Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Abstract

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

How Does Land Cover and Its Heterogeneity Length Scales Affect the Formation of Summertime Shallow Cumulus Clouds in Observations From the US Southern Great Plains?

“…To detect ShCu, we follow Tian et al. (2021) and use the 5‐min reflectance data in the “red” visible channel from the GOES‐16 cloud and moisture imagery data product (Schmit et al., 2010; Wu & Schmit, 2019). In the SGP region, the spatial resolution of the data is about 650 m (Figure 1a).…”

“…Case selection also excludes large-scale weather systems, thus ShCu developments are strongly tied to land surface forcing and boundary layer processes. To detect ShCu, we follow Tian et al (2021) and use the 5-min reflectance data in the "red" visible channel from the GOES-16 cloud and moisture imagery data product (Schmit et al, 2010;Wu & Schmit, 2019). In the SGP region, the spatial resolution of the data is about 650 m (Figure 1a).…”

“…Using Geostationary Operational Environmental Satellite (GOES‐16) reflectance data, Tian et al. (2021) developed a method to detect ShCu around the SGP region (at a resolution of 650‐m every 5 min), which may help shed light on the heterogeneity effect on clouds when paired with high resolution land cover data (Boryan et al., 2011). In this study, we take advantage of the newly developed GOES‐16 ShCu data in Tian et al.…”

“…In this study, we take advantage of the newly developed GOES‐16 ShCu data in Tian et al. (2021) and zoom into a region in the vicinity of SGP with mixed land cover types (mainly forests and grasslands) to answer two questions: (a) Does the ShCu occurrence differentiate among land cover types at the SGP? (b) Does ShCu occurrence depend on the heterogeneity length scale of land cover?…”

“…Tao et al (2019Tao et al ( , 2021 showed that the observed low-level clouds at SGP strongly couple with the land surface properties and the late summer Cloud Fraction (CF) is larger in a region dominated by forest coverage than that dominated by grassland. Using Geostationary Operational Environmental Satellite (GOES-16) reflectance data, Tian et al (2021) developed a method to detect ShCu around the SGP region (at a resolution of 650-m every 5 min), which may help shed light on the heterogeneity effect on clouds when paired with high resolution land cover data (Boryan et al, 2011).…”