Conference Agenda

Ocean wave is one of the important objects of ocean observation by satellite microwave remote sensing. Since the successful launch of TOPEX/Poseidon in 1992, the satellite altimeters had provided the abundant global ocean wave height observations. But the altimeters can only observe the ocean wave height of the points under the satellite along track. Synthetic Aperture Radar (SAR) can obtain ocean wave spectrum data with a certain swath observation, but SAR ocean wave data have the issue of wave wavelength truncation. China-France Oceanography Satellite (CFOSAT) was launched on 20^th Oct. 2018, and the equipped SWIM on CFOSAT provided a new means for global ocean remote sensing observation. In this study, CFOSAT SWIM ocean wave observation data are evaluated by buoy and altimeter data firstly. The nadir and non-nadir ocean wave data of SWIM are compared to buoys and altimeter data. Then the study on ocean wave data fusion based on multi-source satellite remote sensing is carried out, and the global ocean wave remote sensing data from 2016 to 2020 are generated by using HY-2 series, sentinel-3 series, jason-3 altimeter, Sentinel-1 SAR and CFOSAT SWIM ocean wave data. In addition, the components of ocean waves are identified according to the wave age by combining the sea surface wind data, and the swell remote sensing fusion is carried out to generate global ocean swell products with the period more than one year. Finally, the preliminary analysis of ocean wave characteristics is carried out with the global ocean wave products produced in this study.

A SAR internal wave amplitude inversion algorithm based on Euler numerical simulation is proposed. The traditional satellite SAR internal wave amplitude inversion algorithm is based on the analytic relationship between the half width and the amplitude of the internal solitary wave revealed by the KdV equation or its variants. Those methods often underestimate the internal wave amplitude. There are at least two reasons for this problem: 1) KdV and its variants are insufficient to accurately describe the nonlinear behavior of large-amplitude internal waves; 2) The half-width of internal waves on the sea surface observed by SAR are different from that on the water layer where the maximum vertical displacement is located. The proposed new method iteratively conducts the numerical simulation of internal waves with different amplitudes. The best amplitude is obtained when the simulated half-width of the internal waves apprearing on the sea surface is most close to the half-width observed by SAR.

However, there are two possible amplitudes for one half-width. The inversion algorithm has to choose one of the two amplitudes. Such selection is done by comparing the simulated SAR NRCS modulation corresponding to the two amplitudes with the observed SAR NRCS modulation.

Case studies in multiple sea areas around the world show that the amplitude accuracy obtained by the new SAR internal wave amplitude inversion algorithm is significantly better than the KdV algorithm. In addition, in order to accelerate the convergence of the model at large amplitudes, the Miyata equation was used to calculate the initial flow field.

HY-1C and HY-1D are the two ocean color satellites in China which play the important role in routine work of global marine environment monitoring launched separately in 2018 and 2020. The overall objective of HY-1 serial satellite is to monitor global ocean color and SST (Sea Surface Temperature), as well as the coastal zones’ environment. The China France Oceanography Satellite (CFOSAT) and Haiyang-2B (HY-2B) satellites were successively launched in China in 2018. As missions for measuring the dynamic marine environment, both satellites can measure the nadir significant wave height (SWH). Sentinel-2A/B satellites were launched in 2015 and 2017 separately. In this project, all these satellites data have been used to monitor marine disaster and environmental changes. Based on the various methods and different data types, satellite remote sensing monitoring research have been conducted in several typical marine disasters and dynamic environment changes. The results show the advantages both in new algorithms and multiple satellite data applications. The main developments in the mid-term of the project are as follows:
1) Using HY-1C/D and Sentinel-2 satellite data, this project investigates the sea ice, oil spill and green tide disaster in Bohai Sea and the Yellow Sea, as well as the East China Sea. The results show that both HY-1
C/D and Sentinel satellite data have played an important role in ocean ecological disaster monitoring. It’s deserved to point out that the Coastal Zone Imager (CZI) on-board HY-1C/D displays much powerful performance in operational monitoring of marine spills, green-tides and sea-ice disasters because of the large width, rapid coverage and high signal-to noise ratio of data. According to the characteristics of different spatial resolution data, we develop a comprehensive method to classify the difference of monitoring results using various satellite data which could improve the accuracy of greed-tide detection and coherence the green-tide bio-mass evaluations resulted from different satellite data.
2) Based on the time series HY-1C/D satellite data in 2019-2021, the long-term oil spills detection has been conducted in China Seas and coherent areas. The results show that it’s possible to distinguish the various spill types, for example the emulsified and non-emulsified oils, using the CZI satellite data in the condition of different sun-glint reflections which also displays the outstanding advantages of HY-1C/D data applications. According to the 3 years data analysis, the spatial patterns of oil spill distributions have been conducted for the first time in the China Seas.
3）In this project, the HY-2B altimeter and CFOSAT nadir SWHs have been validated against the National Data Buoy Center (NDBC) buoys and the Jason-3 altimeter SWH data, respectively, which resulted in CFOSAT nadir SWH having the best accuracy and HY-2B having the best precision. The SWHs of the two missions are also calibrated by Jason-3 and NDBC buoys. Following calibration, the root mean square error (RMSE) of CFOSAT and HY-2B are 0.21 and 0.27 m, respectively, when compared to Jason-3, and 0.23 and 0.30 m, respectively, compared to the buoys. Our results show that the two missions can provide good-quality SWH and can be relied upon as a new data resource of global SWH.
4）Using simultaneous observations of wind and wave fields by the CFOSAT, this project reports preliminary investigation results of the typhoon waves during the passage of super typhoon Lingling (2019) over the China offshore waters. The results show that the significant wave heights (SWHs) are over 5 m on the right side of the typhoon track for wind speeds over 14 m s-1, agreeing with the theoretical estimates. The dominant waves have wavelengths of 150 – 180 m, and propagate eastward for northwestward blowing winds. The misalignments of the wind and wave directions increase with the distance from the typhoon center, agreeing with theoretical prediction. We also present the typhoon monitoring results with multiple satellites such as CFOSAT, HY-2B and ASCAT.

Better prediction of sea state integrated parameters has a key role in the estimate of momentum and heat fluxes exchanges between ocean and atmosphere. By using deep learning technique we are now able to retrieve Significant Wave Height on the wide swath of scatterometer, as proposed by Wang et al. (2021). The objective of this work is to assess the impact of assimilating wide swath SWH and directional wave spectra from CFOSAT and Seninel-1 on the wave forecasting. We also investigated the impact of improved wave forcing on the ocean mixed layer in a coupled experiment of wave model and ocean model.

During the DRAGON-5 project we have processed two years of wide swath SWH from HY-2B-2C and CFOSAT mission. Wave model runs have been performed with data assimilation and control run for this long period. The validation of the results have been implemented with independent wave data from altimeters and also from buoys networks.

The results show the capacity of using wide swath SWH and directional wave spectra to track and well capture the initial conditions of swell generated in severe storms. We also highlight the complementary of using SWIM and SAR wave spactra for different wavelength scales. This significantly improves the wind-wave growth in critical ocean regions such as the Southern ocean.

Furtehr comments and conclusions will be given during the oral presentation.