Accurate remote sensing measurements of sea surface temperature (SST) are a necessity for weather and climate operational and research activities. Infrared radiometers yield SST to about 0.5 degC accuracy but cannot be used in cloudy areas. Passive microwave techniques are useful in cloudy areas, but are limited to an accuracy of about 1.5 to 2 degC by the relatively large variation of microwave emissivity with surface conditions, such as wind speed. To improve the accuracy of passive microwave estimates of SST, active microwave (radar) observations can be added to estimate emissivity more precisely. To assess this approach the authors performed preliminary active and passive measurements in an outdoor wind-wave tank during the summer of 1993. C-band (5.2 GHz) and X-band (9.4 GHz) radar measurements were combined with C-band radiometer observations of the water surface in a 4 m diameter circular pool. Air flow over the surface was produced by a bank of fans and environmental conditions were measured, including air and water surface temperature, water surface roughness, air flow velocity, etc. Preliminary results showed a strong correlation of the rise in both C- and X-band radar backscatter, C-band in particular, with the rise in radiometer brightness temperature as air flow speed was increased. These results suggest that active and passive microwave observations can be used together to produce more accurate estimates of SST and possibly other ocean surface parameters.< >
HF radar has become an increasingly important tool for mapping surface currents in the coastal ocean. However, the limited range, due to much higher propagation loss and smaller wave heights (relative to the saltwater ocean), has discouraged HF radar use over fresh water, Nevertheless, the potential usefulness of HF radar in measuring circulation patterns in freshwater lakes has stimulated pilot experiments to explore HF radar capabilities over fresh water. The Episodic Events Great Lakes Experiment (EEGLE), which studied the impact of intermittent strong wind events on the resuspension of pollutants from lake-bottom sediments, provided an excellent venue for a pilot experiment. A Multifrequency Coastal HF Radar (MCR) was deployed for 10 days at two sites on the shore of Lake Michigan near St. Joseph, MI. Similarly, a single-frequency CODAR SeaSonde instrument was deployed on the California shore of Lake Tahoe. These two experiments showed that when sufficiently strong surface winds (2 about 7 m/s) exist for an hour or more, a single HE radar can be effective in measuring the radial component of surface currents out to ranges of 10-15 km. We also show the effectiveness of using HF radar in concert with acoustic Doppler current profilers (ADCPs) for measuring a radial component of the current profile to depths as shallow as 50 cm and thus potentially extending the vertical coverage of an ADCP array.
"Summary form only given". It is well known that HF radars are capable of measuring wind direction by using the relative strength of the echoes from the approaching and receding ocean waves at the Bragg resonant wavelengths. Here we investigate the ability of our Multifrequency Coastal Radar (MCR) to measure wind speed as well as direction. In this study we use data collected over Monterey Bay, California in December of 2000. At that time the M1 buoy (deployed by Dr. Francisco Chavez at the Monterey Bay Aquarium Research Institute, MBARI) was in the radar's observational area, near the Bay mouth, and measured wind speed and direction. Two MCR's near Santa Cruz and Moss Landing, California operated at 4.8, 6.8, 13.4 and 21.8 MHz, measuring currents at effective depths of about 2.5, 1.8, 0.9 and 0.6 m respectively. Using the method of partial least squares we developed an algorithm for estimating the surface wind vector from multifrequency HF radar data. This method uses as inputs the relative echo strengths of the approaching and receding Bragg lines as well as the near surface currents estimated for the four effective depths mentioned above. Partial least squares is a predictive technique based on relationships estimated from a training data set within which both inputs and outputs are known. We use the M1 buoy winds as output 'truth' for our training set. Our work indicates that the method produces excellent results. The wind speed and direction are determined with biases of -0.7 m/s and -1/spl deg/, standard errors of prediction or 1.3 m/s and 30.5/spl deg/ and R2 values of 0.66 and 0.89 respectively for all wind speeds. For wind speeds above 5 m/s the performance is significantly better. An investigation of the weights in the partial least squares algorithm indicates that the relative echo strength in the Bragg lines, near surface currents and near surface current shear are important in determining the wind estimates. We show examples of wind field maps over Monterey Bay, California and comparisons with buoy measurements. We think that this method will find useful application in measuring the detailed structure of the wind field in coastal regions on a few kilometer size scale.
In large fresh water lakes in temperate regions, the spring transition from weak to strong stratification is characterized by the formation of a coastal thermal front. This transition is dominated by high gradients in temperature, nutrient and plankton fields. A combination of solar warming, boundary heat flux, coastal bathymetry and surface wind stress causes the frontal system to develop such that a surface convergence forms at the nearly vertical 4/spl deg/C isotherm (the temperature of maximum density). This isotherm propagates offshore as warming of the nearshore water increases and as storms provide a mechanism by which the two water bodies (warm stratified nearshore waters and cold isothermal offshore waters) mix. As part of the NSF Episodic Events Great Lakes Experiment (EEGLE), HF Radar observations were obtained during the development and progression of the vernal thermal bar in Southern Lake Michigan in April 1999. Two Multi-Frequency Coastal Radars (MCRs) were utilized to provide observations of near-surface current vectors and vertical current shear adjacent to the Lake Michigan shoreline near St. Joseph, Michigan. MCR measurements of nearsurface currents show evidence of theoretical vernal thermal front circulation supported by in-situ measurements of thermal and dynamic structure. A two-week study of surface dynamics in the vicinity of the thermal front is presented and compared with in-situ measurements.
Surface currents in the vicinity of Granite Canyon, California (36°25.9′N, 121°55.0′W), were measured hourly using HF-radar in 1990–1992. The 1990 data revealed the M2 and S2 semi-diurnal tidal constituents. These high frequency components were removed from 6-month records taken during part of the upwelling season of 1991 and 1992. Daily and weekly variations in current speed and direction were generally similar in 1991 and 1992 even though 1992 was an El Niño year. Correlation analysis revealed that in both years daily and weekly variation in currents were mostly explained by corresponding changes in the alongshore component of the wind stress, indicating the effects of coastal upwelling. Variation in sea surface temperatures adjacent to the coast were correlated with the currents generated by coastal upwelling in 1991, but not in 1992. These observations are consistent with the hypothesis that during an El Niño event the water is upwelled to the surface from above a depressed thermocline. In 1992, at Granite Canyon, normal coastal upwelling was superimposed upon the El Niño event of that year.
Abstract : The long term goals of this project are to apply the ground wave HF radar technique to the measurement of ocean and fresh water surface currents, near surface vertical current shears, winds and waves. By mapping these quantities with a spatial resolution of 1 to 3 km or better and a temporal resolution of 1 hour or better over areas of thousands of square km we anticipate widespread applications in marine science, military operations and commerce.
Remote sensing of ocean waves by synthetic aperture radar (SAR) has reached a stage where measurement of many gross wave characteristics, such as dominant wavelength and direction, is well established. A significant difficulty is that waves traveling nearly along the radar surface track direction are often not imaged. Although progress is being mode, remote sensing of significant waveheight and the directional waveheight spectrum is still not on a firm footing. Understanding the physics behind SAR imaging of ocean waves will help reduce systematic errors in the wave measurements and put SAR wave measurement technique on a solid basis. At present there are several candidate formulations for a SAR wave imaging theory. Hypotheses drawn from these candidates are now being tested to resolve contradictions and point the way to a reliable theory.
Abstract : The Innovative Coastal-Ocean Observing Network (ICON) is a partnership of government, academic, and industrial entities funded by the National Ocean Partnership Program (NOPP). Its goal is to bring together modern measurement technologies, to develop new technologies, and to integrate them within a data assimilating coastal ocean circulation model. The major components of the observing network include: (1) surface current maps from shore-based high frequency (HF) radar installations; (2) subsurface currents, temperature, salinity, and bio-optical properties plus surface meteorological properties from several deep-ocean moorings; (3) sea surface temperature and color from satellites; and (4) along-track temperature and temperature variances from two acoustic tomography slices through the region. The model performance is quite good at seasonal time scales, which is a validation of the one-way nesting because these variations are successfully tracked by the PWC regional-scale model. At higher frequencies, the model does not reproduce the observed level of variability. For the a long shore currents down to 150 meter depth, data assimilation resulted in greater correlation between modeled and observed currents.
Abstract : Our achievements during this research can be summarized under three headings as follows: (1) Investigations of the knowledge of ocean surface geometry required for accurate estimates of ocean surface, sigma; (2) Investigation of a new method for estimating sigma for the ocean; and (3) Comparison of model results (others, as well as ours) with a comprehensive compilation of observational data sets giving sigma for a wide variety of observational and air-sea environmental parameters.
A new spectrum model for the ocean surface is proposed. We determine the two unknown parameters in this spectrum by fitting it to radar observations. We find that this spectrum combined with two-scale scattering theory can predict much of the observed dependence of the radar cross section on radar frequency, polarization, angle of incidence, and wind velocity at incidence angles in the 0\deg-70\deg range. The spectrum model is combined with a model for swell to examine the effect of swell on the radar cross section. We find that the effect of swell is significant for low radar frequencies ( L band) and near normal incidence but can be nearly eliminated by using higher frequencies ( K_{u} band) and large angles of incidence ( \approx 50\deg ).
