SummaryFuture sea-level changes along the Mediterranean Egyptian coast (southern Levantine sub-basin) are projected using satellite altimetry data and model simulations. Twenty-one years (1993–2013) of satellite altimetry data, represented by dynamic topography (DT), are examined in light of tide-gauge observations. Current DT changes are examined with respect to five atmospheric/oceanic factors. The qualities of three realizations of the Geophysical Fluid Dynamics Laboratory (GFDL) model are examined by comparing these with DT. Finally, the simulations best describing the present DT are used to describe projected sea-level changes in the study area.The results indicate that DT can be used to study coastal and deep-water sea-level changes in the study area. The southern Levantine sub-basin sea level has recently risen by an average of 3.1cmdecade−1 and exhibits significant annual sea-level variation of −17cm to 8cm. The sea-level variation is significantly affected by several factors: sea-level variation west of the Gibraltar Strait, steric sea level, and sea-surface temperature. The GFDL simulations best describing the recent sea level over the study area, i.e., GFDL-CM3 and GFDL-ESM2M, are used to calculate the two-model ensemble mean (GFDL-2ENM), which indicates that Egypt's Mediterranean coast will experience substantial sea-level rise (SLR) this century. The estimated uncertainty over the study area was 4–22cm by 2100, with the emission assumptions dominating the three sources of uncertainty sources. Comparing the projected SLRs with digital elevation data indicates that Egypt's Mediterranean coast will only be safe from flooding by 2100 if effective adaptation methods are applied

This research aims to use eco-friendly Corallina officinalis as an adsorbent for removing harmful malachite green dye streams from industrial effluent, promoting sustainable living and effective microbial growth inhibition. Corallina officinalis biomass was tested for textile dye biosorption, as well as its antibacterial, antioxidant, and cytotoxic properties. The effects of certain parameters, involving pH solution, initial dye concentration, algae dose, and contact time, were investigated on the sorption of dye. Fourier transform infrared spectroscopy and scanning electron microscopy were also used and, the results showed that the functional groups on the surface of algae played an important part in the biosorption process. It was noted that the kinetic data were significantly prominent by the Pseudo-second-order model with regression correlation coefficient $${r}_{2}^{2}$$r 2 2 values with an average of 0.95232. The biosorption was compatible with both the Freundlich (R² = 0.9843), and Langmuir (R² = 0.9653) isotherms, and the maximum removal efficiency for dye reached up to 99.9% in 2 h, 27 °C, stirring speed 120 rpm, pH 6, initial dye concentration 20 mg L⁻¹, and biomass dose 0.03 g L⁻¹. Corallina officinalis had higher antimicrobial activity, with values of minimum inhibitory concentrations ranging from 0.156 to 5 mg mL⁻¹. Corallina officinalis exerted significant radical scavenging activity against tested free radicals. The extract was examined for cytotoxic activity using nine cancer cell lines, which exhibited high cytotoxicity for colon adenocarcinoma with an IC₅₀ value of 25.895 µg mL⁻¹.

Recent and future climate diagrams (surface air temperature, surface relative humidity, surface wind, and mean sea level pressure) for the Saudi Arabian Red Sea Coast are analysed based on hourly observations (2016–2020) and hourly ERA5 data (1979–2020) with daily GFDL mini-ensemble means (2006–2100). Moreover, GFDL mini-ensemble means are calculated based on the results of three GFDL simulations (GFDL-CM3, GFDL-ESM2M, and GFDL-ESM2G). Observation data are employed to describe the short-term current weather variability. However, ERA5 data are considered to study the long-term current weather variability after bias removal via a comparison to observations. Finally, a bias correction statistical model was developed by matching the cumulative distribution functions (CDFs) of corrected ERA5 and mini-ensemble mean data over 15 years (2006–2020). The obtained local statistic were used to statically downscale GFDL mini-ensemble means to study the future uncertainty in the atmospheric parameters studied. There occurred significant spatial variability across the study area, especially regarding the surface air temperature and relative humidity, based on monthly analysis of both observation and ERA5 data. Moreover, the results indicated that the ERA5 data suitably describe Tabuk, Jeddah and Jizan weather conditions with a marked spatial variability. The best performance of ERA5 surface air temperature and relative humidity (surface wind speed and sea level pressure) data was detected in Tabuk (Jeddah). These data for the Saudi Arabian Red Sea coast, 1979–2020, exhibit significant positive trends of the surface air temperature and surface wind speed and significant negative trends of the relative humidity and sea level pressure. The GFDL mini-ensemble mean projection result, up to 2100, contains a significant bias in the studied weather parameters. This is partly attributed to the coarse GFDL resolution (2° × 2°). After bias removal, the statistically downscaled simulations based on the GFDL mini-ensemble mean indicate that the climate in the study area will experience significant changes with a large range of uncertainty according to the considered scenario and regional variations.

The characteristics of near surface air temperature and wind field over the Southeastern Levantine (SEL) sub-basin during the period 1979–2018 were simulated. The simulation was carried out using a dynamical downscaling approach, which requires running a regional climate model system (RegCM-SVN6994) on the study domain, using lower-resolution climate data (i.e., the fifth generation of ECMWF atmospheric reanalysis of the global climate ERA5 datasets) as boundary conditions. The quality of the RegCM-SVN simulation was first verified by comparing its simulations with ERA5 for the studied region from 1979 to 2018, and then with the available five WMO weather stations from 2007 to 2018. The dynamical downscaling results proved that RegCM-SVN in its current configuration successfully simulated the observed surface air temperature and wind field. Moreover, RegCM-SVN was proved to provide similar or even better accuracy (during extreme events) than ERA5 in simulating both surface air temperature and wind speed. The simulated annual mean T2m by RegCM-SVN (from 1979 to 2018) was 20.9 °C, with a positive warming trend of 0.44 °C/decade over the study area. Moreover, the annual mean wind speed by RegCM-SVN was 4.17 m/s, demonstrating an annual negative trend of wind speed over 92% of the study area. Surface air temperatures over SEL mostly occurred within the range of 4–31 °C; however, surface wind speed rarely exceeded 10 m/s. During the study period, the seasonal features of T2m showed a general warming trend along the four seasons and showed a wind speed decreasing trend during spring and summer. The results of the RegCM-SVN simulation constitute useful information that could be utilized to fully describe the study area in terms of other atmospheric parameters.