CMOD4 Model Research Articles

Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.

ASAR imaging for coastal upwelling in the Baltic Sea

Analysis of Envisat Advanced Synthetic Aperture Radar (ASAR) and Aqua/Terra Moderate Imaging Spectrometer (MODIS) infrared (IR) imagery of coastal upwelling in the southeastern Baltic Sea is presented. It is found that upwelling features are well distinct in the SAR images, and the leading imaging mechanism appears to be the change of the marine atmospheric boundary layer (MABL) stratification over the sea surface temperature (SST) front. This finding is supported by model calculations of the MABL transformation supplemented with the SAR backscatter calculations based on the CMOD4 model. In addition an empirical dependence of the SAR contrasts over the upwelling region on the wind speed and the SST drop is suggested. Finally, surface slicks accumulated in the sea surface current convergence zones generate additional distinct features in SAR imagery. This effect is interpreted within the framework of the coastal current circulation model based on analysis of the SST snapshot.

SAR를 이용한 해풍, 파랑, 해류 추출 기법 연구

최근 인공위성 SAR를 이용한 기술은 해풍, 파랑, 해류 등과 같은 해양에서 발생되는 다양한 현상을 관측하고 연구하는데 필수적인 기술로 대두되고 있다. CMOD4, CMOD-IFR2 모델은 해상풍의 크기를 구할 수 있으며, wave-SAR 변환 기법과 inter-look cross-spectra 기법은 파랑의 크기, 방향과 같은 물리적 값을 추출할 수 있다. 또한 Doppler shift 기법을 적용하여 해류속도를 구할 수 있다. 본 연구에서는 위의 기법들을 종합적으로 적용하여 SOP(SAR Ocean Processor) 프로세서를 개발하였다. 이 프로세서를 한반도 연안 지역에 적용하여 RADARSAT-1 영상자료로부터 해풍, 파랑, 해류의 물리적 정보를 추출하였으며, 이를 현장 관련 자료와 비교하여 신뢰할만한 결과를 얻을 수 있었다. Recently satellite SAR techniques have become essential observation tools for various ocean phenomena such as wind, wave, and current. The CMOD4 and CMOD-IFR2 models are used to calculate the magnitude of wind at SAR resolution with no directional information. Combination of the wave-SAR spectrum analysis and the inter-look cross-spectra techniques provides amplitude and direction of the ocean wave over a square-km sized imagette, The Doppler shift measurement of SAR image yields surface speed of the ocean current along the radar looking direction, again at imagette resolution. In this paper we report the development of a SAR Ocean processor(SOP) incorporating all of these techniques. We have applied the SOP to several RADARSAT-1 images of the coast of Korean peninsula and compared the results with oceanographic data, which showed reliability of spaceborne SAR-based oceanographic research.

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Abstract Wind vectors over the ocean were extracted from a large number of synthetic aperture radar (SAR) images from the European Remote Sensing Satellites (ERS-1 and ERS-2). The wind directions are inferred from the orientation of wind streaks that are imaged by the SAR, while the wind speeds are retrieved by inversion of the C-band model CMOD4. The derived wind directions and speeds were compared to wind vectors from the numerical Regional Model (REMO) that are available hourly on a 55-km grid. The large number of comparisons and independent weather situations allowed for an analysis of subsets that are classified by SAR-derived wind speed. A strong decrease of the standard deviation of directional differences with increasing wind speed was found. Biases of directional differences depend on SAR wind speed as well. Furthermore, the influence of the temporal difference between SAR overflight and model and an automatic image filtering on the directional error is demonstrated. Overall, reasonable fields of wind vectors were extracted from SAR imagery in 70 of 80 cases. These fields provide valuable information for validation of numerical models of the atmosphere and case studies of coastal wind fields.

Comparison of two wind algorithms of ENVISAT ASAR at high wind

Two wind algorithms of ENVISAT advanced synthetic aperture radar (ASAR), i. e. CMOD4 model from the European Space Agency (ESA) and CMOD_IFR2 model from Quilfen et al., are compared in this paper. The wind direction is estimated from orientation of low and linear signatures in the ASAR imagery. The wind direction has inherently a 1801 ambiguity since only a single ASAR image is used. The 1801 ambiguity is eliminated by using the buoy data from the NOAA (National Oceanic and Atmospheric Administration) buoys moored in the Pacific. Wind speed is obtained with the two wind algorithms using both estimated wind direction and normalized radar cross section (NRCS). The retrieved wind results agree well with the data from Quikscat. The root mean square error (RMSE) of wind direction is 2.801. The RMSEs of wind speed from CMOD4 model and CMOD_IFR2 model are 1.09 m/s and 0.60 m/s respectively. The results indicate that the CMOD_IFR2 model is slight better than CMOD4 model at high wind.

Ocean wind fields retrieved from the advanced synthetic aperture radar aboard ENVISAT

In this paper an algorithm is presented which enables high-resolution ocean surface wind fields to be retrieved from the advanced synthetic aperture radar (ASAR) data acquired by the European remote sensing satellite ENVISAT. Wind directions are extracted from wind-induced streaks that are visible in ASAR images at scales above 200 m and that are approximately in line with the mean surface wind direction. Wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ASAR images, together with the local ASAR-retrieved wind direction. Therefore the empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. CMOD4 is a semi-empirical model, which was originally developed for the scatterometer of the European remote sensing satellites ERS-1 and 2 operating at C-band with vertical polarization. Consequently, CMOD4 requires modification when applied to ASAR images that were acquired with horizontal polarization in transmitting and receiving. This is performed by considering the polarization ratio of the NRCS. To demonstrate the applicability of the algorithm, wind fields were computed from several ENVISAT ASAR images of the North Sea and compared to atmospheric model results of the German weather service.

Ocean wave spectrum and dissipation rate derived from CMOD4 model function

A simplified version of the energy balance equation is solved to obtain an expression for the ocean wave equilibrium spectrum, which is then used with a two‐scale electromagnetic scattering model to calculate the radar cross section of the ocean surface. Two parameters in the energy balance equation are adjusted to minimize the difference between the calculated radar cross‐section values and those given by the CMOD4 model function over a range of incidence angles and look directions, and for a series of wind speeds. The RMS difference between the CMOD4 and two‐scale radar cross‐section values using this model is 0.16 dB for incidence angles from 25° to 45° and wind speeds from 5 to 15 m/s. The slope variances computed from this model also agree fairly well with those measured by Cox and Munk. However, since the largest wave number influencing the C‐band backscatter is approximately 200 rad/m, the spectrum is probably not valid beyond this wave number. Finally, since the spectrum is determined by the relative magnitudes of the wave growth and dissipation rates, some inferences about these parameters can be drawn. Assuming the exponential growth rate parameter to be equal to previous measurements, the dissipation rate implied by this model is more than an order of magnitude larger than that due to molecular viscosity for wind speeds greater than 7 m/s. This conclusion is consistent with observations by Jähne and Riemer, which also indicated a dissipation rate much larger than the viscous dissipation rate at high wind speeds.

A two-scale model to predict C-band VV and HH normalized radar cross section values over the ocean

This paper presents a two-scale model that can predict C-band, VV polarized (C-VV), normalized radar cross section values generated from the CMOD4 model and calibrated normalized radar cross section values derived from C-band, HH polarized (C-HH), RADARSAT-1 synthetic aperture radar imagery with coincident buoy observations of the local wind. The model is based on standard composite models that incorporate tilt modulations, with a new approach for incorporating hydrodynamic modulations. It is shown that inclusion of the hydrodynamic term does not significantly impact the fit to normalized radar cross section (NRCS) values, but does allow the model to accurately predict the upwind to downwind C-VV ratios and improves the model fit to simultaneous C-VV and C-HH NRCS observations. The model uses a new wave height spectrum that is a linear combination of the Apel and Romeiser spectra, weighted heavily toward the Apel form, and has modified values within the C-band Bragg wavenumber regime which are close to midway between the two spectra. The final model can represent the CMOD4 C-VV NRCS results with a root-mean-square error (RMSE) of 0.47 dB and can represent the RADARSAT-1 C-HH NRCS observations, without any change to the model parameters, with an RMSE of 1.9 dB. The model can accurately reproduce the upwind to downwind C-VV NRCS ratios from CMOD4 (RMSE = 0.15 dB) and fits simultaneous C-VV to C-HH ratios derived from aircraft observations to within 1 dB (RMSE = 0.65 dB). If the C-HH hydrodynamic term is allowed to be scaled differently than the C-VV hydrodynamic term, it lowers the RMSE for the simultaneous C-VV to C-HH aircraft observations to 0.49 dB while not affecting the fit to C-VV and C-HH NRCS values. Compared to other C-HH models published in the literature, this model provides a better fit to the RADARSAT-1 C-HH NRCS data across a larger range of conditions than any other single model, provides a better fit to simultaneous C-VV and C-HH NRCS data at an incidence angle of 20°, and reproduces the decreasing trend in the C-VV to C-HH ratio with increasing wind speed observed in data.

Ocean winds from RADARSAT-1 ScanSAR

This paper discusses an algorithm designed to retrieve high-resolution wind fields from scanning synthetic aperture radar (ScanSAR) data acquired on board the Canadian satellite RADARSAT-1. The ScanSAR operates at C-band with horizontal polarization. The wind directions are extracted from wind-induced streaks, e.g., from atmospheric boundary layer rolls or wind shadowing, which are approximately in line with the mean wind direction near the ocean surface. The wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ScanSAR images, together with the local wind direction retrieved from the image. Therefore the semi-empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. The CMOD4 was originally developed for the scatterometer of the European remote sensing satellites ERS-l and ERS-2 operating at C-band with vertical polarization. Consequently, the CMOD4 required modification for horizontal polarization, which is performed by considering the polarization ratio. To demonstrate the applicability of the algorithm, wind fields were computed from 20 RADARSAT-1 ScanSAR wide-swath images and compared to co-located results from the Danish high-resolution limited-area model (HIRLAM). In addition, the error sources in ScanSAR wind retrieval are discussed and sensitivity studies were carried out to estimate wind speed errors due to uncertainties in the NRCS, wind direction, and incidence angles.

Meteorological and oceanographic surface roughness phenomena in the English Channel investigated using ERS synthetic aperture radar and an empirical model of backscatter

The empirically derived ERS scatterometer model CMOD4 is used to examine the relationship between radar backscatter measured by synthetic aperture radar (SAR) and wind speed in shallow waters. It is demonstrated that the model can be used to obtain accurate mean wind speed information from ERS SAR, using meteorological synoptic charts to provide wind direction; this approach could enable submesoscale wind variations to be monitored. Results from the wind speed analysis were used to investigate the small‐scale (<200 m) variability of the surface roughness detectable by SAR, the aim being to characterize the effects of parameters additional to the mean wind speed which contribute to the modulations of the backscatter signal. It is shown that the natural small‐scale fluctuation of the SAR‐derived mean wind field barely exceeds the radiometric noise limitations of the instrument. Where the small‐scale variability of the calculated “apparent” wind speed was above this level, the cause could be linked to dynamic oceanographic parameters.

Katabatic wind fields in coastal areas studied by ERS‐1 synthetic aperture radar imagery and numerical modeling

Synthetic aperture radar (SAR) images acquired over Mediterranean coastal waters from the first European Remote Sensing Satellite (ERS‐1) showing sea surface manifestations of katabatic wind fields are presented. In particular, sea surface roughness patterns generated by katabatic winds blowing from 1800 in high mountains through a broad valley at the western coast of Calabria (southern Italy) into the Gulf of Gioia is investigated. The ERS‐1 SAR images show that their areal extent and shape vary strongly, depending on the meteorological conditions. The roughness pattern sometimes has the form of a mushroom, an elongated tongue, a broad blob, or a narrow truncated band. For one event (September 8, 1992) we have simulated the wind field at the sea surface by using a nonhydrostatic mesoscale atmospheric model and then compared it with the wind field derived from the ERS‐1 SAR image by using the C band wind scatterometer model CMOD4. The comparison shows that the atmospheric model reproduces quite well the mushroom‐like form of the wind field pattern, while the wind speed is obtained somewhat lower than the one inferred from the SAR image. This study demonstrates that SAR images acquired over coastal waters are well suited to study local wind fields in coastal areas and to test numerical models that describe local wind fields which extend from the coast onto the sea.

A new relationship between radar cross-section and ocean surface wind speed using ERS-t scatterometer and buoy measurements

Abstract The ERS–I spacecraft scatterometer, C-band VV polarization, acquired radar cross-section measurements over the global oceans during 1992 and 1993. We investigate the cross-section dependence on mean wind speed U using collocated buoys within ±25km of the scatterometer cells. These collocated measurements result in over 75000 matches in two diITerent oceanic regions. The buoys measure hourly mean wind speeds from 0·2–10 mS 1 and 0·2–18ms -1 in the equatorial Pacific Ocean and at mid-latitudes off the North American coasts, respectively. We present experimental evidence for a new and compact exponential model dependence on wind speed. The previously used power–law form inadequately characterizes the cross-section measurements based on a single index over a large wind speed range. The cross-sectional slope varies from about zero dB/ms-1 at high wind speeds U=18ms -1 and small incidence angles 0=20° to about 1·3dB/ms -1 at low wind speeds U=3ms -1 and large incidence angles, 0=55°. The CMOD4 model si...

An ERS 1 synthetic aperture radar image of atmospheric lee waves

An ERS 1 synthetic aperture radar (SAR) image of the island Hopen shows a distinct 7.6‐km wavelength wave phenomenon near the island. This wave phenomenon is interpreted as the surface imprint on open water of atmospheric lee waves. The pattern is visible in the SAR image, since the lee waves modulate the horizontal wind speed near the ocean surface which, in turn, modulates the surface roughness and the radar cross section. The physical setting for the observation is presented and discussed. The lower bound on horizontal wind speed modulation is estimated to range from 3±2 ms−1 (for the wind speed minima) to 12±2 ms−1 (for the wind speed maxima) based upon the observed radar cross‐section modulation and the ERS 1 scatterometer wind retrieval model CMOD4. The wavelength and wind speed modulation are consistent with linear lee wave model predications. The model uses an atmosphere with an exponential profile of the Scorer parameter (ratio of buoyancy frequency to wind speed) to represent a shallow, ground‐based inversion layer observed at Bear Island and a bell‐shaped barrier to represent the forcing effects of Hopen.