Measurents Of Offshore Ocean Surface Winds Using ASAR

As a clean energy, wind energy development is of great significance for energy demand, energy structure adjustment and environmental protection. There are abundant wind energy resources which can be utilized in the nearshore zone. With the purpose of exploiting the offshore wind energy, we need to make the assessment of the high-resolution offshore wind resource, which plays a guiding role in the site selection of power plant. With the successful launch of the synthetic aperture radars, the images of SARs can offer high resolution wind field for offshore wind energy resource assessment. In order to provide the prerequisite long time series data for the further study of wind resource assessment for nearshore zone of Zhejiang, this paper retrieved the wind fields based on the obtained 215 ASAR Level 1B images from 2005 to 2011.For the sake of extracting the information such as polarization mode, calibration parameters, longitude, latitude, radar incident angle and amplitude image from ASAR Level 1B data, which are crucial for wind field retrieval, this paper describes the generation and organization of general ASAR product and the structure and data format of ASAR Level 1B product, and then developed a program to complete these information extraction. After a series of pre-processing steps, such as geometric rectification, polarization ratio conversion, masking the land, removing off the vessels, speckle filtering and mean sampling, we can finally get the NRCS (Normalized Radar Cross Section) image for wind speeds retrieval from the original amplitude images.Nowadays, the most common used C-band GMFs (Geophysical Model Function) are CMOD4, CMOD-IFR2 and CMOD5. This paper simulated these three models to find out the relationship between the NRCS and wind speed, relative wind direction and radar incidence angle. This paper retrieved wind fields of Zhejiang offshore using these three GMFs separately, their comparison with CCMP wind speeds shows that the CMOD4 is the best mode for the Zhejiang offshore wind speeds inversion, which has the lowest RMSE at 1.90m/s. And the comparison with in situ measurements andCMOD4 can also draw the same conclusion that their RMSE is 1.77m/s. This is because the offshore wind speeds of Zhejiang are mostly under the moderate wind speeds (<25m/s) all the year round, and CMOD4 is the most suitable mode for low-moderate wind speeds retrieval.In the process of this study, due to massive data and large amount of computation caused by the complexity of the GMFs, this paper introduced parallel computation for wind speeds retrieval from ASAR image under the shared memory environment using MATLAB and C programming language, respectively. After the comparison, we find that C programming language is much more efficient than MATLAB. Among all the schedule strategies of OpenMP, the C language programming paralleled by guided schedule can reach the highest computation efficiency of CPU that can get 10.6 times speedup in an 8-core computer, which is amazing that multi-core computing efficiency can be higher than the single-core computing.In a word, this paper discussed the offshore wind speeds retrieval method based on the ASAR data and elaborated the whole process of programing ideas and methods on how to retrieve sea surface wind speeds from ASAR Level 1B data, and then developed the parallel computation wind speeds retrieval software based on the shared memory environment for the purpose of laying the foundation for future research of wind energy resource assessment and facilitating subsequent researchers.