No abstract

The influence of sea surface temperature (SST) on atmospheric processes over the open ocean has been well documented. However, atmospheric responses to SST in coastal waters are poorly understood. Oceanic stratification (and consequently, SST) in coastal waters largely depends on the fortnightly spring–neap tidal cycle, because of variations in vertical tidal mixing. Here we investigate how changes in SST during the fortnightly tidal cycle affect the lower-level atmosphere over the Seto Inland Sea, Japan. We use a combination of in situ measurements, satellite observations and a regional atmospheric model. We find that the SST in summer shows cool (warm) anomalies over most of the inland sea during spring (neap) tides. Additionally, surface air temperature is positively correlated with the SST as it varies during the fortnightly tidal cycle. Moreover, the fortnightly spring–neap cycle also influences the surface wind speed because the atmospheric boundary layer becomes stabilized or destabilized in response to the difference between air temperature and SST.

A novel observational technique to map surface ocean currents at high spatial resolution in narrow regions is developed. Low-altitude remote sensing using a digital camera suspended from a vessel-towed balloon is used to track trajectories of floating buoys deployed on the ocean. Surface-current velocities are thereafter computed by sequentially moving buoy locations on photo images converted into ground (Cartesian) coordinates. Field experiments were conducted in July and August 2013 using a balloon towed by a research vessel on the Seto Inland Sea. The image-derived currents were compared with those derived from buoy locations recorded by GPS receivers attached to each floating buoy. It was found that surface currents computed using GPS data contain unrealistic values arising from stochastic fluctuations in those data. However, the image-derived currents reproduced well convergent flows and a cyclonic eddy that accumulated foam and marine debris, as actually observed during the surveys. This performance is attributed to the fact that the image processing acts as a filter to remove erroneous buoy locations in computing surface currents. The estimated error was 4.1 cm s−1, sufficiently small to measure snapshots of surface coastal currents with magnitudes greater than several tens of centimeters per second.