Johannes Schulz-Stellenfleth

Global wind speed retrieval from SAR

The global availability of synthetic aperture radar (SAR) wave mode data from the European Remote Sensing (ERS) satellites ERS-1 and ERS-2, as well as ENVISAT, allows for the investigation of the wind field over the ocean on a global and continuous basis. For this purpose, 27 days of ERS-2 SAR wave mode data were processed, representing a total of 34310 imagettes of size 10 km /spl times/5 km, available every 200 km along the satellite track. In this paper, two methods for retrieving wind speeds from SAR imagettes are presented and validated, showing the applicability of ENVISAT alike SAR wave mode data for global ocean wind retrieval. The first method is based on the well-tested empirical C-band scatterometer (SCAT) models, which describe the dependency of the normalized radar cross section (NRCS) on wind speed and direction. To apply C-band models to SAR data, the NRCS needs to be accurately calibrated. This is performed by a new efficient method utilizing a subset of colocated measurements from ERS-2 SCAT and model winds from the European Centre for Medium-Range Weather Forecast (ECMWF). SAR wind speeds are computed from the calibrated imagettes and compared to the entire set of colocated ERS-2 SCAT and ECMWF model data. Comparison to ERS-2 SCAT winds result in a correlation of 0.95 with a bias of -0.01 m s/sup -1/ and an rms error of 1.0 m s/sup -1/. The second approach is based on neural networks (NNs), which allow the retrieval of wind speeds from uncalibrated SAR imagettes. NNs are trained using the mean intensity of ERS-2 SAR imagettes and colocated wind data from the ERS-2 SCAT and ECMWF model data. Validation of the NN-retrieved SAR wind speeds to ERS-2 SCAT and ECMWF model wind data result in a correlation of 0.96 with a bias of -0.04 m s/sup -1/ and an rms error of 0.93 m s/sup -1/.

Tropical Cyclone Intensity Estimated From Wide-Swath SAR Images

Due to the relatively small amount of in situ data available for the open oceans, remote sensing techniques take an important role in the retrieval of geophysical information, particularly during extreme events. The work presented here aims at the improvement of prediction of cyclone intensity using synthetic aperture radar (SAR) images. A new method to measure the hurricane intensity using SAR images, in combination with a parametric Holland-type model of wind speed, is presented. The algorithm is based on a least square minimization of the difference between the parametric model results and the SAR measurement. The radius of the maximum wind speed, required as input for the minimization procedure, is estimated from the SAR image using wavelet analysis. Information on wind direction is extracted from the SAR image through analysis of image features caused by boundary layer rolls. The root-mean-square error of the suggested method has been validated to be equal to 3.9 m/s. The study is based on a data set of wide-swath SAR images of about 400 km × 400 km coverage, acquired by the European Envisat satellite, over tropical cyclones. As a case study, hurricane Katrina is investigated in detail. A total of five tropical cyclone images will be used to validate the results of the new algorithm.

Sea surface imaging with an across-track interferometric synthetic aperture radar: the SINEWAVE experiment

An across track interferometric synthetic aperture radar (InSAR) is used to image ocean waves. Across track InSAR data were acquired during the SAR INnterferometry Experiment for validation of ocean Wave imaging models (SINEWAVE) in the North Sea using an airborne X-band radar with horizontal polarization. A wind sea system was imaged at different flight levels and with different flight directions with respect to the ocean wave propagation direction. Simultaneously, ocean wave spectra were measured by a directional wave rider buoy. Thus, the experiment data comprises synthetic aperture radar (SAR) intensity, coherence, and phase images together with in situ measurements. As shown in a recent theoretical study by Schulz-Stellenfleth and Lehner (2001), across track InSAR provides distorted (bunched) digital elevation models (DEMs) of the sea surface. Using SINEWAVE data the DEM bunching mechanism is verified with in situ ocean wave measurements available for the first time. It is shown that significant waveheight as well as one-dimensional (1D) wavenumber spectra derived from bunched DEMs and buoy data are in good agreement for small nonlinearities. Peak wave directions and peak wavelength detected in bunched DEMs and SAR intensity images are compared with the buoy spectrum. Peak rotations of up to 30/spl deg/ with respect to the buoy spectrum are found depending on flight direction and flight level. Two-dimensional (2D) spectra of bunched DEMs, corresponding coherency maps, and SAR intensity images are intercompared. The signal-to-noise ratio (SNR) of bunched DEM spectra is shown to be about 5 to 10 dB higher than the SNR of SAR intensity image spectra.

Ocean wave imaging using an airborne single pass across-track interferometric SAR

An airborne single pass across-track interferometric synthetic aperture radar (InSAR) is used to image ocean waves. A theoretical model explaining the imaging mechanisms is developed, and simulations of the interferogram as well as the conventional SAR intensity image are presented for given ocean wave spectra. Distortions of digital elevation models (DEM) derived from InSAR data are explained by the motion of the sea surface. A Monte Carlo method based on forward simulations is used to estimate variance spectra of the distorted elevation models. It is shown that a straightforward estimation of wave height using the distorted InSAR elevation model is in good agreement with true wave height for low amplitude swell with about 10% error depending on propagation direction and coherence time. However, severe underestimation of wave height is found for wind seas propagating in flight direction. Forward simulations show that the distorted InSAR DEM is less dependent an the model chosen for the real aperture radar mechanism than conventional SAR images. Data acquired during an experiment over the North Sea by a high precision InSAR system are compared with simulations.

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

High Frequency radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past ten years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A big effort is made in Europe towards a coordinated development of coastal HFR technology and its products within the framework of different European and international initiatives. One recent initiative has been to make an up-to-date inventory of the existing HFR operational systems in Europe, describing the characteristics of the systems, their operational products and applications. This paper offers a comprehensive review on the present status of European HFR network, and discusses the next steps towards the integration of HFR platforms as operational components of the European Ocean Observing System, designed to align and integrate Europe’s ocean observing capacity for a truly integrated end-to-end observing system for the European coasts.

Synergetic Use of Radar and Optical Satellite Images to Support Severe Storm Prediction for Offshore Wind Farming

In this paper, we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale high-resolution wind fields in synergy with cloud parameters from optical data and, thus, help in the task of maintenance and planning offshore wind farms. The aim of this paper is to use synthetic aperture radar (SAR) and medium resolution imaging spectrometer (MERIS) onboard the environmental satellite (ENVISAT) in synergy to analyze severe weather systems, in particular, to describe the spatial evolution of the atmospheric boundary layer processes involved in cold air outbreaks. We investigated the fine-scale structure of a severe weather case on November 1, 2006 over the North Sea using satellite data. The satellite data are compared with numerical model results of the German Weather Service ldquoLokal Modellrdquo (LM) and the high-resolution limited area model (HIRLAM). LM and HIRLAM show differences in mesoscale turbulent behavior and coastal shadowing. Maximum wind speeds of up to 25 m/s are measured by SAR and are confirmed by the models. Significant differences are observed in the location of the maxima. High-resolution ENVISAT ASAR measurements provide very detailed information on small-scale atmospheric features, which seem to not be captured well by the analyzed numerical models, in particular, in coastal areas. Meteosat second generation (MSG) is used to determine the movement of cloud patterns. Cloud patterns seen in the optical data and radar cross-section modulation give a consistent dynamical picture of the atmospheric processes. The relevance for offshore wind farming is discussed.

Extreme wind conditions observed by satellite synthetic aperture radar in the North West Pacific

In this paper some recent results on SAR observation of extreme surface wind conditions are summarized. Particular emphasis is put on the investigation of typhoons occurring in the North West Pacific. The study is based on the use of ENVISAT ASAR wide swath images (400 km×400 km), which allow synoptic measurements of the complete mesoscale system at high resolution (150 m). Surface wind speed for typhoon cases is determined from SAR measurements using the geophysical model function CMOD5. Further structures observed in the image like streaks indicating wind direction and the ring of maximum wind speed are additionally taken into account to reconstruct the typhoon wind field. The influence of heavy rain on the radar cross section is estimated from an existing radiative transfer model and compared to the SAR measurements. A new technique for the estimation of typhoon intensity from SAR data is presented, which makes use of a parametric type model. The main goal of the paper is the improvement of the estimation of maximum typhoon intensity using SAR data.

Validation and intercomparison of ocean wave spectra inversion schemes using ASAR wave mode data

This paper presents a validation and intercomparison of the non-linear Partition Rescaling and Shift Algorithm (PARSA) for deriving full two-dimensional ocean wave spectra from ENIVSAT Advanced Synthetic Aperture Radar (ASAR) Wave Mode (WM) data. ASAR WM data acquired globally are used for the validation exercise by comparing the retrieved significant wave height (SWH), zero up-crossing wave period (T m02), swell SWH (H 12, for waves with a period longer than 12 s), mean wave frequency and mean wave direction to in situ buoy measurements and results from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis wave model and the Deutscher Wetterdienst (DWD) forecast wave model. An intercomparison of results from the PARSA algorithm with those from the quasi-linear retrieval algorithm adopted by the European Space Agency (ESA) to generate the ASAR WM level-2 product (ASA_WVW_2P, termed WVW hereafter) is also presented in this paper. In addition to the intercomparison with the existing ASAR WM WVW product, sea state parameters (SWH and T m02), integrated from the PARSA spectra are also compared to the results derived using the empirical algorithm CWAVE_ENV. Validation results indicate that the PARSA inversion can yield full two-dimensional ocean wave spectra. The retrieved SWH corresponds well to buoy measurements with a scatter index of 21%, as demonstrated by 1247 collocated data pairs. By comparing SWH to the ECMWF reanalysis wave model and the DWD forecast wave model, better agreement is achieved, with scatter indices of 9% and 16%, respectively. In addition to comparing conventional integral wave parameters normally used to assess the quality of inverted spectra, a comparison of individual PARSA spectra chosen in different sea state with the nearest numerical wave model spectra and the WVW spectra is performed to illustrate two-dimensional spectral differences.

Detection of extreme waves using synthetic aperture radar images

Within the last years a considerable number of large ships have been lost due to severe sea state conditions. The cause of accidents are in many cases believed to be rogue waves, which are individual waves of exceptional wave height or abnormal shape. In particular steep breaking waves can be fatal for smaller ships. Damage is sometimes can also be caused by unusual grouping of waves, which can lead to dangerous ship motion. In situ measurements of extreme waves are sparse with most observations reported by ship masters after the encounter. In this paper a global data set of 5 /spl times/ 10 km sized synthetic aperture radar (SAR) images acquired by the European Remote Sensing satellite ERS-2 every 200 km along the track is used to analyse extreme ocean wave events. As the European Space Agency (ESA) does not provide this dataset as a standard product wave mode raw data were reprocessed to complex SAR images using the processor BSAR developed at the German Aerospace Center (DLR). About 1000 globally distributed SAR wave mode images are available every day. Two dimensional ocean wave fields are derived from SAR images by inversion of the SAR imaging mechanism. Individual high waves are detected in the derived wave fields using a matched filter technique. The inhomogeneity of ocean wave fields is analysed using a parameter, which describes the shift invariance of the wave spectrum.

Comparison of offshore wind park sites using SAR wind measurement techniques

Wind farming has grown rapidly in Europe over the last decade. All European countries with shallow coastal waters and strong mean coastal wind speeds are planning or already constructing offshore wind farms. Large parts of the North Sea and Baltic Sea are being investigated to see whether they are suitable for offshore wind parks. In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High-resolution synthetic aperture radar (SAR) images acquired by the European remote sensing satellite ERS-2 showing single wind turbines are investigated. The methods for retrieving high-resolution wind fields from SAR images are explained and statistical comparisons of wind speed and wind direction at the two offshore wind park sites in the North Sea, Horns Rev and Butendiek, are given.