EGU25-4547, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-4547
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 29 Apr, 16:50–17:00 (CEST)
 
Room 1.85/86
Sensitivity of Warm Rain Rates to Lower PBL Structure as Observed by Synthetic Aperture Radar over the Subtropical Ocean
Ryan Eastman1, Justin Stopa2, Ralph Foster3, Doug Vandemark4, and Hauke Schulz5
Ryan Eastman et al.
  • 1University of Washington, Atmospheric and Climate Sciences, Seattle, United States of America (rmeast@atmos.washington.edu)
  • 2University of Hawaii, Dept of Ocean and Resources Engineering
  • 3University of Washington Applied Physics Laboratory
  • 4University of New Hampshire
  • 5Danish Meteorological Institute

Synthetic Aperture Radar (SAR) is capable of detecting wind and rain signatures at a 5-meter resolution on the ocean surface without interference from overlying cloud cover. Here, wind signatures represent the spatial distributions of capillary waves produced by gusts and lulls in the surface winds. These distinct wind signatures vary based on the 3-dimensional structure of the lower boundary layer and fall into two dominant categories: mesoscale convective (MC), and wind streaks (WS). MC boundary layers tend to be associated with gentler motions and lighter winds while WS are associated with stronger overturning “rolls” and heavier winds. SAR can detect rain columns as drops disturb the ocean surface and can also discern cold pools and atmospheric boundaries associated with precipitation. A machine learning routine has been developed to classify SAR images based on these signatures.

 

SAR images classified as MC, WS, or containing boundaries or rain columns are compared to a variety of satellite cloud data in order to independently verify the classification system, and to gain insight into whether these classified PBL states have an effect on cloud and precipitation processes. Randomly spaced and located SAR images taken only at sunrise and sunset during the year 2018 are linked to polar orbiting A-Train satellite observations. Observations are linked by using Lagrangian PBL trajectories, following the cloud-level winds forward and backward from the SAR image to the 1:30 and 13:30 A-Train observation times. This “brackets” the SAR image with satellite data observed 12-hours apart, or in the case of daytime-only data, 24-hours apart. Comparisons are made in four marine subtropical stratocumulus regions.

 

Results show that SAR-observed rain columns and cold pools are associated with higher rain rates as seen by AMSR/2 89 GHz rain rate estimates tuned by CloudSat. PBLs with wind streaks are associated with stronger rain rates and greater cloud liquid water path compared with mesoscale convective PBLs, even after controlling for wind speed. Further analysis shows that WS PBLs tend to be cloudier, shallower, and contain fewer cloud drops. This work highlights the importance of small-scale turbulent boundary layer processes in controlling cloud processes on sub-daily timescales, and motivates investment in future SAR observations over the ocean.

How to cite: Eastman, R., Stopa, J., Foster, R., Vandemark, D., and Schulz, H.: Sensitivity of Warm Rain Rates to Lower PBL Structure as Observed by Synthetic Aperture Radar over the Subtropical Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4547, https://doi.org/10.5194/egusphere-egu25-4547, 2025.