Hazem Nagy

Atmospheric heatwaves (AHWs) and marine heatwaves (MHWs) are intensifying under climate change, yet their coupled behavior in the Red Sea remains insufficiently quantified. This study investigates the spatial and temporal characteristics of AHWs, MHWs, and their concurrent occurrence across the Red Sea from 1990 to 2024 using ERA5 surface air temperature (SAT) and NOAA OISST v2.1 satellite-derived sea surface temperature (SST). Remote-sensing daily satellite-derived Level-4 (L4) OISST products were used in this study to enable spatially complete and temporally consistent detection of MHWs in this narrow, semi-enclosed basin despite contamination and coastal sampling constraints. Both SAT and SST exhibit statistically significant warming trends (p < 0.05), with basin mean increases of 0.40 ± 0.07 °C/decade and 0.31 ± 0.05 °C/decade, respectively. The strongest warming was observed in the central and northern Red Sea. This warming is accompanied by significant increases in the frequency and duration of AHWs, MHWs, and their concurrent AHW-MHW events, particularly after 2010, indicating a shift toward more frequent heatwave conditions. AHWs occur more frequently than MHWs across the Red Sea, whereas MHWs exhibit long duration, particularly in the northern Red Sea, where annual durations exceed 45–50 days/year. Concurrent AHW-MHW events account for about 66% of MHWs in the Red Sea, and their characteristics show a significant increasing trend across the entire basin. These findings identify the Red Sea as a regional hotspot of increasing concurrent heatwave events and highlight the importance of satellite-based monitoring for assessing evolving climate risks in semi-enclosed basins.

Heatwaves are now considered one of the main stressors of global warming. As a result of anthropogenic warming, atmospheric and oceanic heatwaves have increased in frequency, intensity and duration in recent decades. These extreme events have recently become a major concern in climate research due to their economic and environmental impacts on ecosystems. In this study, we investigated the co-occurrence and relationship between atmospheric and marine heatwaves (AHW/MHW) in the Eastern Mediterranean (EMED) over the last four decades (1982–2021). Furthermore, the spatio-temporal variability and trends of sea surface temperature (SST), near-surface air temperature (SAT), AHW and MHW characteristics (frequency and duration) were examined. For these objectives, we used daily gridded high-resolution satellite SST data (0.05° × 0.05°) and the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF-ERA5) atmospheric reanalysis SAT and wind components (0.25° × 0.25°). The results showed an average warming trend of about 0.38 ± 0.08 °C/decade and 0.43 ± 0.05 °C/decade for SAT and SST, respectively. A high statistically significant (p < 0.05) correlation (R = 0.90) was found between AHW and MHW frequency. Our results showed that more than half of the MHWs in the EMED co-occurred with AHWs throughout the study period. The most intense summer MHW in 2021, which co-occurred with AHW, was associated with higher positive anomalies of SAT and SST, and a decrease in the wind speed anomaly.

Clew Bay is an important aquaculture production area in Ireland. In this study, we focused on a high-resolution simulation of the Clew Bay region based on a regional ocean modeling system (ROMS). Freshwater discharges from eight rivers are included in the model and a wetting–drying scheme has been implemented. The Clew Bay model simulation was validated and calibrated with available observations (e.g., acoustic Doppler current profiler (ADCP), vertical salinity and temperature profiles, and a tide gauge) in the geographic area of the model domain. High correlations were found between the model data and observed temperature, salinity and water levels, along with small root mean square errors. This indicates that the model is able to reproduce the oceanographic phenomena in the study area. The Taylor diagram analysis showed a high correlation coefficient (R = 0.99) between the observed bottom temperature in the Inner Bay and Clew Bay model, along with a small centered root mean square error (RMSD = 0.5 °C). High correlation coefficients (R > 0.80) were found between the model and the two ADCPs for the zonal current component. There was a resemblance in structure between the model and the observed salinity profiles, indicating that freshwater was correctly implemented in the model. Moreover, the correlation coefficient between the model and the tidal sea surface height (SSH) was 0.99, with an RMSD of 0.09 m. We discovered that wind direction and speed had a significant impact on the bay’s water inflow rate. The model outputs can be used to provide scientists, fishermen, and decision-makers with hydrodynamic information on ocean conditions in the bay.

Clew Bay is an important aquaculture production area in Ireland. In this study, we focused on a high-resolution simulation of the Clew Bay region based on a Regional Ocean Modelling System (ROMS). Freshwater discharges from eight rivers are included in the model and a wetting-drying scheme has been implemented. The Clew Bay model simulation was validated and calibrated with available observations (e.g., Acoustic Doppler Current Profilers (ADCP), vertical salinity and temperature profiles and tide gauge) in the geographic area of the model domain. High correlations were found between the model outputs and observed temperature, salinity and tide gauge water levels along with small Root Mean Square Errors. This indicates that the model was able to reproduce the oceanographic phenomena in the study area. The Taylor diagram analysis showed a high correlation coefficient (R=0.99) between the ADCP bottom temperature in the Inner Bay and the Clew Bay model, along with a small Centered Root Mean Square Error (RMSD =0.5 ◦ C). High correlation coefficients (R > 0.80) were found between the model and the two ADCPs for the zonal current component. There was a resemblance in structure between the model and the observed salinity profiles, indicating that freshwater was correctly implemented in the model. Moreover, the correlation coefficient between the model and the tidal sea surface height (SSH) was 0.99, with an RMSD of 0.09 m. We discovered that wind direction and speed have a significant impact on the bay's water inflow rate. The model outputs can be used to provide scientists, fishermen and decision-makers with hydrodynamic information on ocean conditions in the bay.

Extreme events such as Marine Heat Waves (MHWs) and Low Chlorophyll-a (LChl-a) in the ocean have devastating impacts on the marine environment, particularly when they occur simultaneously (i.e., the compound of MHWs and LChl-a events). In this study, we investigate the spatiotemporal variability of MHWs and LChl-a events in the Arabian and Omani Gulf. For this purpose, we used satellite-based high-resolution observations of SST (0.05° × 0.05°; from 1982 to 2020) and chlorophyll-a concentration data (0.04° × 0.04°; from 1998 to 2020). Hourly air temperature, wind, and heat flux components from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) were used to explain the link between these extreme events and atmospheric forcings. Moreover, our results revealed that the annual frequency of MHW and LChl-a is related to the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The results revealed an average SST warming trend of about 0.44 ± 0.06 °C/decade and 0.32 ± 0.04 °C/decade for the Arabian Gulf (AG) and the Gulf of Oman (OG), respectively. This warming rate was accompanied by MHW frequency and duration trends of 0.97 events/decade and 2.3 days/decade, respectively, for the entire study region from 1982 to 2020. The highest annual MHW frequencies were recorded in 2010 (6 events) and 2020 (5 events) associated with LChl-a frequency values of 4 and 2, respectively. La Niña events in 1999, 2010, 2011, and 2020 were associated with higher frequencies of MHW and LChl-a. The positive phase of IOD coincides with high MHW frequency in 2018 and 2019. The longest compound MHW and LChl-a event with a duration of 42 days was recorded in 2020 at OG. This extreme compound event was associated with wind stress reduction. Our results provide initial insights into the spatiotemporal variability of the compound MHW and LChl-a events that occurred in the AG and OG.

Marine heatwaves (MHWs) have recently been at the forefront of climate research due to their devastating impacts on the marine environment. In this study, we have evaluated the spatiotemporal variability and trends of sea surface temperature (SST) and MHWs in the Black Sea. Furthermore, we investigated the relationship between the El Niño–Southern Oscillation (ENSO) and MHW frequency. This is the first attempt to investigate MHWs and their characteristics in the Black Sea using high-resolution remote-sensing daily satellite SST data (0.05° × 0.05°) from 1982 to 2020. The results showed that the spatial average of the SST warming rate over the entire basin was about 0.65 ± 0.07 °C/decade. Empirical orthogonal function (EOF) analysis revealed that SST in the Black Sea exhibited inter-annual spatiotemporal coherent variability. The maximum spatial SST variability was discovered in the central Black Sea, whereas the lowest variability was in the Batumi and Caucasus anti-cyclonic eddies in the eastern Black Sea. The highest SST temporal variability was found in 1994. More than two-thirds of all MHW events were recorded in the last decade (2010–2020). The highest annual MHW durations were reported in 1994 and 2020. The highest MHW frequency was detected in 2018 (7 waves). Over the whole study period (1982–2020), a statistically significant increase in annual MHW frequency and duration was detected, with trends of 1.4 ± 0.3 waves/decade and 2.8 ± 1.3 days/decade, respectively. A high number of MHW events coincided with El Niño (e.g., 1996, 1999, 2007, 2010, 2018, and 2020). A strong correlation (R = 0.90) was observed between the annual mean SST and the annual MHW frequency, indicating that more MHWs can be expected in the Black Sea, with serious consequences for the marine ecosystem.

The study of heat and water fluxes is one of the most essential components for understanding the interactions and exchanges between the ocean and atmosphere. Heat transfer across the air–sea interface is an important process in ocean–atmosphere dynamics. In this study, a 40-year (1981–2020) high-resolution (0.25° × 0.25°) ERA-5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to estimate the variability and trends of heat and water flux components in the Red Sea. The results show that the surface net heat flux is negative (loss) in the Northern Red Sea (NRS) and positive (gain) in the Southern Red Sea (SRS). The highest seasonal surface net heat flux is observed in the spring and early summer, while the lowest is reported in the winter. A significant linear trend is found in the surface net heat flux over the NRS and SRS, with values of about −0.12 ± 0.052 (W/m²)/yr and +0.20 ± 0.021 (W/m²)/yr, respectively. The annual mean surface net water flux loss to the atmosphere over the entire Red Sea is +1.46 ± 0.23 m/yr. The seasonal surface net water flux peak occurs in winter as a result of the northeast monsoon wind, which increases evaporation rate over the whole length of the Red Sea. The highest surface net water flux (+2.1 m/yr) is detected during 2020, while the lowest value (+1.3 m/yr) is observed during 1985.

Marine heat waves (MHWs) can have catastrophic consequences for the socio-environmental system. Especially in the Red Sea, which has the world’s second longest coral reef system. Here, we investigate the sea surface temperature (SST) variability and trends, as well as the spatiotemporal characteristics of marine heat waves (MHWs) in the Red Sea, using high resolution daily gridded (1/20°) SST data obtained from the Copernicus Marine Environment Monitoring Service (CMEMS) for the period 1982–2019. Results show that the average warming rate was about 0.342 ± 0.047 °C/decade over the entire Red Sea over the whole study period. The Empirical Orthogonal Function (EOF) analysis reveals that the maximum variability is over the central part of the Red Sea, while the minimum variability is in the southernmost part of the Red Sea. Over the last two decades (2000–2019), we have discovered that the average MHW frequency and duration increased by 35% and 67%, respectively. The results illustrate that the MHW frequency and duration trends have increased by 1.17 counts/decade and 1.79 days/decade, respectively, over the study period. The highest annual MHW frequencies were detected in the years 2018, 2019, 2010, and 2017. A strong correlation (R = 0.89) was found between the annual MHW frequency and the annual mean SST.

Marine heatwaves (MHWs) can cause devastating impacts on marine life. The frequency of MHWs, gauged with respect to historical temperatures, is expected to rise significantly as the climate continues to warm. The MHWs intensity and count are pronounced with many parts of the oceans and semi enclosed seas, such as Eastern Mediterranean Sea (EMED). This paper investigates the descriptive spatial variability and trends of MHW events and their main characteristics of the EMED from 1982 to 2020 using Sea Surface Temperature (SST) data obtained from the National Oceanic and Atmospheric Administration Optimum Interpolation ([NOAA] OI SST V2.1). Over the last two decades, we find that the mean MHW frequency and duration increased by 40% and 15%, respectively. In the last decade, the shortest significant MHW mean duration is 10 days, found in the southern Aegean Sea, while it exceeds 27 days off the Israeli coast. The results demonstrate that the MHW frequency trend increased by 1.2 events per decade between 1982 and 2020, while the MHW cumulative intensity (i_cum) trend increased by 5.4 °C days per decade. During the study period, we discovered that the maximum significant MHW SST event was 6.35 °C above the 90th SST climatology threshold, lasted 7 days, and occurred in the year 2020. It was linked to a decrease in wind stress, an increase in air temperature, and an increase in mean sea level pressure.