OS4.6 | Extremes in marine environment: analysis of multi-temporal and multi-scales dynamics using observations, models and machine learning techniques
EDI
Extremes in marine environment: analysis of multi-temporal and multi-scales dynamics using observations, models and machine learning techniques
Convener: Antonio Ricchi | Co-conveners: Giovanni Liguori, Milena Menna, Matjaz Licer, Clea Denamiel
Orals
| Wed, 26 Apr, 08:30–10:15 (CEST), 10:45–12:30 (CEST)
 
Room L2
Posters on site
| Attendance Wed, 26 Apr, 16:15–18:00 (CEST)
 
Hall X5
Orals |
Wed, 08:30
Wed, 16:15
Despite their socio-economic and environmental impacts, extreme events in the marine environment are generally poorly understood, simulated or predicted. In particular, the dynamics of these events involve multiple temporal and spatial scales and can be driven by different mechanics and complex feedback involving the ocean and its interaction with the other spheres of the climate system.
In response to climate change, frequency and magnitude of these events could dramatically change with significant impacts on human life and properties as well as on marine ecosystems. Hence, advancing our understanding on the dynamics leading to extremes in marine environments is crucial to improving their predictability, which in turn will help to achieve environmental and social sustainability.
Starting with this rationale, the session will focus on marine extremes at multiple time and spatial scales. Studies discussing ocean dynamics and air-sea interactions that can influence the evolution of marine extremes are particularly welcome, as well as ones using techniques ranging from in-situ to remote sensing observations, from numerical models to innovative AI techniques (e.g., machine learning). This diversity of topics will make for a highly multidisciplinary session, open to multiple applications in the field of marine extremes.
Contributions related to the investigation of marine heatwaves, marine storminess, storm surge and sea level rise, dense water formation, deep ocean extreme events, etc. are other examples of potential topics.

Orals: Wed, 26 Apr | Room L2

Chairpersons: Antonio Ricchi, Matjaz Licer, Giovanni Liguori
08:30–08:35
08:35–08:55
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EGU23-5572
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solicited
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On-site presentation
Magnus Hieronymus

A new machine learning based bias correction method is presented and applied to sea level in a regional climate model for the Baltic and the North Sea. The bias corrections introduced by the method depend on the state of the model it corrects. This contrasts with conventional bias correction methods that operate on distributions of output variables. That is, while conventional correction methods adjusts all modelled sea levels of the same height by the same amount, this method instead adjusts all sea level that occur under the same meteorological conditions by the same amount. Model state dependent corrections allow for better performance on classical skill scores, like correction coefficients, but it also limits the applicability of the method to models that can perform hindcasts. This constrain occurs because the method requires observations and model data from an overlapping time period.

The bias correction method is applied to a large ensemble of dynamically downscaled climate scenario data encompassing many different driving global climate models and representative concentration pathways. The prevalence of significant trends in yearly sea level maximum is found to be independent of emission scenario in our ensemble. This suggests that anthropogenic climate change is not a strong driver of storm surge variability in the area. Moreover, it also suggests that very long datasets of corrected sea levels can be created by merging data from different emission scenarios. A dataset is thus produced that contains over 2600 model years and exists for seven different tide-gauge stations on the Swedish Baltic Sea coast. This dataset is used to estimate return levels for very long return periods by fitting generalized extreme value distributions to block maxima sea level time series. At some stations it is found that the block length used in the return level computation affect the result. This suggests that the commonly used annual maximum approach (i.e. having a block length of one year) is not always applicable for determining return levels for sea level in the area.

How to cite: Hieronymus, M.: A novel machine learning based bias correctionmethod and its application to sea level in an ensemble of downscaled climate projections, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5572, https://doi.org/10.5194/egusphere-egu23-5572, 2023.

08:55–09:05
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EGU23-3355
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ECS
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Virtual presentation
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer

We propose a new deep-learning architecture HIDRA2 for sea level and storm tide modeling, which is extremely fast to train and apply and outperforms both our previous network design HIDRA1 and two state-of-the-art numerical ocean models (a NEMO engine with sea level data assimilation and a SCHISM ocean modeling system), over all sea level bins and all forecast lead times. The architecture of HIDRA2 employs novel atmospheric, tidal and sea surface height (SSH) feature encoders as well as a novel feature fusion and SSH regression block. HIDRA2 was trained on surface wind and pressure fields from a single member of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric ensemble and on Koper tide gauge observations. An extensive ablation study was performed to estimate the individual importance of input encoders and data streams. Compared to HIDRA1, the overall mean absolute forecast error is reduced by 13 %, while in storm events it is lower by an even larger margin of 25 %. Consistent superior performance over HIDRA1 as well as over general circulation models is observed in both tails of the sea level distribution: low tail forecasting is relevant for marine traffic scheduling to ports of the northern Adriatic, while high tail accuracy helps coastal flood response. To assign model errors to specific frequency bands covering diurnal and semi-diurnal tides and the two lowest basin seiches, spectral decomposition of sea levels during several historic storms is performed. HIDRA2 accurately predicts amplitudes and temporal phases of the Adriatic basin seiches, which is an important forecasting benefit due to the high sensitivity of the Adriatic storm tide level to the temporal lag between peak tide and peak seiche.

How to cite: Rus, M., Fettich, A., Kristan, M., and Ličer, M.: HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3355, https://doi.org/10.5194/egusphere-egu23-3355, 2023.

09:05–09:15
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EGU23-6824
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ECS
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On-site presentation
Rodrigo Campos-Caba, Lorenzo Mentaschi, Nadia Pinardi, Jacopo Alessandri, Paula Camus, and Massimo Tondello

Urban settlements near to coastal environments are exposed to ocean and cryosphere change, such as sea level rise and extreme sea levels. High-resolution sea level prediction systems have become fundamental tools for taking preventive measures in the face of extreme events, mainly in the most vulnerable coastal locations. Techniques such as Machine Learning (ML) are at the forefront of the development in this sector, as they can reduce the computational time needed to reproduce the results of costly high resolution dynamic models. In this line, different authors have reported results for the prediction of oceanographic variables using ML approaches (Camus et al., 2019; Costa et al., 2020; Zust et al., 2021), mainly for significant wave height, sea level and surge component of sea level. Generally, these works use global and/or regional databases as training data for ML tools.

With the aim of developing a data-driven system for sea level downscaling, by means of very high-resolution circulation model output used as a training data for a ML framework, in this work the results of a long-term numerical modeling of sea level are presented, carried out in the Northern Adriatic. The numerical model implemented correspond to SURF-SHYFEM, a 3-D finite element hydrodynamic model that solves the primitive equations under hydrostatic and Boussinesq approximations. As atmospheric forcing, mean sea level pressure, and meridional and zonal components of wind speed have been included, both from the ERA5 database. For the boundary conditions, sea level has been considered from two databases, the Copernicus Mediterranean Forecasting System (available from November 2020 to present, with tides included in sea level) and the Copernicus Mediterranean Sea Physics Reanalysis (available from 1987 to June 2021, without tides in sea level). Both databases were used on initial analysis in the representation of surge component of sea level when tides are or not included in the boundary condition. The validation of the results has been carried out by comparison with tide gauges located near the Venice Lagoon, from ISPRA[1] and PSMSL[2].

The results show that the model reproduces accurately the sea level (correlation 94% and RMSE 0.09 [m]) and the surge component of sea level (correlation 91% and RMSE 0.06 [m]) measured at the location of the tide gauge. The next step will consist of using such output as a training set for ML-based techniques, with the aim of developing an accurate and cost-effective downscaling tool.


[1] Istituto Superiore per la Protezione e la Ricerca Ambientale. Available at: https://www.mareografico.it/

[2] Permanent Service for Mean Sea Level. Available at: https://psmsl.org/

 

 REFERENCES

Camus, P., Herrera, S., Guitiérrez, J.M. and Losada, I.J. (2019). Statistical downscaling of seasonal wave forecast. Ocean Modelling 138, 1-12.

Costa, W., Idier, D., Rohmer, J., Menendez, M. and Camus, P. (2020). Statistical prediction of extreme storm surges based on a fully supervised weather-type downscaling model. J. Mar. Sci. Eng. 8, 1028.

Zust, L., Fettich, A., Kristan, M. and Licer, M. (2021). HIDRA 1.0: Deep-Learning-Based ensemble sea level forecasting in the Northern Adriatic. Geosci. Model. Dev. 14, 2057-2074.

How to cite: Campos-Caba, R., Mentaschi, L., Pinardi, N., Alessandri, J., Camus, P., and Tondello, M.: Long-term numerical modeling of sea level in the Northern Adriatic for a machine learning downscaling system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6824, https://doi.org/10.5194/egusphere-egu23-6824, 2023.

09:15–09:25
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EGU23-12113
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ECS
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Virtual presentation
Giulia Bonino, Simona Masina, Giuliano Galimberti, and Emanuela Clementi

Marine Heat Waves (MHWs) have significant social and ecological consequences. There is a growing need to predict these extreme events to prevent and possibly mitigate their negative impacts and to better inform decision-makers on MHWs-related risks. In this context, we applied Long Short-Term Memory (LSTM) networks to predict Sea Surface Temperature (SST) time-series and, in turn, MHWs, over the Mediterranean Sea. LSTM networks are types of recurrent neural networks capable of learning order dependence in sequence prediction problems, and they have been widely applied in temperature forecasting problems. The model is a multi-step LSTM model, which means that it predicts seven time-steps of SST into the future. In order to build an efficient prediction model, as input times-series, LSTM exploits SST together with other relevant atmospheric variables (e.g. Geopotential Height, Incoming solar radiation), selected as potential MHWs drivers. The datasets used to train and to test the model are the European Space Agency (ESA) Climate Change Initiative (CCI) Sea Surface Temperature (SST) v2.1 for SST and ERA5 reanalysis for the atmospheric components from 1981 to 2016.  Preliminary results over target areas suggest that, besides the SST itself, the incoming solar radiation has the highest predictive skill on SST variability with respect to the other atmospheric variables. The model is accurate in predicting the occurrence of MHWs in the test dataset at the earliest days of forecast. In addition, the root mean square error analysis between predicted and actual SST time-series shows that LSTM models errors compare favorably with respect to the Copernicus Mediterranean Forecasting System (MedFS, i.e. dynamical model) errors, at least at the earliest days of forecast.

How to cite: Bonino, G., Masina, S., Galimberti, G., and Clementi, E.: A deep machine learning approach to predict Sea Surface Temperature and Marine Heatwaves occurrences over the Mediterranean Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12113, https://doi.org/10.5194/egusphere-egu23-12113, 2023.

09:25–09:35
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EGU23-16745
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Virtual presentation
Sangyoung Son and Xiaojuan Qian

This study aims to generalize the synthetic effects of TS, LA, and coastal geometries on a maximum surge height (MSH) along the coast through the numerical simulations of a series of idealized scenarios as well as real-scale event. A two-dimensional model in Delft3D-FM was adopted in this study to simulate the MSHs. The model domain consists of multi-resolution grids ranging from 16 km to 1 km considering the cyclone’s landfall spot at the center of the coastline. All these simulations were implemented without tides and waves since this study aims to investigate the synthetic effects on main surge levels. The hypothetical cyclones were generated under various TSs and LAs conditions. The TSs were altered while LAs ranged varied from 0° to 180°. Additionally, the coastal layout and bathymetry were also controlled. For bathymetry, a constant bed, beds with different continental shelf widths, and a multi-sloped bed were also considered. For coastal layout, an open coast and bays characterized by the morphological ratio were considered. Totally, 763 idealized scenarios were simulated to obtain the MSHs distributions along the coast. The realistic scenarios based on historical typhoon Maemi in 2003 was additionally simulated with various TSs and LAs conditions to apply developed idea from idealized scenario cases. The effects of the TS, LA, and coastal geometries on MSH were analyzed by simulating idealized and realistic scenarios. The trends of MSHs along the open coast extracted from each scenario were found to be almost identical despite minor discrepancies. The results revealed that MSHs along the open coast were amplified by fast-moving TSs. For constant bed, the results exhibited a distinct characteristic that generated the Kelvin wave propagating in a down-coast direction, while certain types of sharp LAs with a slow-moving cyclone might generate other types of resonant waves. For the beds with different dimensions of continental shelves, trends of the MSHs were distinguishable between slow and faster-moving TSs. Nevertheless, the continental shelf with narrow width led to a peak at a sharp LA under all TSs, implying that the shelf geometry can limitedly affect the MSH. As for the multi-sloped bed, slope geometry strongly influenced the surge process in that it enhanced the MSH due to the Greenspan resonance. For bays, the trends of MSHs were essentially coincident with those of open coast, while an enhancement of MSHs was observed when L/E was close to 1. Additionally, the realistic scenarios based on a historical typhoon were simulated to validate outcomes from idealized scenarios, indicating that super typhoons like Maemi with a  LA, tend to slow down and generate an extreme surge in Masan Bay in the future sight.

How to cite: Son, S. and Qian, X.: On the effect of tropical cyclones' translation speed and landfall trajectory on the storm surge dynamics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16745, https://doi.org/10.5194/egusphere-egu23-16745, 2023.

09:35–09:45
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EGU23-5835
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Highlight
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On-site presentation
Marco Bajo, Christian Ferrarin, Mirko Orlić, Silvio Davolio, Georg Umgiesser, and Piero Lionello

On 12 November 2019, an exceptional flood event occurred in Venice, second only to the one that had occurred on 4 November 1966. The event caused the flooding of about 90% of the streets in the historic centre and the sea level reached a value of 189 cm compared to the local mean-sea-level datum. Subsequent analysis of the meteorological event highlighted the contributions at different temporal and spatial scales. A sub-synoptic cyclone, centred in the Tyrrhenian Sea, caused a strong Sirocco wind along the entire Adriatic basin, with a fairly typical atmospheric configuration. However, embedded in the first cyclone, a second meso-beta scale cyclone developed and moved in the north-westward direction over the Adriatic Sea along the Italian coast. This cyclone had a speed of about 12 m/s, very close to the speed of the shallow water waves for the depth of the northern Adriatic basin. The perturbation then triggered a Proudman resonance, as confirmed by the numerical simulations, and caused a meteotsunami-like wave that affected the north-western coasts of the Adriatic Sea. Through model simulations, we have estimated that the mesoscale cyclone contributed about 40 cm, of which about 40% may be attributed to the air-pressure forcing, amplified through the Proudman resonance, and the rest to the wind forcing influencing both the open Adriatic Sea and the shallow Venetian lagoon. Finally, we have also analysed the propagation and transformation of the perturbation upon its entrance into the Venetian lagoon. This work is part of the COST action CA19109 MEDCYCLONES (European Network for Mediterranean Cyclones in weather and climate) and the Interreg Italy-Croatia STREAM project (Strategic development of flood management, project ID 10249186).

How to cite: Bajo, M., Ferrarin, C., Orlić, M., Davolio, S., Umgiesser, G., and Lionello, P.: The exceptional flood in Venice on 12 November 2019: contribution of a meteotsunami, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5835, https://doi.org/10.5194/egusphere-egu23-5835, 2023.

09:45–09:55
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EGU23-7002
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ECS
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On-site presentation
Yuri Pepi, Leandro Ponsoni, and Wieter Boone

Infragravity waves have been identified as driving force behind various nearshore processes including beach and dune erosion, the development of seiches in harbors, and wave-driven coastal inundation when not accounted for in the design calculations. These waves have been observed to cause extreme water levels and resulting damage in various locations around the world.

Field observations and measurements are essential for understanding the behavior and impacts of infragravity waves, which are long surface waves with low and with significantly longer periods than the peak frequency of the incident wave spectrum. The period is typically between 30 and 300 seconds (0.03 – 0.003 Hz), the amplitude ranges from a few millimeters to tens of centimeters and has a wavelength scale of kilometers.

In this study, we first revisit field observations, instrumentation, and sampling techniques that have been used to study this phenomenon. The advantages and limitations of different approaches are discussed, as well as the challenges and best practices for collecting high-quality data in the field are addressed.

Field observations were conducted using multipurpose mooring frames equipped with both ADCP-based acoustic surface tracking and high-accuracy quartz pressure sensors. Data were collected continuously for 3 months, covering storm and moderate wave conditions. The measurements from ADCP and pressure sensor were combined and the infragravity wave characteristics were determined. Algorithms to calculate the wave characteristics were developed and combined with data from tide gauges and wave buoys to calibrate the sensors and cross-validate the results.

The observations showed that infragravity waves can be effectively monitored using ADCP and high-accuracy quartz pressure sensors, providing useful information regarding impacts on the coastal environment. The results showed the relevance and occurrence of these waves along the Belgian coast and valuable insights into their generation and propagation and the interaction with Sea-swell waves, including with relation to their spatio-temporal variability.

How to cite: Pepi, Y., Ponsoni, L., and Boone, W.: Field observations of Infragravity waves along the Belgian coast, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7002, https://doi.org/10.5194/egusphere-egu23-7002, 2023.

09:55–10:05
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EGU23-13205
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ECS
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On-site presentation
Flora Desmet, Nicolas Gruber, Matthias Münnich, Meike Vogt, and Eike E. Köhn

Superimposed on long-term ocean acidification are ocean acidity extremes (OAXs), i.e., periods of unusual acidity in the marine environment. Such extremes form through the interplay of the various spatio-temporal scales of variability associated with the ocean’s carbonate system, ranging from multi-decadal trends to subseasonal dynamics. Using a high-resolution regional ocean model coupled to a biogeochemical-ecosystem model (ROMS-BEC) we assess the role of five mechanisms associated with different scales of variability – namely atmospheric CO2 rise, the decadal North Pacific Gyre Oscillation (NPGO), the interannual El-Niño-Southern Oscillation (ENSO), seasonal upwelling, and mesoscale eddies – in the occurrence of OAXs in a 300 km nearshore band along the U.S. West Coast and the Alaskan coast over the period 1984 to 2019. We find that the annual fraction of the upper 250 m depth that is hit by OAXs increases at a rate of 0.16 % units.μatm-1 driven by the increase in atmospheric CO2 concentration. In addition, our analysis reveals that Pacific climate variability substantially modulates OAXs occurrence on interannual timescales. The fraction of the upper 250 m depth that is hit by OAXs increases by 0.53 % units per unit decrease in the ENSO index, and 0.39 % units per unit increase in the NPGO index. Last but not least, we find that seasonal upwelling and mesoscale cyclonic eddies are key regional drivers of OAXs along the U.S. West Coast. Our results show that coastal upwelling forms intense and shallow OAXs near the coast, while mesoscale cyclonic eddies drive large and long-lasting OAXs that propagate over hundreds of kilometers from the coast to the offshore. Altogether, our results quantify the respective imprint of five mechanisms associated with different scales of variability on the occurrence of OAXs in coastal regions. This knowledge opens new perspectives for improving the predictability of OAXs in the highly productive coastal regions of the northeast Pacific.  

How to cite: Desmet, F., Gruber, N., Münnich, M., Vogt, M., and Köhn, E. E.: Ocean acidity extremes in the northeast Pacific, from multi-decadal trends to mesoscale drivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13205, https://doi.org/10.5194/egusphere-egu23-13205, 2023.

10:05–10:15
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EGU23-6673
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ECS
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Virtual presentation
Aniello Florio, Diana Di Luccio, Ciro Giuseppe De Vita, Gennaro Mellone, Guido Benassai, Giorgio Budillon, and Raffaele Montella

The development and implementation of Early Warning Systems (EWSs) are decisive as they allow for timely measures before the arrival of the flooding waters. EWS enhances the prevention and preparedness activities that mitigate the effects of disasters on lives, property, and the environment. Forecasting outcomes supply decision-makers at local, regional, or national levels with relevant information and comprise an essential part of monitoring and warning procedures. These decisions must be taken quickly to allow mitigation measures, so computer time acceleration is decisive. 
The proposed innovation for implementing an Early Warning System (EWS) is the parallelization model. The proposed parallelization model is based on different parallel sub-schemes. Each parallelization sub-schema can be combinable with each other, providing a hierarchical parallelization scheme. The problem size (the number of transects along the Campania coast) is divided into lots and distributed to several executors. Each executor is an instance of a computer program (process) in charge of computing the partition of the problem in its duty. Due to CPUs being composed of more computing cores, each process can decompose its part of the problem to each computing core running concurrently (threads). While the threads of the same process share the same memory, processes communicate by exchanging data messages. As demonstrated later in the paper, the problem decomposition makes the overall computing performance remarkable as the problem size increase.
The EWS has been designed and developed, leveraging a high-performance computing system. This approach is motivated by the goal of managing and running scientific workflows. Therefore, the performance evaluation has been performed considering a production workflow executing diverse and different numerical and A.I. models): the community Weather Research and Forecasting (WRF),  the Wavewatch III (WW3) numerical models, and, finally, 3) the novel Shoreline Alert Model (SAM).
SAM implements the empirical approach to evaluate the alert level as a function of the shoreline characteristics. The workflow starts with the WRF numerical model to forecast the atmospheric forcing needed to fuel the WW3 model for estimating the offshore waves, which drives the initial and boundary conditions for modeling waves in shallow water. Then, according to the wave decay submodel, these conditions assess the run-up height and overtopping discharge. The results are associated with an alert system triggered by the duration and intensity of storm events forecasted by the models. Finally, it is obtained considering the geomorphology of the area of interest and the presence/absence of protection structures.
The case study under examination covers a coastal stretch located in the municipality of Torre del Greco, in the Gulf of Naples, consisting of a beach varying in width from 10 to 20 meters, which is protected by an artificial reef up of natural blocks. In recent years, the succession of extreme weather events has created coastal flooding, like during the extreme storm of October 2018, which caused considerable damage in this area.

How to cite: Florio, A., Di Luccio, D., De Vita, C. G., Mellone, G., Benassai, G., Budillon, G., and Montella, R.: A Shoreline Alert Model for coastal early warning system in the Gulf of Naples (Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6673, https://doi.org/10.5194/egusphere-egu23-6673, 2023.

Coffee break
Chairpersons: Giovanni Liguori, Matjaz Licer, Antonio Ricchi
10:45–10:50
10:50–11:10
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EGU23-14540
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ECS
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solicited
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On-site presentation
Ronan McAdam, Simona Masina, and Silvio Gualdi

Marine heat waves (MHWs) cause devastating damage to ecosystems and ocean services, with effects being identified mostly below the ocean surface. Current forecasting efforts, however, focus only on metrics based on sea surface temperature. To create a more user-relevant detection system, it is necessary to provide forecasts of subsurface events. Here, we demonstrate the feasibility of seasonal forecasting of subsurface MHWs by using ocean heat content, a more relevant indicator than surface temperature for marine stakeholders. We validate summer MHW indicators in a fully-coupled seasonal forecast system against a global ocean reanalysis and satellite data. Our main result is that subsurface summer MHWs are predicted with greater skill than surface MHWs across much of the global ocean. Sub-surface MHWs are typically longer-lasting than surface events, rendering them easier targets for forecasting systems. Despite the long-lasting nature of subsurface MHWs, we also show that the dynamical forecast system used here typically outperforms a MHW-persistence model, indicating the capability for capturing the onset and decay of MHWs. Lastly, we highlight the role of warming oceans in MHW detection skill, by removing linear trends. This work highlights the need for a wider appreciation of subsurface ocean phenomena and the increased uptake of seasonal forecasting indicators by marine stakeholders such as marine protected areas and fisheries.

How to cite: McAdam, R., Masina, S., and Gualdi, S.: Seasonal forecasting of subsurface marine heat waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14540, https://doi.org/10.5194/egusphere-egu23-14540, 2023.

11:10–11:20
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EGU23-6094
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ECS
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On-site presentation
Lorine Behr, Niklas Luther, Elena Xoplaki, Stamatis Petalas, Elina Tragou, and Vassilis Zervakis

Atmospheric and marine heatwaves (AHW/MHW) have been observed around the world and are expected to increase in intensity and frequency under future climate change. Despite numerous studies that have examined AHW or MHW independently, only few regional studies investigated potential associations between these two types of extreme events. However, the co-occurrence of AHW and MHW could have broader and greater environmental, human, and economic impacts than an individual event, such as changes in species distributions, land and marine mass mortalities, or increased heat stress in coastal areas due to interactions between warm and moist air over the ocean. Based on research on AHW and MHW, we propose a comprehensive and globally applicable definition that relates the two extreme events and the two realms, and allows comparison with past and present concurrent and single events. Our definition is based on a conditional approach: We define a concurrent heatwave as an extreme event where sea surface temperature (SST) and 2 m air temperature (Tair) exceed their daily 90th percentiles, based on a 30-year historical baseline period, for at least 5 and 3 consecutive days, respectively (Perkins & Alexander 2013; Hobday et al. 2016). Thereby, we account for a potential lagged relationship between the two extremes by calculating and choosing the lag that provides the maximum probability of observing a MHW and an AHW simultaneously or delayed. In this work, we show the results of the most common heatwave metrics, such as duration, frequency, intensity, and cumulative intensity, for concurrent and single heatwaves in the Mediterranean Sea, Western Australia, and the Northwest Atlantic. We use SSTs from Advanced Very High-Resolution Radiometer (AVHRR) satellite data (NOAA OISST V2) as well as Tair from the ECMWF Reanalysis v5 (ERA5), both provided daily and globally on a high resolution (0.25°) for the period 1982 – 2022. In the Mediterranean Sea, we find concurrent heatwaves to be shorter and less frequent, but more intense and cumulatively intense than their single variants. For concurrent events, the MHW component (SST) is observed to be most intense in summer and spring, and the AHW component (Tair) in fall and winter. Moreover, the MHW appears to determine the strength of the concurrent heatwave in that region.

How to cite: Behr, L., Luther, N., Xoplaki, E., Petalas, S., Tragou, E., and Zervakis, V.: A global approach to defining Concurrent Atmospheric and Marine Heatwaves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6094, https://doi.org/10.5194/egusphere-egu23-6094, 2023.

11:20–11:30
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EGU23-7735
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On-site presentation
Nathalie Verbrugge, Andrea Pisano, Jérémy Augot, Eric Greiner, Angela Landolfi, Francesca Leonelli, Vincenzo Da Toma, Emanuele Organelli, Salvatore Marullo, and Rosalia Santoleri

The ongoing project “deteCtion and threAts of maRinE Heat waves – CAREHeat”, funded by ESA in the framework of the Ocean Health initiative, aims at improving the current Marine Heatwaves (MHW) detection and characterization methodologies at the sea surface, at analysing MHW vertical propagation through the development of 4D temperature fields by using Machine Learning approaches, at providing a global atlas of MHW at the sea surface, at advancing the understanding of the physical processes involved in MHW development and at assessing the MHW impact on marine Ecosystems and Biogeochemistry.  

This presentation will focus on the first phase of the project. The mostly used MHW detection method (Hobday approach) has been revisited by carrying out sensitivity studies on different threshold parameters such as the choice of the percentile threshold and the minimum duration of the events. Specific work has also been done to investigate the impact of sea surface temperature (SST) trends and prominent climate modes, as El Nino Southern Oscillation (ENSO), in order to disentangle the slow-varying SST component and quasi-periodic oscillations from the abrubt changes that are characteristics of these extreme events . Many metrics are provided along with the global atlas to help the characterization of these events. In parallel with this work, a machine learning approach based on observations has been used to reconstruct a 4D temperature field from the surface up to 300-m depth and MHWs have been estimated. Subsurface MHWs can also impact ecosystems and phase shifts with the surface events can be observed. This product helps to analyse this propagation in depth.  

The work is focused on three areas of interest: the tropical Pacific, the western Mediterranean, the Madeira Island region. In these regions, the main outcomes of the 2D and 4D analysis will be presented 

Please visit the CAREHeat website (www.careheat.org) and follow us on Twitter (@ careheat_) to stay up to date about the project research and results 

How to cite: Verbrugge, N., Pisano, A., Augot, J., Greiner, E., Landolfi, A., Leonelli, F., Da Toma, V., Organelli, E., Marullo, S., and Santoleri, R.: deteCtion and threAts of maRinE Heat waves (CAREHeat) ESA project:  How to better characterize Marine Heatwaves ? , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7735, https://doi.org/10.5194/egusphere-egu23-7735, 2023.

11:30–11:40
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EGU23-12509
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ECS
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On-site presentation
Cécile Pujol, Iván Pérez-Santos, Alexander Barth, Pamela Linford, and Aida Alvera-Azcárate

Marine heatwaves (MHWs) are described as anomalously warm temperature events over a portion of the ocean during at least five consecutive days, developing in both coastal and open-ocean environments.

MHWs have been subject to numerous studies over the last years and it has been proved that their frequency and intensity is increasing through the decades in connection with human-induced global warming. Most of the studies are focusing on open-ocean MHW events and few in coastal environments, principally due to the lack of adequate data. Indeed, the detection of MHWs requires a long-term climatology of the ocean’s surface temperature, generally made with satellite data. Nevertheless, the complexity of coastal environments makes the use of satellite data non-optimal because of insufficient temporal coverage with high resolution data and interferences with land systems.

The primary purpose of this study is to detect MHWs in a semi enclosed sea, with the study case of the Sea of Chiloé, North Chilean Patagonia. This sea is characterised by multiple fjords and channel systems, and has a cloudy and rainy climate; consequently, this kind of environment is not compatible with the use of satellite data to build the long-term climatology of the sea temperature at a high resolution required to detect the MHWs. Here, we use another way to calculate the climatology, using in situ data and interpolating them in order to have a continuous field. Indeed, the inner seas of North Patagonia have been quite well sampled across the years, with measurements realised since the 1950s, spatially scattered in all the regions at both surface and depth (including fjords and channels). To spatially interpolate these data, we used the tool DIVAnd (Data-Interpolating Variational Analysis) which allows to spatially interpolate in an optimal way discrete observations onto a regular grid, taking advantage of the information in the 4 dimensions. Doing this interpolation, we got a monthly climatology at 32 different depths, from the surface to 400m. MHWs were then detected by comparing the climatology to the local temperature in the Reloncaví Sound, in the Northern part of the Sea of Chiloé, where an anchored buoy recording the temperature of the sea surface since 2017 is present. We focused on MHWs that occurred during the last five years. Strong ones were detected during summers 2021 and 2022: two successive very intense and brief events occurred in January and February 2021, and several short successive events with increasing intensity from November 2021 to February 2022. We also realised the comparison between MHWs detected using in situ data and detected using satellite data.

How to cite: Pujol, C., Pérez-Santos, I., Barth, A., Linford, P., and Alvera-Azcárate, A.: How to detect marine heatwaves in a fjord-like environment ? Study case of the semi-enclosed inner seas of North Patagonia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12509, https://doi.org/10.5194/egusphere-egu23-12509, 2023.

11:40–11:50
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EGU23-13058
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Highlight
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On-site presentation
Francisco Pastor and Samira Khodayar

The Mediterranean Sea has suffered accelerated warming in the last 40 years, bringing higher temperatures mainly in the extended summer season. Sea surface temperature (SST) is not only experiencing higher extremes but also persistent high values. In this context, marine heat waves (MHW), considered as persistent and spatially extensive SST anomalies, have emerged as a key global change-induced high impact on the oceans. Hence, the characterization and trend analysis of MHWs has become of major interest. In this work MHWs in a relatively small, but complex, basin such as the Mediterranean, have been characterized and long-term trends assessed from SST satellite data analysis. In this study, a minimum area threshold, 5 % of the area basin, has been applied to avoid heat spikes or small-scale events. A trend to more frequent, intense, and longer MHWs is found in the 1982–2021 period in the Mediterranean. In the analysis, regional differences were apparent in MHWs characteristics and trends across the different sub-basins evidencing the fact that, even in a relatively small basin such as the Mediterranean, it is necessary to include a spatial perspective in the MHW analysis. Regarding the characterization of MHWs and trend analysis in the Mediterranean, a growing trend has been found in terms of frequency, duration, and intensity that accelerated since 2000 and especially in the last decade. This indicates not only the intensification and higher frequency of MHWs but the emergence of a new type of more intense, long-lasting and spatially extensive MHWs in recent years.

How to cite: Pastor, F. and Khodayar, S.: Marine heat waves: Characterizing a major climate impact in the Mediterranean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13058, https://doi.org/10.5194/egusphere-egu23-13058, 2023.

11:50–12:00
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EGU23-13986
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ECS
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On-site presentation
Sofia Darmaraki, Robin Waldman, Florence Sevault, and Samuel Somot

The Mediterranean Sea, a global climate change hot-spot region, has experienced an increase in marine heatwave (MHW) frequency and intensity since the early 1990s. These extreme events have been associated with a range of local-ecological impacts in the basin, which hosts a large marine biodiversity in addition to 480 million inhabitants along its coasts. According to 21st century projections, the increasing MHW trends are likely to continue in the Mediterranean Sea. This calls for a deeper understanding of MHW drivers that can lead to a higher degree of MHW predictability. Therefore, this study investigates the dominant physical processes behind an ensemble of past Mediterranean MHWs, using the output of a dedicated, fully-coupled regional climate system model in hindcast mode, over the 1980-2018 period. In particular, we explore the vertical signature of multiple events in a local scale through “online” diagnostics of a mixed layer heat budget, where we disentangle the relative role of local-scale dynamics (e.g air-sea interactions, ocean currents, entrainment, mixing) during their development and decline. Preliminary results indicate a key role of atmosphere heat fluxes, wind forcing and vertical mixing on most events and a predominant horizontal advection presence only at smaller-scale. We present here a statistical overview of the dominant MHW drivers at the regional scale, across seasons and different regions in the Mediterranean basin, providing stakeholders and economy sectors affected by these marine extreme events, with critical information on their causes.

How to cite: Darmaraki, S., Waldman, R., Sevault, F., and Somot, S.: Dominant drivers of Past Mediterranean Marine Heatwaves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13986, https://doi.org/10.5194/egusphere-egu23-13986, 2023.

12:00–12:10
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EGU23-16991
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ECS
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On-site presentation
Seonju Lee, Myung-Sook Park, Minho Kwon, Young Gyu Park, Young-Ho Kim, and Nakbin Choi

Under a warming climate, extreme ocean warming events, namely Marine Heatwaves (MHW), have become more frequent and stronger in global ocean regions. This study examines how the long-term variability of global marine heatwave characteristics is affected by global warming. We quantify the long-term trends (1982-2022) of MHW and investigate the connection between mean climate change and MHW trends. Since 1982, MHW properties over most global regions have increased positive signals during winter and summer. We investigate the rapidly variation of marine heatwave duration and intensity over the global ocean regions compared to the global average change. In addition, this study reveals the possible atmospheric and oceanic processes driving these rapidly changes in ocean areas where MHW occurs dramatically increasing. For example, during winter, the MHW has increased rapidly over the northern East Sea region (over 600 %) compared to the past two decades and this region is influenced on the northward shift of warm ocean current.  

How to cite: Lee, S., Park, M.-S., Kwon, M., Park, Y. G., Kim, Y.-H., and Choi, N.: Variation and possible causes of Marine Heatwaves under global warming condition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16991, https://doi.org/10.5194/egusphere-egu23-16991, 2023.

12:10–12:20
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EGU23-17173
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ECS
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On-site presentation
Eike Eduard Köhn, Nicolas Gruber, Matthias Münnich, and Meike Vogt

In recent decades, the Eastern Pacific has been subject to many pronounced marine heatwaves (MHWs), with far-reaching consequences for marine ecosystems. As MHWs are commonly detected at the sea surface, little is known about their vertical structure, let alone the temporal variability of this structure. To fill this gap, we detect and characterise vertically extended MHWs within a high-resolution model hindcast simulation (1979-2019) of the Eastern Pacific. Considering the vertical dimension in the MHW detection furthermore enables the tracking of vertical MHW propagation. We find that 71% of MHWs are on average confined to the mixed layer, while 29% reach at least 10m below. By clustering the MHWs, we identify four main vertical propagation patterns. While the majority of MHWs remains at the surface throughout their lifetime, 18% (13%) of MHWs subduct beneath (shoal towards) the surface, while 12% rather sit beneath the surface and exhibit multi-surfacing behaviour. As a consequence of the vertical propagation, MHWs affect upper ocean ecosystems substantially longer than diagnosed from the sea surface (40 vs. 30 days on average).In the mid-latitude Northeast Pacific, we find a seasonal cycle in the vertical MHW propagation clusters. We find that wintertime MHWs can detrain from the mixed layer, persist in the seasonal thermocline and re-entrain into the ML at a later stage. This finding agrees well with previous work on the role of the re-emergence phenomenon of sea surface temperature anomalies in the North Pacific and suggests potential sources of predictability for MHWs at the sea surface. At lower latitudes, we find that interannual variability associated with the El Niño-Southern Oscillation strongly dominates any seasonality in the occurrence of the different MHW clusters. Lastly, we find that accounting for the vertical MHW propagation almost doubles the average Eastern Pacific area affected by MHWs, compared to the surface only perspective. These new insights regarding MHW depth structures and their temporal variability mark an important step towards a better understanding of MHW drivers and the consequences of MHWs for marine ecosystems.

How to cite: Köhn, E. E., Gruber, N., Münnich, M., and Vogt, M.: On the structure and variability of vertically propagating marine heatwaves in the Eastern Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17173, https://doi.org/10.5194/egusphere-egu23-17173, 2023.

12:20–12:30
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EGU23-6472
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ECS
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On-site presentation
Riccardo Martellucci, Milena Menna, Marco Reale, Gianpiero Cossarini, Stefano Salon, Giulio Notarstefano, Elena Mauri, Pierre-Marie Poulain, Antonella Gallo, and Cosimo Solidoro

In October 2021, the Sicily Channel and the central-western Ionian Sea were affected by the passage of the tropical-like cyclone, or MEDICANE, Apollo. The system reached its maximum intensity between 29 and 30 October 2021 producing several damages, intense precipitations and huge coastal floodings in Sicily and Calabria regions. The surface circulation in the MEDICANE impacted area was characterized by permanent cyclonic vortices, offering the chance to describe the impact of a tropical-like cyclone on a pre-existing cold circulation structure. Atmospheric and ocean reanalyses (ERA5 and Marine Copernicus Service), as well as in-situ data from Argo floats, were used to describe the temporal evolution of Apollo, the resulting air-sea interaction, the thermohaline and biological response to its passage in the upper layer (0-150 m) of the western Ionian Sea. During the event, the core of the marine cyclone was characterized by a dramatic drop in temperature, corresponding to a local maximum in the wind-stress curl, Ekman pumping and current field relative vorticity. The strengthening of the cyclonic circulation led by the wind stress curl produced a strong vertical mixing in the surface layer (from 0 m to the Mixed Layer Depth - MLD) and an upwelling in the subsurface layer below the thermocline (MLD-150 m). The combined effect of vertical mixing and upwelling resulted in a shoaling of MLD, deep chlorophyll-a maximum, nutricline, and halocline. Oxygen and chlorophyll-a concentrations increased at surface, due to the enhanced oxygen solubility in the cooler water and higher productivity due to the increase of nutrients upwelled to the surface layer. These results show that the pre-existing cyclonic vortex along Apollo's trajectory leads to a different physical response compared to the one observed during previous MEDICANEs, confirming the influence of the conditions in place in driving the ocean’s reply to the extreme weather systems.

How to cite: Martellucci, R., Menna, M., Reale, M., Cossarini, G., Salon, S., Notarstefano, G., Mauri, E., Poulain, P.-M., Gallo, A., and Solidoro, C.: A case study of impacts of the extreme weather system on ocean circulation features in the Mediterranean Sea: Medicane Apollo (2021), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6472, https://doi.org/10.5194/egusphere-egu23-6472, 2023.

Posters on site: Wed, 26 Apr, 16:15–18:00 | Hall X5

Chairpersons: Giovanni Liguori, Cosimo Enrico Carniel, Matjaz Licer
Short convener introduction
X5.395
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EGU23-212
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ECS
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Jun Yu Puah

COASTAL CURRENTS AND THEIR EXTREMES IN SINGAPORE

Jun Yu Puah*1, David Lallemant1,2, Ivan D. Haigh3, Kyle M. Morgan1,2, Dongju Peng2, Adam D. Switzer1,2

1Asian School of the Environment, Nanyang Technological University, Singapore

2Earth Observatory of Singapore, Nanyang Technological University, Singapore 

3School of Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, UK

*a210012@e.ntu.edu.sg

 

Extreme currents are integral as they affect ship navigation and public safety. However, research on extreme currents is scarce and further hampered by the lack of long-term observational records. In this study we estimate the characteristics of extreme shallow-water currents in Pulau Hantu and Kusu Island located in the Singapore Strait and investigate their potential drivers. We apply harmonic analysis to around 12 months of data to decompose the observed currents into tidal and residual components. The tail distribution of the residual component was estimated using extreme value analysis by fitting a non-homogeneous Poisson process to the data, accounting for temporal and directional dependences. Random simulations of tidal currents were then combined with residual currents via the Joint Probability Method to generate new observed current realizations. Finally, wind data was extracted from ERA5 Reanalysis to investigate how well monsoonal winds correlates with residual currents across monsoon periods. Tidal variance ranges from 29-69% across all sites, which is lower than expected given the dominance of tidal currents in the Singapore Strait. Extreme currents orient mainly in 2 directions along the coastline contours. Mean speed in Pulau Hantu is greater than Kusu Island and may be attributed to the hydrodynamic pressure gradient set up by the monsoons. Lastly, the stronger correlation observed in some sites during the inter-monsoon periods demonstrates the importance of localized winds from local systems such as Sumatra squalls in driving extreme currents. The variability of the study results highlights the challenges in modelling currents in the Singapore Strait given its complex bathymetry, equatorial weather patterns and complex tidal regime. Future work could include the integration of shipborne Automated Information Systems to examine extreme currents and evaluate the role of meteorological effects in driving extreme currents in the region. 

How to cite: Puah, J. Y.: Coastal Currents and their Extremes in Singapore, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-212, https://doi.org/10.5194/egusphere-egu23-212, 2023.

X5.396
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EGU23-3740
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ECS
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solicited
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Saranya Jayanthi Sasikumar and SungHyun Nam

Extreme oceanic conditions known as marine heatwaves (MHWs) are characterized by high seawater temperature (beyond the 90th percentile threshold) that has a negative impact on marine ecosystems and humanity. The East Sea (Japan Sea), a semi-enclosed deep basin connected to the outside seas/ocean by shallow and narrow straits, has recently experienced the most rapid upper ocean warming in the world seas. Characteristics and evolution of MHWs in the East Sea, including their subsurface evolution, need to be better understood as still poorly understood in spite of recent reports on their increasing frequency and severity. Here, the sea’s MHWs retrieved from ocean reanalysis/model data (Simple Ocean Data Assimilation (SODA), HYbrid Coordinate Ocean Model (HYCOM), Global Ocean Reanalysis product (GLORYS) and Estimating the Circulation and Climate of the Ocean (ECCOVr4)) were initially compared to those from a long-term (from 2000 to 2014) time-series observations conducted near the east coast of Korea using a surface mooring named the East Sea Real-Time Ocean Buoy (ESROB). Then, a rising frequency of annual mean and summer (JJA) MHWs from 1982 to 2019 throughout the entire East Sea was characterized using the SODA, HYCOM, GLORYS, and ECCOVr4, yielding a maximum increasing rate of 0.45 occurrences per decade. Using unsupervised machine learning clustering techniques (K-mean and Hierarchical), three different types of MHW evolutions were identified — subsurface to surface evolution (Type-A), surface evolution (Type-B), and surface to subsurface evolution (Type-C) in six sub-regions — three in the west and three in the east. This study discusses possible explanations for these types of MHW evolution in the selected sub-regions of the sea, providing better understanding of surface and subsurface MHWs in the most rapidly warming marginal sea.

How to cite: Jayanthi Sasikumar, S. and Nam, S.: Types of the evolution and dynamics of marine heatwaves in the East Sea (Japan Sea), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3740, https://doi.org/10.5194/egusphere-egu23-3740, 2023.

X5.397
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EGU23-4662
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ECS
Panini Dasgupta, SungHyun Nam, Saranya Jayanthi Sasikumar, and Roxy Mathew Koll

Recent intensification of the west Pacific warmpool has altered the western boundary currents and subtropical gyres, and turned East-Asian marginal seas (EAMS) into the most rapid warming ocean bodies on Earth. Along with the long-term increasing temperature, the EAMS often experience episodic events of incredibly high sea surface temperatures (SST), known as marine heatwaves (MHWs), which significantly adversely affect the vibrant marine ecosystems in these regions. Interannual climate forcing, such as the decaying El Niño Southern Oscillation (ENSO), also creates favourable conditions for MHWs in EAMS. However, in addition to the long-term trend and interannual background conditions, dominant intraseasonal variability in the tropics, such as Madden Julian Oscillation (MJO) in boreal winter and Boreal Summer Intraseasonal Oscillation (BSISO) in boreal summer, may influence the EAMS SST remotely. This study explores the pathways and mechanisms by which MJO and BSISO influence MHWs in the EAMS region. We show that specific phases of MJO (phases 2, 3, and 4) during boreal winter and summer (BSISO phases 5, 6, and 7) create favourable conditions for the occurrence of MHWs in these regions. Using Estimating the Circulation and Climate of the Ocean (ECCOv4) reanalysis datasets, we further separate the relative contribution of heat and salt changes by MJO and BSISO to the MHWs in EAMS, suggesting key factors that are vital in triggering MHWs in different areas of EAMS.

How to cite: Dasgupta, P., Nam, S., Jayanthi Sasikumar, S., and Mathew Koll, R.: Impact of Madden Julian Oscillation and boreal summer intraseasonal oscillation on the marine heat waves of East-Asian Marginal Seas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4662, https://doi.org/10.5194/egusphere-egu23-4662, 2023.

X5.398
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EGU23-10885
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ECS
Hyoeun Oh and Jin-Yong Jeong

In 2022, there were record-breaking long-lasting marine heatwaves in the East China Sea, which persisted for 62 days during boreal summer. It was more than sixfold compared to the average duration of the marine heatwaves, which is 9.73 days. It would be recorded as a year when not only marine heatwaves but also various extreme events occurred throughout Asia, such as the summer flood in China and Pakistan. The question arises whether it is caused by La Niña, the first “triple-dip” of the century. Here we will show key local and remote processes that caused the 2022 long-lasting marine heatwaves in the East China Sea. We have conducted a diagnostic analysis based on the mixed-layer heat budget equation to discover the characteristics of the marine heatwaves, i.e., frequency, duration, and intensity. Based on the equation, we found that weakening ocean vertical mixing and entrainment caused by a density stratification would drive the onset of the marine heatwave in the East China Sea. A large river discharge from the Yangtze River related to extreme rainfall in China would be responsible for the stratification by inducing a shallow mixed layer, and it could affect the weak ocean dynamics. Simultaneously, an anomalous anticyclonic circulation was settled in the corresponding region, and the combined effect of the ocean and atmosphere led to the onset of the marine heatwave. The anticyclonic circulation was sustained longer, resulting in the prolonged marine heatwaves in the East China Sea via enhanced shortwave radiation. In this study, we will discuss further where the stationary Rossby wave train originated and how it could lead to the persistent anticyclonic circulation in the East China Sea.

How to cite: Oh, H. and Jeong, J.-Y.: The record-breaking 2022 long-lasting marine heatwaves in East China Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10885, https://doi.org/10.5194/egusphere-egu23-10885, 2023.

X5.399
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EGU23-11032
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ECS
Seung-Woo Lee, Suyun Noh, Gyundo Pak, Jae-Hyoung Park, Su-Chan Lee, and Jin-Yong Jeong

Due to climate change, the occurrence of extreme events such as typhoons, marine heat waves, storminess, and cold waves is increasing in many regions, and these events could dramatically change with significant impacts on the marine environment (e.g., ocean circulation). The East Korea Warm Current (EKWC) has been recognized to flow along the western boundary current of the East Sea (Japan Sea). To examine the variations of EKWC, six bottom-mounted current profiler moorings were operated off the east coast of Korea (the Hupo Bank and Wangdolcho) since June 2021. The observed mean current speed and their principal axis were 0.40 m/s and 58o (counterclockwise from the east) implying northeastward EKWC over the region. In August 2021, an unprecedentedly strong surface current was observed with a maximum of 1.89 m/s and observed currents showed similar variability at mooring sites and several depths. This strong current lasted for about a month, and then rapidly disappeared within a few days. At that time, the geostrophic currents based on satellite-altimetry has a strong current pattern with the Inertial Boundary Current pattern, which is one of the EKWC patterns that flows strongly northward currents closer coast. In addition, the highest mean speed of the EKWC near the mooring sites from 1993 was found in August 2021. The high-speed period was similar to the period of the North Pacific marine heat waves that were already reported, and the low-speed period was related to typhoon passage. This study reported the results of observed EKWC for two years from 2021 and the unprecedentedly enhanced EKWC in August 2021. In particular, it can be a case in which the rapid changes of western boundary currents interact with extreme events such as marine heatwaves and typhoons.

How to cite: Lee, S.-W., Noh, S., Pak, G., Park, J.-H., Lee, S.-C., and Jeong, J.-Y.: Observation of intensification of western boundary current in summer of 2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11032, https://doi.org/10.5194/egusphere-egu23-11032, 2023.

X5.400
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EGU23-11442
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ECS
Sounav Sengupta, Yosef Ashkenazy, and Hezi Gildor

The Gulf of Eilat is a body of water located at the northern tip of the Red Sea and is
known for its unique marine ecosystem. We analyzed the sea temperature and
salinity, air temperature, heat flux, and other climatological data in order to better
understand the processes driving the Gulf's dynamics. The sea temperature data
was based on 18 years of measurements taken at depths up to 700 meters, while
the meteorological data was based on 16 years of observations. The analysis
indicates the sea temperature is significantly increasing at all depths; yet, no clear
trends were found in the air temperature. The increased warming is associated with
much fewer deep mixing events and used to occur more frequently. We constructed
the ocean-atmosphere heat fluxes and concluded that the horizontal advection of
heat from the southern part of the Red Sea might underlie the increase in water
temperature in the Gulf of Eilat. This conclusion is also supported by the recent IPCC
reports and previous studies. Our results indicate that local ocean warming is not
necessarily linked to a local increase in air temperature but rather to the warming of
other remote places.

How to cite: Sengupta, S., Ashkenazy, Y., and Gildor, H.: Warming of the Gulf of Eilat (Red Sea) water due to advection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11442, https://doi.org/10.5194/egusphere-egu23-11442, 2023.

X5.401
|
EGU23-14714
Rossella Ferretti, Lorenzo Sangelantoni, Gianluca Redaelli, Cosimo Enrico Carniel, and Dino Zardi

From December 23rd 2021 to January 4th 2022 and from December 20th to January 8th 2023, two “Extreme Warm Spell” (EWS) episodes have occurred in the Mediterranean Basin and central-western Europe. These phenomena led to several and long-lasting record-breaking atmospheric temperatures in the impacted areas. Combining both intensity and duration, these two episodes can be identified as extremely warm winter events. In the first one (2021-2022), 850hpa temperatures over 15°C were recorded near Spanish, Italian and French coasts and the Western Mediterranean (WM) in general, and a SST anomaly of 1°C in December over the WM sea. The second event (2022-2023) was characterized by a zonal development, affecting the Balearic Sea, Northern Africa coasts and Italy, with 850hPa temperatures that, in different impulse, reached 12-16°C and a strong SST anomalies, affecting both previous months (showing peaks between +6.8 and +5 °C in September and November) and December (+2/3°C). In this work, the two EWSs are statistically analyzed by comparison with the climatology data set from both atmospheric and oceanic point of view using EOF analysis. Then, the last 40-year trend is assessed. Using satellite, Argo float, buoy and model dataset we characterize the 6 months preceding the EWS, exploring the Surface Temperature, Mixed Layer Depth (MLD) and its dynamic, estimating the Ocean Heat Content (OHC). Moreover, we investigated the impact of SST anomalies and Mixed Layer Depth on the atmospheric structure, and vice-versa, using WRF-ARW (Weather Research and Forecasting System) numerical model at 5km resolution horizontal grid, covering all the Mediterranean and central Europe, and SST provided by CMEMS-GOS 1 km resolution daily dataset and ECMWF-IFS boundary conditions. WRF-ARW model is coupled with a 1D ocean model (SLAB ocean model), computing the evolution of the MLD and SST in function of heat fluxes at the air-sea interface, to estimate how much heat was exchanged between the two environments. We also performed a sensitivity run (for each event), in which we removed the SST anomaly and the MLD anomaly, with the aim of isolating the contribution of the OHC in the atmospheric dynamics, and the impact of the atmosphere on the SST and OHC anomaly. Results show two distinct conditions, despite the EWSs are driven by similar large-scale forcing and atmospheric patterns. In particular, the preconditioning features of SST and OHC are very different (the 2022-2023 event derives from 6 month of strong positive anomaly if compared to 2021-2022 event). In general, the SST anomaly impacts especially humidity and ground temperature, up to 850 hPa pressure level. Nevertheless, the main driver is the synoptic atmospheric circulation, precisely a deep trough in the central Atlantic which advects warm air from the tropics and interacts with the mild Mediterranean Sea. On the other hand, the sea does not show high heat fluxes during December–January (usually period of strong cooling in the WM) retaining a large part of OHC between the surface and the thermocline, with possible role on subsequent events, both in thermohaline circulation and in atmospheric dynamics.

How to cite: Ferretti, R., Sangelantoni, L., Redaelli, G., Carniel, C. E., and Zardi, D.: Analysis of extreme Winter Warm Spell and Sea Surface Temperature Anomaly during 2021 and 2022 over Western Mediterranean Sea., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14714, https://doi.org/10.5194/egusphere-egu23-14714, 2023.

X5.402
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EGU23-5243
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ECS
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solicited
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaz Licer

We propose a new DEep Learning WAVe Emulating model (DELWAVE) which successfully emulates the behaviour of a numerical surface ocean wave model SWAN, thus enabling numerically cheap large-ensemble prediction over synoptic to climate timescales. DELWAVE training inputs consist of 6-hourly surface COSMO-CLM wind fields during period 1971 - 1998, while its targets are surface wave significant wave height, mean wave period and mean wave direction. Testing input set consists of surface winds during 1998-2000 and cross-validation period is the far-future climate timewindow of 2071-2100. Several detailed ablation studies were performed to determine optimal performance regarding input fields, temporal horizon of the training set and network architecture. DELWAVE reproduces SWAN model significant wave heights with a mean absolute error (MAE) between 5 and 10 cm, mean wave directions with a MAE of 10-25 degrees and mean wave period with a MAE of 0.2 s. SWAN and DELWAVE time series are compared against each other in the end-of-century scenario (2071-2100), and compared to the control conditions in the 1971-2000 period. Good agreement between DELWAVE and SWAN is confirmed also when considering climatological statistics, with a small (5%), though systematic, underestimate of 99th percentile values. Compared to control climatology, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modeling is substantially weaker than the climate change signal.

How to cite: Mlakar, P., Ricchi, A., Carniel, S., Bonaldo, D., and Licer, M.: DELWAVE 1.0: Deep-learning surrogate model of surface wave climate in the Adriatic Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5243, https://doi.org/10.5194/egusphere-egu23-5243, 2023.

X5.403
|
EGU23-14722
Aniello Russo, M. Marcello Miglietta, Rossella Ferretti, Gianluca Redaelli, Francesco Barbariol, Alvise Benetazzo, Davide Bonaldo, Francesco Falcieri, Mauro Sclavo, Silvio Davison, and Sandro Carniel

From 6 to 8 November 2011, a baroclinic wave moved from North Atlantic to Balearic Sea, produced a cut-off, at all altitudes, and developed into a Tropical-Like Cyclone (TLC) characterized by a deep-warm core. This TLC led to a mean sea level pressure minimum of about 987 hPa, 10 m wind speeds higher than 30 m/s around the eye, and very intense rainfall, especially in the Gulf of Lion and the surrounding areas, close to the mountain chains (floods in Genoa and Elba Island).

To explore in details the effect of the sea surface temperature on the TLC development, we employed the coupled modeling system COAWST, which consists of the following models: ROMS for the hydrodynamic part, WRF for the meteorological part and SWAN for the surface wave modeling, using a 5 km horizontal grid over all Mediterranean Sea.

COAWST was used with different configurations: Stand Alone (SA) approach using only the atmospheric part, atmosphere-ocean coupled mode (AO), and fully coupled version including also surface waves (AOW). Comparing the three runs, the effects of different simulations on the TLC trajectory are significant only in the later stage of the cyclone lifetime. On the other hand, wind intensity is higher in the SA case w.r.t. both coupled runs. When compared to case AO, winds are about 1 m/s larger, even though the spatial distribution is very similar (possibly because of the lower SST produced by case AO). Case AOW produces less intense winds than SA and AO case in the areas where the wave is most developed (differences are about 2-4 m/s), while winds are more intense nearby the cyclone’s eye. Moreover, the inclusion of the wave model (AOW) has implications in the water column, by increasing the mixing in the ocean, changing the depth of the ocean mixed layer along the track of the TLC, increasing the surface drag and the net heat fluxes from ocean to atmosphere, so that eventually SST in AOW run is colder than in AO.

It is observed that SST of the SA case is overestimated compared to the coupled cases, and in particular the best performances are observed using the fully coupled case, with the wave motion implementation. The best description of the SST impacts the cyclone intensity and the amount of precipitation at catchment scale. The vertical profiles show that wave induced mixing modifies the mixed layer structure and cools the water column, removing much of the SST (and Ocean Heat Content) anomaly present in the mixed layer.

The date chosen for the run initialization appears important: an earlier initial condition allows to properly simulate the evolution of the cyclone from the cyclogenesis between the inclusion and setting-up of air sea interaction effect, through the coupled models.

Warming SST in the Mediterranean Sea induced by climate change might increase TLC frequency and/or intensity, potentially becoming more harmful for coastal populations and infrastractures. Fully coupled AOW models might be better suited for studying such aspects. 

Funding from the STO Office of Chief Scientist (907EUR30) is gratefully acknowledged.

How to cite: Russo, A., Miglietta, M. M., Ferretti, R., Redaelli, G., Barbariol, F., Benetazzo, A., Bonaldo, D., Falcieri, F., Sclavo, M., Davison, S., and Carniel, S.: On the use of coupled atmosphere-ocean-wave model for investigate air-sea interaction and ocean response to extreme Tropical-Like Cyclone “ROLF”, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14722, https://doi.org/10.5194/egusphere-egu23-14722, 2023.

X5.404
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EGU23-6526
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ECS
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solicited
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Rossella Ferretti, Giovanni Liguori, Leone Cavicchia, Mario Marcello Miglietta, Davide Bonaldo, Antonio Ricchi, and Sandro Carniel

An enhanced understanding of Climate Change related implications in the maritime domain is needed in order to improve coastal infrastructure resilience and possible future operations, also in terms of climate security. Although the Mediterranean Sea is a relatively mild basin, it is however characterized by high geopolitical and economic relevance, occasionally showing intense cyclones with tropical-like characteristics known as Tropical-Like Cyclones (TLC). Many studies have highlighted that sea surface temperature (SST) distribution and anomalies play a crucial role in modulating the intense air-sea exchange, hence controlling both development and evolution of TLCs. However, given the complex interplay among ocean mixed layer, heat content and temperature, the role of the mixed layer depth (MLD) is of paramount importance. In this study we investigated the role of both SST anomaly, horizontal gradients and MLD profile on the origin and evolution of a recent record-breaking TLC (named IANOS). This cyclone originated over the southern Ionian Sea from 14 Sept 2020 to 19 Sept 2020, moving over the Central Ionian Sea from south-west to North-East, and made landfall over Greece mainland coast. It developed over a basin where a positive SST anomaly up to 4 °C was detected, which coincided with the sea area where it reached the maximum intensification and strength. We conducted a series of experiments using an atmospheric model (WRF - Weather Research and Forecasting system) driven by underlying SST (standalone configuration), either with daily update or coupled to a simple mixed-layer ocean model (SLAB ocean), with SST calculated at every time step using the SLAB ocean for a given value of the MLD. Sensitivity tests were performed increasing or decreasing MLD depth by 10 m, 30 m, 50 m, 75 m, 100 m, removing the horizontal gradients, removing the SST anomaly. Then, possible past and future climatological scenarios of MLD thickness were identified and tested. Preliminary results show that the MLD influences not only the intensity of the cyclone but also the structure of the precipitation field both in terms of magnitude and location. The fundamental role of the SST anomaly was also found to be essential to provide intense characteristics to IANOS. Results deserve further investigation in particular in the context of climate change scenarios that can provide useful insights into impact on coastal civil and military infrastructures in the whole Mediterranean region.

 

How to cite: Ferretti, R., Liguori, G., Cavicchia, L., Miglietta, M. M., Bonaldo, D., Ricchi, A., and Carniel, S.: Exploring how a warmer Mediterranean Sea affects the origin and development of destructive Tropical-Like Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6526, https://doi.org/10.5194/egusphere-egu23-6526, 2023.

X5.405
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EGU23-14597
Antonella Gallo, Annunziata Pirro, Riccardo Martellucci, Elisabeth Kubin, Elena Mauri, Giulio Notarstefano, Massimo Pacciaroni, Antonio Bussani, and Milena Menna

Marine Heatwaves are periods of persistent anomalously warm ocean temperatures, which can have significant impacts on ecosystems as well as coastal communities and economies. Their magnitude and frequency have increased over the last couple of decades as shown by surface satellite observations, but our understanding of the structure of their depth is still limited. 

The present work investigates the temperature anomaly of the 2022 Marine Heatwave in the Mediterranean Sea down to 2000 m depth using in-situ Argo floats observations. The Ocean Heat Content anomaly of 2022, estimated with respect to a float-derived climatology relative to the period 2001-2020, was used to define the regions most affected by warming in different layers. In these areas (North-Western Med, Central Ionian Sea, Southern Adriatic) float profiles were divided in three categories, based on the heat vertical penetration: category 1 (shallow, 0-150 m), category 2 (intermediate, 150-800 m), category 3 (deep, > 800 m). Profiles from category 1 showed near-zero or slightly negative temperature anomaly in a thin layer between 50 m and 150 m of depth, while displaying a warming below the intermediate layer. Profiles characterized by larger heat vertical penetration (categories 2 and 3) were mainly located within mesoscale or sub-basin scale structures and showed the largest positive temperature anomaly in the surface layer and in the thermocline. All profile categories exhibited a warming between 200 and 800 m depth. This study highlights the impact of Marine Heatwaves on the Mediterranean subsurface layers and the influence of ocean circulation on their characteristics, opening the way to describe their consequences on the deep ecosystems. 

How to cite: Gallo, A., Pirro, A., Martellucci, R., Kubin, E., Mauri, E., Notarstefano, G., Pacciaroni, M., Bussani, A., and Menna, M.: Subsurface temperature anomaly observed by Argo floats during the 2022 Mediterranean Marine heatwave, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14597, https://doi.org/10.5194/egusphere-egu23-14597, 2023.

X5.406
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EGU23-17294
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ECS
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solicited
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Joel Wong, Nicolas Gruber, and Matthias Münnich

Marine extreme events can be detrimental to organisms and ecosystems across the global ocean. Marine heatwaves (MHW), ocean acidity extremes (OAX) and low oxygen extremes (LOX) occur everywhere, superimposed on the already changing trends of temperature, pH, and oxygen. When such extremes concurrently occur in the vertical column, the habitable space for marine organisms can be severely reduced. We use daily output from a hindcast simulation with the Community Earth System Model coupled with Biological Elemental Cycling (CESM-BEC) for the period 1961-2020 to characterise such compound extremes. Extreme conditions are identified on a moving baseline with the 95th or 5th percentile, and an additional absolute threshold of 150 μM for low oxygen conditions. To investigate compound events in the vertical dimension, at least 50 m out of the top 300 m is required to be extreme with respect to each stressor. Such an event is termed a column-compound extreme event (CCX). On average, 1% of the global ocean volume is occupied by CCXs and up to 5% at maximum. On a fixed baseline these values increase to 8% and 27% respectively. CCXs decrease habitable space by up to 75% and have high intensity index of more than 2 in many regions around the globe. El Niño-Southern Oscillation events are found to be strongly associated with CCXs in the tropical and subtropical Pacific, but also other ocean basins through teleconnections. The global volume of CCXs is expected in increase in the future, exacerbating impacts and reducing habitable space of marine organisms.

How to cite: Wong, J., Gruber, N., and Münnich, M.: Characteristics of Recent Column-Compound Extremes in the Global Ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17294, https://doi.org/10.5194/egusphere-egu23-17294, 2023.