Articles | Volume 15, issue 1
Atmos. Meas. Tech., 15, 117–129, 2022
https://doi.org/10.5194/amt-15-117-2022
Atmos. Meas. Tech., 15, 117–129, 2022
https://doi.org/10.5194/amt-15-117-2022
Research article
05 Jan 2022
Research article | 05 Jan 2022

New sampling strategy mitigates a solar-geometry-induced bias in sub-kilometre vapour scaling statistics derived from imaging spectroscopy

Mark T. Richardson et al.

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Cited articles

Arakawa, A., Jung, J.-H., and Wu, C.-M.: Toward unification of the multiscale modeling of the atmosphere, Atmos. Chem. Phys., 11, 3731–3742, https://doi.org/10.5194/acp-11-3731-2011, 2011. 
Bacmeister, J. T., Eckermann, S. D., Newman, P. A., Lait, L., Chan, K. R., Loewenstein, M., Proffitt, M. H., and Gary, B. L.: Stratospheric horizontal wavenumber spectra of winds, potential temperature, and atmospheric tracers observed by high-altitude aircraft, J. Geophys. Res.-Atmos., 101, 9441–9470, https://doi.org/10.1029/95JD03835, 1996. 
Bedka, K. M., Nehrir, A. R., Kavaya, M., Barton-Grimley, R., Beaubien, M., Carroll, B., Collins, J., Cooney, J., Emmitt, G. D., Greco, S., Kooi, S., Lee, T., Liu, Z., Rodier, S., and Skofronick-Jackson, G.: Airborne lidar observations of wind, water vapor, and aerosol profiles during the NASA Aeolus calibration and validation (Cal/Val) test flight campaign, Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, 2021. 
Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., and van den Bosch, J.: MODTRAN6: a major upgrade of the MODTRAN radiative transfer code, in: Proceedings Volume 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, edited by: Velez-Reyes, M. and Kruse, F. A., SPIE, Baltimore, MD, USA, 90880H, 2014. 
Berk, A., Conforti, P., and Hawes, F.: An accelerated line-by-line option for MODTRAN combining on-the-fly generation of line center absorption within 0.1 cm−1​​​​​​​ bins and pre-computed line tails, in: Proceedings Volume 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, edited by: Velez-Reyes, M. and Kruse, F. A., SPIE, Baltimore, MD, USA, 947217, 2015. 
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Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that smears 2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is towards or away from the Sun, so calculating across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.