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This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling's influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ∼25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes' relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections. [ABSTRACT FROM AUTHOR]

There is an urgent need to enhance climate projections for Central Equatorial Africa (CEA), given the region's high vulnerability to climatic hazards and its economy's heavy dependence on climate‐sensitive sectors. This study aims to evaluate the performance of the regional earth system model ROM, composed of the atmosphere‐only regional climate model (RCM) REMO coupled with the global Max Planck Institute for Meteorology Ocean Model (MPIOM), in reproducing the precipitation climatology over CEA. ROM results are compared to those of REMO in two sets of experiments, one driven by the ERA‐Interim reanalysis and the other by the MPI‐ESM‐LR earth system model (ESM), both at ∼25‐km horizontal resolution. Results show that ocean coupling improves rainfall climatology thanks to a better representation of the physical processes and mechanisms underlying the rainfall system. In particular, an improved sea surface temperature (SST) results in a more realistic simulation of land‐atmosphere‐ocean interactions, and subsequently the atmospheric baroclinicity. Specifically, the coupling reduces the positive SST bias inherited by the driving ESM across the entire Guinea Gulf and Benguela‐Angola coastal seas. This leads to better simulated land‐ocean thermal and pressure contrasts. Improvements in land‐ocean contrasts, in turn, enhance the representation of the regional atmospheric circulation, and thus precipitation. Interestingly, the coupling is more beneficial when ROM is driven by the ESM than the reanalysis. This study emphasizes the advantage of dynamically downscaling ESMs using regional earth system models rather than atmosphere‐only RCMs, with the potential to enhance confidence in future climate projections. Plain Language Summary: Designing timely and relevant societal responses to climate‐related impacts and risks to humans and natural systems requires reliable information about climate variability and projected change, especially at regional scales. For this purpose, considerable efforts were devoted to the improvement of the numerical models used to represent the climate system, including better formulation of the models' physical and dynamical components and the inclusion of feedback between different components of the climate systems, such as those between the ocean and the atmosphere. In this study we aim at investigating whether the use of a regional climate model which includes an explicit representation (coupling) of the ocean is able to better simulate (i.e., adds value) the main mechanisms responsible for precipitation over Central Equatorial Africa. The results show that the coupled model is indeed able to simulate more realistically the complex physical processes and mechanisms underpinning the rainfall system. Our findings advocate for the use of the global ocean‐regional atmosphere coupling approach for regional climate change projection analyses. Key Points: The global ocean‐regional atmosphere coupling improves the rainfall climatology compared to its atmosphere‐only counterpart modelThe added value resulting from the coupling is plausible, as associated with improvements in the processes underpinning the rainfall systemThe added value is modulated by the boundary conditions, with better suitability under the imperfect forcing mode [ABSTRACT FROM AUTHOR]

Global warming has caused an increase in the emergence of Vibrio species in marine and estuarine environments as well as fresh water bodies. Over the past decades, antimicrobial resistance (AMR) has evolved among Vibrio species toward various antibiotics commonly used for the treatment of Vibrio infections. In this study, we assessed virulence and resistance patterns of Vibrio cholerae non-O1/non-O139 strains derived from Germany and other European countries. A total of 63 clinical and 24 environmental Vibrio cholerae non-O1/non-O139 strains, collected between 2011 and 2021, were analyzed. In silico antibiotic resistances were compared with resistance phenotypes according to EUCAST breakpoints. Additionally, genetic relatedness between isolates was assessed by two cgMLST schemes (SeqSphere +, pubMLST). Both cgMLST schemes yielded similar results, indicating high genetic diversity among V. cholerae nonO1/non-O139 isolates. Some isolates were found to be genetically closely related (allelic distance < 20), which suggests an epidemiological link. Thirtyseven virulence genes (VGs) were identified among 87 V. cholerae nonO1/non-O139 isolates, which resulted in 38 virulence profiles (VPs). VPs were similar between clinical and environmental isolates, with the exception of one clinical isolate that displayed a higher abundance of VGs. Also, a cluster of 11 environmental isolates was identified to have the lowest number of VGs. Among all strains, the predominant virulence factors were quorum sensing protein (luxS), repeats-in-toxins (rtxC/rtxD), hemolysin (hlyA) and different type VI secretion systems (T6SS) genes. The genotypic profiles revealed antibiotic resistance genes (ARGs) associated with resistance to beta-lactams, quinolones, macrolides, tetracycline, antifolate, aminoglycosides, fosfomycin, phenicols and sulfonamide. Carbapenemase gene VCC-1 was detected in 10 meropenemresistant V. cholerae non-O1/non-O139 isolates derived from surface water in Germany. The proportion of resistance among V. cholerae non-O1/nonO139 species isolates against first line treatment (3rd generation cephalosporin, tetracycline and fluoroquinolone) was low. Empirical treatment would likely have been effective for all of the clinical V. cholerae non-O1/non-O139 isolates examined. Nevertheless, carbapenem-resistant isolates have been present in fresh water in Germany and might represent a reservoir for ARGs. Monitoring antimicrobial resistance is crucial for public health authorities to minimize the risks for the human population. [ABSTRACT FROM AUTHOR]

Most standalone atmospheric models do not perform well in simulations of coastal boundary layer jets (BLJs), important weather processes that can trigger heavy rain in coastal areas by supplying both moisture and dynamic lifting. We compared 33‐year simulations with a coupled atmosphere–ocean model and its standalone atmospheric component, the REgional atmosphere MOdel (REMO), forced by the prescribed sea surface temperature (SST). We validated our results using the Tropical Rainfall Measuring Mission SST and the ERA5 hourly reanalysis data set. We found that the coupled model gave a more realistic SST standard deviation than the REMO on BLJ days and corrected the overestimated air temperature over land during the day. The coupled atmosphere–ocean model showed a lower land–sea thermal contrast in the boundary layer. This increased the effects of inertial oscillation, which caused the ageostrophic flows to veer southwest, which is the direction of the maximum wind speed on BLJ days. This reproduced a more reasonable land–sea thermal contrast in the boundary layer as a result of strong air–sea mixing in coastal weather processes, which led to a more robust inertial oscillation and a larger SST standard deviation over the central South China Sea. These findings deepen our understanding of the influence of a fully mixed air–sea boundary on coastal weather processes. These results show that operational numerical weather prediction models can be improved by applying atmosphere–ocean coupling to advance their ability to forecast the weather (e.g., BLJ events) in coastal areas. Plain Language Summary: Coastal boundary layer jets (BLJs) are important coastal weather processes and, because they are precursor signals of heavy rain, they can be used to improve operational numerical weather forecasts. Coupled atmosphere–ocean models improve the predictability of BLJs in South China, but we still need a deeper understanding of the mechanism leading to their occurrence. We compared 33‐year simulations with a coupled atmosphere–ocean model and its standalone atmospheric component forced by the prescribed sea surface temperature (SST). Through validation against remote sensing SSTs and ERA5 hourly reanalysis data, we found that the coupled model gave a more realistic SST standard deviation and corrected the overestimated air temperature over land surfaces. These improvements helped the coupled atmosphere–ocean model to reproduce a more reasonable land–sea thermal contrast in the boundary layer as a result of strong air–sea mixing in coastal weather processes, which led to a more robust inertial oscillation and a larger SST standard deviation over the central South China Sea. We conclude that the impact of the influence of a fully mixed air–sea boundary on coastal weather processes is larger than previously recognized. Key Points: The use of atmosphere‐ocean coupling can improve the predictability of coastal boundary layer jets in South ChinaThe coupled model gave a more realistic sea surface temperature standard deviation and corrected the overestimated air temperatureStrong air‐sea mixing led to a more robust inertial oscillation, veering the ageostrophic flows toward the direction of the maximum wind [ABSTRACT FROM AUTHOR]