OS4.4 | Ocean Remote Sensing
Ocean Remote Sensing
Convener: Aida Alvera-Azcárate | Co-conveners: Tong Lee, Craig Donlon, Guoqi Han, Adrien Martin
| Tue, 16 Apr, 16:15–18:00 (CEST)
Room L2
Posters on site
| Attendance Tue, 16 Apr, 10:45–12:30 (CEST) | Display Tue, 16 Apr, 08:30–12:30
Hall X4
Posters virtual
| Attendance Tue, 16 Apr, 14:00–15:45 (CEST) | Display Tue, 16 Apr, 08:30–18:00
vHall X5
Orals |
Tue, 16:15
Tue, 10:45
Tue, 14:00
Advanced remote sensing capabilities have provided unprecedented opportunities for monitoring and studying the ocean environment as well as improving ocean and climate predictions. Synthesis of remote sensing data with in situ measurements and ocean models have further enhanced the values of oceanic remote sensing measurements. This session provides a forum for interdisciplinary discussions of the latest advances in oceanographic remote sensing (using electromagnetic or acoustic waves) and the related applications and to promote collaborations.

We welcome contributions on all aspects of the oceanic remote sensing and the related applications. Topics for this session include but are not limited to: physical oceanography, marine biology and biogeochemistry, biophysical interaction, marine gravity and space geodesy, linkages of the ocean with the atmosphere, cryosphere, and hydrology, new instruments and techniques in ocean remote sensing, new mission concepts, development and evaluation of remote sensing products of the ocean, and improvements of models and forecasts using remote sensing data. Applications of multi-sensor observations to study ocean and climate processes and applications using international (virtual) constellations of satellites are particularly welcome.

Orals: Tue, 16 Apr | Room L2

Chairpersons: Aida Alvera-Azcárate, Tong Lee, Adrien Martin
Sollicited talk
On-site presentation
Ivona Cetinic and Jeremy Werdell

The PACE mission, scheduled to launch in Feb 2024, represents NASA’s next great investment in ocean biology, clouds, and aerosol data records to enable advanced insight into ocean and atmospheric responses to Earth’s changing climate. A key aspect of PACE is its inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI) to measure the “colors” of the ocean, land, and atmosphere. Whereas heritage instruments observe roughly six visible wavelengths from blue to red, OCI will collect a continuum of colors that span the visible rainbow from the ultraviolet to near infrared and beyond. In doing so, OCI will be the first of its kind to collect such “hyper”spectral radiometry on daily global scales, which will allow unique and highly advanced continuous identification of aquatic phytoplankton communities, as well as atmospheric aerosol, cloud, and terrestrial data products. PACE will also include two small multi-angle polarimeters that also measure “color”, but with additional capabilities to do so in multiple directions and with consideration of polarized light. Both polarimeters will substantially improve how we view our atmosphere and the interaction of airborne particles and clouds.  Overall, This PACE instrument suite will revolutionize studies of global biogeochemistry, carbon cycles, and hydrosols / aerosols in the ocean-atmosphere system.

How to cite: Cetinic, I. and Werdell, J.: Keeping the PACE with the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4682, https://doi.org/10.5194/egusphere-egu24-4682, 2024.

On-site presentation
Chiara Volta, Salvatore Marullo, and Sandro Calmanti

Previous studies, based on satellite observations, suggested that global warming caused all subtropical gyres to expand over time (Polovina et al., 2008; Leonelli et al., 2022). This raised major concerns about the potential increase in ocean desertification and its impact on the Earth’s climate system. Here, the longest satellite chlorophyll-a (chl-a) concentration dataset currently available is used to analyze the evolution of the most oligotrophic areas in the five major subtropical gyres on Earth at a fine spatial-temporal resolution over 25 years (January 1998 - December 2022). These gyres include the North and South Atlantic SubTropical Gyres (NASTG and SASTG, respectively), the North and South Pacific SubTropical Gyres (NPSTG and SPSTG, respectively), and the Indian Ocean SubTropical Gyre (IOSTG). Different thresholds of chlorophyll-a concentrations are used to defined three subregions within each gyre: the oligotrophic area, whose chl-a is less than or equal to 0.1 mg m-3, and the ultra- and hyper- oligotrophic areas where chl-a does not exceed 0.07 and 0.04 mg m-3, respectively. Our results indicate that ultraoligotrophic conditions prevail in all five systems, and that oligotrophic and ultraoligotrophic zones in all gyres combined have reduced and expanded, respectively, at the same rate (0.3%/yr) since 1998, while the hyperoligotrophic area has increased globally at an annual rate of 3.4%. Results also reveal that the most affected gyres are the NASTG, the NPSTG and the IOSTG, where the hyperoligotrophic subregions have expanded at an annual rate of 17.8, 22.8 and 8.6%, respectively, and their combined area in 2022 was about 5 times larger than it was in 1998. No statistically significant (p>0.05) trends were detected in the SASTG and SPSTG, although an increasing tendency in their hyperoligotrophic subregions is observed. Altogether, the results suggest that, despite no significant variation in the overall size of subtropical gyres being observed in 25 years, their hyperoligotrophic cores are expanding and would lead to reduced productivity in these systems.


Polovina, J.J., Howell, E.A., and Abecassis, M. (2008). Ocean’s least productive waters are expanding. Geophysical Research Letters, 25, L03618, doi:10.1029/2007GL031745

Leonelli, F.E., Bellacicco, M., Pitarch, J., Organielli, E., Buongiorno Nardelli, B., de Toma, V., Cammarota, C., Marullo, S., and Santoleri, R. (2022). Ultra-oligotrophic Waters Expansion in the North Atlantic Subtropical Gyre Revealed by 21 Years of Satellite Observations. Geophysical Research Letters, 49, e2021GL096965, doi:10.1029/2021GL096965

How to cite: Volta, C., Marullo, S., and Calmanti, S.: Variability and trends in subtropical gyres derived from 25-year satellite chlorophyll-a observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9426, https://doi.org/10.5194/egusphere-egu24-9426, 2024.

On-site presentation
Chiara Lapucci, Andrea Antonini, Emanuele Böhm, Emanuele Organelli, Luca Massi, Alberto Ortolani, Carlo Brandini, and Fabio Maselli

Assessing and monitoring water ecological quality in coastal areas is crucial for safeguarding marine ecosystems, and consequently has a central role in European Union environmental policies. In this work we present the use of in situ monitoring and satellite Earth Observation (EO) techniques as an innovative approach to assess water quality using machine learning. This study shows the use of Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery from Copernicus Marine Service to evaluate the ecological quality of Italian coastal waters, focusing on the Trophic Index (TRIX, Vollenweider et al., 1998), used as a key indicator within the Marine Strategy Directive (2008/56/EC) to characterize the trophic status of coastal waters. Specifially, we investigated the possibility of integrating remote sensing and machine learning techniques to estimate TRIX levels in Italian coastal waters, using an in situ dataset for TRIX estimation obtained from the Marine Strategy Directive Monitoring database (ISPRA). Given that TRIX computation is traditionally based on in situ data, the exploitation of satellite data presents an opportunity to obtain it on a larger spatial and temporal scale. As the TRIX index relies significantly on chlorophyll a, that often exhibits correlations with other components (Massi et al., 2019), we initially explored the relationships between TRIX variables, especially chlorophyll a concentration, and water spectral reflectance using in situ multispectral observations. Encouraged by the results, the effectiveness of OLCI full-resolution data was tested for evaluating the trophic status of Tuscany coastal waters. Our findings initially showed distinctive geographic patterns of in situ TRIX values in the Ligurian, Tyrrhenian, and Ionian coastal regions of Italy, revealing regions with eutrophic conditions near estuaries and others exhibiting oligotrophic characteristics. A Random Forest Regression algorithm was applied to this database, constituted by in situ data and OLCI data, optimizing calibration parameters to predict TRIX levels. This method, via the Feature Importance analysis, underscored the significance of specific spectral bands related to chlorophyll spectral response. The statistical analysis validates the model's performance, indicating in the initial test described above a moderate level of error (MAE of 0.51) and satisfactory explanatory power (R2 of 0.37) (Lapucci et al., 2023). These outcomes show the potentiality of a synergistic use of remote sensing and machine learning in environmental monitoring and management. Current investigations are aimed at refining methodologies and broaden datasets to further test and enhance TRIX monitoring capabilities from a spatial perspective.


  • Vollenweider, R.A.; Giovanardi, F.; Montanari, G.; Rinaldi, A. Characterization of the trophic conditions of marine coastal waters with special reference to the NW Adriatic Sea. Environmetrics 1998, 9, 329–357.
  • Massi, L.; Maselli, F.; Rossano, C.; Gambineri, S.; Chatzinikolaou, E.; Dailianis, T.; Arvanitidis, C.; Nuccio, C.; Scapini, F.; Lazzara,L. Reflectance spectra classification for the rapid assessment of water ecological quality in Mediterranean ports. Oceanologia 2019,61, 445–459.
  • Lapucci, C.; Antonini, A.; Böhm, E.; Organelli, E.; Massi, L.; Ortolani, A.; Brandini, C.; Maselli, F. Use of Sentinel-3 OLCI Images and Machine Learning to Assess the Ecological Quality of Italian Coastal Waters. Sensors 2023, 23, 9258.


How to cite: Lapucci, C., Antonini, A., Böhm, E., Organelli, E., Massi, L., Ortolani, A., Brandini, C., and Maselli, F.: Integrating satellite remote sensing and Machine Learning techniques for ecological quality assessment in Italian coastal waters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18960, https://doi.org/10.5194/egusphere-egu24-18960, 2024.

On-site presentation
Clovis Thouvenin-Masson, Jacqueline Boutin, Vincent Echevin, Alban Lazar, and Jean-Luc Vergely

​​​​​In tropical regions, the fresh water flux entering into the ocean originates primarily from precipitations and, in a lesser extent, from continental rivers. Nevertheless, at regional scale, river flows can have a significant impact on the surface ocean dynamics. Riverine fresh water modifies salinity, and therefore density, stratification and circulation in the surface layer. The eastern Southern North Tropical Atlantic (e-SNTA) region off Northwest Africa, with its particular coastline, relatively high cumulative river discharge and the vicinity of ITCZ, is a particularly interesting location to study the linkage between precipitations, river flows and Sea Surface Salinity (SSS). In particular, the effect of river flows interannual anomalies on SSS have been unexplored in this region.

In this work, we focus on the regional SSS interannual variability, and their relations to river discharge and rainfall. We quantify the impact of these forcings on surface salinity and dynamics, combining informations coming from the CROCO regional ocean model and from SSS remote sensing.  Several simulations forced by different interannual and climatological forcings are analyzed. We compare the simulated SSS with satellite (ESA CCI product), in-situ (Argo, ships and Melax mooring datasets), and Glorys reanalysis. The mixed layer salinity budget is investigated to better understand the dynamics driving SSS variability.

Overall, the simulations are in good agreement with the observations, with a slight statistical improvement in the river plume regions when using ISBA interannual runoff and IMERG precipitation. 
We find that interannual SSS variability depends on surface circulation, river discharge, precipitation and wind variability.  Strong anomalies are mostly linked to strong precipitation anomalies. The impact of river discharge is highly dependent on surface currents. This highlights the importance of properly constraining river runoff and precipitation to simulate realistic sea surface salinities. 

This study shows the value of satellite salinity data for validating ocean models, and highlights the potential contribution of future L-band radiometric missions for coastal ocean observation.

How to cite: Thouvenin-Masson, C., Boutin, J., Echevin, V., Lazar, A., and Vergely, J.-L.: Interannual variability of Sea Surface Salinity in North-Eastern tropical Atlantic: influence of freshwater fluxes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17817, https://doi.org/10.5194/egusphere-egu24-17817, 2024.

On-site presentation
Florian Le Guillou, Marie-Helene Rio, Daniele Ciani, Andrea Storto, and Bruno Buongiorno Nardelli

For many years, satellite observations of sea surface height (SSH) and sea surface temperature (SST) have provided invaluable information on the dynamics of the upper ocean at many scales. SSH and SST variables are dynamically linked, and are very often used together for many scientific studies (e.g. estimating heat transport in the upper layer by SSH-derived geostrophic currents). As observations are unevenly distributed in space and time (SSH is measured along one-dimensional trajectories and SST measurements are affected by clouds), many scientific and operational applications rely on gridded SSH and SST products. However, these products suffer from two main limitations. Firstly, conventional mapping techniques rely on static optimal interpolation schemes, which limits the estimation of nonlinear dynamics at scales poorly sampled by altimetry or, for SST, in regions densely affected by clouds (e.g. near western boundary currents). Secondly, SSH and SST reconstructions are performed separately, without relying on synergies between the two variables, which has an impact on the consistency of the two reconstructed fields.

We introduce an original dynamical mapping algorithm to simultaneously reconstruct SSH and SST from multi-sensor satellite observations. This innovative method combines a weakly constrained, reduced-order, 4-dimensional variational scheme with simple physical models – quasi-geostrophic for SSH and advection-diffusion for SST. The weak constraint of the models on the inversion procedure ensures that the reconstructed SSH and SST fields closely match the observations while preserving the space-time continuity of the dynamical structures.

The work focuses on the North Atlantic Ocean over the year 2023 and considers the available along-track altimetric SSH, microwave and infrared SST data. The performances of the method are evaluated through Observing System Experiments, utilizing independent altimetric (from conventional and SWOT satellites) and drifter data. Results show a significant improvement of the reconstruction of short energetic structures, both in terms of SSH and SST, compared to operational products. The benefit of using SST observations for reconstructing SSH fields increases as the number of altimeters is reduced. This opens new opportunity to use the method for sea-level related climate applications that rely on a stable two altimeters constellation.

How to cite: Le Guillou, F., Rio, M.-H., Ciani, D., Storto, A., and Buongiorno Nardelli, B.: Simultaneous dynamical reconstructions of Sea Surface Height and Temperature from multi-sensor satellite observations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17175, https://doi.org/10.5194/egusphere-egu24-17175, 2024.

On-site presentation
Zorana Jelenak, Paul Chang, and Suleiman Alsweiss

The first satellite microwave sea surface temperature (MSST) estimates were provided from TRMM Microwave Imager radiometer on board of Tropical Rainfall Microwave Mission in 1997. Since then the MSST became on of one of most sought after parameters for new microwave missions in both operational and research communities. In that respect the WindSat, AMSR-E, ASMR-2 and GMI instruments all empployed either C- or X-band channels or both in order to provide the SST measurements. While the resolution of MSST is relativly course due to utilization of the low frequency channels, the main advantage of the MSST is in its ability to fill the gap in observations in cloud covered regions. While However the SST coverage is still spars heavy clouds and precipitation areas.

To maximaze utility of MSST for operations we investigated different combinations of microwave brighntess temperatures that minimize precipitation effect on measurements and maximaze its sensitivity to SST. Guided by this goal we developed a statistically based algorithm that relies on three empirical quantities utilizing linear combinations of 6, 10 and 18GHz vertically and horizontally polirized channels. This approach allowed us to come up with the unique, first of a kind MSST product from AMSR-2 microwave ocean observations that provides SST estimates even in the heavy precipitation areas such as one observed within Tropical Cyclones. Utilization of higher frequency channels had an added advantage of increasing the the MSST resolution relative to products that utilized only 6 or 10GHz measurements. Another added advantage was substantially minimized sun glint areas that were traditionally excluded from measurements swaths and resulted in substantially reduced coverage in the southern hempisphere.

The measurement technique, validation results and data availability will be discussed and presented.

How to cite: Jelenak, Z., Chang, P., and Alsweiss, S.: Sea Surface Temperature Retrievals in Heavy Precipitation From AMSR-2 Microwave Measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12124, https://doi.org/10.5194/egusphere-egu24-12124, 2024.

On-site presentation
Francesco De Biasio, Stefano Vignudelli, and Ron Abileah

In the Northern Adriatic Sea, the Marano-Grado and Venice coastal lagoons lay at the edge of a coastal plain of 2.400 km2 of low-lying areas along 300 km of coast (Bondesan et al., 1995). Defined as geographically distinct water bodies, coastal lagoons are shallow, enclosed by barriers, intermittently connected to the ocean through restricted inlets, and typically aligned parallel to the shore (Tagliapietra et al., 2009). Such sheltered coastal regions are characterized by slow water flow, low waves and intertidal marshes partially protecting the surface from wind. However, they face dual threats of storm surges and rising sea level, which shape their geomorphological evolution.

Satellite radar altimetry emerges as an indispensable tool for studying these environments, as traditional tide gauges are insufficient for discerning sea level changes independent of land shifts. Unlike classical open ocean altimetry, which loses accuracy within 10–15 km of the coast, modern coastal altimetry, bolstered by advancements like Delay-Doppler processors and high burst-repetition frequencies (e.g., 80 Hz), extends reliable coverage to sheltered coastal areas. Recent enhancements, such as the implementation of SAR and SARin processing algorithms developed by the HYDROCOASTAL project team, further strengthen the capabilities of coastal altimetry (https://eo4society.esa.int/projects/hydrocoastal/) and are implemented in the ESA GPOD/Earth Console® Altimetry Virtual Lab service. Notably, the PISA algorithm, specializing in conditions like specular reflection, leverages Radar Cross Section (RCS) classification to distinguish between specular, quasi-specular, and non-specular behavior (Abileah and Vignudelli, 2021). This algorithm capitalizes on the superior signal-to-noise ratio of specular surfaces, enabling precise range retrieval in challenging scenarios.

In this study, high-resolution radar data are employed in the examination of the Venice and Marano-Grado coastal lagoons. The Marano-Grado Lagoon serves as a validation platform, with a comparative analysis of data in two Sentinel-3 tracks. Subsequently, the utility of these data, encompassing wind speed and significant wave height, is evaluated within the coastal zone of the Venice Lagoon. These two coastal zones are chosen not only for their geographical significance but also due to the availability of in-situ observations from various instruments, including tide gauges, wave recorders, and wind instruments: this multi-instrumental approach offers distinct advantages for comprehensive comparison and interpretation purposes.

The motivation driving this study is rooted in the recognition of approximately 32,000 lagoons, spanning 13% of the world's coastline (Carter et al., 1996; Barnes, 1980). Limited in-situ measurements, particularly in developing nations, propel the reliance on satellite data as the most viable option for monitoring sea level changes. The cost and logistical challenges associated with in-situ observations further underscore the importance of satellite altimetry in providing a seamless observational continuum across open oceans, coastal regions, and inland waters.


Bondesan et al. (1995). Journal of Coastal Research, 1354-1379.

Tagliapietra et al. (2009). Marine and freshwater Research, 60(6), pp.497-509, doi:10.1071/MF08088.

Abileah and Vignudelli (2021). Remote Sensing of Environment, 264, 112580, doi:10.1016/j.rse.2021.112580.

Carter and Woodroffe (1995). ISBN 0521598907. doi:10.1017/CBO9780511564420.

Barns (1981). Journal of the Marine Biological Association of the United Kingdom, 61, 2, pp. 549, doi:10.1017/S0025315400047135. 

How to cite: De Biasio, F., Vignudelli, S., and Abileah, R.: Satellite Altimetry In Coastal Lagoons: The Case Of The Marano-Grado And Venice Lagoons In The Northern Adriatic Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21059, https://doi.org/10.5194/egusphere-egu24-21059, 2024.

On-site presentation
Marcello Passaro, Florian Schlembach, Frithjof Ehlers, Marcel Kleinherenbrink, Denise Dettmering, Florian Seitz, and Cornelis Slobbe

Estimating the three geophysical variables significant wave height (SWH), sea surface 
height, and wind speed from satellite altimetry continues to be challenging in the 
coastal zone because the received radar echoes exhibit significant interference from 
strongly reflective targets such as mud banks, sheltered bays, ships etc. Fully focused 
SAR (FF-SAR) processing exhibits a theoretical along-track resolution of up to less 
than half a metre. This suggests that the application of FF-SAR altimetry might give 
potential gains over unfocused SAR (UF-SAR) altimetry to resolve and mitigate smallscale 
interferers in the along-track direction to improve the accuracy and precision of 
the geophysical estimates. 

The objective of this study is to assess the applicability of FF-SAR-processed Sentinel- 
6 Michael Freilich (S6-MF) coastal altimetry data to obtain SWH estimates as close as 
possible to the coast. 
We have developed a multi-mission FF-SAR processor and applied the coastal 
retracking algorithm CORALv2 to estimate SWH. We assess different FF-SAR and UFSAR 
processing configurations, as well as the baseline Level-2 product from 
EUMETSAT, by comparison with the coastal, high-resolution SWAN-Kuststrook wave 
model from the Deltares RWsOS North Sea operational forecasting system. This 
includes the evaluation of the correlation, the median offset, and the percentage of 
cycles with high correlation as a function of distance to the nearest coastline. 
Moreover, we analyse the number of valid records and the L2 noise of the records. The 
case study comprises five coastal crossings of S6-MF that are located along the Dutch 
coast and the German coast along the East Frisian Islands in the North Sea. 

We find that the FF-SAR-processed dataset with a Level-1b posting rate of 140 Hz 
shows the greatest similarity with the wave model. We achieve a correlation of ~0.8 at 
80% of valid records and a gain in precision of up to 29% of FF-SAR vs UF-SAR for 1- 
3 km from the coast. FF-SAR shows, for all cycles, a high correlation of greater than or 
equal to 0.8 for 1-3 km from the coast. We estimate the decay of SWH from offshore at 
30 km to up to 1 km from the coast to amount to 26.4%+-3.1%. 

How to cite: Passaro, M., Schlembach, F., Ehlers, F., Kleinherenbrink, M., Dettmering, D., Seitz, F., and Slobbe, C.: Benefits of fully focused SAR altimetry to coastal wave height estimates: A case study in the North Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5859, https://doi.org/10.5194/egusphere-egu24-5859, 2024.

On-site presentation
Romain Husson, Annabelle Ollivier, Beatriz Molero, Charles Peureux, Baptiste Gombert, Manal Yassine, Pierre Dubois, Adrien Nigou, Lotfi Aouf, Cedric Tourain, Gérald Dibarboure, and Alejandro Bohé


Various spaceborne Radar instruments are now operating with the common ability to observe long waves propagating across the oceans: the C-band Synthetic Aperture Radar (SAR) onboard Sentinel-1 (~23-36° of incidence), SWIM rotating Ku-band Radar onboard the Chinese-French CFOSAT satellite (~2 to 10° of incidence) and the Ka-band radar Interferometer (KaRIn) onboard the Surface Water Ocean Topography (SWOT) (1 to 5° of incidence).  

The directional swell measurements are investigated using model and in situ measurements but also co-locations between the spaceborne instruments (also known as cross-overs in altimetry). These latter co-locations involve both static and so-called “dynamic co-locations" where waves are propagated using a linear wave propagation model over a few hundred kilometers to maximize the number of co-locations between the sensors. Intercomparisons can therefore be performed either for specific case studies or for massive statistical comparisons. 

In this study, we use wave measurements from Sentinel-1A (S1-A) wave mode Level-2 Ocean (OCN) products (distributed by ESA) and SWIM L2P products from the new Near-Real Time (NRT) processing that extends the range of swell measurements up to 1200m wavelength (500m before) and better filter non-wave signatures (distributed by CNES/CLS, Q1 2024). We also investigate the possibility to use KaRIn SWOT spectral content of measurements from either the Sigma0 or the Sea Surface Height Anomaly (SSHA) observations to image so-called “forerunners”, the longest period swells that propagate ahead of the most energetic swell components (from Munk 1947). 

Intercomparisons show the promising synergies between these sensors and the potential to derive worldwide multi-sensor swell monitoring. First, SWIM shows great capabilities to image the shortest swell that S1 can totally miss or partially image because of its cutoff limitation. Then, S1 has shown capabilities to observe long swell (with peak wavelength larger than 800m), but their imaging mechanism is still limited by the reduced velocity bunching and tilt modulation of longest forerunners. On the other hand, comparisons with SWOT indicate that KaRIn unsmoothed (ocean data at their highest resolution) SSHA measurements can further extend the range of visible swell up to kilometric scales thanks to its interferometric capability. 

A significant work is still necessary to better understand, compare and inter-calibrate these directional swell measurements but they offer very promising perspectives for the exhaustive description of swell events, from the longest forerunners to the short wind sea. 

How to cite: Husson, R., Ollivier, A., Molero, B., Peureux, C., Gombert, B., Yassine, M., Dubois, P., Nigou, A., Aouf, L., Tourain, C., Dibarboure, G., and Bohé, A.: Comparing and combining directional swell measurements from Sentinel-1, SWIM and SWOT, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17323, https://doi.org/10.5194/egusphere-egu24-17323, 2024.

Posters on site: Tue, 16 Apr, 10:45–12:30 | Hall X4

Display time: Tue, 16 Apr 08:30–Tue, 16 Apr 12:30
Chairpersons: Tong Lee, Adrien Martin, Guoqi Han
Haoyu Jiang

The validation and error analysis of remote sensing data are important for their application. Currently, due to the relative scarcity of in-situ observations in the ocean, the accumulation of collocations between remote sensing and in-situ data is slow. This study proposes an engineering trick to address this issue: using the output of numerical models as a "bridge" to connect remote sensing data with in-situ data, thereby expanding the spatiotemporal window of collocation and improving collocation efficiency. The basic idea of this method is that numerical models based on differential equations can partially simulate the local spatiotemporal variations of the parameter near in-situ data. These variations can be used to compensate for the representation errors caused by the spatiotemporal differences between remote sensing and in-situ observations. Therefore, this method can enlarge the spatiotemporal window for collocation when the error limit is given. This collocation process considers the dynamic processes through numerical models and is thus named "dynamic collocation." This study demonstrates through several simple experiments that this dynamic method is superior to traditional "static" windows and has application potential. In addition to improving data collocation efficiency in the open ocean, dynamic collocation can also address the issue of the difficulty of direct comparison between satellite and buoy data in coastal areas due to significant spatial gradients in sea waves. Besides data comparison, dynamic collocation can provide a larger sample size for the model training of narrow swath sensors' empirical algorithms. For example, we applied this method to SWIM data from CFOSAT and proposed a high-precision empirical retrieval algorithm for wave mean periods.

How to cite: Jiang, H.: Dynamic collocation between satellite and in-situ measurements in wave remote sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3336, https://doi.org/10.5194/egusphere-egu24-3336, 2024.

Lung-Chih Tsai, Chien Hwa, Shin-Yi Su, and Jun-Xian Lv

In this study, low-cost software-defined GPS and SBAS Reflectometry (GPS&SBAS-R) systems have been built and proposed to measure ocean-surface wave parameters on board the research vessel New Ocean Researcher 1 (R/V NOR-1) and other ground-based coastal stations of Taiwan. A power-law ocean wave spectrum model has been used and applied with the Small Perturbation Method (SPM) approach to solve the electromagnetic wave scattering problem from rough ocean surface and compare with experimental seaborne GPS&SBAS-R observations. Meanwhile, the intensity scintillations of high-sampling GPS&SBAS-R signal acquisition data are thought to be caused by the moving rough surfaces of the targeted oceans. We found that each derived scintillation power spectrum is a Fresnel filtering result on sea/ocean-surface elevation fluctuations and depends on the First Fresnel Zone (FFZ) value and the ocean-surface wave velocity. The determined ocean-surface wave parameters, e.g. wave velocity and spectral index, have been compared and validated against nearby buoy measurements.

How to cite: Tsai, L.-C., Hwa, C., Su, S.-Y., and Lv, J.-X.: Ocean-surface wave measurements using scintillation theories on seaborne and coastal software-defined GPS and SBAS reflectometry observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5059, https://doi.org/10.5194/egusphere-egu24-5059, 2024.

Anis Elyouncha, Adrien Martin, and Christine Gommenginger

Synthetic aperture radar (SAR) offers the possibility to observe the sea surface current with very high spatial resolution thanks to techniques such as Doppler centroid analysis and Along-Track Interferometry. These observations are relevant in coastal areas and shelf seas. SAR has been routinely providing valuable information on sea surface winds and waves for decades. However, the Doppler signature of the surface (aka Wind-wave Artefact Surface Velocity - WASV) is strongly affected by the waves and needs to be corrected accurately. In this study, we assess how strongly and how far convergent and divergent current fields impact the wave fields, hence the WASV. This is a numerical study, combining a numerical wave model (Simulating WAves Nearshore - SWAN) with a semi-empirical wave Doppler electromagnetic simulator (Yurovsky et al., 2019 - KaDOP).

In this study, the simulation of the effect of the wave-current interaction on the significant wave height is carried out using the SWAN model. Simulations are carried out for two different wind speeds 5 m/s and 10 m/s to represent different wave height regimes and two current profiles, convergent and divergent. The domain grid is one dimensional from x=0 to x=200 km with a spacing of 1 km. The depth is set to a constant value of 1000 m. The direction of propagation of the waves is perpendicular to the current front. Two scenarios are simulated waves propagating along the current and waves propagating against the current. The wind is set uniform over the whole fetch. The Doppler model KaDOP is used to estimate wave Doppler velocity (UD). This model takes as inputs the incidence angle, wind speed, relative wind direction, significant wave height (Hs) and peak radial frequency (Ωp) for wind sea and swell. The latter two quantities are affected by the wave-current interaction which affects the estimated wave Doppler. 

In summary, a combination of two different front widths (1 km and 3 km) and two wind speeds (5 m/s and 10 m/s) resulted in eight simulations. First,  it is shown that the spectral density increases (decreases) due to the convergent (divergent) current. The modulation is more important at the intermediate waves between the peak and around 0.6 Hz while it is negligible at the lowest and highest frequencies. As expected, the variation magnitude of Hs and UD increases with increasing magnitude of the current divergence and wind speed. It is also noted that the convergent current, when the waves propagate in a direction opposing the current, yields larger variations ∆Hs and ∆UD. Only in cases when the current front is 1 km wide, i.e. the divergence ≈ 0.19 10−3, ∆UD exceeds 0.1 m/s, but this limit is only exceeded locally (over a few pixels). 

How to cite: Elyouncha, A., Martin, A., and Gommenginger, C.: Simulation of the wave-current interaction effect on the SAR-derived radial velocity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16367, https://doi.org/10.5194/egusphere-egu24-16367, 2024.

Mingyi Chen, Yufu Liou, Kanghung Yang, and Hwa Chien

    This study delves into the impact of wave age on GNSS-R L1 observations, with a specific emphasis on Delay-Doppler Map (DDM) and Normalized Bistatic Radar Cross Section (NBRCS) signal strength, as well as its consequent effects on L2 wind speed inversion. Conventionally, DDMs have been simplified in wind speed inversion algorithms to solely represent sea surface roughness influenced by wind speed. However, this research underscores the significant, yet often overlooked, role of sea surface roughness induced by wave characteristics in the reflection of microwave signals. Wave age, denoting the delay of waves under wind influence and the proportion of swell to wind waves, is identified as a crucial factor affecting sea surface roughness and, thereby, the scattering properties of ocean surface signals.

    Recognizing the intricate physical correlation between wave age and sea surface wind speed, along with the multi-variable dependency inherent in GNSS-R observation theory, the study employed machine learning techniques to assess the extent of wave age's influence throughout the observation to wind speed inversion process. For this purpose, the Resnet18 deep convolutional neural network was chosen for its adept handling of the complex features present in DDM data, which can be considered as images. This choice was anchored in Resnet18’s robust feature extraction abilities and its proven track record in tasks requiring high-accuracy image classification.

    This study utilized CyGNSS L1 data along with corresponding ECMWF wind speed and sea surface parameter data for specific time and location. To conduct a comparative analysis, two methodologies were used: a traditional geophysical model function (GMF) developed by our self and machine learning. Preliminary testing indicated a marked enhancement in the accuracy of wind speed predictions when incorporating wave age into both GMF and machine learning approaches. The root mean square error notably decreased from approximately 1.8-2 meters per second to about 1.1 meters per second. The study also found a link between wave age and NBRCS intensity distribution, noting that larger inverse wave ages correlate with more signal scattering and weaker signal strength, underlining the vital impact of wave age on NBRCS intensity distribution.

How to cite: Chen, M., Liou, Y., Yang, K., and Chien, H.: Assessing the Impact of Wave Age on GNSS-R L1 products and L2 Wind Speed Inversion, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8952, https://doi.org/10.5194/egusphere-egu24-8952, 2024.

Mariia Usoltseva, Marcello Passaro, and Denise Dettmering

Coral reefs, among other benefits, provide natural protection from waves for coastal communities. In the context of climate change and its role in the degradation of coral reefs and the intensification of extreme weather events, there has been a growing interest in understanding the sheltering properties of coral reefs. Despite this interest, there remains a lack of comprehensive studies that systematically assess wave behaviour on coral reefs using remote sensing techniques.

This study utilized along-track altimetry observations from the European Space Agency's Sea State Climate Change Initiative (CCI) v3 L3 dataset, complemented by ERA5 data, to examine the influence of coral reefs on wave height. Changes in significant wave height (SWH) on coral reefs, derived from the multi-mission altimetry dataset, are compared with those computed from ERA5 reanalysis in its gridded format and interpolated on satellite tracks. The assessment is conducted on a global and regional scale, considering different offshore sea states. Additionally, the study explores the influence of the structural complexity of coral reefs on their capacity to attenuate waves. This is achieved through a regional analysis of altimetry measurements in years with a high percentage of hard coral cover and years after destructive storms.

The results demonstrate a high degree of agreement between SWH attenuation computed from the satellite altimetry dataset and ERA5 interpolated on the satellite tracks, yielding a correlation coefficient of 0.724. Additionally, this study contributes to the expanding body of knowledge regarding the influence of coral reefs on wave height. Despite the pronounced variability contingent upon the state of coral reefs and the local wave climate, about 80% of observations show a reduction in wave height as waves traverse coral reefs. Statistical evaluation reveals an increase in the reduction of wave height with an increase in offshore wave conditions, as evident in the analysis of all three datasets. Furthermore, case studies on extreme events show a regional decrease in wave attenuation on coral reefs with reduced hard coral cover. The study highlights the potential of satellite altimetry in the observation of wave height changes across coral reefs, as well as the ability of coral reefs to attenuate waves and mitigate the destructive potential of storms, thereby contributing to coastal protection and resilience.

How to cite: Usoltseva, M., Passaro, M., and Dettmering, D.: Effect of Coral Reefs on Wave Height, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10674, https://doi.org/10.5194/egusphere-egu24-10674, 2024.

Ocean-wave retrieval from Sentinel-6 radar altimeter cross-spectra
Sergi Hernández, Marcel Kleinherenbrink, Ferran Gibert, and Michel Guerra
An Cheng, Huan Meng Chang, Hwa Chien, and Hsin Yu Yu

    This study focuses on the spatiotemporal analysis of High Frequency Radar (HFR) signal intensity under various environmental conditions, utilizing data from four LERA MKIII systems along the northern coast of Taiwan. This investigation spans from 2023 to 2024. The radar systems are strategically positioned at different locations: Shalun station operates at 24.4 MHz with a boresight angle of 0 degrees, Beigang station at 26.77 MHz with a boresight of 345 degrees, Chaojing station at 27.75 MHz with a boresight of 0 degrees, and Zhongjiao Bay station at 31.75 MHz with a boresight of 55 degrees. The coordinates for these stations are respectively 121.24°E, 25.11°N (Shalun); 121.16°E, 25.08°N (Beigang); 121.80°E, 25.14°N (Chaojing); and 121.63°E, 25.24°N (Zhongjiao Bay). Each HFR system consists of a linear array of 16 receiving antennas and utilizes the beamforming method to process signals within a boresight angle range of ±60 degrees.
    This study's methodology employs time series analysis techniques to scrutinize High Frequency Radar (HFR) data, correlating it with various environmental observations. By charting the Signal-to-Noise Ratio (SNR) of the radar signals across different range cells along the radar's boresight azimuth over time, we identify temporal and spatial trends. Notably, periodic fluctuations in the radar signal time series have been observed. These fluctuations seem intricately linked to tidal cycles, exhibiting a significant correlation with the angular disparity between tidal flow direction and the radar's boresight azimuth. Additionally, a decrease in radar signal strength coupled with an increase in noise levels was noticed under conditions of elevated winds and waves. The research aims to precisely quantify the interplay between radar signals and the collective influence of tides, waves, and wind speeds. This thorough analysis seeks to deepen our understanding of how environmental elements impact radar performance, thereby contributing to a more nuanced comprehension of coastal ocean dynamics.

How to cite: Cheng, A., Chang, H. M., Chien, H., and Yu, H. Y.: Exploring Environmental Impacts on High Frequency Radar Signal Variability in Taiwan's Northern Coastal Waters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15081, https://doi.org/10.5194/egusphere-egu24-15081, 2024.

Yu-Hao Tseng and Chung-Ru Ho

Using absolute dynamic topography and satellite altimeter eddy tracking data, the intrusion of the Kuroshio caused by the impingement of mesoscale cyclone eddies east of Taiwan into the northern South China Sea (NSCS) through the Luzon Strait was studied. Between 1993 and 2021, a total of 12 such cases were identified. Six of them occurred when the Kuroshio upstream (east of Luzon) strengthened and the Kuroshio downstream (east of Taiwan) weakened. A composite analysis of all cases shows that the average time from when a mesoscale cyclonic eddy impinges the Kuroshio east of Taiwan to when the NSCS reaches maximum negative vorticity is about 28 days. When the Kuroshio upstream strengthens and downstream weakens, the negative vorticity of the NSCS west of the Luzon Strait increases by 45% compared with normal conditions. The duration of the interaction between the Kuroshio and the mesoscale cyclonic eddy east of Taiwan is 28 days, compared with the normal 41 days.

How to cite: Tseng, Y.-H. and Ho, C.-R.: On the connection between eddy impingement east of Taiwan and Kuroshio intrusion into South China Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4534, https://doi.org/10.5194/egusphere-egu24-4534, 2024.

Wenzhou Zhang, Fei Chai, Huijie Xue, and Leo Oey

The Gulf Stream (GS) transports a massive amount of heat northward to high latitudes and releases sensible and latent heat to the atmosphere, playing an important role in the North Atlantic and European climate change. The change trends of the GS transport and pathway are still uncertain to date. Our analyses of altimeter observations from 1993 to 2016 indicate that the linear trends in surface maximum speed, transport and latitudinal location of the GS are significant east of 61ºW at the 95% level while they are small and not significant between 72ºW and 61ºW. The weakening trend of the GS during the period from 1993 to 2016 is accompanied with a southward-shifting path, which is associated with the decline of the North Atlantic Oscillation (NAO) and possibly reduction in the Atlantic meridional overturning circulation (AMOC). 

How to cite: Zhang, W., Chai, F., Xue, H., and Oey, L.: Remote sensing linear trends of the Gulf Stream from 1993 to 2016, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4592, https://doi.org/10.5194/egusphere-egu24-4592, 2024.

A near-global improved gridded multi-mission daily SLA product slightly beyond real-time
(withdrawn after no-show)
Mathias Jensen, Casper Bang-Hansen, Ole Baltazar Andersen, Carsten Ludwigsen, and Mads Ehrhorn
sarah asdar, Daniele Ciani, and Bruno Buongiorno Nardelli

Direct in situ measurements of ocean currents are still quite limited and, due to its small magnitude, measurements of the vertical velocity remain one of the biggest challenges in oceanography. Vertical velocities are therefore generally inferred indirectly, and a common approach to diagnose them is to use the quasi-geostrophic omega equation. In the framework of the European Space Agency World Ocean Circulation project, a new high-resolution (1/10°) data-driven dataset of 3D ocean currents, including the vertical component, has been developed: the WOC-NATL3D dataset. The product domain extends over a wide portion of the North Atlantic Ocean from the surface down to 1500 m depth, and the dataset covers the period between 2010 and 2019. This entire domain holds immense importance for fishery activities and is identified as a key area within international conventions for the conservation of fishing resources, such as tuna and tuna-like fishes under ICCAT (International Commission for the Conservation of Atlantic Tunas). To generate this product, a diabatic quasi-geostrophic diagnostic model is applied to data-driven 3D temperature and salinity fields obtained through a deep learning technique, along with ERA5 fluxes and empirical estimates of the horizontal Ekman currents based on input provided by the European Copernicus Marine Service. The assessment of WOC-NATL3D currents is performed by direct validation of the total horizontal velocities with independent drifter estimates at various depths (0, 15 and 1000 m) and by comparing them with existing reanalyses that are obtained through the assimilation of observations into ocean general circulation numerical models. Our estimates of the ageostrophic components of the flow improve the total horizontal velocity reconstruction, being more accurate and closer-to-observations than model reanalyses in the upper layers, also providing an indirect proof of the reliability of the resulting vertical velocities.

How to cite: asdar, S., Ciani, D., and Buongiorno Nardelli, B.: 3D reconstruction of horizontal and vertical quasi-geostrophiccurrents in the North Atlantic Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18280, https://doi.org/10.5194/egusphere-egu24-18280, 2024.

Margaret Srinivasan and Vardis Tsontos

An international partnership of space agencies has contributed a continuous time series of more than thirty years of global satellite altimetry data. Beginning with TOPEX/Poseidon, and proceeding through the Jason 1, 2, and 3 satellite missions, Sentinel-6 Michael Freilich, and the newest Surface Water and Ocean Topography (SWOT) mission, this U.S./NASA, France and European partnership has enabled important research discoveries and has significantly aided in the development of several valuable operational and commercial, user-driven applications. Substantial resources have been committed over the decades by national space agencies to advance both the science and applications outcomes of these missions. Over the next decade NASA and partners will launch several new satellites with technologies that will extend and expand this constellation even further, providing a rich resource to support science and operational applications. New discoveries and advances in societally focused applications will be enabled by the increased spatial and temporal resolution of satellite remote sensing data that will continue to support ocean, coastal, and hydrology operations and decision makers. Here we highlight existing and potential uses of data from these missions for such applications for societal benefit. Applications areas include marine operations, fisheries and marine biodiversity, coastal planning, and water resource management. We share information on the NASA programs in place to advance and engage with these applied user communities, and on opportunities to collaborate in our efforts.

How to cite: Srinivasan, M. and Tsontos, V.: Satellite Altimetry Missions Applications for Oceanographic, Coastal and Surface Water User Communities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20919, https://doi.org/10.5194/egusphere-egu24-20919, 2024.

K Andrew Peterson, Gregory C Smith, Dorina Surcel-Colan, Kamel Chikhar, and Brayden Zheng

The Synergistic Observing Network for Ocean Prediction (SynObs) project (https://oceanpredict.org/synobs) seeks to find synergies between ocean observations and ocean prediction through a multi-system approach to an Observing System Experiment (OSE). Best estimates and predictions for locations of eddies, shape of ocean sound speed profiles, ocean currents, sea surface temperature and ocean water masses are important ocean diagnostics for a variety of ocean and/or coupled NWP applications. Skillful estimates of these diagnostics is presumably determined by the quantity and quality of ocean observations used in the ocean state estimation, but the exact value of the observations, and in particular, which observations are most crucial is unknown. 

In the context of the SynObs project, Environment and Climate Change Canada's (ECCC's) system the Global Ice Ocean Prediction System (GIOPS) has performed several observation withholding experiments.  The importance of each withholding experiment will be studied by looking first at our standard innovation metrics of observation minus model misfits in the context of both assimilated observations and withheld profile observations.    Further analysis against novel observation metrics, such as an eddy tracking diagnostic comparison, drifting buoy current velocity measurements and sound profile (from T/S profile) comparisons will be detailed.  Finally, preliminary results from a set of short lead (10d) coupled forecast runs may also be presented.  

How to cite: Peterson, K. A., Smith, G. C., Surcel-Colan, D., Chikhar, K., and Zheng, B.: Importance of ocean observations to the ECCC global ocean analysis system, GIOPS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6770, https://doi.org/10.5194/egusphere-egu24-6770, 2024.

Jacqueline Boutin and Cloivs Thouvenin-Masson and the CCI+SSS consortium

Sea Surface Salinity (SSS) is an increasingly-used Essential Ocean and Climate Variable. The SMOS, Aquarius, and SMAP satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI+SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well-established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in-depth analysis of the measurements themselves, together with some limited use of independent reference data [Boutin et al., 2021]. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well-suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale.

In this poster, we review recent advances of the CCI+SSS phase 2 project and the performances of the last (version 4) CCI+SSS product which covers the 2010-2022 period.

With respect to global CCI+SSS v3 dataset, CCI+SSS v4 dataset includes the following updates. According to several users recommendations, global fields are now on a rectangular 0.25°grid, and polar fields on EASE polar grid are also delivered. The ice filtering has been refined (it was too strong in CCI v3). A correction for contamination by radio frequency interferences has been developed and applied around Samoa island, Barbados island and in the Gulf of Guinea. Latitudinal-seasonal corrections have been applied on SMOS, Aquarius and SMAP SSS. SSS changes related to SMOS direct models updates (wind, dielectric constant, rain) have also been taken into account. This leads to significant improvements at high latitudes, allowing to monitor the interannual SSS variability in the Barents Sea, or the spatio-temporal evolution of a fresh event west of Greenland in Fall 2021. In the tropics, we show that the RFI contamination correction allows to restore the interannual SSS variability related to ENSO which was completely masked by RFI contamination around the island of Samoa. We also illustrate how the CCI+SSS fields have been used to assess model results, at global scale with or without data assimilation (GLORYS model), and in the Amazone plume (NEMO-PISCES biogeochemical model).


Boutin, J., et al. (2021), Satellite-Based Sea Surface Salinity Designed for Ocean and Climate Studies, Journal of Geophysical Research: Oceans, 126(11), e2021JC017676, doi:https://doi.org/10.1029/2021JC017676.

Gévaudan et al. (2022). Influence of the Amazon-Orinoco discharge interannual variability on the western tropical Atlantic salinity and temperature. Journal of Geophysical Research: Oceans, 127, e2022JC018495. https://doi.org/10.1029/2022JC018495

How to cite: Boutin, J. and Thouvenin-Masson, C. and the CCI+SSS consortium: Recent advances from the ESA CCI+Sea Surface Salinity project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11240, https://doi.org/10.5194/egusphere-egu24-11240, 2024.

Impact of observed temperature and salinity assimilation in Global Ocean Data Assimilation System (GODAS) using MOM5 
(withdrawn after no-show)
Hasibur Rahaman, Samir Pokhrel, Subodh Kumar Saha, Stephen Penny, Eric Hackert, James Carton, Raheema Rahaman, and T M Balakrishna Nair
Alain Fumenia, Hubert Loisel, Daniel Jorge, Marine Bretagnon, Julien Demaria, and Antoine Mangin

The concentration of particulate organic nitrogen (PON) in seawater plays a central role in ocean biogeochemistry. Limited availability of PON data obtained directly from in situ sampling methods hinders our ability to better characterize the spatio-temporal variability of PON within the global ocean. Tight relationships have recently been developed between in situ measurements of seawater inherent optical properties (IOPs) and PON. Knowing that IOPs can now be estimated from ocean color remote-sensing, these relationships could then be used to assess PON from semi-analytical algorithms applied to satellite ocean color observations. The present study aims at evaluating which IOPs, as estimated from space, can be used as the best proxy for the remote sensing retrieval of PON. The different considered IOPs are the absorption coefficients of total particulate matter, ap(λ), phytoplankton, aph(λ), and non-algal particles, ad(λ), as well as the particulate backscattering coefficient, bbp(l). IOPs have been derived from satellite ocean remote-sensing reflectance, Rrs(l), using different available inverse methods. The validation of the algorithms is based on matchup between an extensive dataset of 156 concurrent measurements of in situ PON and satellite-derived particulate IOPs. Our results show that reasonably strong PON vs satellite-derived IOPs relationships hold across a range of diverse oceanic and coastal environments. aph(443) shows the best ability to serve as a PON proxy over a broad range of PON from open ocean oligotrophic to coastal waters (MdAPD of 25.39 %). bbp(555) can also be considered as a good proxy of PON in open ocean environments (MdAPD of 22.03 %). Comparison with in situ time series over ten years shows also the good performance of the algorithm to reproduce the seasonal variation of PON. The application of this algorithm to Moderate-Resolution Imaging Spectroradiometer (MODIS; 2002-present) observations provides global PON distributions pattern which agree with in situ PON expected geographical distribution. High PON concentrations are observed in turbid shelf and coastal regions as well as in upwelling areas; while low PON are observed in oligotrophic regions. The presented relationships demonstrate a promising means to assess long-term trends and/or budget of PON in specific areas of the ocean or at the global oceanic scale.

How to cite: Fumenia, A., Loisel, H., Jorge, D., Bretagnon, M., Demaria, J., and Mangin, A.: New ocean color algorithms for estimating the concentration of particulate organic nitrogen from remote sensing in oceanic surface waters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15346, https://doi.org/10.5194/egusphere-egu24-15346, 2024.

Aida Alvera-Azcárate, Bayoumi Mohamed, Aleander Barth, Joppe Massant, and Dimitry Van der Zande

Marine Heat Waves (MHWs) are defined as discrete periods of anomalously warm water temperature at a given location. MHWs can have a huge impact on marine ecosystems, already under stress because of the effects of a warming ocean under climate change and high anthropogenic pressure. This work will assess the spatio-temporal evolution of MHWs in the southern North Sea, with an emphasis on the 2022 events. Studying the impact of MHWs on coastal marine ecosystems is currently hampered by the resolution mismatch between traditional satellite data (typically 1 km spatial resolution for SST and CHL) and species habitat/substrate. In the southern North Sea, a multitude of shallow sandbanks, sand, mud and coarser sediment substrats are for instance present, offering a multitude of habitats to different species. With ocean dynamics, and hence water mass and temperature distribution being impacted by the presence of these sandbanks, fine spatial resolution data are required for accurate analysis of the consequences of MHWs and cold spells on the ecosystem. The Thermal InfraRed Sensor (TIRS) sensor onboard the Landsat constellation provides SST at a spatial resolution of 30 m with an accuracy of 0.1 to 0.2K, and can allow the study of the evolution of small-scale dynamics in coastal regions, including the development of MHWs. However, Landsat data have a very low revisit time (7-9 days), not optimal to study specific MHW events, which can evolve on a daily basis. This work will assess the synergy between Landsat data and daily, low-spatial resolution SST data to analyse the evolution of MHWs at coastal regions. DINEOF (Data Interpolating Empirical Orthogonal Functions) will be used to merge these tow data sources and provide high spatial and temporal resolution SST data. This work is a first attempt at linking MHW variability and their consequences on marine ecosystems at very fine spatio-temporal scales, and is part of the North-Heat project. We aim at providing key insights for our comprehension of MHWs in the southern North Sea, a region where marine ecosystems are already under high anthropogenic pressure.


How to cite: Alvera-Azcárate, A., Mohamed, B., Barth, A., Massant, J., and Van der Zande, D.: High spatial resolution Sea Surface Temperature data for the study of Marine Heat Waves in the souther North Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16471, https://doi.org/10.5194/egusphere-egu24-16471, 2024.

Shuangling Chen, Yuntao Wang, and Fei Chai

Sea Surface Nitrate (SSN) plays an important role in assessing new production and phytoplankton growth in the ocean, yet it has been challenging to estimate SSN from satellites due to its complex and varying relationship with different environmental proxies. The different SSN trends in the northwest Pacific reported in previous studies call for more detailed research to examine the interannual variabilities in SSN. We addressed this problem by developing a stacking-random-forest (SRF) based algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS). It allows estimating SSN from daily sea surface temperature (SST) and Chlorophyll-a concentration (Chl) at a spatial resolution of 4 km. For SSN ranging between 0.0005 and 25.88 μmol/kg, the model had a root mean square difference of 1.34 μmol/kg (5.3%) and coefficient of determination of 0.92. Further independent validation and sensitivity tests demonstrated the validity of the algorithm in retrieving SSN. Using this novel data record, for the first time, we investigated the SSN interannual variabilities and trends from MODIS. Overall, the SSN showed a weak decreasing trend of -0.01±0.007 μmol kg-1 yr-1 (p < 0.05) in the northwest Pacific in 2002-2020, associated with an increasing trend in SST. The interannual variabilities of SSN were significantly correlated with the environmental proxies (SST, Chl) and the climate indices (Pacific Decadal Oscillation and North Pacific Gyre Oscillation). The SSN trends can be further restricted with more data available.

How to cite: Chen, S., Wang, Y., and Chai, F.: Remote estimates of sea surface nitrate from ocean color in the northwest Pacific , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21436, https://doi.org/10.5194/egusphere-egu24-21436, 2024.

Posters virtual: Tue, 16 Apr, 14:00–15:45 | vHall X5

Display time: Tue, 16 Apr 08:30–Tue, 16 Apr 18:00
Chairpersons: Tong Lee, Adrien Martin, Aida Alvera-Azcárate
F. Lihue Ferro, Olaia Laguéns-Expósito, Borja Aguiar-González, Nuria Varo-Cruz, Ana Liria-Loza, Alejandro Usategui-Martín, and Francisco Manchín

A pioneering exploration into oceanographic phenomena in Macaronesia and the west North Atlantic Ocean is presented utilizing animal telemetry data collected from four captive-born Loggerhead sea turtles. Noting the cosmopolitan nature and migratory behaviors of sea turtles, this analysis assesses the potential of sea turtles to offer valuable insights into oceanic environmental variables. 


The turtles' interactions with upwelling sites, eddies, and ocean currents are revealed through the integration of georeferenced data (location and time) and oceanographic products from the Marine Copernicus Service. The oceanographic data were interpolated to the turtles’ location in time to obtain remotely-sensed Sea Surface Temperature (SST), chlorophyll-a (chl-a) concentrations and altimeter-derived ocean currents along the routes they performed. 


The results showcase the versatility of these animals as ocean gliders if they were instrumented with temperature and chl-a sensors, providing valuable measurements mostly about the atmosphere-ocean interaction, given their known diving behavior usually ranges from the surface down to 200 m. One of the turtles stayed for over two years near Banc d’Arguin. The simulation of its performance (if it were instrumented with oceanographic sensors) resembled that of a mooring in a key region of high productivity, capturing the seasonal cycle of SST and the chl-a bloom. A second turtle crossed the North Atlantic Subtropical Gyre as if it were an ocean glider leaving the Canary Islands and reaching the Gulf Stream in about 4 months. The path followed by this turtle reveals likely corridors used by sea turtles in cross-basin migrations which would be of high interest to be used for long-term and recurrent monitoring of the upper open ocean interior. Lastly, the third and fourth turtle navigated along the shelf of the Northwest African upwelling area, demonstrating their capability to sample not only open ocean but also coastal areas; the latter being particularly important given the relevance of counting with in situ SST measurements for validation of satellite data. 


Jointly, the four turtles of study and their associated navigational routes encourage further study of the potential of instrumenting Loggerhead sea turtles in Macaronesia as a complementary tool to more traditional approaches for measuring environmental variables.

How to cite: Ferro, F. L., Laguéns-Expósito, O., Aguiar-González, B., Varo-Cruz, N., Liria-Loza, A., Usategui-Martín, A., and Manchín, F.: Exploring Oceanographic Frontiers: Insights from Animal Telemetry Data of four Captive-Born Loggerhead Sea Turtles released in the Macaronesia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13362, https://doi.org/10.5194/egusphere-egu24-13362, 2024.

Vanessa Hui Fen Neo, Joseph Mbui Maina, Jens Zinke, Thomas Fung, Chris Merchant, Kyle Zawada, and Hedwig Krawczyk




Coral reefs are extremely vulnerable to climate-driven warming of the ocean, which threatenstheir survival. Coral responses to rising temperatures are currently studied and predictedusing sea surface temperature (SST) from multiple sources. Despite the importance ofharmonizing complementary data from different sources, there is no clear understanding ofthe consistency or lack of it among the main datasets used and the predictions made usingthem. Understanding the consistency among the different SST data applied to coral reefsmay facilitate monitoring and understanding global warming's impact on coral reefs. Fourtypes of SST data across North-Western and South-Western Australia are compared toassess their differences and ability to predict historical coral bleaching events. Four decadesof coral bleaching indicators, Degree Heating Week (DHW) and Degree Heating Month (DHM)were calculated based on satellite-derived SST, global climate models (GCM), and coral corederived proxies. Both DHW and DHM were inconsistent among datasets and did notaccurately predict moderate and severe bleaching events. Despite high DHWs and DHMs,some reefs did not experience bleaching, suggesting site-specific coral adaptation. SST datafrom different sources had better consistency for frequency and were consistent with coralcore derived proxies of SST, highlighting the importance of coral cores in understanding pastthermal stress. By exploring the differences and similarities among data sources, this studyhighlights the need to compare thermal stress indicators from different datasets for a betterunderstanding and a more robust prediction of coral response to thermal stress.

How to cite: Neo, V. H. F., Maina, J. M., Zinke, J., Fung, T., Merchant, C., Zawada, K., and Krawczyk, H.:  Inconsistencies in Ocean Temperature Monitoring for Coral Reef Applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13356, https://doi.org/10.5194/egusphere-egu24-13356, 2024.