Horizontal Structure of Dynamical Instability at Marine Stratocumulus Cloud Top Revealed in Polarized Light
Abstract:Marine stratocumulus (Sc) layers cover vast regions and, due to their high opacities, they play a major role in the Earth's solar radiation budget. They also have remarkably flat upper boundaries due to strong gradients in relative humidity at the top of the boundary layer (BL). However, those very gradients are unstable at scales as small as meters depending on fluctuations of temperature and liquid water content, hence radiative cooling in the thermal IR. The ensuing turbulent mixing of moist and dry air at cloud top due to such small-scale dynamical processes is not benign. It controls the structure of the entire marine BL, hence the Sc life-cycle, hence large-scale subsidence, hence global circulation and, ultimately, climate. This physical connection across many orders of magnitude in scale makes the prognosis and microphysical parameterization of marine Sc particularly challenging for climate modelers. It also makes these clouds high-value targets for remote sensing, both space-based and airborne.
Airborne sensors can easily achieve the resolution required to image cloud-top instabilities but natural sunlight is so highly scattered that the finest spatial features are all but erased by the "radiative smoothing" process. However, we will show that JPL's Airborne Multi-angle Spectro-Polarimetric Imager (AirMSPI), which flies on NASA's ER-2 aircraft at 20 km altitude, reveals in near-backscattered polarized light the previously unseen horizontal structure of the marine Sc cloud top physics and dynamics at 10 m resolution across a 10 km swath. It appears as a complex network of meandering filaments.
Large-Eddy Simulation modeling of these oceanic clouds with bin microphysics and state-of-the-art polarized 3D radiative transfer have been harnessed to model AirMSPI observations of the first three Stokes vector components in the relevant observational geometry for a 2.5x2.5 km^2 region. Synthetic imagery obtained at JPL's High-Performance Computing facility shows good qualitative agreement with observations, which opens the path toward a pixel-scale retrieval of the key cloud properties using AirMSPI data.