakhomov, V. P., and Sal'nikov, I. B.: Analysis of the application of the optical method to the measurements of the water vapor content in the atmosphere – Part 1: Basic concepts of the measurement technique, Atmos. Meas. Tech., 4, 843–856, https://doi.org/10.5194/amt-4-843-2011, 2011. a
Gattinger, R. L. and Jones, A. V.: Quantitative Spectroscopy of the Aurora.
II. The Spectrum of Medium Intensity Aurora Between 4500 and 8900 Å,
Can. J. Phys., 52, 2343–2356, https://doi.org/10.1139/p74-305, 1974. a, b
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019. a
Glindemann, A.: Relevant Parameters for Tip-Tilt Systems of Large Telescopes, Publ. Astron. Soc. Pac., 109, 682,
https://doi.org/10.1086/133932, 1997. a
Golay, M.: Introduction to Astronomical Photometry, vol. 41 of
Astrophysics and Space Science Library, D. Reidel Publishing Company,
https://doi.org/10.1007/978-94-010-2169-2, 1974. a, b
Gueymard, C. A.: Parameterized transmittance model for direct beam and
circumsolar spectral irradiance, Sol. Energy, 71, 325–346,
https://doi.org/10.1016/S0038-092X(01)00054-8, 2001. a
Gutierrez-Moreno, A. and Stock, J.: The Accuracy of Extinction
Determinations, Publicaciones Departmento de Astronomia Universidad de
Chile, Observatorio Astronómico Nacional Cerro Calan, 1, 19–22,
available at: https://ui.adsabs.harvard.edu/abs/1966PDAUC...1...19G/abstract (last access: 21 September 2021),
1966. a, b, c
Halthore, R. N., Eck, T. F., Holben, B. N., and Markham, B. L.: Sun
photometric measurements of atmospheric water vapor column abundance in the
940-nm band, J. Geophys. Res.-Atmos., 102, 4343–4352,
https://doi.org/10.1029/96JD03247, 1997. a
Hanuschik, R. W.: A flux-calibrated, high-resolution atlas of optical sky
emission from UVES, Astron. Astrophys., 407, 1157–1164,
https://doi.org/10.1051/0004-6361:20030885, 2003. a
Hardie, R.: Photoelectric Reductions, in: Stars and Stellar Systems, edited
by: Hiltner, W., vol. 2, chap. Astronomic, p. 180, The University of Chicago
Press, Chicago, USA, available at: http://www.worldcat.org/oclc/534975 (last access: 21 September 2021), 1962. a
He, F., Wei, Y., and Wan, W.: Equatorial aurora: the aurora-like airglow in
the negative magnetic anomaly, Natl. Sci. Rev., 7, 1606–1615,
https://doi.org/10.1093/nsr/nwaa083, 2020. a
Herber, A. B., Thomason, L. W., Gernandt, H., Leiterer, U., Nagel, D., Schulz, K.-H., Kaptur, J., Albrecht, T., and Notholt, J.: Continuous day and night aerosol optical depth observations in the Arctic between 1991 and 1999, J. Geophys. Res.-Atmos., 107, AAC 6-1–AAC 6-13,
https://doi.org/10.1029/2001JD000536, 2002. a, b
Hill, C., Yurchenko, S. N., and Tennyson, J.: Temperature-dependent molecular absorption cross sections for exoplanets and other atmospheres, Icarus, 226, 1673–1677, https://doi.org/10.1016/j.icarus.2012.07.028, 2013. a
Holben, B. N., Tanré, D., Smirnov, A. V., Eck, T. F., Slutsker, I.,
Abuhassan, N., Newcomb, W. W., Schafer, J. S., Chatenet, B., Lavenu, F.,
Kaufman, Y. J., Castle, J. V., Setzer, A., Markham, B., Clark, D., Frouin,
R., Halthore, R., Karneli, A., O'Neill, N. T., Pietras, C., Pinker, R. T.,
Voss, K., and Zibordi, G.: An emerging ground-based aerosol climatology:
Aerosol optical depth from AERONET, J. Geophys. Res.-Atmos., 106, 12067–12097, https://doi.org/10.1029/2001JD900014, 2001. a
Ivănescu, L.: Une application de la photométrie stellaire à
l'observation de nuages optiquement minces à Eureka, NU, MS thesis, UQAM, available at: https://www.archipel.uqam.ca/id/eprint/8417 (last access: 21 September 2021),
2015. a
Ivănescu, L.: Accuracy in starphotometry – code and data, Zenodo [data set], https://doi.org/10.5281/zenodo.4633904, 2021. a
Ivănescu, L., O'Neill, N. T., and Blanchet, J. P.: Spectrophotometric Catalog for Atmospheric Remote Sensing Through Star-photometry, in: American
Geophysical Union, Fall Meeting 2017, New Orleans Ernest N. Morial Convention Center, New Orleans, LA, USA, 11–15 December 2017, vol. 2017, abstract A23H-05,
available at: https://ui.adsabs.harvard.edu/#abs/2017AGUFM.A23H..05I (last access: 21 September 2021), 2017. a
Johnson, H. and Morgan, W.: Fundamental stellar photometry for standards of
spectral type on the revised system of the Yerkes spectral atlas,
Astrophys. J., 117, 313, https://doi.org/10.1086/145697, 1953. a
Jones, A. V. and Gattinger, R. L.: Quantitative Spectroscopy of the Aurora. I. The Spectrum of Bright Aurora between 7000 and 9000 Å at 7.5 Å
Resolution, Can. J. Phys., 50, 1833–1841,
https://doi.org/10.1139/p72-249, 1972. a
Jones, A. V. and Gattinger, R. L.: Quantitative Spectroscopy of the Aurora.
III. The Spectrum of Medium Intensity Aurora Between 3100 Å and 4700 Å, Can. J. Phys., 53, 1806–1813, https://doi.org/10.1139/p75-231,
1975. a
Jones, A. V. and Gattinger, R. L.: Quantitative spectroscopy of the aurora.
IV. The spectrum of medium intensity aurora between 8800 Å and 11 400 Å, Can. J. Phys., 54, 2128–2133, https://doi.org/10.1139/p76-251,
1976. a
Kaiser, M. and Access Team: ACCESS: Design, Calibration Strategy, and
Status, in: The Science of Calibration, edited by: Deustua, S., Allam, S.,
Tucker, D., and Smith, J., vol. 503 of Astronomical Society of the
Pacific Conference Series, p. 221, available at: http://aspbooks.org/custom/publications/paper/503-0221.html (last access: 21 September 2021),
2016. a
Kent, S., Kaiser, M. E., Deustua, S. E., Smith, J. A., Adelman, S., Allam, S., Baptista, B., Bohlin, R. C., Clem, J. L., Conley, A., Edelstein, J., Elias, J., Glass, I., Henden, A., Howell, S., Kimble, R. A., Kruk, J. W., Lampton, M., Magnier, E. A., McCandliss, S. R., Moos, W., Mostek, N., Mufson, S., Oswalt, T. D., Perlmutter, S., Prieto, C. A., Rauscher, B. J., Riess, A.,
Saha, A., Sullivan, M., Suntzeff, N., Tokunaga, A., Tucker, D., Wing, R.,
Woodgate, B., and Wright, E. L.: Photometric Calibrations for 21st Century
Science, Astro2010: The Astron. Astrophys. Decadal Survey, p. 8, arXiv [preprint], arXiv:0903.2799, 16 March 2009. a
King, I.: Effective extinction values in wide-band photometry, Astron. J., 57, 253, https://doi.org/10.1086/106766, 1952. a
King, M. D. and Byrne, D. M.: A Method for Inferring Total Ozone Content from the Spectral Variation of Total Optical Depth Obtained with a Solar Radiometer, J. Atmos. Sci., 33, 2242–2251, https://doi.org/10.1175/1520-0469(1976)033<2242:AMFITO>2.0.CO;2, 1976. a
Kippenhahn, R., Weigert, A., and Weiss, A.: Stellar Structure and Evolution, Springer, Berlin, Heidelberg, Germany, https://doi.org/10.1007/978-3-642-30304-3, 2012. a
Knyazeva, L. and Kharitonov, A.: Standard Stars for the Alma-Ata Catalog –
Energy Distribution in the Spectrum of VEGA, Sov. Astron., 34, 626,
available at: http://adsabs.harvard.edu/full/1990SvA....34..626K (last access: 21 September 2021), 1990. a
Krassovsky, V., Shefov, N., and Yarin, V.: Atlas of the airglow spectrum
3000–12 400 Å, Planet. Space Sci., 9, 883–915,
https://doi.org/10.1016/0032-0633(62)90008-9, 1962. a
Kyrölä, E., Tamminen, J., Leppelmeier, G., Sofieva, V., Hassinen,
S., Bertaux, J., Hauchecorne, A., Dalaudier, F., Cot, C., Korablev, O.,
Fanton d'Andon, O., Barrot, G., Mangin, A., Théodore, B., Guirlet, M.,
Etanchaud, F., Snoeij, P., Koopman, R., Saavedra, L., Fraisse, R., Fussen,
D., and Vanhellemont, F.: GOMOS on Envisat: an overview, Adv. Space
Res., 33, 1020–1028, https://doi.org/10.1016/S0273-1177(03)00590-8, 2004. a
Lebedev, V. A., Stepanov, V. V., Zykov, L., and Syundyukov, A. Y.: Method for determining the transparency of the atmosphere by photometry of stars, Federal Service for Intellectual Property, Russia,
available at: https://patents.google.com/patent/RU2620784C1 (last access: 21 September 2021), 2016 (in Russian). a
Le Borgne, J.-F., Bruzual, G., Pelló, R., Lançon, A.,
Rocca-Volmerange, B., Sanahuja, B., Schaerer, D., Soubiran, C., and
Vílchez-Gómez, R.: STELIB: A library of stellar spectra at
R=2000, Astron. Astrophys., 402, 433–442,
https://doi.org/10.1051/0004-6361:20030243, 2003. a
Leiterer, U., Naebert, A., Naebert, T., and Alekseeva, G. A.: A new star
photometer developed for spectral aerosol optical thickness measurements in
Lindenberg, Contributions to atmospheric physics, 68, 133–141,
available at: http://www.worldcat.org/oclc/3416825 (last access: 21 September 2021), 1995. a, b
Leiterer, U., Alekseeva, G. A., Galkin, V. D., Dier, D., Güldner, J.,
Naebert, A., Naebert, T., Novikov, V. V., Rentsch, H., and Sakunov, G.:
Water vapor column content and optical depths measurements by a sun- and
starphotometer, Contributions to atmospheric physics, 71, 401–420,
available at: http://www.worldcat.org/oclc/3416825 (last access: 21 September 2021), 1998. a, b
Lindenmaier, R., Strong, K., Batchelor, R. L., Bernath, P. F., Chabrillat, S., Chipperfield, M. P., Daffer, W. H., Drummond, J. R., Feng, W., Jonsson,
A. I., Kolonjari, F., Manney, G. L., McLinden, C., Menard, R., and Walker,
K. A.: A study of the Arctic NOy budget above Eureka, Canada, J. Geophys.
Res., 116, D23302, https://doi.org/10.1029/2011JD016207, 2011. a
Marouani, H. and Dagenais, M. R.: Internal Clock Drift Estimation in Computer Clusters, Journal of Computer Systems, Networks, and Communications, 2008, 1–7, https://doi.org/10.1155/2008/583162, 2008. a
Michalsky, J. J., Liljegren, J. C., and Harrison, L. C.: A comparison of Sun
photometer derivations of total column water vapor and ozone to standard
measures of same at the Southern Great Plains Atmospheric Radiation
Measurement site, J. Geophys. Res., 100, 995–1021,
https://doi.org/10.1029/95jd02706, 1995. a
Michalsky, J. J., Beauharnois, M., Berndt, J., Harrison, L., Kiedron, P., and
Min, Q.: O2-O2 absorption band identification based on optical depth spectra
of the visible and near-infrared, Geophys. Res. Lett., 26,
1581–1584, https://doi.org/10.1029/1999GL900267, 1999. a
Mitchell, R. M. and Forgan, B. W.: Aerosol Measurement in the Australian
Outback: Intercomparison of Sun Photometers, J. Atmos. Ocean. Tech., 20, 54–66, https://doi.org/10.1175/1520-0426(2003)020<0054:AMITAO>2.0.CO;2, 2003. a
Nijegorodov, N. and Luhanga, P. V.: Air mass: Analytical and empirical
treatment; an improved formula for air mass, Renew. Energ., 7, 57–65,
https://doi.org/10.1016/0960-1481(95)00111-5, 1996. a
Novikov, V.: Community comment on “Accuracy in starphotometry” by Liviu
Ivănescu et al., Atmos. Meas. Tech. Discuss.,
https://doi.org/10.5194/amt-2021-88-CC1, 2021. a
Nyassor, P. K., Buriti, R. A., Paulino, I., Medeiros, A. F., Takahashi, H., Wrasse, C. M., and Gobbi, D.: Determination of gravity wave parameters in the airglow combining photometer and imager data, Ann. Geophys., 36, 705–715, https://doi.org/10.5194/angeo-36-705-2018, 2018. a, b
Ochsenbein, F., Bauer, P., and Marcout, J.: The VizieR database of
astronomical catalogues, Astron. Astrophys. Sup., 143,
23–32, https://doi.org/10.1051/aas:2000169, 2000. a
Oke, J. and Schild, R. E.: The absolute spectral energy distribution of Alpha Lyrae, Astrophys. J., 161, 1015, https://doi.org/10.1086/150603, 1970. a
O'Neill, N. T., Eck, T., Holben, B. N., Smirnov, A. V., Dubovik, O., and Royer, A.: Bimodal size distribution influences on the variation of Angstrom
derivatives in spectral and optical depth space, J. Geophys.
Res.-Atmos., 106, 9787–9806, https://doi.org/10.1029/2000JD900245, 2001. a, b
O'Neill, N. T., Eck, T. F., Smirnov, A. V., Holben, B. N., and Thulasiraman,
S.: Spectral discrimination of coarse and fine mode optical depth, J. Geophys. Res., 108, 4559, https://doi.org/10.1029/2002JD002975, 2003. a
Orphal, J. and Chance, K.: Ultraviolet and visible absorption cross-sections
for HITRAN, J. Quant. Spectrosc. Ra., 82,
491–504, https://doi.org/10.1016/S0022-4073(03)00173-0, 2003. a
Orphal, J., Fellows, C. E., and Flaud, P.-M.: The visible absorption spectrum of NO3 measured by high-resolution Fourier transform spectroscopy, J. Geophys. Res.-Atmos., 108, 4077–4087,
https://doi.org/10.1029/2002JD002489, 2003. a
Owens, J. C.: Optical Refractive Index of Air: Dependence on Pressure,
Temperature and Composition, Appl. Optics, 6, 51–59,
https://doi.org/10.1364/AO.6.000051, 1967. a
Paraskeva, V., Norton, M., Hadjipanayi, M., and Georghiou, G. E.: Calibration of Spectroradiometers for Outdoor Direct Solar Spectral Irradiance Measurements, 28th European Photovoltaic Solar Energy Conference and Exhibition, Villepinte, France, 30 September–4 October 2013, 3466–3471, https://doi.org/10.4229/28THEUPVSEC2013-4AV.6.35, 2013. a
Peretz, E., Mather, J., Slonaker, R., O'Meara, J., Seager, S., Campbell, R.,
Hoerbelt, T., and Kain, I.: Orbiting Configurable Artificial Star (ORCAS)
for Visible Adaptive Optics from the Ground, Bulletin of the AAS, 51,
available at: https://baas.aas.org/pub/2020n7i284 (last access: 21 September 2021), 2019. a
Pérez-Ramírez, D., Aceituno, J., Ruiz, B., Olmo, F. J., and
Alados-Arboledas, L.: Development and calibration of a star photometer to
measure the aerosol optical depth: Smoke observations at a high mountain
site, Atmos. Environ., 42, 2733–2738,
https://doi.org/10.1016/j.atmosenv.2007.06.009, 2008a. a
Pérez-Ramírez, D., Ruiz, B., Aceituno, J., Olmo, F. J., and
Alados-Arboledas, L.: Application of Sun/star photometry to derive the
aerosol optical depth, Int. J. Remote Sens., 29,
5113–5132, https://doi.org/10.1080/01431160802036425, 2008b. a, b
Pérez-Ramírez, D., Lyamani, H., Olmo, F. J., and Alados-Arboledas, L.: Improvements in star photometry for aerosol characterizations, J. Aerosol Sci., 42, 737–745, https://doi.org/10.1016/j.jaerosci.2011.06.010, 2011. a
Pickering, E. C.: Revised Harvard Photometry: a catalogue of the positions,
photometric magnitudes and spectra of 9110 stars, mainly of the magnitude
6.50, and brighter observed with the 2 and 4 inch meridian photometers,
Annals of Harvard College Observatory, 50, 1,
available at: https://ui.adsabs.harvard.edu/abs/1908AnHar..50....1P/abstract (last access: 21 September 2021),
1908. a
Pickles, A. J.: A Stellar Spectral Flux Library: 1150–25 000 Å,
Publ. Astron. Soc. Pac., 110, 863–878,
https://doi.org/10.1086/316197, 1998. a
Qie, L., Li, Z., Goloub, P., Li, L., Li, D., Li, K., Zhang, Y., and Xu, H.:
Retrieval of the aerosol asymmetry factor from Sun–sky radiometer
measurements: application to almucantar geometry and accuracy assessment,
Appl. Optics, 56, 9932–9940, https://doi.org/10.1364/ao.56.009932, 2017. a
Racine, R.: The Telescope Point Spread Function, Publ. Astron. Soc. Pac., 108, 699, https://doi.org/10.1086/133788, 1996. a, b, c
Rapp-Arrarás, Í. and Domingo-Santos, J. M.: Functional forms for
approximating the relative optical air mass, J. Geophys.
Res.-Atmos., 116, D24308, https://doi.org/10.1029/2011JD016706, 2011. a
Rauch, T., Werner, K., Bohlin, R. C., and Kruk, J. W.: The virtual observatory service TheoSSA: Establishing a database of synthetic stellar flux standards, Astron. Astrophys., 560, A106,
https://doi.org/10.1051/0004-6361/201322336, 2013. a
Robertson, J. G.: Detector Sampling of Optical/IR Spectra: How Many Pixels per FWHM?, Publ. Astron. Soc. Aust., 34, e035,
https://doi.org/10.1017/pasa.2017.29, 2017. a
Roscoe, H. K., Jones, R. L., Freshwater, R. A., Fish, D., Wolfenden, R.,
Harries, J. E., and Oldham, D. J.: A star-pointing UV-visible spectrometer
for remote sensing of the stratosphere, in: Proceedings of SPIE, Optical
Methods in Atmospheric Chemistry, 1715, 374–380,
https://doi.org/10.1117/12.140226, 1993. a
Rothman, L., Gordon, I., Barbe, A., Benner, D., Bernath, P., Birk, M., Boudon, V., Brown, L., Campargue, A., Champion, J.-P., Chance, K., Coudert, L., Dana, V., Devi, V., Fally, S., Flaud, J.-M., Gamache, R., Goldman, A., Jacquemart, D., Kleiner, I., Lacome, N., Lafferty, W., Mandin, J.-Y., Massie, S., Mikhailenko, S., Miller, C., Moazzen-Ahmadi, N., Naumenko, O., Nikitin, A., Orphal, J., Perevalov, V., Perrin, A., Predoi-Cross, A., Rinsland, C.,
Rotger, M., Šimečková, M., Smith, M., Sung, K., Tashkun,
S., Tennyson, J., Toth, R., Vandaele, A., and Vander Auwera, J.: The
HITRAN 2008 molecular spectroscopic database, J. Quant.
Spectrosc. Ra., 110, 533–572,
https://doi.org/10.1016/j.jqsrt.2009.02.013, 2009. a
Rufener, F.: Technique et réduction des mesures dans un nouveau
système de photométrie stellaire, Archives des Sciences,
Genève, 16, 30, available at: http://www.worldcat.org/oclc/491819702 (last access: 21 September 2021), 1963. a
Samus, N. N., Kazarovets, E. V., Durlevich, O. V., Kireeva, N. N., and
Pastukhova, E. N.: General catalogue of variable stars: Version GCVS 5.1,
Astron. Rep.+, 61, 80–88, https://doi.org/10.1134/S1063772917010085, 2017. a
Shannon, C. E.: A Mathematical Theory of Communication, Bell Syst. Tech. J., 27, 379–423, https://doi.org/10.1002/j.1538-7305.1948.tb01338.x, 1948. a
Shaw, G. E.: Error analysis of multi-wavelength sun photometry, Pure Appl. Geophys., 114, 1–14, https://doi.org/10.1007/BF00875487, 1976. a
Shiobara, M., Asano, S., Shiobara, M., and Asano, S.: Estimation of Cirrus
Optical Thickness from Sun Photometer Measurements, J. Appl. Meteorol., 33, 672–681, https://doi.org/10.1175/1520-0450(1994)033<0672:EOCOTF>2.0.CO;2, 1994. a
Silva, D. R. and Cornell, M. E.: A new library of stellar optical spectra,
Astrophys. J. Supple. S., 81, 865, https://doi.org/10.1086/191706,
1992. a, b
Sivanandam, S., Graham, J. R., Abraham, R., Tekatch, A., Steinbring, E., Ngan, W., Welch, D. L., and Law, N. M.: Characterizing near-infrared sky
brightness in the Canadian high arctic, Proc. SPIE, 8446,
612–643, https://doi.org/10.1117/12.926251, 2012. a
Smirnov, A. V., Zhuravleva, T. B., Segal-Rosenheimer, M., and Holben, B. N.:
Limitations of AERONET SDA product in presence of cirrus clouds, J.
Quant. Spectrosc. Ra., 206, 338–341,
https://doi.org/10.1016/J.JQSRT.2017.12.007, 2018. a
Steinbring, E., Millar-Blanchaer, M., Ngan, W., Murowinski, R., Leckie, B., and Carlberg, R.: Preliminary DIMM and MASS Nighttime Seeing Measurements at
PEARL in the Canadian High Arctic, Publ. Astron. Soc. Pac., 125, 866–877, https://doi.org/10.1086/671482, 2013. a
Stock, J.: The atmospheric extinction in photoelectric photometry, Vistas Astron., 11, 127–146, https://doi.org/10.1016/0083-6656(69)90008-7, 1969. a, b, c, d
Stone, R. C.: An Accurate Method for Computing Atmospheric Refraction,
Publ. Astron. Soc. Pac., 108, 1051,
https://doi.org/10.1086/133831, 1996. a
Stubbs, C. W. and Tonry, J. L.: Toward 1 % Photometry: End‐to‐End
Calibration of Astronomical Telescopes and Detectors, Astrophys. J., 646, 1436–1444, https://doi.org/10.1086/505138, 2006. a
Taha, G. and Box, G. P.: New method for inferring total ozone and aerosol
optical thickness from multispectral extinction measurements using eigenvalue
analysis, Geophys. Res. Lett., 26, 3085–3088,
https://doi.org/10.1029/1999GL010823, 1999. a
Tomasi, C. and Petkov, B. H.: Calculations of relative optical air masses for various aerosol types and minor gases in Arctic and Antarctic atmospheres, J. Geophys. Res.-Atmos., 119, 1363–1385,
https://doi.org/10.1002/2013JD020600, 2014. a
Tomasi, C., Vitale, V., and De Santis, L. V.: Relative optical mass
functions for air, water vapour, ozone and nitrogen dioxide in atmospheric
models presenting different latitudinal and seasonal conditions, Meteorol. Atmos. Phys., 65, 11–30, https://doi.org/10.1007/BF01030266, 1998. a
Tyler, G. A.: Bandwidth considerations for tracking through turbulence,
J. Opt. Soc. Am. A, 11, 358–367,
https://doi.org/10.1364/JOSAA.11.000358, 1994. a
Vestine, E. H.: The Geographic Incidence of Aurora and Magnetic Disturbance,
Northern Hemisphere, J. Geophys. Res., 49, 77–102,
https://doi.org/10.1029/TE049i002p00077, 1944. a
Voigt, S., Orphal, J., Bogumil, K., and Burrows, J.: The temperature
dependence (203–293 K) of the absorption cross sections of O3 in the
230–850 nm region measured by Fourier-transform spectroscopy, J.
Photoch. Photobio. A, 143, 1–9,
https://doi.org/10.1016/S1010-6030(01)00480-4, 2001. a
Volz, F. E.: Depth and Shape of the 0.94-µm Water Vapor Absorption Band for Clear and Cloudy Skies, Appl. Optics, 8, 2261–2264,
https://doi.org/10.1364/AO.8.002261, 1969. a
Wagner, T., von Friedeburg, C., Wenig, M., Otten, C., and Platt, U.:
UV-visible observations of atmospheric O4 absorptions using direct moonlight
and zenith-scattered sunlight for clear-sky and cloudy sky conditions,
J. Geophys. Res., 107, 4424, https://doi.org/10.1029/2001JD001026, 2002. a
Wang, T., Fetzer, E. J., Wong, S., Kahn, B. H., and Yue, Q.: Validation of
MODIS cloud mask and multilayer flag using CloudSat-CALIPSO cloud profiles
and a cross-reference of their cloud classifications, J. Geophys.
Res., 121, 11620–11635, https://doi.org/10.1002/2016JD025239, 2016. a
Wenger, M., Ochsenbein, F., Egret, D., Dubois, P., Bonnarel, F., Borde, S.,
Genova, F., Jasniewicz, G., Laloë, S., Lesteven, S., and Monier, R.:
The SIMBAD astronomical database, Astron. Astrophys. Sup., 143, 9–22, https://doi.org/10.1051/aas:2000332, 2000. a
Witze, A.: Earth's magnetic field is acting up and geologists don't know why, Nature, 565, 143–144, https://doi.org/10.1038/d41586-019-00007-1, 2019.
a
WMO: WMO/GAW Experts Workshop on a Global Surface-Based Network for Long Term Observations of Column Aerosol Optical Properties, Tech. rep., World
Meteorological Organization, Geneva, available at: https://library.wmo.int/index.php?lvl=notice_display&id=11094 (last access: 21 September 2021),
2005. a
WMO: WMO/GAW Aerosol Measurement Procedures, Guidelines and Recommendations, Tech. Rep. WMO No. 1177; GAW Report No. 227, World Meteorological Organization, available at: https://library.wmo.int/doc_num.php?explnum_id=3073 (last access: 21 September 2021), 2016. a
Xia, X. and Wang, M.: Commentary on “New method for inferring total ozone and aerosol optical thickness from multispectral extinction measurements using eigenvalue analysis” by G. Taha and G. P. Box, Geophys. Res. Lett.,
28, 1997–1998, https://doi.org/10.1029/2000GL012561, 2001. a
Young, A. T.: Observational Technique and Data Reduction, chap. 3, in: Methods in Experimental Physics, Elsevier, vol. 12, 123–192,
https://doi.org/10.1016/S0076-695X(08)60495-0, 1974. a, b, c, d
Young, A. T.: High-Precision Photometry, in: Automated Telescopes for
Photometry and Imaging, vol. 28, p. 73, ASP Conference Series,
available at: https://ui.adsabs.harvard.edu/abs/1992ASPC...28...73Y (last access: 21 September 2021), 1992. a
Young, A. T.: Air mass and refraction, Appl. Optics, 33, 1108–1110,
https://doi.org/10.1364/AO.33.001108, 1994. a
Young, A. T. and Irvine, W. M.: Multicolor photoelectric photometry of the
brighter planets. I. Program and Procedure, Astron. J., 72, 945,
https://doi.org/10.1086/110366, 1967. a
Zhao, G., Zhao, Y.-H., Chu, Y.-Q., Jing, Y.-P., and Deng, L.-C.: LAMOST
spectral survey – An overview, Res. Astron. Astrophys., 12, 723–734,
available at: http://www.raa-journal.org/raa/index.php/raa/article/view/1171 (last access: 21 September 2021),
2012. a
Zhao, G., Zhao, C., Kuang, Y., Bian, Y., Tao, J., Shen, C., and Yu, Y.: Calculating the aerosol asymmetry factor based on measurements from the humidified nephelometer system, Atmos. Chem. Phys., 18, 9049–9060, https://doi.org/10.5194/acp-18-9049-2018, 2018. a
Zimmer, P., McGraw, J., Zirzow, D., Cramer, C., Lykke, K., and Woodward IV,
J.: A Path to NIST Calibrated Stars over the Dome of the Sky, in: The
Science of Calibration, edited by: Deustua, S., Allam, S., Tucker, D., and
Smith, J., vol. 503 of Astronomical Society of the Pacific Conference
Series, p. 145, available at: http://aspbooks.org/custom/publications/paper/503-0145.html (last access: 21 September 2021),
2016. a
Short summary
Starphotometry seeks to provide accurate measures of nocturnal optical depth (OD). It is driven by a need to characterize aerosols and their radiative forcing effects during a very data-sparse period. A sub-0.01 OD error is required to adequately characterize key aerosol parameters. We found approaches for sufficiently mitigating errors to achieve the 0.01 standard. This renders starphotometry the equal of daytime techniques and opens the door to exploiting its distinct star-pointing advantages.
Starphotometry seeks to provide accurate measures of nocturnal optical depth (OD). It is driven...
