Examine downstream impacts of mesoscale sea surface temperature anomalies on trade cumulus clouds using satellite observations

Trade-wind cumuli play a key role in the earth’s radiative budget and are at the heart of the longstanding uncertainty in climate sensitivity estimates. Understanding the mesoscale spatial organization (20 to 2000 km) of trade cumuli is at the forefront of addressing this uncertainty. Recent studies have shown that trade cumulus cloudiness is locally modulated by the weak yet ubiquitous sea surface temperature (SST) spatial variation over O(10-100) km in the Northwest Tropical Atlantic trade wind region. However, the downstream evolution of local cloudiness in response to SST perturbations remains unclear. To investigate this question, we employ a Lagrangian framework where trade cumulus trajectories are estimated using ERA5 wind fields at 925 hPa. These Lagrangian cloud trajectories are initiated over the daily centroids of warm and cold mesoscale SST anomalies identified from the GOES-POES blended gridded SST analysis. Cloud properties from GOES-16 and cloud organization metrics are extracted and computed along the trajectories. Using data from the winter months of 2014 to 2020, we will show preliminary analyses quantifying the downstream imprints of mesoscale SST anomalies on cloud properties and cloud morphologies. The outcome of this study will help clarify the role of mesoscale air-sea interaction in trade cumulus cloud organization and their cloud radiative effect.