Karen S. Friedman

Observation of hurricane-generated ocean swell refraction at the Gulf Stream north wall with the RADARSAT-1 synthetic aperture radar

We analyze the refraction of long oceanic waves at the Gulf Streams north wall off the Florida coast as observed in imagery obtained from the RADARSAT-1 synthetic aperture radar (SAR) during the passage of Hurricane Bonnie on August 25, 1998. The wave spectra are derived from RADARSAT-1 SAR images from both inside and outside the Gulf Stream. From the image spectra, we can determine both the long waves dominant wavelength and its propagation direction with 180/spl deg/ ambiguity. We find that the wavelength of hurricane-generated ocean waves can exceed 200 m. The calculated dominant wavelength from the SAR image spectra agree very well with in situ measurements made by National Oceanic and Atmospheric Administration National Data Buoy Center buoys. Since the waves mainly propagate toward the continental shelf from the open ocean, we can eliminate the wave propagation ambiguity. We also discuss the velocity-bunching mechanism. We find that in this very long wave case, the RADARSAT-1 SAR wave spectra should not be appreciably affected by the azimuth falloff, and we find that the ocean swell measurements can be considered reliable. We observe that the oceanic long waves change their propagation directions as they leave the Gulf Stream current. A wave-current interaction model is used to simulate the wave refraction at the Gulf Stream boundary. In addition, the wave shoaling effect is discussed. We find that wave refraction is the dominant mechanism at the Gulf Stream boundary for these very long ocean swells, while wave reflection is not a dominant factor. We extract 256-by-256 pixel full-resolution subimages from the SAR image on both sides of the Gulf Stream boundary, and then derive the wave spectra. The SAR-observed swell refraction angles at the Gulf Stream north wall agree reasonably well with those calculated by the wave-current interaction model.

Synthetic Aperture Radar as a Tool for Investigating Polar Mesoscale Cyclones

Abstract Polar mesoscale cyclones are intense vortices that form in cold, marine air masses poleward of major jet streams and frontal zones. Synthetic aperture radar (SAR) should be considered as a potential tool for the study of polar mesoscale cyclones because of its ability to remotely sense, at least qualitatively, the high-resolution near-surface wind field independent of daylight and atmospheric conditions. Four case studies demonstrating this ability are presented. SAR imagery from the Canadian Space Agency’s RADARSAT are compared to corresponding infrared imagery, surface analyses, and upper-air analyses. In three of the four case studies, it is argued that the addition of SAR imagery to the process of generating a manual surface analysis would have led to a better product. Moreover, it is demonstrated that the SAR imagery reveals a host of marine-meteorological phenomena in the vicinity of the polar mesoscale cyclones including atmospheric gravity waves, roll vortices, and cellular convection. Be...

GhostNet marine debris survey in the Gulf of Alaska – Satellite guidance and aircraft observations

Marine debris, particularly debris that is composed of lost or abandoned fishing gear, is recognized as a serious threat to marine life, vessels, and coral reefs. The goal of the GhostNet project is the detection of derelict nets at sea through the use of weather and ocean models, drifting buoys and satellite imagery to locate convergent areas where nets are likely to collect, followed by airborne surveys with trained observers and remote sensing instruments to spot individual derelict nets. These components of GhostNet were first tested together in the field during a 14-day marine debris survey of the Gulf of Alaska in July and August 2003. Model, buoy, and satellite data were used in flight planning. A manned aircraft survey with visible and IR cameras and a LIDAR instrument located debris in the targeted locations, including 102 individual pieces of debris of anthropogenic or terrestrial origin.

Using Spaceborne Synthetic Aperture Radar to Improve Marine Surface Analyses

Abstract The ever-changing weather and lack of in situ data in the Bering Sea warrants experimentation with new meteorological observing systems for this region. Spaceborne synthetic aperture radar (SAR) is well suited for observing the sea surface footprints of marine meteorological phenomena because its radiation is sensitive to centimeter-scale sea surface roughness, regardless of the time of day or cloud conditions. The near-surface wind field generates this sea surface roughness. Therefore, the sea surface footprints of meteorological phenomena are often revealed by SAR imagery when the main modulator of sea surface roughness is the wind. These attributes, in addition to the relatively high resolution of SAR products, make this instrument an excellent candidate for filling the meteorological observing needs over the Bering Sea. This study demonstrates the potential usefulness of SAR for observing Bering Sea meteorology by focusing on its ability to image the sea surface footprints of polar mesoscale ...

Validation of a CFAR vessel detection algorithm using known vessel locations

The National Oeanic and Atmospheric Administration (NOAA)/National Environmental Satellite, Data, And Information Service (NESDIS) is in the second year of a two-year demonstration of Synthetic Aperture Radar (SAR) derived products called the Alaska SAR Demonstration (AKDEMO). This demonstration provides near real-time SAR data and derived products, including wind images and vectors, hard target locations, along with ancillary data, to specific users in the government community. One of the derived products are vessel positions obtained from a constant false alarm rate (CFAR) vessel detection algorithm developed by Veridian ERIM. This algorithm has been tested and validated to maximize the number of ships found while minimizing the number or false alarms on one SAR image of the Red King Crab fishery in Bristol Bay on October 18, 1999. This resulted in using a detection statistic threshold of about 5.5, depending on image resolution used. Until now, this validation has been done with only general knowledge of fishing fleet size and location, but no in situ vessel information. This paper presents the results of a validation of the SAR vessel detection algorithm using observer reported vessel positions along with information on vessel size and local wind speed.

GoMEx-an experimental GIS system for the Gulf of Mexico region using SAR and additional satellite and ancillary data

The National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) is in the third year of the Alaska SAR Demonstration (AKDEMO), an applications project using RADARSAT-1 synthetic aperture radar (SAR) and derived products. The success of this demonstration in providing near real-time SAR data, derived products, and other ancillary data to federal and state agencies, has motivated the development of a similar experimental multi-sensor data fusion system for the Gulf of Mexico and Caribbean region called GoMEx. Unlike the AKDEMO system which focused on near-real time data, this project will begin by using archived data from diverse remote sensing sensors such as RADARSAT-1 SAR, GOES imagers, SeaWiFS, MODIS, AVHRR, scatterometers, as well as data from moored buoy measurements and numerical weather models to study issues and phenomena unique to the region. Other agencies that will contribute and use this system include the National Ocean Service (NOS), Louisiana State University, National Marine Fisheries Service and the University of Maryland. Sample applications of this system are presented including detection of algal blooms, coral reefs off of Belize, oil slicks and rigs off of Louisiana, and fishery applications.

Synthetic aperture radar imaging of axial convergence fronts in Cook Inlet, Alaska

Axial fronts of tidal currents are observed in Cook Inlet, AK, on a RADARSAT-1 standard mode synthetic aperture radar (SAR) image taken at 16:31:47 coordinated universal time (UTC) on July 12, 2002. The longest front appears as a 100-km-long quasi-linear bright feature in the SAR image. This front is characterized by an increase in the normalized radar cross section (NRCS) of 7 dB in the C-band horizontal polarization (C-HH) RADARSAT-1 SAR image. Two other smaller fronts exist in the middle of the inlet. The NRCS modulations appear to be less, at about 5 dB. A diagnostic Cook Inlet tidal model is developed to calculate the current velocity fields of the inlet and to demonstrate that the variation in bottom friction caused by the bathymetry distribution generates axial convergence at different tidal stages. The model, using the actual bathymetry, is driven by predicted tides from six tidal stations along the inlet coast. The model results show that the tidal current flowed into the inlet at the time the SAR image was obtained. Tidal current along two transects in the inlet is extracted to show that there is a significant cross-channel convergence of the along-channel velocity component, with a magnitude of 4 to 6 times 10-4 s-1 near the observed front positions. In general, a higher velocity convergence from the model corresponds to higher NRCS return areas in this SAR image.

The sea surface imprint of island lee waves as observed by RADARSAT synthetic aperture radar

As stratified air flows over a mountain or an island, it often sets up large standing atmospheric gravity waves called atmospheric lee waves. This type of wave can carry aircraft upward or downward, sometimes causing serious safety problems. There are two types of lee wave patterns: (1) the transverse wave type where the wave crests are nearly perpendicular to the wind direction; and (2) the diverging wave type where the wave crests are orientated outwards from the center of the wake. The atmospheric lee waves are often associated with cloud patterns, which can be imaged with various visible remote sensors. Since the atmospheric lee waves modulate the sea surface wind field, and thus modulate the sea surface roughness, these waves can also be observed over the open ocean in SAR images. In this study, we analyze the diverging atmospheric lee wave pattern found in two RADARSAT SAR images. The first one is near Kodiak Island in the Gulf of Alaska taken on June 27, 1997. The second one is near St. Lawrence Island in the Bering Sea taken on August 4, 1997. There are two groups of atmospheric lee waves behind two islands south of Kodiak Island and four groups of diverging wave patterns imaged by the RADARSAT SAR on the lee side of the four major mountains of St. Lawrence Island. We consider the island mountains as point sources that generate atmospheric lee waves.

Validation of an automatic vessel detection algorithm using SAR data and known vessel fleet distributions

The National Oceanic and Atmospheric Administration (NOAA) National Environmental, Satellite, Data, and Information Service (NESDIS) is conducting a two-year demonstration of synthetic aperture radar (SAR) derived products called the Alaska SAR Demonstration (AKDEMO). This demonstration provides near real-time SAR data and derived products to the U.S. government community working in the waters near Alaska. One of these products is a constant false alarm rate (CFAR) vessel detection algorithm developed by Veridian ERIM International. This algorithm derives vessel positions from SAR data and delivers them within the context of the AKDEMO to users such as the U.S. Coast Guard, National Marine Fisheries Service, and the Alaska Department of Fish & Game (ADF&G), for management and regulatory purposes. The ScanSAR Wide B mode on RADARSAT-1 has an image swath width of 480 km, which covers a much larger area than is practical from ship, aircraft, and helicopter platforms. During the AKDEMO, SAR swaths are taken up to twice a day in both the Bering Sea and the Gulf of Alaska. During events such as fishery openings, extra data are also collected. A validation of the CFAR algorithm is presented using RADARSAT-1 SAR data along with ship fleet locations and sizes collected by the ADF&G at times nearly coincident with the SAR data.

Mesoscale oceanic and atmospheric feature detection through fusion of RADARSAT SAR with GOES/Imager data

Synthetic aperture radar (SAR) data from the Canadian RADARSAT satellite, along with infrared and visible data from operational weather satellites, is being collected over the ocean off the U.S. East, Gulf of Mexico, Gulf of Alaska, and Bering Sea coasts. Mesoscale features observed in the SAR data are identified using coincident Geostationary Operational Environment Satellite (GOES) data to decide whether the signature is atmospheric or oceanic in origin. Combining the two data sources allows information in the marine atmospheric boundary layer (MABL) to be observed. This technique of feature detection using multiple data sets is referred to as data fusion. This paper focuses on a single storm event that is imaged by RADARSAT SAR in the Bering Sea on February 5, 1998 at 06:00 UTM. From the fusion of SAR and GOES data, frontal boundaries can be deciphered.