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Stratocumulus clouds are common in the tropical and subtropical marine boundary layer, and understanding these clouds is important due to their significant impact on the earth's radiation budget. Observations show that the marine boundary layer contains complex, but poorly understood processes, which, from time to time, result in the observable self-organization of cloud structures at scales ranging from a few to a few thousand kilometers. Such shallow convective cloud features, typically observed as hexagonal cells, are known generally as mesoscale cellular convection (MCC). Actinoform clouds are rarer, but visually more striking forms of MCC, which possess a radial structure.
Because mesoscale cloud features are typically too large to be observed from the ground, observations of hexagonal cells historically date only to the beginning of satellite meteorology. Examples of actinoform clouds were shown in the venerable “Picture of the Month” series in Monthly Weather Review in the early 1960s, but these clouds were generally forgotten as research focused on hexagonal cells.
Recent high-resolution satellite images have, in a sense, “rediscovered” actinoform clouds, and they appear to be much more prevalent than had been previously suspected. We show a number of examples of actinoform clouds from a variety of locations worldwide. In addition, we have conducted a detailed case study of an actinoform cloud system using data from the Multiangle Imaging SpectroRadiometer (MISR) and the Geostationary Operational Environmental Satellite (GOES), including analysis of cloud heights, radiative properties, and the time-evolution of the cloud system. We also examine earlier theories regarding actinoform clouds in light of the new satellite data.
Stratocumulus clouds are common in the tropical and subtropical marine boundary layer, and understanding these clouds is important due to their significant impact on the earth's radiation budget. Observations show that the marine boundary layer contains complex, but poorly understood processes, which, from time to time, result in the observable self-organization of cloud structures at scales ranging from a few to a few thousand kilometers. Such shallow convective cloud features, typically observed as hexagonal cells, are known generally as mesoscale cellular convection (MCC). Actinoform clouds are rarer, but visually more striking forms of MCC, which possess a radial structure.
Because mesoscale cloud features are typically too large to be observed from the ground, observations of hexagonal cells historically date only to the beginning of satellite meteorology. Examples of actinoform clouds were shown in the venerable “Picture of the Month” series in Monthly Weather Review in the early 1960s, but these clouds were generally forgotten as research focused on hexagonal cells.
Recent high-resolution satellite images have, in a sense, “rediscovered” actinoform clouds, and they appear to be much more prevalent than had been previously suspected. We show a number of examples of actinoform clouds from a variety of locations worldwide. In addition, we have conducted a detailed case study of an actinoform cloud system using data from the Multiangle Imaging SpectroRadiometer (MISR) and the Geostationary Operational Environmental Satellite (GOES), including analysis of cloud heights, radiative properties, and the time-evolution of the cloud system. We also examine earlier theories regarding actinoform clouds in light of the new satellite data.
Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus CloudsAbstract
Passive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.
Abstract
Passive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.
