Frank M. Monaldo

Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements

As part of the Alaska synthetic aperture radar (SAR) Demonstration Project in 1999 and 2000, wide-swath RADARSAT SAR imagery has been acquired on a regular basis in the Gulf of Alaska and the Bering Sea. During 1998 and 1999, similar data were acquired off the East Coast of the United States as part of the StormWatch Project. The radar cross section measurements from these images were combined with wind direction estimates from the Navy Operational Global Atmospheric Prediction System model to produce high-resolution maps of the surface wind speed. For this study, 2862 SAR image frames were collected and examined. Averaged wind estimates from this data base have been systematically compared with corresponding wind speed estimates from buoy measurements and model predictions, and very good agreement has been found. The standard deviation between the buoy wind speed and the SAR estimates is 1.76 m/s. Details of the SAR wind extraction procedure are discussed, along with implications of the comparisons on the C-band polarization ratio.

On the Estimation of Wave Slope-and Height-Varnance Spectra from SAR Imagery

A procedure is described for using synthetic aperture radar (SAR) imagery to estimate two-dimensional ocean wave slope-and height-variance spectra. The logic underpinning the procedure is based both on the results of the numerical simulation of SAR wave imagery and analytic descriptions of the SAR imaging process. The procedure, when applied to SAR imagery of waves acquired during the recent Shuttle Imaging Radar Mission (SIR-B), is shown to produce spectra that agree with independent measures of both the two-dimensional slope-and height-variance spectra. The implications of these results for future SAR missions aimed at measuring ocean waves are considered.

A systematic comparison of QuikSCAT and SAR ocean surface wind speeds

We performed a systematic comparison of wind speed measurements from the SeaWinds QuikSCAT scatterometer and wind speeds computed from RADARSAT-1 synthetic aperture radar (SAR) normalized radar cross section measurements. These comparisons were made over in the Gulf of Alaska and extended over a two-year period, 2000 and 2001. The SAR wind speed estimates require a wind direction to initialize the retrieval. Here, we first used wind directions from the Navy Operational Global Atmospheric Prediction System (NOGAPS) model. For these retrievals, the standard deviation between the resulting SAR and QuikSCAT wind speed measurements was 1.78 m/s. When we used the QuikSCAT-measured wind directions to initialize the inversion, comparisons improve to a standard deviation of 1.36 m/s. We used these SAR-scatterometer comparisons to generate a new C-band horizontal polarization model function. With this new model function, the wind speed inversion improves to a standard deviation of 1.24 m/s with no mean bias. These results strongly suggest that SAR and QuikSCAT measurements can be combined to make better high-resolution wind measurements than either instrument could alone in coastal areas.

Remote Sensing Observation Used in Offshore Wind Energy

Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind turbines where meteorological masts do not enable observations across the rotor-plane, i.e., at 100 to 200 m above ground level. Light detection and ranging (LiDAR) and sound detection and ranging (SoDAR) offer capabilities to observe winds at high heights. Airborne synthetic aperture radar (SAR) used for ocean wind mapping provides the basis for detailed offshore wind farm wake studies and is highly useful for development of new wind retrieval algorithms from C-, L-, and X-band data. Satellite observations from SAR and scatterometer are used in offshore wind resource estimation. SAR has the advantage of covering the coastal zone where most offshore wind farms are located. The number of samples from scatterometer is relatively high and the scatterometer-based estimate on wind resources appears to agree well with coastal offshore meteorological observations in the North Sea. Finally, passive microwave ocean winds have been used to index the potential offshore wind power production, and the results compare well with observed power production (mainly land-based) covering nearly two decades for the Danish area.

Preliminary Evaluation of Sentinel-1A Wind Speed Retrievals

The accuracy of wind speed retrievals from synthetic aperture radars (SARs) is strongly dependent upon the accuracy of the normalized radar cross section measurement. Here, we make a preliminary assessment of wind speed retrievals from Sentinel-1A. In particular, we use Sentinel-1A SAR imagery to compute wind speed at 500-m resolution. These measurements are averaged to 25 km and compared with advanced scatterometers (ASCAT) wind speed measurements from the METOP-A and METOP-B satellites. Spatially coincident measurements separated by less than 2 h are shown to agree to better than 2 m/s in standard deviation for wind speeds less that 20 m/s. Particularly, good agreement is found for Sentinel-1A VV-polarization measurements, though both HH- and VV-measurements exceed the 2 m/s accuracy standard.

Using SAR Remote Sensing, Field Observations, and Models to Better Understand Coastal Flows in the Gulf of Alaska

Abstract The steeply rising coastal terrain of southeast Alaska can produce a wide variety of terrain-induced flows such as barrier jets, gap flows, and downslope wind storms. This study uses a combination of satellite remote sensing, field observations, and modeling to improve our understanding of the dynamics of these flows. After examining several thousand synthetic aperture radar (SAR) high-resolution wind speed images over the Gulf of Alaska, several subclasses of barrier jets were identified that do not fit the current conceptual model of barrier jet development. This conceptual model consists of an acceleration and turning of the ambient cross-barrier flow into the along-barrier direction when the ambient low-level flow is blocked by terrain; however, the SAR imagery showed many barrier jet cases with significant flow variability in the along-coast direction as well as evidence for the influence of cold, dry continental air exiting the gaps in coastal terrain. A subclass of jets has been observed w...

Improvement in the estimation of dominate wavenumber and direction from spaceborne SAR image spectra when corrected for ocean surface movement

Because a synthetic aperture radar (SAR) is a Doppler device, ocean surface movement can degrade a SAR ocean image. Ocean surface movement causes the redistribution of apparent radar cross section in a SAR image to neighboring image elements. It is demonstrated in this paper that this aspect of SAR imaging can be treated as a simple resolution loss in a linear system. Such an approach explains the falloff in response at high azimuth wavenumbers experienced in SAR image spectra. More importantly, this approach allows for a straightforward method to alleviate the problem of ocean surface motion. Correction of SAR image spectra using a linear systems approach results in SAR image spectra in which the locations in wavenumber-space of surface wave spectral peaks are more consistent with the estimated location of storm sources than are the locations of peaks from uncorrected spectra.

Combined estimates improve high‐resolution coastal wind mapping

The operational meteorological community and the numerical weather prediction community share a common need for high-resolution estimates of the near-surface wind field in data-sparse regions of the globe, such as the coastal zones of Alaska and the Pacific Northwest. Wind estimates over coastal waters using conventional multiple-antenna scatterometers or passive microwave sensors are difficult to obtain because the large footprint associated with these sensors results in significant contamination from land. Since synthetic aperture radar (SAR) can provide high-resolution imagery of the surface virtually up to the shoreline, “SAR scatterometry” represents a potentially significant new technique for measuring ocean-surface wind fields at resolutions more than an order of magnitude finer than is now possible with any other spaceborne technique.

Comparison of SIR-C SAR wavenumber spectra with WAM model predictions

During April and October of 1994, the Space Radar Laboratory (SRL) flew on the space shuttle Endeavour at the relatively low altitude of 215 km. Using horizontal polarization, C-band signal from the spaceborne imaging radar (SIR-C), an onboard processor, designed and fabricated by the Johns Hopkins University Applied Physics Laboratory, formed synthetic aperture radar (SAR) images and computed over 100,000 corresponding image spectra. The low altitude, small look angle (23°–25°) and the use of horizontal polarization minimized both the loss of azimuth resolution caused by ocean surface motion and the relative contribution of the hydrodynamic component of the modulation transfer function. As a result, the SIR-C SAR was able to image azimuth-traveling waves with minimal distortion. After using linear inversions to convert image spectra to wave height-variance spectra, the distributions of wavenumber and propagation direction from the processor-derived spectra were consistent with wave model (WAM) predictions. Although the SAR wave height-variance spectra underestimated significant wave height (SWH) at the higher SWHs, this error is compensated for by a simple linear correction. We collected 57 pairs of crossover spectra where the ground track pairs were nearly orthogonal. The crossovers were separated by 6 hours. Crossover comparisons show that the retrieved spectral parameters are independent of wave propagation direction. At this altitude and configuration, the SAR range and azimuth responses are nearly equal. The real-time processing of spaceborne SAR data to produce accurate estimates of wavenumber, propagation direction, and SWH is clearly feasible with the orbital and instrument geometry of SIR-C.

Ocean Wind Speed Climatology from Spaceborne SAR Imagery

Spaceborne synthetic aperture radar (SAR) imagery can make high-resolution (≤500 m) ocean wind speed measurements. The authors anticipate reprocessing the full decade and a half of Radarsat-1 SAR imagery and generating a SAR wind speed archive. These data will be of use for studies of coastal atmospheric phenomena and assessment of offshore wind power potential. To illustrate the potential of this latter application, they review the ability of SARs to measure wind speed, discuss an approach for using SARs to create wind speed climatologies useful for wind power resource assessments, and consider issues concerning the applicably of such data for these assessments.