SAR image statistics related to atmospheric drag over sea ice

The possibility of using synthetic aperture radar (SAR) data to distinguish sea-ice regions with different atmospheric drag is explored. Both the amplitude of the radar return and statistics derived from SAR image data are examined. Roughness statistics data from several pack-ice areas are used in a backscatter model to predict the return from surfaces with measured drag coefficients. The results suggest that the scattering coefficient for typical radar wavelengths is insensitive to the roughness elements responsible for the observed drag coefficient variations over pack ice free of major ridges. For marginal ice zones, where ice concentration and floe deformation contribute to atmospheric drag, a simple model for the atmospheric boundary layer is used to provide qualitative relationships between drag coefficient and regional ice properties (ice concentration, floe size distribution, floe edge density) derivable from SAR data. Simple algorithms to produce maps of ice concentration and edge density are outlined and applied to 23.5-cm SAR digital image data     

ERS-1 SAR images of atmospheric gravity waves

ERS-1 synthetic aperture radar (SAR) images of atmospheric gravity waves over the ocean are discussed. Several case studies are presented in detail. It is shown that the well-organized long wavelength (1 to 10 km) wave phenomena which often are seen in SAR images over the ocean may be atmospheric gravity waves. The waves appear in the SAR images because they modulate the surface wind speed which in turn modulates the surface roughness and the radar cross section. The wavelength may be measured directly from the SAR image, and the mean wind speed and wind speed modulation near the ocean surface may be estimated from the observed radar cross section modulation using a wind retrieval model. The atmospheric gravity waves usually were generated by the approach or passing of a meteorological front. Atmospheric soundings and a two-layer model for the lower troposphere indicate that, in general, the observed atmospheric wave phenomena could have been supported by accompanying temperature inversion layers and wind shears     

Evaluation of JERS-1 SAR images from a coastal wind retrieval point of view

Wind retrieval from Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) using an L-band model function in coastal regions is evaluated. It is known that JERS-1 SAR has excessive ambiguities. This paper also gives a quantitative evaluation of excessive ambiguities in coastal scenes of JERS-1 SAR. First, focusing on the cases where wind blows from the shore in Sagami Bay, we investigate phenomena of wind speed increase with offshore distance using European Remote sensing Satellite-1 (ERS-1) SAR-derived wind speeds. The relation between wind speed and offshore distance is well formulated, which indicates the transition of the atmospheric boundary layer from land to sea surface. Wind speeds derived from JERS-1 SAR should be overestimated due to the excessive ambiguity. Then, for observation time of each JERS-1 SAR capturing the cases that wind blows from the shore in Sagami Bay, the expected wind speed growth profile is derived from the wind speed growth formula and an in situ wind observation of Hiratsuka Experiment Station. We convert the wind-speed profile into the sigma-0 profile by an L-band model function. Finally, the profiles of JERS-1 SAR-observed and the estimated sigma-0 are compared, and the excessive ambiguity is estimated as the difference between them. As a result, the dynamic range of first azimuth ambiguity is as large as that of the wind-relating signal from the ocean surface. Moreover, higher order azimuth ambiguities and range ambiguity also may have a significant impact on near-shore wind retrieval.     

Analysis of surface roughness and morphology of first-year sea ice melt ponds: implications for microwave scattering

Variations in wind forcing over summer first-year sea ice (FYI) melt ponds occur at hourly to weekly scales and are a significant contributor to microwave backscatter (/spl sigma//spl deg/) variability observed from spaceborne synthetic aperture radar (SAR) platforms (e.g., ENVISAT-ASAR and RADARSAT-1). This variability impairs our ability to use SAR to derive information on summer sea ice thermodynamic state and energy balance parameters such as albedo and melt pond fraction. The surface roughness contribution of FYI melt ponds in the Canadian Arctic Archipelago to like-polarized, C-band /spl sigma//spl deg/ estimates is analyzed through a spectral and statistical analysis of surface wave height profiles for varying wind speeds, upwind fetch lengths, and melt pond depths. A unique derivation of melt pond surface wave height spectra is presented based on digital video of melt pond surface wave trains. Significant scale surface roughness was observed even at wind speeds of 3 m/spl middot/s/sup -1/, resulting in small perturbation model estimates of /spl sigma//spl deg/ (HH) ranging from -5 dB at 20/spl deg/ incidence to -22 dB at 50/spl deg/ incidence. Results from a multivariate linear regression analysis show that 53.5% of observed variance in /spl sigma//spl deg/ (HH or VV) can be explained by wind speed, upwind fetch from melt pond edges, and melt pond depth, with no appreciable difference in the relative contribution of explanatory variables. Modeled omnidirectional /spl sigma//spl deg/ as a function of wind speed and incidence angle for 100-m transects collected throughout the melt pond season act to elaborate the role of fetch and depth, as well as the modulating effect of hummocks, on /spl sigma//spl deg/.     

Comparison of SAR-derived wind speed with model predictions andocean 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     

A new wind vector algorithm for C-band SAR

Ocean wind speed and wind direction are estimated simultaneously using the normalized radar cross sections /spl sigma//sup 0/ corresponding to two neighboring (25-km) blocks, within a given synthetic aperture radar (SAR) image, having slightly different incidence angles. This method is motivated by the methodology used for scatterometer data. The wind direction ambiguity is removed by using the direction closest to that given by a buoy or some other source of information. We demonstrate this method with 11 ENVISAT Advanced SAR sensor images of the Gulf of Mexico and coastal waters of the North Atlantic. Estimated wind vectors are compared with wind measurements from buoys and scatterometer data. We show that this method can surpass other methods in some cases, even those with insufficient visible wind-induced streaks in the SAR images, to extract wind vectors.     

Fusion of satellite active and passive microwave data for sea icetype concentration estimates

Young first-year sea ice is nearly as important as open water in modulating heat flux between the ocean and atmosphere in the Arctic. Just after the onset of freeze-up, first-year ice is in the early stages of growth and will consist of young first-year and thin ice. The distribution of sea ice in this thickness range impacts heat transfer in the Arctic. Therefore, improving the estimates of ice concentrations in this thickness range is significant. The NASA Team Algorithm (NTA) for passive microwave data inaccurately classifies sea ice during the melt and freeze-up seasons because it misclassifies multiyear ice as first-year ice. We developed a hybrid fusion technique for incorporating multiyear ice information derived from synthetic aperture radar (SAR) images into a passive microwave algorithm to improve ice type concentration estimates. First, we classified SAR images using a dynamic thresholding technique and estimated the multiyear ice concentration. Then we used the SAR-derived multiyear ice concentration to constrain the NTA and obtained an improved first-year ice concentration estimate. We computed multiyear and first-year ice concentration estimates over a region in the eastern-central Arctic in which field observations of ice and in situ radar backscatter measurements were performed. The fused estimates of first-year and multiyear ice concentration appear to be more accurate than NTA, based on ice observations that were logged aboard the US Coast Guard Icebreaker Polar Star in the study area during 1991     

星载合成孔径雷达遥感海洋风场波浪场

星载合成孔径雷达(SAR)能够全天时、全天候、高空间分辨率、宽刈幅观测海洋表面，是获取海面风场和波浪场信息的重要微波传感器。该文综述了多极化SAR海面风场遥感原理、地球物理模式函数，以及潜在应用(海气边界层现象、海上风能资源开发、台风监测与预警预报)，系统总结了传统星载SAR、新型干涉和极化SAR海浪遥感方法和技术。随着雷达卫星编队飞行技术的逐步成熟，未来海洋卫星组网将成为全球海洋和极地观测新趋势，合成孔径雷达海面风场和波浪场定量遥感将从科学研究向业务化海洋动力环境监测发展。      

An L-band geophysical model function for SAR wind retrieval using JERS-1 SAR

An L-band geophysical model function is developed using Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) data. First, we estimate the SAR system noise, which has been a serious problem peculiar to the JERS-1 SAR. It is found that the system noise has a feature common in all the SAR images and that the azimuth-averaged profile of noise can be expressed as a parabolic function of range. By subtracting the estimated noise from the SAR images, we can extract the relatively calibrated ocean signals. Second, using the noise-removed SAR data and wind vector data from the NASA Scatterometer and buoys operated by the Japan Meteorological Agency, we generate a match-up dataset, which consists of the SAR sigma-0, the incidence angle, the surface wind speed, and wind direction. Third, we investigate the sigma-0 dependence on incidence angle, wind speed, and wind direction. While the incidence angle dependence is negligible in the present results, we can derive distinct sigma-0 dependence on wind speed and direction. For wind speeds below 8 m/s, the wind direction dependence is not significant. However, for higher wind speeds, the upwind-downwind asymmetry becomes very large. Finally, taking into account these characteristics, a new L-band-HH geophysical model function is produced for the SAR wind retrieval using a third-order harmonics formula. Resultant estimates of SAR-derived wind speed have an rms error of 2.09 m/s with a negligible bias against the truth wind speed. This result enables us to convert JERS-1 SAR images into the reliable wind-speed maps.     

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.     

Validating a scatterometer wind algorithm for ERS-1 SAR

The ocean surface wind field is observed from space operationally using scatterometry. The European Space Agency's (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 ±2 m/s for wind speed and ±37° for wind direction at a 25-km spatial resolution     

On shape, orientation, and structure of atmospheric cells inside wind rolls in two SAR images

Synthetic aperture radar (SAR) images of the sea surface often show roll-vortex structures and other features which, in general, are spread out over several length scales and may present spatial periodicity as well as intermittence. Standard techniques, such as two-dimensional (2-D) Fourier analysis, are unsuitable both when it is of interest to detect intermittent phenomena and to analyze the spatial disposition of the backscatter structures inside the SAR images. For the above reasons, the 2-D continuous wavelet transform analysis has been applied to two European Remote Sensing mission SAR images over the Mediterranean Sea, showing wind rolls and atmospheric gravity waves. Through the evaluation of the wavelet variance map, which ideally corresponds to the 2-D Fourier spectrum, it has been possible to assess the presence of two main energy areas at large (from 7-28 km) and small (from 0.5-2 km) spatial scales. While the large-scale fluctuations may be ascribed to atmospheric gravity waves and other features induced by the surroundings, the small-scale fluctuations reveal the inner structure of the atmospheric wind rolls. The SAR-like maps, obtained by adding the wavelet coefficient maps pertaining to the small scales, have permitted us to highlight the high- and low-intensity backscatter cells associated with the wind rolls. These cells have been statistically characterized by means of the frequency distributions of the size of the cells maximum and minimum axes, of the orientation of the maximum axis, and of their area. The results indicate that high- and low-intensity backscatter cells have similar characteristics in both cases studied: they appear of elliptic shape, with the major axis along the wind roll direction; the average axes ratio is 2.5:1. The frequency distributions of the cell area indicate a continuous distribution of sizes, without significant gaps.     

An ERS-1 synthetic aperture radar image of a tropical squall linecompared with weather radar data

A radar image acquired by the C-band synthetic aperture radar (SAR) aboard the European Remote Sensing satellite ERS-2 over the coastal waters south of Singapore showing radar signatures of a strong tropical squall line (“Sumatra Squall”) is compared with coincident and collocated weather radar data. Squall line features such as the gust front, areas of updraft convergence, and rain areas are identified. Possible attenuation effects from the rain drops in the atmosphere under very heavy rain (rain rate >100 mm/h) is suggested. In addition, the possibility of extracting the associated geophysical parameters, i.e., rain rate and wind speed from SAR imagery is investigated. The rain rate is estimated from the attenuation signature in the SAR image. Comparison between the estimated rain rate and weather radar rain rate shows consistency. Wind speed associated with the squall line is estimated based on the CMOD4 wind scatterometer model. The estimated wind speed pattern appears to be in agreement with the observed squall line structure. Possible errors in the wind estimation due to effects of rain are suggested     

Effects of precipitation and cloud ice on brightness temperaturesin AMSU moisture channels

Extinction by ice and rain at the AMSU frequencies used in water vapor profile retrievals is investigated with DMSP observations and brightness temperature simulations of a convective storm system. The simulations are based on mesoscale forecast model output of atmospheric, cloud, and rain profiles from which the absorption and scattering due to both liquid and frozen hydrometeors are calculated. Comparison with satellite observations indicates discrepancies of more than 90% (up to 60 K), of which only about 20% results from ignoring scattering by model-prescribed ice. The major source of error is the inability of the forecast model to produce the spatially localized high ice concentrations which cause the low microwave brightness temperatures. A criterion based on the difference between measured brightness temperatures at 183.31±3 and 183.31±1 GHz is suggested to screen out convective events before water vapor retrieval. Application to the case study examined improved agreement between simulated and observed brightness temperatures by up to a factor of two     

一种新的基于网格编码和区域合并的SAR图像快速分割算法

该文建立一种新的基于八邻域网格编码的SAR图像分割模型,并用区域合并技术实现了模型的快速求解。利用多方向比例边缘检测算子提取SAR图像的比例边缘强度映射(RESM),提出一种新的阈值处理方法抑制RESM均质区域内部的极小值,进而减少了对阈值处理后的RESM进行分水岭变换获得的初始分割的区域个数。递归地合并相邻区域来求取分割模型的次优解。利用区域邻接图(RAG)及其最近邻图(NNG)特性来加速区域合并过程。引入精确度(P)和召回率(R)来评价分割算法的边缘定位精度。与常用方法相比,该文方法具有高的边缘定位精度和低的时间复杂度。     

On the utility of SeaWinds/QuikSCAT data for the estimation of the thermodynamic state of first-year sea ice

The thermodynamic state of sea ice is important to accurately and remotely monitor in order to provide improved geophysical variable parameterizations in sea ice thermodynamic models. Operationally, monitoring the thermodynamic state of sea ice can facilitate eased ship navigation routing. SeaWinds/QuikSCAT (QuikSCAT) dual-polarization [i.e., horizontal (HH) and vertical (VV)] active microwave data are available at a sufficiently large spatial scale and high temporal resolution to provide estimates of sea ice thermodynamics. This analysis evaluated the temporal evolution of the backscatter coefficient (/spl sigma//spl deg/) and VV/HH copolarization ratio from QuikSCAT for estimating sea ice thermodynamics. QuikSCAT estimates were compared against RADARSAT-1 synthetic aperture radar (SAR) imagery and the Canadian Ice Service (CIS) prototype operational ice strength algorithm. In situ data from the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE) for 2000, 2001, and 2002 were used as validation. Results indicate that the temporal evolution of /spl sigma//spl deg/ from QuikSCAT is analogous to RADARSAT-1. The QuikSCAT /spl sigma//spl deg/ temporal evolution has the ability to identify winter, snow melt, and ponding thermodynamic states. Moreover, the copolarization VV/HH ratio of QuikSCAT could provide a second estimate of the ponding state in addition to identifying the drainage state that is difficult to detect by single-polarization SAR. QuikSCAT detected thermodynamic states that were found to be in reasonable agreement to that of in situ observations at the C-ICE camp for all years. Operational implications of this analysis suggest QuikSCAT is a more effective and efficient medium for monitoring ice decay compared to RADARSAT-1 and can be utilized to provide more robust modeled ice strength thresholds.     

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° 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 σ 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° to the right of the surface wind direction and can be used to estimate the surface wind direction to within ±19° and 2) utilizing these estimated wind directions from the SAR imagery subsequently improves wind speed estimation, generating errors of approximately ±1.2 m/s, for ERS-1 SAR data collected during the Norwegian Continental Shelf Experiment in 1991     

Wind speed effect on L-band brightness temperature inferred from EuroSTARRS and WISE 2001 field experiments

The results from two field experiments in the Mediterranean Sea are used to study the wind speed dependence of brightness temperature at L-band. During the EuroSTARRS airborne experiment, an L-band radiometer made measurements across a large wind speed gradient, enabling us to study this dependence at high wind speed. We compare our results with a two-scale emissivity model using several representations of the sea state spectrum. While the results are encouraging, unfortunately the accuracy of the measurements does not permit us to distinguish between the so-called twice Durden and Vesecky spectrum and the Elfouhaily spectrum above 7 m/spl middot/s/sup -1/. The effect of foam is certainly small. During the WISE 2001 field experiment carried on an oil rig, we studied this dependence at low wind speed, finding an abrupt decrease of the wind speed effect on the brightness temperature below 3 m/spl middot/s/sup -1/.     

A microwave backscattering model for deformed first-year sea iceand comparisons with SAR data

Like-polarized backscattering from randomly tilted ice blocks in deformed first-year sea ice is modeled. An approximation for the coherent and incoherent scattering cross section of a single ice block is formulated and validated by comparison with moment method computations. It is found that the model is accurate for lossy ice blocks but underestimates the scattering when the loss is low, which is attributed to multiple scattering within the blocks. The backscattering coefficient is evaluated by averaging over an ensemble of blocks with a distribution of slopes and effects of shadowing are estimated. In situ measurements of ice ridge properties in the Baltic Sea are used as input when comparing the model results with coincident ERS-1 SAR data. The model is found to agree with the data to within 1.5 dB, where the discrepancies are mainly due to the uncertainty of the dielectric loss factor in the ice blocks. The model also shows good agreement with airborne 5.3 GHz SAR data of a first-year shear ridge in the Beaufort Sea for incidence angles between 25-50