Description: In this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

Description: In the last decades, offshore wind harvesting has increased enormously, and is seen as a renewable energy resource with great potential in many regions of the world. Therefore, it is crucial to understand how this resource will evolve in a warming climate. In the present study, offshore wind resource in the Southwestern African region is analysed for the present and future climates. A ROM (REMO-OASIS-MPIOM) climate simulation in uncoupled and coupled atmosphere–ocean mode, at 25 km horizontal resolution, and a multi-model ensemble built with a set of regional climate models from the CORDEX-Africa experiment at 0.44° resolution were used. The projected changes of the offshore wind energy density throughout the twenty-first century are examined following the RCP4.5 and RCP8.5 greenhouse gas emissions scenarios. Characterised by strong coastal-parallel winds, the Southwestern African offshore region shows high values of wind energy density at 100 m, up to 1500 Wm⁻² near the coast, particularly offshore Namibia and west South Africa. Conversely, along Angola’s coast the available offshore wind energy density is lower. Throughout the twenty-first century, for the weaker climate mitigation scenario (RCP8.5), an increase of the offshore wind resource is projected to occur along Namibia and South African western coasts, more pronounced at the end of the century (+ 24%), while a decrease is projected along Angola’s coasts, reaching a negative anomaly of about − 32%. Smaller changes but with the same pattern are projected for the stronger climate mitigation scenario (RCP4.5). The future deployment of offshore floating hub turbines placed at higher heights may allow higher production of energy in this region. Along offshore Namibia and west South Africa, the wind energy density at 250 m showed differences that range between 30 and 50% relative to wind energy density at 100 m.

Description: The Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere–ocean regionally coupled model. The regional coupled model presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. The coupled system reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. Moreover, it shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields, showing the impact of the higher resolution and coupling for CCUS climate modelling. The model is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of the regionally coupled model to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence.

Description: The North African coastal low-level jet (NACLLJ) lies over the cold Canary current and is synoptically linked to the Azores Anticyclone and to the continental thermal low over the Sahara Desert. Although being one of the most persistent and horizontally extended coastal wind jets, this is the first high resolution modelling effort to investigate the NACLLJ climate. The current study uses a ROM atmospheric hindcast simulation with ~ 25 km resolution, for the period 1980–2014. Additionally, the underlying surface wind features are also scrutinized using the CORDEX-Africa runs. These runs allow the building of a multi-model ensemble for the coastal surface flow. The ROM and the CORDEX-Africa simulations are extensively evaluated showing a good ability to represent the surface winds. The NACLLJ shows a strong seasonal cycle, but, unlike most coastal wind jets, e.g. the California one, it is significantly present all year round, with frequencies of occurrence above 20%. In spring and autumn, the maxima frequencies are around 50%, and reach values above 60% in summer. The location of maximum frequency of occurrence migrates meridionally from season to season, being in winter and spring upwind of Cap-Vert, and in summer and autumn offshore the Western Sahara. Analogously, the lowest jet wind speeds occur in winter, when the median is below 15 m/s. In summer, the jet wind speed median values are ~ 20 m/s and the maxima are above 30 m/s. The jet occurs at heights ~ 360 m. A momentum balance is pursued disclosing that the regional flow is almost geostrophic, dominated by the pressure gradient and Coriolis force. Over the jet areas the ageostrophy is responsible for the jet acceleration.

Description: The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean–atmosphere coupled processes make the region’s climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air–sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air–sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.

Description: A regional coupled atmosphere–ocean model is developed to study the monsoon climate over South Asia. Most of the climate models (both GCM and RCM) underestimate precipitation over South Asia, but overestimate precipitation over the Bay of Bengal and the equatorial Indian Ocean. These systematic differences between the models may be related to a fundamental problem of atmospheric models: the inability to simulate intraseasonal variability. The intraseasonal oscillations of the South Asian monsoon play a major role in influencing the seasonal mean monsoon characteristics and their interannual variability (Goswami and Mohan, 2001). Several GCM studies with focus on the South Asian monsoonal region have concluded that GCMs have difficulties in simulatingthe mean monsoon climate (Turner and Annamalai, 2012). RCMs do simulate better orographic induced precipitation, but also show limited ability to simulate the land precipitation (Lucas-Picher et al., 2011; Kumar et al., 2013). For this study, differences in coupled and uncoupled simulations are analyzed to investigate the effect of coupling on the simulated climate, especially precipitation spatial patterns.

Description: Currently, Global Coupled Models (GCMs) have difficulty capturing key phenomena and achieving accurate climate projections on regional and local scales because limitations in computer po wer do not allow them to reach the necessary horizontal resolutions. Regional climate models (RCMs) provide dynamically downscaled climate information within the region of interest, improving this drawback of current GCMs. At this point, naturally raises the question of how much, if any, the RCM can improve the GCMs results. It has been argued that regional models can reproduce an observed climatology but are not able to predict the change of the climatology in response to a changing climate (e.g. Kerr, 2013). However, Feser et al. (2011) could demonstrate an added value in those parameters that exhibit high spatial variability such as near surf ace temperature in different regional atmospheric models. They show that the added value originates mainly from the higher resolved orography in the regional models.