Articles | Volume 20, issue 5
https://doi.org/10.5194/os-20-1087-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-20-1087-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Sep 2024
Research article |
| 06 Sep 2024
| 06 Sep 2024
Investigating the long-term variability of the Red Sea marine heatwaves and their relationship to different climate modes: focus on 2010 events in the northern basin
GeoHydrodynamics and Environment Research (GHER), University of Liège, Liège, Belgium
Oceanography Department, Faculty of Science, Alexandria University, Alexandria, Egypt
Aida Alvera-Azcárate
GeoHydrodynamics and Environment Research (GHER), University of Liège, Liège, Belgium
George Krokos
Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
Ocean Physics, Institute of Oceanography, Hellenic Centre for Marine Research, Anavyssos, Greece
Ibrahim Hoteit
Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
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Geosci. Model Dev., 18, 5549–5573, https://doi.org/10.5194/gmd-18-5549-2025, https://doi.org/10.5194/gmd-18-5549-2025, 2025
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Accurate sea surface temperature data (SST) are crucial for weather forecasting and climate modeling, but satellite observations are often incomplete. We developed a new method called CRITER, which uses machine learning to fill in the gaps in SST data. Our two-stage approach reconstructs large-scale patterns and refines details. Tested on Mediterranean, Adriatic, and Atlantic sea data, CRITER outperforms current methods, reducing errors by up to 44 %.
Alexander Ukhov, Georgiy Stenchikov, Jordan Schnell, Ravan Ahmadov, Umberto Rizza, Georg Grell, and Ibrahim Hoteit
EGUsphere, https://doi.org/10.5194/egusphere-2025-4124, https://doi.org/10.5194/egusphere-2025-4124, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Volcanic eruptions are natural hazards impacting aviation, environment, and climate. Here, we improve the simulation of volcanic material transport using the Weather Research and Forecasting (WRF-Chem) v4.8 model. Analysis of ash, sulfate, and SO2 mass budgets was performed. The direct radiative effect of volcanic aerosols was implemented. A preprocessor, PrepEmisSources, was developed to streamline the preparation of volcanic emissions.
Ibrahim Hoteit, Eric Chassignet, and Mike Bell
State Planet, 5-opsr, 21, https://doi.org/10.5194/sp-5-opsr-21-2025, https://doi.org/10.5194/sp-5-opsr-21-2025, 2025
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This paper explores how using multiple predictions instead of just one can improve ocean forecasts and help prepare for changes in ocean conditions. By combining different forecasts, scientists can better understand the uncertainty in predictions, leading to more reliable forecasts and better decision-making. This method is useful for responding to hazards like oil spills, improving climate forecasts, and supporting decision-making in fields like marine safety and resource management.
Andreas Schiller, Simon A. Josey, John Siddorn, and Ibrahim Hoteit
State Planet, 5-opsr, 18, https://doi.org/10.5194/sp-5-opsr-18-2025, https://doi.org/10.5194/sp-5-opsr-18-2025, 2025
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The study illustrates the way atmospheric fields are used in ocean models as boundary conditions for the provisioning of the exchanges of heat, freshwater, and momentum fluxes. Such fluxes can be based on remote sensing instruments or provided directly by numerical weather prediction systems. Air–sea flux datasets are defined by their spatial and temporal resolutions and are limited by associated biases. Air–sea flux datasets for ocean models should be chosen with the applications in mind.
Matthew J. Martin, Ibrahim Hoteit, Laurent Bertino, and Andrew M. Moore
State Planet, 5-opsr, 9, https://doi.org/10.5194/sp-5-opsr-9-2025, https://doi.org/10.5194/sp-5-opsr-9-2025, 2025
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Observations of the ocean from satellites and platforms in the ocean are combined with information from computer models to produce predictions of how the ocean temperature, salinity, and currents will evolve over the coming days and weeks and to describe how the ocean has evolved in the past. This paper summarises the methods used to produce these ocean forecasts at various centres around the world and outlines the practical considerations for implementing such forecasting systems.
Ségolène Berthou, John Siddorn, Vivian Fraser-Leonhardt, Pierre-Yves Le Traon, and Ibrahim Hoteit
State Planet, 5-opsr, 20, https://doi.org/10.5194/sp-5-opsr-20-2025, https://doi.org/10.5194/sp-5-opsr-20-2025, 2025
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Ocean forecasting is traditionally done independently from atmospheric, wave, or river modelling. We discuss the benefits and challenges of bringing all these modelling systems together for ocean forecasting.
Aida Alvera-Azcárate, Dimitry Van der Zande, Alexander Barth, Antoine Dille, Joppe Massant, and Jean-Marie Beckers
Ocean Sci., 21, 787–805, https://doi.org/10.5194/os-21-787-2025, https://doi.org/10.5194/os-21-787-2025, 2025
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This work presents an approach for increasing the spatial resolution of satellite data and interpolating gaps due to cloud cover, using a method called DINEOF (data-interpolating empirical orthogonal functions). The method is tested on turbidity and chlorophyll-a concentration data in the Belgian coastal zone and the North Sea. The results show that we are able to improve the spatial resolution of these data in order to perform analyses of spatial and temporal variability in coastal regions.
Bayoumy Mohamed, Alexander Barth, Dimitry Van der Zande, and Aida Alvera-Azcárate
EGUsphere, https://doi.org/10.5194/egusphere-2025-1578, https://doi.org/10.5194/egusphere-2025-1578, 2025
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We quantified the role of climate change and internal variability on marine heatwaves (MHWs) in the North Sea over more than four decades (1982–2024). A key finding is the 2013 climate shift, which was associated with increased warming and MHWs. Long-term warming accounted for 80 % of the observed trend in MHW frequency. The most intense MHW event in May 2024 was attributed to an anomalous anticyclonic atmospheric circulation. We also explored the impact of MHWs on chlorophyll concentrations.
Cécile Pujol, Alexander Barth, Iván Pérez-Santos, Pamela Muñoz-Linford, and Aida Alvera-Azcárate
EGUsphere, https://doi.org/10.5194/egusphere-2025-1421, https://doi.org/10.5194/egusphere-2025-1421, 2025
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Marine heatwaves and cold spells are periods of extreme sea temperatures. This study focuses on Chilean Northern Patagonia, a fjord region vulnerable due to its aquaculture. It aims to understand these events' distribution and identify the most affected basins. Results show higher intensity in enclosed areas like Reloncaví Sound and Puyuhuapi Fjord. Marine heatwaves are becoming more frequent over time, while cold spells are decreasing.
Ehsan Mehdipour, Hongyan Xi, Alexander Barth, Aida Alvera-Azcárate, Adalbert Wilhelm, and Astrid Bracher
EGUsphere, https://doi.org/10.5194/egusphere-2025-112, https://doi.org/10.5194/egusphere-2025-112, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Phytoplankton are vital for marine ecosystems and nutrient cycling, detectable by optical satellites. Data gaps caused by clouds and other non-optimal conditions limit comprehensive analyses like trend monitoring. This study evaluated DINCAE and DINEOF gap-filling methods for reconstructing chlorophyll-a datasets, including total chlorophyll-a and five major phytoplankton groups. Both methods showed robust reconstruction capabilities, aiding pattern detection and long-term ocean colour analysis.
Alexander Barth, Julien Brajard, Aida Alvera-Azcárate, Bayoumy Mohamed, Charles Troupin, and Jean-Marie Beckers
Ocean Sci., 20, 1567–1584, https://doi.org/10.5194/os-20-1567-2024, https://doi.org/10.5194/os-20-1567-2024, 2024
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Most satellite observations have gaps, for example, due to clouds. This paper presents a method to reconstruct missing data in satellite observations of the chlorophyll a concentration in the Black Sea. Rather than giving a single possible reconstructed field, the discussed method provides an ensemble of possible reconstructions using a generative neural network. The resulting ensemble is validated using techniques from numerical weather prediction and ocean modelling.
Yasser O. Abualnaja, Alexandra Pavlidou, James H. Churchill, Ioannis Hatzianestis, Dimitris Velaoras, Harilaos Kontoyiannis, Vassilis P. Papadopoulos, Aristomenis P. Karageorgis, Georgia Assimakopoulou, Helen Kaberi, Theodoros Kannelopoulos, Constantine Parinos, Christina Zeri, Dionysios Ballas, Elli Pitta, Vassiliki Paraskevopoulou, Afroditi Androni, Styliani Chourdaki, Vassileia Fioraki, Stylianos Iliakis, Georgia Kabouri, Angeliki Konstantinopoulou, Georgios Krokos, Dimitra Papageorgiou, Alkiviadis Papageorgiou, Georgios Pappas, Elvira Plakidi, Eleni Rousselaki, Ioanna Stavrakaki, Eleni Tzempelikou, Panagiota Zachioti, Anthi Yfanti, Theodore Zoulias, Abdulah Al Amoudi, Yasser Alshehri, Ahmad Alharbi, Hammad Al Sulami, Taha Boksmati, Rayan Mutwalli, and Ibrahim Hoteit
Earth Syst. Sci. Data, 16, 1703–1731, https://doi.org/10.5194/essd-16-1703-2024, https://doi.org/10.5194/essd-16-1703-2024, 2024
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We present oceanographic measurements obtained during two surveillance cruises conducted in June and September 2021 in the Red Sea and the Arabian Gulf. It is the first multidisciplinary survey within the Saudi Arabian coastal zone, extending from near the Saudi–Jordanian border in the north of the Red Sea to the south close to the Saudi--Yemen border and in the Arabian Gulf. The objective was to record the pollution status along the coastal zone of the kingdom related to specific pressures.
Pamela Linford, Iván Pérez-Santos, Paulina Montero, Patricio A. Díaz, Claudia Aracena, Elías Pinilla, Facundo Barrera, Manuel Castillo, Aida Alvera-Azcárate, Mónica Alvarado, Gabriel Soto, Cécile Pujol, Camila Schwerter, Sara Arenas-Uribe, Pilar Navarro, Guido Mancilla-Gutiérrez, Robinson Altamirano, Javiera San Martín, and Camila Soto-Riquelme
Biogeosciences, 21, 1433–1459, https://doi.org/10.5194/bg-21-1433-2024, https://doi.org/10.5194/bg-21-1433-2024, 2024
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The Patagonian fjords comprise a world region where low-oxygen water and hypoxia conditions are observed. An in situ dataset was used to quantify the mechanism involved in the presence of these conditions in northern Patagonian fjords. Water mass analysis confirmed the contribution of Equatorial Subsurface Water in the advection of the low-oxygen water, and hypoxic conditions occurred when the community respiration rate exceeded the gross primary production.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
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In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196, https://doi.org/10.5194/gmd-15-2183-2022, https://doi.org/10.5194/gmd-15-2183-2022, 2022
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Earth-observing satellites provide routine measurement of several ocean parameters. However, these datasets have a significant amount of missing data due to the presence of clouds or other limitations of the employed sensors. This paper describes a method to infer the value of the missing satellite data based on a convolutional autoencoder (a specific type of neural network architecture). The technique also provides a reliable error estimate of the interpolated value.
Estrella Olmedo, Verónica González-Gambau, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Marilaure Gregoire, Aida Álvera-Azcárate, Luminita Buga, and Marie-Hélène Rio
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-364, https://doi.org/10.5194/essd-2021-364, 2021
Revised manuscript not accepted
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We present the first dedicated satellite salinity product in the Black Sea. We use the measurements provided by the European Soil Moisture and Ocean Salinity mission. We introduce enhanced algorithms for dealing with the contamination produced by the Radio Frequency Interferences that strongly affect this basin. We also provide a complete quality assessment of the new product and give an estimated accuracy of it.
Oliver Miguel López Valencia, Kasper Johansen, Bruno José Luis Aragón Solorio, Ting Li, Rasmus Houborg, Yoann Malbeteau, Samer AlMashharawi, Muhammad Umer Altaf, Essam Mohammed Fallatah, Hari Prasad Dasari, Ibrahim Hoteit, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 24, 5251–5277, https://doi.org/10.5194/hess-24-5251-2020, https://doi.org/10.5194/hess-24-5251-2020, 2020
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The agricultural sector in Saudi Arabia has expanded rapidly over the last few decades, supported by non-renewable groundwater abstraction. This study describes a novel data–model fusion approach to compile national-scale groundwater abstractions and demonstrates its use over 5000 individual center-pivot fields. This method will allow both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.
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Short summary
Our study focuses on the characteristics of MHWs in the Red Sea during the last 4 decades. Using satellite-derived sea surface temperatures (SSTs), we found a clear warming trend in the Red Sea since 1994, which has intensified significantly since 2016. This SST rise was associated with an increase in the frequency and days of MHWs. In addition, a correlation was found between the frequency of MHWs and some climate modes, which was more pronounced in some years of the study period.
Our study focuses on the characteristics of MHWs in the Red Sea during the last 4 decades. Using...
