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B2: ID.10412 Ocean Resources & Microwaves RS
Recent Progresses of Microwave Marine Remote Sensing
1State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China; 2National Ocean Technology Center, State Oceanic Administration, China; 3Ocean College, Zhejiang University, China;
It is presented in this paper the recent progresses of ESA-MOST China Dragon Cooperation Program (ID. 10412) in the field of microwave marine remote sensing including (1) ocean surface wind fields and ocean waves remote sensing by using full polarization synthetic aperture radars (SAR), (2) joint retrieval of directional ocean wave spectra from SAR and wave spectrometer data (3) error analysis on ESA's Envisat ASAR wave mode significant wave height retrievals using triple collocation model, (4) typhoon observation by using multiple satellites including SAR and optical sensors, (5) ocean internal wave observation by using multiple satellites including SAR and optical sensors, (6) ocean eddy observation by using multiple satellites including SAR and optical sensors, (7) retrieval models of water vapor and wet tropospheric path delay for the HY-2A calibration microwave radiometer, (8) calibration of significant wave height from HY-2A satellite altimeter, (9) data fusion of multiple satellite altimetry, (10) storm surges observed by HY-2A satellite altimetry and tide gauges.
Crossing Swell and Origins : Global View from ASAR Wave Mode Fireworks
1National Ocean Technology Center, China; 2Ifremer, Laboratorie d’Oceanographie Spatiale, Plouzané, France; 3Collecte Localisation Satellites, Plouzané, France; 4State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China;
Crossing swell, is a complicated sea state characterized by the co-existence of swell systems generating from different swell origins. Although many investigations have focused on the global swell climatology, our understanding of global statistical distribution for the crossing swell is still limited. In this paper, we present a global view of crossing swell using 10-years Synthetic Aperture Radar (SAR) derived directional swell spectra from Envisat ASAR in Wave Mode from 2003 to 2011. In contrast to analyze the directly but occasionally SAR captured sea state of crossing swell, we employ an approach of propagating observed swell taking advantage of the internal consistency of swells. Results reveal three dominated crossing swell areas termed “crossing swell pools”, in Pacific, Atlantic and Indian Oceans. The pool in Atlantic Ocean shows a relative stable behavior for all seasons, in contrast to the one in Indian Ocean with seasonal occurrence and the one in Pacific Ocean shrinking during boreal summer. The sources of the crossing swell are also inferred from ASAR wave mode data, and its golbal distribution analysis results indicate good agreement with the seasonal variation of crossing swell pools.
Data fusion of SST from HY-2A satellite radiometer in China Sea and its adjacent waters
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China.;
Abstract: This paper focuses on using data fusion method to solve the problem that the global sea surface cannot be covered by the along-track sea surface temperature (SST) data of scanning microwave radiometer on board Haiyang-2A (HY-2A), which is the first ocean dynamic environment satellite of China launched on 16th August 2011. The procedure includes following steps. Firstly, the HY-2A SST data within 200 km of the coastline were identified and removed, the outliers of the HY-2A SST data and the SST data from the operational, high-resolution, combined sea surface temperature and sea ice analysis（OSTIA）system were also identified and removed. Secondly, the HY-2A SST data were gridded, filtered and corrected. The OSTIA SST data were only filtered. Finally, the HY-2A SST data were merged into OSTIA SST data by the inverse distance weighted method. Next, the above procedure was tested in the ocean area on the southeast of China. The longitude range of the ocean area is from 105°E to 165°E, and the latitude range of the ocean area is from 0° to 35°N. The global 1-km sea surface temperature (G1SST) data were used as the reference data. The results of the procedure with and without the second step were made comparisons, and the results implied that the application of median filter and third-order polynomial curve fitting in the second step could help to improve performance of the merged SST data. The along-track SST data of HY-2A can be merged into OSTIA SST data successfully by using this method, and the blank areas among the tracks are filled up.
Effect of Precipitation to the Wind Retrieval from Synthetic Aperture Radar
1Ocean College, Zhejiang University, Hangzhou, China,; 2State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China;
As one of the most powerful air-sea interaction in the weather system, typhoon always accompany with a wide range of heavy rainfall. Synthetic Aperture Radar (SAR) plays an important role in typhoon wind field retrieval, because it can work all-day, all-weather and has high spatial resolution. SAR can also observe sea surface with multi-frequency, multi-polarization and multi-angle of view. But due to the influence of the rainfall on the radar signal, the inversion precision of sea surface wind field will decline. With the exploration of high wind speed inversion model, much more researchers focus on the influence of large precipitation to the wind field retrieval.
In this paper, combined with the sea wind direction information from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data, high accuracy and high-resolution wind field was obtained by using geophysical model function CMOD5 with several RADARSAT-2, ENVISAT ASAR typhoon cases. Then through comparing with Tropical Rainfall Measuring Mission satellite (TRMM) quasi-synchronize rainfall data, the effect and deviation made by rainfall was calculated. After that, we substitute the wind speed data in rainy area with adjacent wind speed data without rainfall to get a more accurate wind field. At last, comparing with the forecast data, ground radar data or scatterometer data, corrective wind field is verified in order to prove its optimization.
Research on the intensity characteristics of internal solitary waves in the northeast of Taiwan using remote sensing
The First Institute of Oceanography，SOA,China， People's Republic of;
Northeast of Taiwan is one of the hot spots for internal solitary waves in the adjacent seas of China. Internal solitary waves in this area are complicated due to many factors, such as the intrusion of subsurface water of the Kuroshio, upstream and complex topography. Remote sensing is an effective method for the detection of internal solitary waves, and have been applied to investigate the spatial and temporal distribution of internal solitary waves. However, intensity characteristics of internal solitary waves is relatively rare. In this paper, research on the intensity characteristics of internal solitary waves in the northeast of Taiwan is conducted with numerous optical (GF-1) and SAR (ERS-2, ENVISAT ASAR, Sentinel-1A) images. The statistic model describing intensity characteristics of internal solitary waves was developed based on the reflectivity of optical remote sensing images and backscatter intensity of SAR images. The distribution characteristic of intensity of internal solitary waves in the northeast of Taiwan was presented, using long-time dataset of remote detection of internal waves. Time-varying intensity of internal solitary waves were analyzed systematically and affecting factors were also discussed.
A Ku-band low incidence backscatter model for retrieving wind speeds
Second Institute of Oceanography, China, People's Republic of;
A new Ku-band low incidence backscatter model (KuLMOD) for retrieving wind speeds from Tropical Rainfall Mapping Mission (TRMM) precipitation radar (PR) data is proposed. The data set consisted of TRMM PR observations and collocated National Data Buoy Center (NDBC) and Tropical Ocean Global Atmosphere program (TOGA) buoy-measured wind and wave data. The TRMM PR data properties were analyzed with regard to their dependence on spatial resolution, wind speed, relative wind direction, and significant wave height. The KuLMOD model was developed using incidence angles (0.5–6.5°) and wind speeds (1.5–16.5 m/s) as inputs. The model coefficients were derived by fitting the collocated data. The KuLMOD-derived normalized radar cross section, σ0, was compared with those obtained from the TRMM PR observations and a quasi-specular theoretical model and showed good agreement. With the KuLMOD, the wind speeds were retrieved from the TRMM PR data using the least squares method and validated with the buoy measurements, yielding a root mean square error of 1.45 m/s. The retrieval accuracies for the different incidence angles, wind speeds, and spatial resolutions were obtained.
Error Analysis on ESA’s Envisat ASAR Wave Mode Significant Wave Height Retrievals Using Triple Collocation Model
1National Ocean Technology Center, State Oceanic Administration, China; 2State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China;
Nowadays, spaceborne Synthetic Aperture Radar (SAR) has become a powerful tool for providing significant wave height (SWH). Traditionally, validation of SAR derived SWH has been carried out against buoy measurements or model outputs, which only yield an inter-comparison, but not an “absolute” validation. In this study, the triple collocation error model has been introduced in the validation of Envisat ASAR derived SWH products. SWH retrievals from ASAR wave mode using ESA’s algorithm are validated against in situ buoy data, and wave model hindcast results from WaveWatch III wave model, covering a period of six years. From the triple collocation validation analysis, the impacts of the collocation distance and water depth on the error of ASAR SWH are discussed. It is found that the error of Envisat ASAR SWH product is linear to the collocation distance, and decrease with the decreasing collocation distance. Using the linear regression fit method, the absolute error of Envisat ASAR SWH was obtained with zero collocation distance. The absolute Envisat ASAR wave height error of 0.49 m is presented in deep and open ocean from this triple collocation validation work, in contrast to a larger error of 0.56 m in coastal and shallow waters. One of the reasons for the larger Envisat ASAR SWH errors in the coastal waters may be the inaccurate Modulation Transfer Function (MTF) adopted in the Envisat ASAR wave retrieval algorithm.
MARINE TARGET DETECTION IN Pol-SAR DATA
Second Institute of Oceanography, State Oceanic Administration, China, People's Republic of;
In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.
Rainband Feature Tracking For Wind Speeds Around Typhoon Eyes Using Multiple Sensors
1State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China; 2Ocean College, Zhejiang University, Hangzhou 310058, China;; 3Department of Atmospheric Sciences, National Taiwan University, Taipei 10617, Taiwan;
No direct measurements of surface winds are available now except that by aircraft at a high cost, thus tracking and monitoring ocean features which have short coherent time periods from sequential satellite images is a good option to estimate extreme wind speeds associated with typhoons. In this study, five typhoon cases observed by quasi-concurrent satellite-based Synthetic Aperture Radar (SAR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data, and one of the cases also by ground-based Doppler radar observations were studied. The rainband features around typhoon eyes were first delineated using wavelet analysis, and then the wind speeds were estimated by feature tracking using quasi-concurrent multi-sensor images. It was found that the resulting wind speeds are reasonable compared with the maximum wind speed reported from the Joint Typhoon Warning Center (JTWC), which accounts for the radial dependence of wind speed using the Rankine combined vortex approximation. In a special case, with the aid of the Doppler radar near the northern coast of Taiwan, wind speed estimation based on the multi-sensor also shows consistent results. This study demonstrates that the local wind distribution of cyclonic winds around typhoon eyes at different radial distances from the typhoon centres may be derived from rainband feature tracking using quasi-concurrent multi-sensor images. This technique may offer useful wind information for typhoon simulations and forecasting.
Study on Extracting and Verifying the Internal Wave Parameters from SAR Images
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, China;
Oceanic internal waves are often observed by SAR. So SAR provides a new technique for measuring internal wave in a large area. And it is complementary to traditional measurements. The procedures are given in this paper for extracting the direction, wavelength, amplitude, speed and depth of internal waves. ENVISAT ASAR and Radarsat-2 SAR images of South China Sea are used to extract the parameters. And HJ-1 optical images are used to assist. Then some in-situ data from buoy is used to verifying the extraction results. The times of in-situ data and SAR image are similar. The results are shown that: 1) The internal wave parameter can be extracted from SAR images, although sometime the extraction needs other data. 2) The error of wave direction between SAR and in-situ is less than 15 degree. The error of wave amplitude between SAR and in-situ is less than 15m, the relative error is less than 20%. 3) The wavelength of internal wave can’t be measured by buoy. The wave depth, measured by buoy, is the depth where the velocity of flow is maximum. It isn’t the depth of internal wave.
Coastline Extraction from SAR Images Using Discriminant Cuts Segmentation
1Shanghai Ocean University, China, People's Republic of; 2Zhaoqing University, Guangzhou, China, People's Republic of;
In this paper, a new automatic approach was proposed to extract the coastline from SAR images by using discriminant cuts segmentation. Discriminant cuts is a graph-based spectral cluster algorithm. It completely satisfies the general criterion of the cluster algorithms: maximizing the within-cluster similarities while minimizing between-cluster associations. Compared with normalized cuts, discriminant cuts has better grouping performance in image segmentation. In the proposed approach, discriminant cuts is applied to discriminate water from land in SAR images. The approach was verified by using actual SAR data collected over the coastal area of Shanghai, China.
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Conference: 2016 Dragon 3 Final Results Symposium
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