NASA’s Surface Water Ocean Topography (SWOT) satellite, expected to launch in 2021, will measure sea level height variations on spatial scales down to a few kilometers. This mission will ultimately allow the ocean’s submesoscale (spatial scales from kilometers to a few 10’s of kilometers) variations to be observed from space.  AIRSWOT is the airborne calibration and validation instrument to support the planned SWOT mission, with a key objective to understand the spatial scales of ocean features that will potentially be resolved with SWOT. The AIRSWOT instrument utilizes across-track interferometry with Ka-band frequency (35 GHz) to obtain centimeter-level height maps of the ocean as well as land water surfaces. Recent AIRSWOT engineering flights were conducted over the Santa Barbara Channel, California, to obtain the first set of ocean data needed to test the instrument and evaluate the derived ocean surface topography observations. In support of these initial flights, a small team was enlisted to provide in situ sampling and aerial sea surface temperature (SST) maps of submesoscale ocean features in the Santa Barbara Channel. The team was composed of Jeroen Molemaker (UCLA), Carter Ohlmann (UCSB), and Ben Holt (JPL), who have developed a unique coordinated observational approach to measuring submesoscale ocean dynamics from field experiments in the Southern California Bight in support of a NASA-funded project targeting submesoscale flows.
The AIRSWOT field campaign consisted of in situ sampling and aerial imagery. In situ instruments included water-following drifters, surface salinity and temperature sensors, an acoustic Doppler current profiler (ADCP), and a conductivity-temperature-depth (CTD) sensor. The key aerial sensor was a near infrared (NIR) camera, which flew on a small plane chartered by UCLA. The ocean instruments were deployed using UCLA’s 28-foot inflatable boat, a comparatively small but high-speed craft specifically intended to access and sample submesoscale features including eddies and fronts that can evolve and move rapidly in time. The sampling approach involves first identifying submesoscale features with fine-resolution satellite and aircraft imagery, and then quickly deploying the UCLA boat and its instrumentation to the identified feature for rapid in-situ sampling. The aerial SST provides fine-resolution data over a region, 2-3 times per day, and utilizes onboard processing and air-to-boat data downlink to guide the UCLA boat to identified features.

The flexibility of the boat and ocean measurement capabilities provided a means to rapidly sample submesoscale features identified in the field under varying conditions, with the features having short temporal and small spatial scales. Useful measurements were also obtained over a fairly large region (40 km by 40 km) during a single day of operation.  The team is working towards a comprehensive view of the submesoscale structure through the synthesis of all data collected. The in situ data, along with the aerial and satellite SST will be valuable for interpreting AIRSWOT observations of sea surface height.

Dataset NameProcessing
Start/StopFormatSpatial ResolutionTemporal
GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)4 to PresentNETCDF-40.01 degrees (Latitude) x 0.01 degrees (Longitude)Hourly - < Daily