Conference Agenda

Altimeter and radiometer are import means for marine dynamic phenomenon monitoring by remote sensing. In this paper we will present a comprehensive comparison of marine remote sensing products e.g. wave height, mesoscale eddy, sea ice, and sea surface salinity. The performance and accuracy of remote sensing production are validated.

For oceanic dynamic production, sea surface height and significant wave height of Sentinel-3A/3B SRAL are compared at their self-crossovers and mutual-crossovers, and biases, trends and precisions of these data are analyzed. Furthermore, mesoscale eddy detection applications based on unified Sentinel-3A/3B SRAL data are analyzed by comparing with the mesoscale eddy detection results of the Jason-2/Jason-3 series satellites.

For sea surface salinity, a new method is introduced to estimate the representativeness error and apply it to the triple collocation data set of Argo, SMAP and SMOS for the year of 2015-2017. The spatial-temporal scales of all three data sets are studied and the representativeness error as well as the random errors is obtained.

For sea ice, ice freeboard extracted by CryoSAT-2 and Sentinel-3 are compared at different waveform retracking methods, snow models and retracking thresholds. Accuracy of two kinds of ice freeboard productions is also validated by Operation IceBridge data.

With an increasing number of SAR systems in space that are operated at different frequencies
and provide different imaging modes, there is a need to re-evaluate strategies for operational sea
ice mapping and for scientific process studies such as interactions between atmosphere, sea ice,
and ocean. In our presentation we will focus on aspects of using images acquired at different
radar frequencies, different polarizations, and spatial resolutions. Examples will be shown that
demonstrate how the anaylsis of sea ice conditions can be improved for a given problem such
as thin ice detection and classification or identification of ice deformation structures. For this purpose
we used L-, C-, and X-band SAR images from different satellites and from airborne campaigns
acquired over different ice regimes. We address the additional gain of complementary data sources
such as optical and thermal images and model simulations of ice growth.

Sea ice is a fundamental component of the Earth climate system since it influences directly the albedo of our planet and regulates the heat exchange between the atmosphere and the ocean. The launch of the EC/ESA's CryoSat-2 and Sentinel-3 missions offer the opportunity to observe the near real-time sea ice thickness information. However, the characteristics of individual radar types differ for the available altimeter missions. Hence, it is important and our goal to study the consistency between single sensors in order to develop long and consistent time series. Here, a comprehensive comparison between freeboard measurements of the CryoSat-2 and Sentinel-3 is tested. We first examine the relationship between snow depth and ice and radar freeboard by comparing in situ snow depth measurements from OIB missions. And then move to the intercomparison of freeboards from CryoSat-2 and Sentinel-3 to investigate the penetration of the radar signal into the snow layer. We also compare total ice freeboard calculated from CryoSat-2 and Sentinel-3 with OIB data. Further we also investigate whether we can improve the accuracy of the freeboard retrieval from CryoSat-2 and Sentinel-3 by changing the threshold used in the retracking process, and examine the merits of adjusting the retracking threshold in a quest for an accurate sea-ice freeboard estimation.

The main detection modes of the existing sea-ice microwave remote sensors are normal incidence (0°, represented by the altimeter) and medium-angle incidence (20°-60°, represented by the scatterometer and SAR). With the development of the remote sensing technology, the low-incidence-angle microwave detectors have been put into use increasingly, which are represented by the Precipitation Radar (PR, Global Precipitation Measurement program) and the Surface Wave Investigation and Monitoring (SWIM, CFOSAT Satellite). Both of the Dual-frequency Precipitation Radar (DPR) and the SWIM can observe the Pole sea ice and have the potential of the sea-ice detection. SWIM is now in the in-orbit test phase whose data has not been released yet. Therefore, the microwave scattering characteristics of the sea ice at the low-incidence angles will be studied, and the sea-ice detection capability of the DPR will been assessed based on the CryoSat-2 and DPR scatterometer data of the Antarctic Weddell Sea from 2014 to 2019 in this paper. Firstly, the Cryosat-2 and DPR backscattering coefficients are matched for the resolution and the temporal-spatial information, the type information of the objects (including three types of the sea ice, sea water and leads) provided by the Cryosat-2 L2I products are also added in. It is ensured that each point in the study area contains both the backscattering coefficients of the two remote sensors and the type information; Secondly, intra- and inter-annual analysis of the sea-ice backscattering coefficients derived from the Cryosat-2 and DPR are carried out. For example, during the period of the sea-ice freezing, developing and melting from January to December of each year, the microwave scattering characteristics of the sea-ice at the low-incidence angles are studied based on the DPR data, which are compared with the Cryosat-2 normal incidence mode. Thirdly, intra- and inter-annual analysis of the different types for the backscattering coefficients of the Cryosat-2 and DPR are carried out. For example, during the freezing period of the sea ice, the DPR backscattering characteristics of the sea ice, sea water and leads are compared, which are compared with those of the Cryosat-2. Finally, the sea-ice detection capability of the DPR at low-incidence angles is evaluated. In the next step, we will add the sea-ice thickness information for research and analysis.

The Sentinel-3A and Sentinel-3B satellites, which were equipped with SAR Rader Altimeter (SRAL), were launched by ESA on February 26, 2016 and April 25, 2018, respectively. The simultaneous observations of Sentinel-3A/3B satellite altimeters will increase the spatial and temporal coverage of altimeter global observations and improve their data application. In this study, observation data (Sea Surface Height, Significant Wave Height and backscattering coefficient) and corrections data (wet troposphere correction, ionosphere correction and sea state bias correction) of Sentinel-3A/3B SRAL are compared at their self-crossovers and mutual-crossovers, and biases, trends and precisions of these data are analyzed. Data unification method of Sentinel-3A/3B SRAL data is given based on their comparisons. Furthermore, mesoscale eddy detection applications based on unified Sentinel-3A/3B SRAL data are analyzed by comparing with the mesoscale eddy detection results of the Jason-2/Jason-3 series satellites, and the joint application capabilities of Sentinel-3A/3B SRAL data are summarized.

Sea surface salinity (SSS) is one of the key parameters for us to understand the oceans better. Since the L-band radiometers SMOS, Aquarius and SMAP have observed the SSS from space for years, the scientific community have devoted enormous efforts to the validation of the retrieved SSS data, based on the “double match” procedure between the in-situ and remote sensed measurements. However, the direct comparison based on the double match procedure has its limitations. Firstly, it assumes the in-situ data is error free and only give the relative accuracy of remote-sensed SSS data. To resolve this problem, the triple match method, which uses three independent SSS data sources to develop a triple collocation data set, can estimate the random error of all three data sets. Secondly, the in-situ data present the “point” measurements and its spatial-temporal scale is clearly smaller than the space borne SSS data which is the spatial average within the antenna footprint with the typical value of 100 km. Consequently, the in-situ data contain the true small-scale SSS variation information which cannot be resolved by radiometer retrieved SSS data. The effect of this small-scale SSS is neglected in the direct comparison method and it is regarded as a part of remote sensed SSS error which leads to an overestimation of retrieved SSS error. In the triple match method, researchers introduce the representativeness error to describe the effect of this small-scale SSS variations in high resolution SSS data. However, the estimation of representativeness error remains challenging. In this study, we introduce a new method to estimate the representativeness error and apply it to the triple collocation data set of Argo, SMAP and SMOS for the year of 2015 ~2017. The spatial-temporal scales of all three data sets are studied and the representativeness error as well as the random errors is obtained. It is founded that the ascending order of spatial-temporal scale of all three data sources is Argo, SMAP and SMOS. The representativeness error (SSS variations observed by Argo and SMAP but not by SMOS) is 0.093 psu². The random error of Argo in-situ measurements is better than 0.21 psu which is superior to the other data sources. At the spatial-temporal scale of SMOS, the random error of SMOS (0.41 psu) is better than SMAP (0.45 psu). But at the spatial-temporal scale of SMAP, SMAP has the lower random error (0.32 psu) than SMOS (0.51 psu).

he amplitude of internal solitary waves is one of the key techniques for parameters inversion on remote sensing images. The relationship is established, which aims to match optical remote sensing characteristic parameters with internal solitary wave factors. In this paper, based on the mechanism of optical remote sensing imaging, combined with the dimension analysis method and similarity principle of hydrodynamics, an optical remote sensing detection system for internal solitary waves is constructed in the laboratory, as shown in Figure 1. The optical remote sensing imaging characteristics of internal solitary waves under the condition of two-layer fluid are studied. Internal solitary waves are generated in a three-dimensional straight flume by gravity collapse method. Optical platform and observation recording equipment are set up to complete the continuous synchronous observation of optical remote sensing images and internal solitary wave factor images in the field of view. The optical remote sensing response of internal solitary waves is detected in the laboratory.

The convergence and divergence of surface are modulated by the propagation of internal solitary waves in the pycnocline. In addition to bright-dark pattern distance, the grayscale change is also a significant phenomenon in the experiment. Figure 2 shows the synchronous response of optical remote sensing of internal solitary waves extracted by time series method. Therefore, the relationship between gray difference of optical remote sensing images and amplitude of internal solitary waves is explored in the laboratory. The amplitude of the incident internal solitary wave is setting by the height of gravity collapse, the water stratification is setting by the thickness ratio of upper and lower fluid. The experimental results show that the gray difference caused by internal solitary waves on optical remote sensing images increases with the increase of amplitude. The linear fitting for the scatters is shown in Figure 3. The relationship between gray difference and amplitude of all collapse heights under the same stratification is Δgray=0.57A+0.80. With the increase of the proportion of upper water depth to total water depth, the gray difference caused by internal solitary waves with the same amplitude decreases, as shown in Figure 4. The quantitative expression is k_Δgray-A=4.00exp(-8.13h₁/h). The change of grayscale coincides with the fact that the upper layer of the real ocean is thicker in winter and internal solitary waves with small amplitude are difficult to be observed.

Since the large-scale bloom in 2008, green tide, as a marine natural disaster, happens every year along the coast of Qingdao. It brings huge economic losses to society every year. So, obtaining the real time dynamic information about green tide distribution becomes very urgent. Generally, researches on green tide are mainly focused on the coverage area. For Operational Application of Disaster Emergency Response,the influence rangeof the green tide is what people isconcerned about. The influence rangeof the green tide can not only give information about the gaps between small green tide patches but also show the trend of development of greed tide. Our research is mainly about the influence range of the green tide. Wedesigned an algorithm for extracting the green tide distribution boundaries automatically.Principle of the algorithmis based on mathematical morphology dilation/erosion operation. Several issues such as the division of green tide regions, the extraction of basic distributions, the abnormity of distribution contour, and the elimination of islands, are solved in the paper. Since green tide mainly bursts along the Qingdao Coast and there is no established system so far, a green tide monitoring system is built. The system is based on IDL/GIS secondary development technology in the integrated environment of RS and GIS. It has the abilities of RS monitoring and information extraction. Optical remote sensing and microwave remote sensing are employed in this system. Special processing flow and information extraction algorithm are designed according to the different characteristics of these data. Without using this system, a complete data process from beginning to endingneeds 2 hours, but it can be finished in 10-15 minutes now in our system. The system runs smoothly and successfully in the State Oceanic Administration for three years till now.

Mesoscale eddies are rotating coherent structures of ocean currents, which generally refer to ocean signals with spatial scales from tens to hundreds of kilometers and time scales from days to months. Eddies can be found nearly everywhere in the world ocean, and dominate the ocean’s kinetic energy. Over the recent decades, with the advancements in remote sensing satellites and the abundance of in-situ observations data, people find that mesoscale eddies can transport water, heat, salt, and energy as they propagate in the ocean. By combining satellite altimetry and Argo profiling float data, the analysis of eddy three-dimensional structure becomes an important part of studying the oceanic eddy.

The South China Sea (SCS) is the largest marginal sea in the tropics and has a maximum depth of over 5000 m. Mesoscale eddies are an important phenomenon in the SCS, that change dynamic conditions within the ocean and play an important role in the transport of heat, salt and other chemical substances. SCS climate is part of the East Asia monsoon system. In winter, the SCS is dominated by the strong northeasterly monsoon, whereas in summer the winds reverse direction to southwesterly. The alternating monsoons in winter and summer lead to the transformation of the upper circulation and formation of several seasonal eddies in the SCS. The higher eddy kinetic energy (EKE) centers in the SCS are observed to the east of Vietnam and to the west of Taiwan, areas that are also characterized as having high mesoscale eddy activity.

In this paper, we investigated mean properties and the spatiotemporal variability of eddies in the SCS, identified using the winding angle method and 25 years of satellite altimetry data. A series of statistical analysis methods were used to study the statistical characteristics of the mesoscale eddies in the region, e.g., eddy number and lifetime, geographical distribution of eddies, evolution of eddy properties, and seasonal variation of eddy activities. Then, based on Argo profile data and climatology data, the eddy synthesis method is used to construct the three-dimensional temperature and salt structure of the eddy in SCS. The growth and decay of long-lived eddies and characteristics and mechanism of temporal variation in eddy activity are incompletely documented.

During the last decade the radar altimetry has entered in its golden age as demonstrated by the different number of missions (Jason-2/-3, CryoSat-2, Saral/Altika, Sentinel-3) currently operating and the forthcoming ones (Sentinel-6). The relatively new operational synthetic aperture radar (SAR) mode in CryoSat-2 and Sentinel-3 missions, opens a new paradigm in the capabilities that can offer an altimetric radar mission. In this line, a scientific proposal within the DRAGON-4 tries to exploit the lessons learned from classical 2-D SAR focusing to evaluate the imaging-like capability of delay-Doppler altimetric radar mounted on Sentinel-3 over coastal areas. In this way, the altimetric product gets closer to the conventional SAR imaging data, but in the altimeter case a “strip-like” image is obtained compared to the classical 2D SAR image.

Conventional delay-Doppler processor (DDP) coherently integrates a series of pulses (around some miliseconds) to provide specific Doppler beams focused to a specific location, which after being correctly aligned provide several looks that can be incoherently averaged, increasing the performance in terms of geophysical retrieval and leading to along-track resolutions of ~300 m. The fully focused DDP moves one step ahead and performs a coherent processing over the entire aperture defined by the along-track antenna beamwidth (around some seconds) to get an even higher along-track resolution (~0.5 m) and with higher number of looks for the same resolution as the conventional DDP.

The main objective of the scientific proposal within the DRAGON-4 is to evaluate the potential capabilities offered by the fully focused DDP (FF-DDP), specifically when exploiting state-of-the-art Sentinel-3 operational synthetic aperture radar (SAR) mode. This will confer the SAR altimetric product a very high resolution (in the order of 0.6 m) of great interest for Coastal Altimetry (being able to get closer to the coastline), providing much higher number of looks that can be averaged to improve the altimetric performance as anticipated by Raney in [RD-1].

The core of this presentation is to show the operation of the FF-DDP and its evaluation using simulated data. The current implementation of the processor, based on a backprojection algorithm, will be revisited. The potential capability of the FF-DDP in terms of resolution will be verified using point target simulations. This exercise will be complemented by processing open ocean scenario simulations with a comparison on the retrieved waveforms against conventional DDP. ESA Sentinel-6 simulated data with its two operation modes (RAW and RMC) will be exploited as testbed; these data sets might be complemented with simulations from the new altimetric mission proposal PICE (polar ice).

References:

[RD- 1] Raney, R. K., 1998. The delay/Doppler radar altimeter. IEEE Transactions on Geoscience and Remote Sensing, 36, 1578–1588. doi:10.1109/36.718861.

[RD- 2] Egido, A., & Smith, W. H. F., 2017. Fully Focused SAR Altimetry: Theory and Applications, in IEEE Transactions on Geoscience and Remote Sensing, 55, 1, 392-406, Jan. 2017. doi: 10.1109/TGRS.2016.2607122

[RD- 3] E. Makhoul, M. Roca, R. Escolà, A. Garcia-Mondejar, G. Moyano, P. Garcia, M. Fornari, M. Kuschnerus, R. Cullen. S6 P4 GPP: Fully Focused Delay-Doppler Processing applied on RAW and RMC data- preliminary results, in Ocean Surface Topography Science Team Meeting, 27-28 September 2018.