C.C. Wackerman

Wind vector retrieval using ERS-1 synthetic aperture radar imagery

An automated algorithm intended for operational use is developed and tested for estimating wind speed and direction using ERS-1 SAR imagery. The wind direction comes from the orientation of low frequency, linear signatures in the SAR imagery that the authors believe are manifestations of roll vortices within the planetary boundary layer. The wind direction thus has inherently a 180/spl deg/ ambiguity since only a single SAR image is used. Wind speed is estimated by using a new algorithm that utilizes both the estimated wind direction and /spl sigma//sub 0/ values to invert radar cross section models. The authors show that: 1) on average the direction of the roll vortices signatures is approximately 11/spl deg/ to the right of the surface wind direction and can be used to estimate the surface wind direction to within /spl plusmn/19/spl deg/ and 2) utilizing these estimated wind directions from the SAR imagery subsequently improves wind speed estimation, generating errors of approximately /spl plusmn/1.2 m/s, for ERS-1 SAR data collected during the Norwegian Continental Shelf Experiment in 1991.

Coastal ocean fronts and eddies imaged with ERS 1 synthetic aperture radar

ERS 1 C band synthetic aperture radar (SAR) data were collected during the Norwegian Continental Shelf Experiment (NORCSEX) both in November 1991 during the ERS 1 commissioning phase and at different seasons in 1992 and 1993. Characteristic SAR image expressions are observed in relation to perturbation of the surface current- short wave interaction across the Norwegian Coastal Current front for winds less than 10-12 rn s -1. In situ measurements document the existence of alternating zones of convergence and divergence coexisting with a strong near-surface current shear of nearly 4f (where f is the Coriolis parameter) across a distance of a few kilometers. Under calm to moderate winds, i.e., 4-7 rn s -1, characteristic expressions of upper ocean circulation features also include the manifestation of eddies through the presence of surface film which damps the Bragg waves. Comparison of a near-coincident National Oceanic and Atmospheric Administration advanced very high resolution radiometer image and an ERS 1 SAR image supports the interpretation that surface current fronts are imaged by SAR. In combination with an SAR image simulation model, the relative quantitative importance of shear, convergence, and divergence along the front is examined. Although the model formulation is simple and the absolute magnitude of the perturbations is uncertain, the study shows that the SAR images can sometimes be used to interpret frontal dynamics, including growth and decay of meanders.

Validating a scatterometer wind algorithm for ERS-1 SAR

The ocean surface wind field is observed from space operationally using scatterometry. The European Space Agencys (ESAs) ERS-1 satellite scatterometer routinely produces a wind product that is assimilated into forecast models. Scatterometry cannot give accurate wind estimates close to land, however, because the field of view of a spaceborne scatterometer is on the order of 50 km. Side lobe contamination, due to the large contrast in backscatter between land and water, compounds the problem. Synthetic aperture radar (SAR) can provide wind speed and direction estimates on a finer scale, so that high-resolution wind fields can be constructed near shore. An algorithm has been developed that uses the spectral expression of wind in SAR imagery to estimate wind direction and calibrated backscatter to estimate wind strength. Three versions, based on C-band scatterometer algorithms, are evaluated for accuracy in potential operational use. Algorithm estimates are compared with wind measurements from buoys in the Gulf of Alaska, Bering Strait, and off the Pacific Northwest coast by using a data set of 61 near-coincident buoy and ERS-1 SAR observations. Representative figures for the accuracy of the algorithm are /spl plusmn/2 m/s for wind speed and /spl plusmn/37/spl deg/ for wind direction at a 25-km spatial resolution.

The modified beta density function as a model for synthetic aperture radar clutter statistics

The authors show that the modified beta distribution function is an adequate model for the underlying distribution function of the random variable used to model synthetic-aperture radar (SAR) image data. The model represents a range of SAR returns from different sea ice types by using a simple change in its parameter. The ability is explained by describing the distribution functions in, width. modified skewness space where the modified beta function covers a region while the other, more common, distribution functions cover only a curve. A procedure for comparing simple distribution functions with analytical functions specifically for digitized SAR data is presented. >

Tropical Cyclone Winds Retrieved From C-Band Cross-Polarized Synthetic Aperture Radar

This paper presents a geophysical model function (GMF) that has been developed to describe the relation of the ocean surface wind with the normalized radar cross section (NRCS) at C-band cross polarization (cross-pol). Synthetic aperture radar (SAR) images have been simultaneously collected at copolarization (co-pol) and cross-pol at moderate to high wind speeds. Using the SAR co-pol retrieved wind fields and an uncertainty estimate of the retrieved wind speeds, the cross-pol dependencies of the NRCS are investigated with respect to wind, incidence angle, and polarization pairs. For wind speeds above 10 m/s, there is a significant dependence of the NRCS on wind speed. However, the SAR cross-pol data are also significantly affected by the noise floor and crosstalk between the channels. Estimates of the noise floor are determined and removed from the NRCS. Three GMFs are developed: the first is for transmission at horizontal (H) polarization and the second at vertical (V) polarization. A third GMF accounts for wind direction dependence. Validation of the GMFs is conducted by comparison with collocated Stepped Frequency Microwave Radiometer (SFMR) data. The resulting bias of -0.7 m/s and standard deviation of 3.7 m/s demonstrate the excellent performance for these GMFs for wind speed retrieval between 10 and 35 m/s. Furthermore, comparisons show that SAR cross-pol retrieved wind speeds are of similar quality as those of SFMR and are significantly better in the moderate to high wind speed regime than SAR co-pol retrieved winds.

Detection of surface current features with ERS-1 SAR

ERS-1 SAR image expressions of mesoscale coastal ocean circulation features are examined. The dominating geophysical quantities and processes that are participating in the formation of the image expression are discussed. An attempt to characterise dynamics of the current features is carried out employing a SAR simulation model. Preliminary results suggest that systematic combination of simulation models and SAR images can lead to better quantitative interpretation of SAR images.<<ETX>>

Simulation of SAR images of submesoscale ocean phenomena

Patterns are observed on radar images of the ocean surface on scales of 10-1000 meters which are related to phenomena such as internal waves, current or temperature fronts, and tidal flow over shallow bottom topography. These features are caused by a complex set of interactions between surface waves, air flow above the surface, current fields at and below the surface, and the electromagnetic waves which are used to form the images. Simulation models provide a means of synthesizing our present knowledge of these interactions in order to make predictions that can be tested by comparison with actual radar images. The authors summarize the status of SAR simulation models, present comparisons between simulated and actual images for several types of ocean surface features, and make some inferences about the present state of knowledge of the interactions incorporated in these models. In general, the present models are capable of predicting or explaining features observed with radar wavelengths larger than about 10 cm (e.g. L-band) but do not perform well at shorter wavelengths. Uncertainties in wave growth and dissipation, as well as increasing importance of strong nonlinear effects at short wavelengths, are thought to contribute to this breakdown.<<ETX>>

Marginal ice zone signatures observed by the ERS-1 SAR during SIZEX '92

Coincident ship based X-, C-, and L-band scatterometer data and measurements of physical ice and snow properties were collected during ERS-1 synthetic aperture radar (SAR) overflights in the Barents Sea in March of 1992. One aspect of this Seasonal Ice Zone Experiment (SIZEX) concentrated on the marginal ice zone (MIZ), where a variety of sea ice types and open ocean conditions were encountered. A specific objective of SIZEX was to determine which MIZ ice types can be clearly discerned using ERS-1 SAR C-band imagery. First- and second-order statistics were generated to characterize ERS-1 ice signature. Comparing these statistics for each ice type, reveals that many of the ice types observed in the MIZ have comparable tones, as indicated by their means (i.e., multiyear and pancakes). However, the use of the SAR image texture may be used in conjunction with the tonal properties to successfully discern the various ice types and open water (all wind regimes) found in the MIZ.<<ETX>>

Geophysical Information On The Winter Marginal Ice Zone Obtained From Cearex Sar Data

During the 1989 Coordinated Eastern Arctic Experiment (CEAREX) a total of sixteen synthetic aperture r adar (SAR) data collections were flown. Each mission covered approximately a 100 x 200 km area surrounding the ice strengthened vessel M/S POLARBJORN. SAR viewing geometries, frequencies, and polarizations varied based on the objectives of each individual mission. On-board processors enabled personnel stationed at Svalbard and Andoya for flight coordination to review the real-time data. Observations and interpretations including ice edge, type, concentration and floe size made from this imagery were used to plan successive SAR missions and were transmitted to POLARBJORN enabling scientists on-board to select areas of special interest for intensive study and sea truthi ng .

Use of satellite remote sensing to monitor lead dynamics

How much radiation is reflected or absorbed at the Earths surface is important for use in global climate models. The Earths energy balance is determined by the spectral properties of the atmosphere and terrain surfaces. In the polar ocean, this balance is determined by the presence of open water, the thickness of sea ice, and the thickness of snow cover. Snow-covered ice causes much of the incident energy to be reflected; while, in the case of open water, a significant proportion is absorbed. Detection of and monitoring the openings in the polar pack during winter is important in assessing the coverage of open water and the production of new ice. This information is required in the study of the air-ice-ocean processes and the determination of an important contributor to ocean-atmosphere heat flux and ice-ocean brine flux. In this paper, the authors utilize multisensor observations to assess changes during the formation and closure of lead systems.