Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

In this study, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C-band Gaofen-3 (GF-3) SAR. More than 10,000 Vertical-Vertical (VV) and Horizontal-Horizontal (HH) polarization GF-3 images acquired in quad-polarization stripmap (QPS) and wave (WV) modes have been collected during the last three years, in which wind patterns are observed over open seas with incidence angles ranging from 18° to 52°. These images, collocated with wind vectors from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis at 0.125° resolution, are used to re-tune the C-SARMOD2 algorithm to specialize it for the GF-3 SAR (CSARMOD-GF). In particular, the CSARMOD-GF performs differently from the C-SARMOD2 at low-to-moderate incidence angles smaller than about 34°. Comparisons with wind speed data from the Advanced Scatterometer (ASCAT), Chinese Haiyang-2B (HY-2B) and buoys from the National Data Buoy Center (NDBC) show that the root-mean-square error (RMSE) of the retrieved wind speed is approximately 1.8 m/s. Additionally, the CSARMOD-GF algorithm outperforms three state-of-the-art methods – C-SARMOD, C-SARMOD2, and CMOD7 – that, when applied to GF-3 SAR imagery, generating a RMSE of approximately 2.0–2.4 m/s

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

Synthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution. The geophysical model function (GMF), which is widely employed for wind speed retrieval from SAR data, describes the relationship between the SAR normalized radar cross-section (NRCS) at the copolarization channel (vertical-vertical and horizontal-horizontal) and a wind vector. SAR-measured NRCS at cross-polarization channels (horizontal-vertical and vertical-horizontal) correlates with wind speed. In this study, a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function. GF-3 SAR can acquire data in a quad-polarization strip mode, which includes cross-polarization channels. The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts. In particular, the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS. The accuracy of SAR-derived wind speed is around 2.10 m s-1 root mean square error, which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration. The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms. This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction

Evaluation of Chinese Quad-polarization Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval

Our work describes the accuracy of Chinese quad-polarization Gaofen-3 (GF-3) synthetic aperture radar (SAR) wave mode data for wave retrieval and provides guidance for the operational applications of GF-3 SAR. In this study, we evaluated the accuracy of the SAR-derived significant wave height (SWH) from 10,514 GF-3 SAR images with visible wave streaks acquired in wave mode by using the existing wave retrieval algorithms, e.g., the theoretical-based algorithm parameterized first-guess spectrum method (PFSM), the empirical algorithm CSAR_WAVE2 for VV-polarization, and the algorithm for quad-polarization (Q-P). The retrieved SWHs were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field with 0.125° grids. The root mean square error (RMSE) of the SWH is 0.57 m, found using CSAR_WAVE2, and this RMSE value was less than the RMSE values for the analysis results achieved with the PFSM and Q-P algorithms. The statistical analysis also indicated that wind speed had little impact on the bias with increasing wind speed. However, the retrieval tended to overestimate when the SWH was smaller than 2.5 m and underestimate with an increasing SWH. This behavior provides a perspective of the improvement needed for the SWH retrieval algorithm using the GF-3 SAR acquired in wave mode

Evaluation of wave retrieval for Chinese Gaofen-3 synthetic aperture radar

The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) images. More than 200 GF-3 SAR images of the coastal China Sea and the Japan Sea for dates from January to July 2020 were acquired in the Quad-Polarization Strip (QPS) mode. The images had a swath of 30 km and a spatial resolution of 8 m pixel size. They were processed to retrieve Significant Wave Height (SWH), which is simulated from a numerical wave model called Simulating WAves Nearshore (SWAN). The first-guess spectrum is essential to the accuracy of Synthetic Aperture Radar (SAR) wave spectrum retrieval. Therefore, we proposed a wave retrieval scheme combining the theocratic-based Max Planck Institute Algorithm (MPI), a Semi-Parametric Retrieval Algorithm (SPRA), and the Parameterized First-guess Spectrum Method (PFSM), in which a full wave-number spectrum and a non-empirical ocean spectrum proposed by Elfouhaily are applied. The PFSM can be driven using the wind speed without calculating the dominant wave phase speed. Wind speeds were retrieved using a Vertical-Vertical (VV) polarized geophysical model function C-SARMOD2. The proposed algorithm was implemented for all collected SAR images. A comparison of SAR-derived wind speeds with European Center for Medium-Range Weather Forecasts (ECMWF) ERA-5 data showed a 1.95 m/s Root-Mean-Squared Error (RMSE). The comparison of retrieved SWH with SWAN-simulated results demonstrated a 0.47 m RMSE, which is less than the 0.68 m RMSE of SWH when using the PFSM algorithm.Output Status: Forthcoming/Available Onlin

Analysis of waves observed by synthetic aperture radar across ocean fronts

In this study, synthetic aperture radar (SAR) imaging of waves across ocean fronts was investigated using C-band Sentinel-1 VV-polarized SAR imagery collected over the Yangtze and the Zhujiang estuaries. The presence of ocean fronts in the study area was confirmed by collocated sea surface temperature (SST) data provided by the Advanced Very High Resolution Radiometer (AVHRR) and sea surface current information from the National Ocean Partnership Program (NOPP) based on the HYbrid Coordinate Ocean Model (HYCOM). The experimental results revealed that as the current speed increased, the cut-off wavelength (λc) increased as well. The effect of the increasing azimuth cut-off wavelength, however, was relatively weak in terms of variations of the normalized radar cross-section (NRCS), i.e., it was within 2 dB for λc ≤ 60 m. Hence, it was weaker than the NRCS variation related to SST. Larger NRCS variations (i.e., within 5 dB) occurred for λc values up to 120 m. In addition, the experimental results also demonstrated that the parameterized first-guess spectrum method (PFSM) wave retrieval performance was affected by ocean fronts. In particular, overestimations occurred when ocean fronts were present and λc was < 100

Microwave Satellite Measurements for Coastal Area and Extreme Weather Monitoring

In this project report, the main outcomes relevant to the Sino-European Dragon-4 cooperation project ID 32235 “Microwave satellite measurements for coastal area and extreme weather monitoring” are reported. The project aimed at strengthening the Sino-European research cooperation in the exploitation of European Space Agency, Chinese and third-party mission Earth Observation (EO) microwave satellite data. The latter were exploited to perform an effective monitoring of coastal areas, even under extreme weather conditions. An integrated multifrequency/polarization approach based on complementary microwave sensors (e.g., Synthetic Aperture Radar, scatterometer, radiometer), together with ancillary information coming from independent sources, i.e., optical imagery, numerical simulations and ground measurements, was designed. In this framework, several tasks were addressed including marine target detection, sea pollution, sea surface wind estimation and coastline extraction/classification. The main outcomes are both theoretical (i.e., new models and algorithms were developed) and applicative (i.e., user-friendly maps were provided to the end-user community of coastal area management according to smart processing of remotely sensed data). The scientific relevance consists in the development of new algorithms, the effectiveness and robustness of which were verified on actual microwave measurements, and the improvement of existing methodologies to deal with challenging test cases

Ocean Wave Parameters Retrieval from TerraSAR-X Images Validated against Buoy Measurements and Model Results

An ocean surface wave retrieval algorithm, Parameterized First-guess Spectrum Method (PFSM), which was initially developed for C-band Synthetic Aperture Radar (SAR), is modified to extract wave parameters from X-band TerraSAR-X (TS-X) images. Wave parameters, including significant wave height (SWH) and mean wave period (MWP) were extracted from nine TS-X HH-polarization images and were compared to in situ buoy measurements. The range of these wave retrievals is from 1 to 5 m of SWH and from 2 to 10 s of MWP. The retrieval accuracy could reach 80%. After that, a total of 16 collected TS-X HH-polarization images were used to invert wave parameters and then the retrieval results were compared to the operational WAVEWATCH-III wave model results. The SAR and in situ buoy wave comparison shows a 0.26 m Root-Mean-Square Error (RMSE) of SWH and a 19.8% of Scatter Index (SI). The SAR and WAVEWATCH-III model comparison yields slightly worse results with an RMSE of 0.43 m of SWH and a 32.8% of SI. For MWP, the SAR and buoy comparison shows the RMSE is 0.45 s with an SI of 26%, which is better than the results from the SAR and WAVEWATCH-III model comparison. Our results show that the PFSM algorithm is suitable to estimate wave parameters from X-band TS-X data

Preliminary Assessment of Wind and Wave Retrieval from Chinese Gaofen-3 SAR Imagery

The Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) launched by the China Academy of Space Technology (CAST) has operated at C-band since September 2016. To date, we have collected 16/42 images in vertical-vertical (VV)/horizontal-horizontal (HH) polarization, covering the National Data Buoy Center (NDBC) buoy measurements of the National Oceanic and Atmospheric Administration (NOAA) around U.S. western coastal waters. Wind speeds from NDBC in situ buoys are up to 15 m/s and buoy-measured significant wave height (SWH) has ranged from 0.5 m to 3 m. In this study, winds were retrieved using the geophysical model function (GMF) together with the polarization ratio (PR) model and waves were retrieved using a new empirical algorithm based on SAR cutoff wavelength in satellite flight direction, herein called CSAR_WAVE. Validation against buoy measurements shows a 1.4/1.9 m/s root mean square error (RMSE) of wind speed and a 24/23% scatter index (SI) of SWH for VV/HH polarization. In addition, wind and wave retrieval results from 166 GF-3 images were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis winds, as well as the SWH from the WaveWatch-III model, respectively. Comparisons show a 2.0 m/s RMSE for wind speed with a 36% SI of SWH for VV-polarization and a 2.2 m/s RMSE for wind speed with a 37% SI of SWH for HH-polarization. Our work gives a preliminary assessment of the wind and wave retrieval results from GF-3 SAR images for the first time and will provide guidance for marine applications of GF-3 SAR

Study on Polarisation Ratio for X-Band Using Dual-Polarisation Terra-SAR X Image

In this study, we present the analysis of measurements of normalized radar cross section (NRCS) and the polarisation ratio (PR) in dual-polarisation TerraSAR-X (TS-X) images. Based on two PR functions proposed for C-band SAR (denoted as the Thompson model and Elfouhaily model respectively) and the relationship between NRCS and incidence angle for X-band (it is called X-PR), three PR models are tuned using 45 dual-polarisation TS-X images. The PR is found to be dependent of the incidence angle and VV-polarisation NRCS is larger than HH-polarisation NRCS when the incidence angle is larger than 23°. A total of 20 HH-polarisation TS-X images are analyzed for retrieving the wind field using three PR models and XMOD algorithm together. The results are compared to QuikSCAT data and buoy measurements for validation. The root-mean-square error (RMSE) of wind speed is 2.34m/s, 2.16m/s and 1.99m/s with a correlation of 0.82, 0.87 and 0.88 by using Thompson model, Elfouhaily model and X-PR model respectively for the cases

Ocean Wave Parameters Retrieval from TerraSAR-X Images Validated against Buoy Measurements and Model Results

An ocean surface wave retrieval algorithm, Parameterized First-guess Spectrum Method (PFSM), which was initially developed for C-band Synthetic Aperture Radar (SAR), is modified to extract wave parameters from X-band TerraSAR-X (TS-X) images. Wave parameters, including significant wave height (SWH) and mean wave period (MWP) were extracted from nine TS-X HH-polarization images and were compared to in situ buoy measurements. The range of these wave retrievals is from 1 to 5 m of SWH and from 2 to 10 s of MWP. The retrieval accuracy could reach 80%. After that, a total of 16 collected TS-X HH-polarization images were used to invert wave parameters and then the retrieval results were compared to the operational WAVEWATCH-III wave model results. The SAR and in situ buoy wave comparison shows a 0.26 m Root-Mean-Square Error (RMSE) of SWH and a 19.8% of Scatter Index (SI). The SAR and WAVEWATCH-III model comparison yields slightly worse results with an RMSE of 0.43 m of SWH and a 32.8% of SI. For MWP, the SAR and buoy comparison shows the RMSE is 0.45 s with an SI of 26%, which is better than the results from the SAR and WAVEWATCH-III model comparison. Our results show that the PFSM algorithm is suitable to estimate wave parameters from X-band TS-X data