Abstract. High-frequency (HF) radar systems can provide periodic, two-dimensional, vector current estimates over an area approaching 1000 km •. As the use of these HF systems has gained wider acceptance, a number of attempts have been made to estimate the accuracy of such systems. However, comparisons of HF radar current estimates with in situ sensors are difficult to interpret since HF systems measure currents averaged over an area of-1 km 2 and to a depth of only -50 cm while in situ sensors measure currents at a point and somewhat greater depths (-1 to 10 m). Previous studies of the accuracy of HF radar technology have thus attributed the differences observed between HF radar and in situ sensors to an unknown combination of vertical shear, horizontal inhomogeneity, in situ instrument errors, and HF radar system errors. This study examines the accuracy of HF radar current measurements using data from the 1993 High Resolution Remote Sensing Experiment, conducted off Cape Hatteras, North Carolina. Data from four shipborne in situ current meters are compared with data from an Ocean Surface Current Radar (OSCR), a commercial current-measuring radar.We attempt to discern the predominant sources of error in these data by using multiple simultaneous measurements from different sensors and by examining the variation of observed current differences as a function of location. The results suggest an upper bound on the accuracy of the OSCR-derived radial currents of 7 to 8 cm/s.
Slope spectral density resolved in wave number and direction is an important statistical descriptor of water surface waves. Experimentalists have estimated this descriptor from optical wave imagery by assuming that light from the surface is modulated linearly by the component of wave slope aligned with the imaging azimuth. The level of error arising from this assumption of linearity depends on the optical conditions and can be severe. We have numerically explored this error when only reflected radiance is imaged by using a synthesized sea surface and a clear sky model to simulate sea surface imaging. Additionally, we have developed a method for identifying geometries which minimize nonlinearity. This paper describes our analytic models, our numerical techniques, and the character of our results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.