William Cabos

Med-CORDEX initiative for Mediterranean climate studies

The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hot spots” of the 21st 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 Med-CORDEX initiative aims at coordinating the Mediterranean climate modeling community towards 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.

Regionally coupled atmosphere‐ocean‐sea ice‐marine biogeochemistry model ROM: 1. Description and validation

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.

The South Atlantic Anticyclone as a key player for the representation of the tropical Atlantic climate in coupled climate models

The key role of the South Atlantic Anticyclone (SAA) on the seasonal cycle of the tropical Atlantic is investigated with a regionally coupled atmosphere–ocean model for two different coupled domains. Both domains include the equatorial Atlantic and a large portion of the northern tropical Atlantic, but one extends southward, and the other northwestward. The SAA is simulated as internal model variability in the former, and is prescribed as external forcing in the latter. In the first case, the model shows significant warm biases in sea surface temperature (SST) in the Angola-Benguela front zone. If the SAA is externally prescribed, these biases are substantially reduced. The biases are both of oceanic and atmospheric origin, and are influenced by ocean–atmosphere interactions in coupled runs. The strong SST austral summer biases are associated with a weaker SAA, which weakens the winds over the southeastern tropical Atlantic, deepens the thermocline and prevents the local coastal upwelling of colder water. The biases in the basins interior in this season could be related to the advection and eddy transport of the coastal warm anomalies. In winter, the deeper thermocline and atmospheric fluxes are probably the main biases sources. Biases in incoming solar radiation and thus cloudiness seem to be a secondary effect only observed in austral winter. We conclude that the external prescription of the SAA south of 20°S improves the simulation of the seasonal cycle over the tropical Atlantic, revealing the fundamental role of this anticyclone in shaping the climate over this region.

Ocean Modeling on a Mesh With Resolution Following the Local Rossby Radius

We discuss the performance of the Finite Element Ocean Model (FESOM) on locally eddy-resolving global unstructured meshes. In particular, the utility of the mesh design approach whereby mesh horizontal resolution is varied as half the Rossby radius in most of the model domain is explored. Model simulations on such a mesh (FESOM-XR) are compared with FESOM simulations on a smaller-size mesh, where refinement depends only on the pattern of observed variability (FESOM-HR). We also compare FESOM results to a simulation of the ocean model of the Max Planck Institute for Meteorology (MPIOM) on a tripolar regular grid with refinement toward the poles, which uses a number of degrees of freedom similar to FESOM-XR. The mesh design strategy, which relies on the Rossby radius and/or the observed variability pattern, tends to coarsen the resolution in tropical and partly subtropical latitudes compared to the regular MPIOM grid. Excessive variations of mesh resolution are found to affect the performance in other nearby areas, presumably through dissipation that increases if resolution is coarsened. The largest improvement shown by FESOM-XR is a reduction of the surface temperature bias in the so-called North-West corner of the North Atlantic Ocean where horizontal resolution was increased dramatically. However, other biases in FESOM-XR remain largely unchanged compared to FESOM-HR. We conclude that resolving the Rossby radius alone (with two points per Rossby radius) is insufficient, and that careful use of a priori information on eddy dynamics is required to exploit the full potential of ocean models on unstructured meshes.

The effect of additional citations in the stability of Journal Citation Report categories

We use a new approach to study the ranking of journals in JCR categories. The objectives of this study were to empirically evaluate the effect of increases in citations on the computation of the journal impact factor (JIF) for a large set of journals as measured by changes in JIF, and to ascertain the influence of additional citations on the rank order of journals according their new JIFs within JCR groups. To do so, modified JIFs were computed by adding additional citations to the number used by Thomson-Reuters to compute the JIF of journals listed in the JCR for 2008. We considered the effect on rank order of a given journal of adding 1, 2, 3 or more citations to the number used to compute the JIF, keeping everything else equal (i.e., without changing the JIF of other journals in a given group). The effect of additional citations on the internal structure of rankings in JCR groups increased with the number of citations added. In about one third of JCR groups, about half the journals changed their rank order when 1–5 citations were added. However, in general the rank order tended to be relatively stable after small increases in citations.

Consistency of climate change projections from multiple global and regional model intercomparison projects

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021–2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM–RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

Exploring the Hjif-Index, an Analogue to the H-Like Index for Journal Impact Factors

We used the Journal Impact Factor (JIF) to develop the hjif-index, calculated in a similar way to h-like indices. To this end, we mapped the JIFs of one JCR group to natural numbers, and evaluated the degree of correspondence between the interval from zero to the highest JIF in the group and a set of natural numbers. Next, we plotted the straight line y = x to obtain the group’s hjif-index as the JIF corresponding to the journal immediately above the straight line. We call the set of journals above the straight line the hjif-core. We calculated hjif-indices corresponding to the 2-year JIF (hjif2-index) and 5-year JIF (hjif5-index) windows for all 176 JCR groups listed in the 2014 Science edition. We also studied derived indicators such as the distribution of journals in JCR groups according to their hjif-indices, the distribution of journals and JIFs in the hjif-core, and other variables and indicators. We found that the hjif2- and hjif5-index behaved in a similar way, and that in general their distribution showed a peak followed by a relatively long tail. The hjif-index can be used as a tool to rank journals in a manner that better reflects the variable number of journals within a given JCR group and in each group’s hjif-core as an alternative to the more arbitrary JCR-based percentile ranking.

The Relative Influence of Atmospheric and Oceanic Model Resolution on the Circulation of the North Atlantic Ocean in a Coupled Climate Model

It is often unclear how to optimally choose horizontal resolution for the oceanic and atmospheric components of coupled climate models, which has implications for their ability to make best use of available computational resources. Here we investigate the effect of using different combinations of horizontal resolutions in atmosphere and ocean on the simulated climate in a global coupled climate model (Alfred Wegener Institute Climate Model [AWI‐CM]). Particular attention is given to the Atlantic Meridional Overturning Circulation (AMOC). Four experiments with different combinations of relatively high and low resolutions in the ocean and atmosphere are conducted. We show that increases in atmospheric and oceanic resolution have clear impacts on the simulated AMOC, which are largely independent. Increased atmospheric resolution leads to a weaker AMOC. It also improves the simulated Gulf Stream separation; however, this is only the case if the ocean is locally eddy resolving and reacts to the improved atmosphere. We argue that our results can be explained by reduced mean winds caused by higher cyclone activity. Increased resolution of the ocean affects the AMOC in several ways, thereby locally increasing or reducing the AMOC. The finer topography (and reduced dissipation) in the vicinity of the Caribbean basin tends to locally increase the AMOC. However, there is a reduction in the AMOC around 45°N, which relates to the reduced mixed layer depth in the Labrador Sea in simulations with refined ocean and changes in the North Atlantic current pathway. Furthermore, the eddy‐induced changes in the Southern Ocean increase the strength of the deep cell.

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

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.