The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hotspots” of the twenty-first century, and the physical mechanisms underlying this finding are still not clear. Furthermore, complex interactions and feedbacks involving ocean–atmosphere–land–biogeochemical processes play a prominent role in modulating the climate and environment of the Mediterranean region on a range of spatial and temporal scales. Therefore, it is critical to provide robust climate change information for use in vulnerability–impact–adaptation assessment studies considering the Mediterranean as a fully coupled environmental system. The Mediterranean Coordinated Regional Downscaling Experiment (Med-CORDEX) initiative aims at coordinating the Mediterranean climate modeling community toward the development of fully coupled regional climate simulations, improving all relevant components of the system from atmosphere and ocean dynamics to land surface, hydrology, and biogeochemical processes. The primary goals of Med-CORDEX are to improve understanding of past climate variability and trends and to provide more accurate and reliable future projections, assessing in a quantitative and robust way the added value of using high-resolution and coupled regional climate models. The coordination activities and the scientific outcomes of Med-CORDEX can produce an important framework to foster the development of regional Earth system models in several key regions worldwide.

The large uncertainty in the mineral dust direct radiative effect (DRE) hinders projections of future climate change due to anthropogenic activity. Resolving modeled dust mineral speciation allows for spatially and temporally varying refractive indices consistent with dust aerosol composition. Here, for the first time, we quantify the range in dust DRE at the top of the atmosphere (TOA) due to current uncertainties in the surface soil mineralogical content using a dust mineral-resolving climate model. We propagate observed uncertainties in soil mineral abundances from two soil mineralogy atlases along with the optical properties of each mineral into the DRE and compare the resultant range with other sources of uncertainty across six climate models. The shortwave DRE responds region-specifically to the dust burden depending on the mineral speciation and underlying shortwave surface albedo: positively when the regionally averaged annual surface albedo is larger than 0.28 and negatively otherwise. Among all minerals examined, the shortwave TOA DRE and single scattering albedo at the 0.44–0.63 µm band are most sensitive to the fractional contribution of iron oxides to the total dust composition. The global net (shortwave plus longwave) TOA DRE is estimated to be within −0.23 to +0.35 W m⁻². Approximately 97 % of this range relates to uncertainty in the soil abundance of iron oxides. Representing iron oxide with solely hematite optical properties leads to an overestimation of shortwave DRE by +0.10 W m⁻² at the TOA, as goethite is not as absorbing as hematite in the shortwave spectrum range. Our study highlights the importance of iron oxides to the shortwave DRE: they have a disproportionally large impact on climate considering their small atmospheric mineral mass fractional burden (∼2 %). An improved description of iron oxides, such as those planned in the Earth Surface Mineral Dust Source Investigation (EMIT), is thus essential for more accurate estimates of the dust DRE.

This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average −0.09 W m⁻² with a standard deviation due to interannual variability of 0.25 W m⁻², showing no significant drift. The global surface air temperature in the simulation is on average 14.08 ^∘C with an interannual standard deviation of 0.17 ^∘C, exhibiting a small drift of 0.015 ± 0.005 ^∘C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 ^∘C, and its transient climate response is estimated at 2.1 ^∘C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995–2014 has an average bias of −0.86 ± 0.05 ^∘C with a standard deviation across ensemble members of 0.35 ^∘C in the Northern Hemisphere and 1.29 ± 0.02 ^∘C with a corresponding standard deviation of 0.05 ^∘C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091–2100) of 4.9 ^∘C above the preindustrial mean. A 0.5 ^∘C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 ^∘C.

We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m⁻² and at the top of the atmosphere between −0.20 and −0.28 W m⁻². Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO₂ in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NO_x and HNO₃ are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO₂ columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NO_x from March to August, probably due to an underestimation of NO_x emissions in the region. Overall, the comparison of the modeled CO and NO₂ with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O₃) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O₃ and its vertical distribution. However, the model tends to overestimate O₃ throughout the troposphere in several stations. This may be attributed to an overestimation of CO concentration over the Southern Hemisphere leading to an excessive production of O₃ or to the lack of specific chemistry (e.g., halogen chemistry, aerosol chemistry). Overall, O₃ correlations range between 0.6 and 0.8 for daily mean values. The overall performance of the NMMB-MONARCH is comparable to that of other state-of-the-art global chemistry models.