Abstract
Abstract. Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.
Highlights
The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) was launched in 2015
Clearsky O2 band ratios depend on a number of factors such as surface elevation and Sun–view geometry that impact the total absorption air mass; these factors need to be accounted for
We use both the radiative transfer theory and model simulations to quantify the relationship between the O2 band ratios with surface elevation and zenith angles
Summary
The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) was launched in 2015. The current EPIC CM algorithm adopts a general threshold method, which uses two sets of spectral tests for each of the three scene types: ocean, land, and ice/snow (Yang et al, 2019). Over snow- and ice-covered regions, the O2 A- and B-band ratios are used for cloud detection since the contrast between surface and clouds is small in the visible and UV channels. The current work aims to improve EPIC cloud masking through a better understanding of the variability of the O2 band ratios under various clear and cloudy conditions over snow and ice surfaces. Radiative transfer model simulations and observed reflectance will be examined to derive dynamic thresholds for the O2 band ratios so that the new algorithm is applicable to all snow and ice surfaces, i.e., Antarctica, Greenland, snow in high latitude, and glaciers over high mountains.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
