Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama
Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center; Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- National Science Foundation (NSF); USDOE; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC); USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Contributing Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Grant/Contract Number:
- AC05-76RL01830; AC52-07NA27344
- OSTI ID:
- 2481140
- Report Number(s):
- LLNL-JRNL-865075; PNNL-SA-198091; e2024JD041512
- Journal Information:
- Journal of Geophysical Research. Atmospheres, Journal Name: Journal of Geophysical Research. Atmospheres Journal Issue: 24 Vol. 129; ISSN 2169-897X
- Publisher:
- American Geophysical Union (AGU)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
The Largely Ignored but Important Role of Non‐Rooted, Submersed Vegetation and Small Waterbodies on Greenhouse Gas Emissions
Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site