Conference Agenda

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 2023 of the project are as follows:

1) 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.

2)Using HY-1C/D and MODIS satellite data, this project investigates the green tide biomass in the Yellow Sea and East China Sea. 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. The results show that : 1)Compared with both of pixel area and cover area, the uncertainty of biomass estimations is the least one which could reduce the scale differences involved in the area estimations evidently and could be used to quantify the green-tide monitoring . 2) Based on the CZI and MODIS data in 2021, the comprehensive monitoring of green-tide using biomass-like method has been conducted to display the reasonable spatial distributions as well as the evolution tendency with high accuracy.

3) A new method is proposed to compare and verify ocean wave spectrum by remote sensing and in situ measurements at the spectral level. Under different sea conditions and sea surface conditions，mean directional wave height spectra from surface waves investigation and monitoring (SWIM/CFOSAT) are compared at the spectral level to the buoy counterparts, in different classes of the sea state. Under medium and high sea conditions, 8 ° and 10 °SWIM spectra have a high consistency with buoy observations.Under low sea conditions, bias between SWIM and buoy observation mainly due to parasitic peak, non-linear surfboard effect and a slight underestimation of speckle noise spectral density.

4）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.

5）Icebergs are big chunks of ice floating on the ocean surface, and melting of the icebergs contribute for the major part of the freshwater flux into ocean. Dynamic monitoring of the icebergs and accurate estimation of their volume are of great importance to predict the trend of freshwater budget of the Southern Ocean. Prydz Bay in Antarctica with a large number of icebergs is selected as the study area. In this work, a normalized shadow pixel index (NSPI) is designed to identify iceberg shadows with different shapes in HY-1C/D CZI and Sentinel-2 MSI images. Besides, the iceberg freeboard can be determined with considerable precision (~1.13 m). Moreover, the basal melting of icebergs has been preliminarily assessed according to the variation of iceberg freeboard using repeated MSI observations. The results indicate that icebergs in Prydz Bay were with a mean freeboard of ~56 m in early December 2022, and experienced a reduction in freeboard of ~1.89 m within two months, in correspondence with the Antarctic seasonal trend. The new methodological framework, therefore, turns out to be a reliable complementary approach to studying the iceberg freeboard in polar regions.

The use of Significant Wave Heights (SWH) on the swath of scatterometers satellite missions has been shown to be of great interest for monitoring wave propagation in storm conditions and improving wave forecasting in coastal areas. In this work, the production of swath significant wave heights for all HY2B, 2C and 2D satellite missions is pursued and assimilation tests of these data have been implemented and evaluated with independent buoys and altimeters wave data. Morever combined assimilation experiments of swath SWH jointly with CFOSAT and Sentinel-1 directional spectra have been performed with the latest CFOSAT level 2 processing (IPF-6). This latter provides improved antenna gain and directional wave spectra with better data quality filtering.
We will also present in this work the development of maximum wave height retrieval using deep learning technique for HY2 missions and their use for the detection of dangerous waves by combining with parameters computed on the directional wave spectra of CFOSAT and Sentinel-1. Extreme events with strong wave-current interactions and wave propagation in cyclone conditions have been investigated.

This work investigates the recent implementation of significant wave height from SAR wave spectra by machine learnig technique. Assimilation experiments have been performed by using SWH from Sentinel-1 and SAR and SWIM directional wave spectra. The validation with buoy wave data indicates very good consistency in terms of bias and scatter index of SWH.

Further results related to impact of the assimilation of these new wave products on the coupling with ocean model and what consequences on upper ocean mixed layer.