Non-Lambertian snow surface reflection models for simulated top-of-the-atmosphere radiances in the NIR and SWIR wavelengths
2024
Mikkonen, Antti | Lindqvist, Hannakaisa | Peltoniemi, Jouni | Tamminen, Johanna | Maanmittauslaitos | National Land Survey of Finland | 0000-0002-4701-128X
Accurately modeling snow reflectance is one way to improve satellite observations in the high-latitude regions. Snow surfaces are known to be challenging for atmospheric retrievals in the short-wave infrared (SWIR) wavelength regime due to their low reflectance. For example, current algorithms for satellite-based remote sensing of atmospheric carbon dioxide (CO ) do not take into account the unique reflective properties of snow surfaces. In this paper, we present a measurement-based snow surface reflectance model in the near-infrared (NIR; 755–775 nm) and SWIR (1590–1620 nm, 2040–2080 nm) bands used in remote sensing of atmospheric CO . We study snow reflectance in detail using a novel atmospheric radiative transfer model (RTM) software and a measurement-based model for snow bi-directional reflectance distribution function (BRDF) to identify how the observations could be optimized in regards of observation geometry and wavelengths. The novel simulation software for NIR-SWIR atmospheric radiative transfer, Raysca, is presented and validated. Top-of-the-atmosphere radiance simulations show that forward-viewing geometries over snow-covered surfaces yield higher radiances than the traditional nadir-viewing geometries, which could indicate the preferability of forward-viewing observation modes in the retrieval of atmospheric CO2. Similarly, atmospheric observations in the 1.6 m CO2 absorption band might be preferable to the 2.0 m CO absorption band due to higher radiances in the 1.6 m band.
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