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Continuum sea ice models have been applied close to the presumed limits of their validity for many years, yet they remain compatible with current observations. The resolution requirements for sea ice models varies considerably depending on the application (e.g., large ensembles, paleoclimate simulations, short-range forecasting), and therefore continuum models will likely remain useful for many years to come. Meanwhile, it is highly desirable to explore the potential of DEMs. These models are expected to be more physically faithful at the highest resolutions envisioned for sea ice in ESMs, provided they incorporate all the required processes. DEMs may also prove more efficient for some new computer architectures. Such perspectives highlight the need for the sea ice modeling community to have a clear and consistent vision of the future evolution of HPC systems. Sea ice models are used for many different purposes and therefore benefit from modularity, which allows the activation or exclusion of parameterizations and code features. Thus, users can adjust model complexity to fit their specific application. Considering limited human resources among core sea ice modeling groups, engagement of the wider community has proven a very efficient way to advance large-scale sea ice models. However, there is still scope for further integration of the wider community in model development activities. An important feature of the Laugarvatn sea ice modeling workshop was the open minded atmosphere in which very different views were exchanged. The workshop successfully brought together model developers and users of sea ice models for Earth system modeling, operational forecasting and (re)analyses. International sea ice modeling workshops such as this foster collaboration and community engagement in the field of sea ice modeling. A recommendation from this workshop is that the exercise should be repeated every 2-3 years to maintain community engagement, exchange cutting-edge ideas, and reinforce collaborative momentum. © 2020 American Meteorological Society.

We study how mesoscale air-sea interactions over the North Atlantic can influence weather extremes, e.g. heavy precipitation and wind storms, and the overall atmospheric circulation both locally and downstream in the midlatitudes. We use a global coupled climate model with a high-resolution North Atlantic grid (dx ~ 8 km) and an atmosphere model resolution of either 125 km or 25 km. The high-resolution North Atlantic grid allows the model to resolve the current systems and SST fronts associated with e.g. the Gulf Stream and North Atlantic Current. As air-sea fluxes of momentum, heat and freshwater are calculated on the atmosphere grid, spatial variations in fluxes associated with sharp SST fronts are much better represented when using the high-resolution atmosphere then when using the low-resolution model. Preliminary results show that coupling to the high-resolution (dx ~ 25 km) rather than low-resolution (dx ~ 125 km) atmosphere model increases the intensity and variance of surface heat and freshwater fluxes over eddy-rich regions such as the Gulf Stream. As a result, the high-resolution model simulates more intense heavy precipitation events over most of the North Atlantic Ocean. We also show that more frequent coupling between the atmosphere and ocean components increases the intensity of the air-sea fluxes, in particular wind stress, which has a large impact on the ocean. More intense air-sea fluxes can provide more energy for cyclogenesis and we will discuss how the oceanic mesoscale, in particular in the eddy-rich regions, can alter the storm tracks and jet stream to influence extreme weather and the climate over Europe. The coupled model comprises NEMO 3.6/LIM2 ocean and OpenIFS 40r1 atmosphere, and works by allowing the global OpenIFS model to send and receive fields from both a global coarse-resolution ocean grid and a refined grid over the North Atlantic grid via the OASIS3-MCT4 coupler. The ability to run these simulations is a very recent development and we will give a brief overview of the coupled modelling system and benefits of using regional grid refinement in coupled models.

The ability of a high-resolution coupled atmosphere–ocean general circulation model (with a horizontal resolution of a quarter of a degree in the ocean and of about 0.5° in the atmosphere) to predict the annual means of temperature, precipitation, sea-ice volume and extent is assessed based on initialized hindcasts over the 1993–2009 period. Significant skill in predicting sea surface temperatures is obtained, especially over the North Atlantic, the tropical Atlantic and the Indian Ocean. The Sea Ice Extent and volume are also reasonably predicted in winter (March) and summer (September). The model skill is mainly due to the external forcing associated with well-mixed greenhouse gases. A decrease in the global warming rate associated with a negative phase of the Pacific Decadal Oscillation is simulated by the model over a suite of 10-year periods when initialized from starting dates between 1999 and 2003. The model ability to predict regional change is investigated by focusing on the mid-90’s Atlantic Ocean subpolar gyre warming. The model simulates the North Atlantic warming associated with a meridional heat transport increase, a strengthening of the North Atlantic current and a deepening of the mixed layer over the Labrador Sea. The atmosphere plays a role in the warming through a modulation of the North Atlantic Oscillation: a negative sea level pressure anomaly, located south of the subpolar gyre is associated with a wind speed decrease over the subpolar gyre. This leads to a reduced oceanic heat-loss and favors a northward displacement of anomalously warm and salty subtropical water that both concur to the subpolar gyre warming. We finally conclude that the subpolar gyre warming is mainly triggered by ocean dynamics with a possible contribution of atmospheric circulation favoring its persistence.

A high-resolution global atmospheric model is used to investigate the influence of the representation of small-scale North Atlantic sea surface temperature (SST) patterns on the atmosphere during boreal winter. Two ensembles of forced simulations are performed and compared. In the first ensemble (HRES), the full spatial resolution of the SST is maintained while small-scale features are smoothed out in the Gulf Stream region for the second ensemble (SMTH). The model shows a reasonable climatology in term of large-scale circulation and air–sea interaction coefficient when compared to reanalyses and satellite observations, respectively. The impact of small-scale SST patterns as depicted by differences between HRES and SMTH shows a strong meso-scale local mean response in terms of surface heat fluxes, convective precipitation, and to a lesser extent cloudiness. The main mechanism behind these statistical differences is that of a simple hydrostatic pressure adjustment related to increased SST and marine atmospheric boundary layer temperature gradient along the North Atlantic SST front. The model response to small-scale SST patterns also includes remote large-scale effects: upper tropospheric winds show a decrease downstream of the eddy-driven jet maxima over the central North Atlantic, while the subtropical jet exhibits a significant northward shift in particular over the eastern Mediterranean region. Significant changes are simulated in regard to the North Atlantic storm track, such as a southward shift of the storm density off the coast of North America towards the maximum SST gradient. A storm density decrease is also depicted over Greenland and the Nordic seas while a significant increase is seen over the northern part of the Mediterranean basin. Changes in Rossby wave breaking frequencies and weather regimes spatial patterns are shown to be associated to the jets and storm track changes.

A climate model represents a multitude of processes on a variety of time and space scales; a canonical example of multi-physics multi-scale modeling. The underlying climate system is physically characterized by sensitive dependence on initial conditions, and natural stochastic variability, so very long integrations are needed to extract signals of climate change. Algorithms generally possess weak scaling and can be I/O and/or memory bound. Such weak-scaling, I/O and memory-bound multi-physics codes present particular challenges to computational performance. Traditional metrics of computational efficiency such as performance counters and scaling curves do not tell us enough about real sustained performance from climate models on different machines. They also do not provide a satisfactory basis for comparative information across models. We introduce a set of metrics that can be used for the study of computational performance of climate (and Earth System) models. These measures do not require specialized software or specific hardware counters, and should be accessible to anyone. They are independent of platform, and underlying parallel programming models. We show how these metrics can be used to measure actually attained performance of Earth system models on different machines, and identify the most fruitful areas of research and development for performance engineering. We present results for these measures for a diverse suite of models from several modeling centres, and propose to use these measures as a basis for a CPMIP, a computational performance MIP.

The impact of increased greenhouse gases (GHG) and aerosols concentrations upon the West African monsoon (WAM) is investigated for the late twenty-first century period using the Meteo-France ARPEGE-IFS high-resolution atmospheric model. Perturbed (2070–2100) and current (1961–2000) climates are compared using the model in time-slice mode. The model is forced by global sea surface temperatures provided by two transient scenarios performed with low-resolution coupled models and by two GHG evolution scenarios, SRES-A2 and SRES-B2. Comparing to reanalysis and observed data sets, the model is able to reproduce a realistic seasonal cycle of WAM despite a clear underestimation of the African Easterly Jet (AEJ) during the boreal summer. Mean temperature change indicates a global warming over the continent (stronger over North and South Africa). Simulated precipitation change at the end of the twenty-first century shows an increase in precipitation over Sudan-Sahel linked to a strong positive feedback with surface evaporation. Along Guinea Gulf coast, rainfall regimes are driven by large-scale moisture advection. Moreover, results show a mean precipitation decrease (increase) in the most (less) enhanced GHG atmosphere over this region. Modification of the seasonal hydrological cycle consists in a rain increase during the monsoon onset. There is a significant increase in rainfall variance over the Sahel, which extends over the Guinea coast region in the moderate emission scenario. Enhanced precipitation over Sahel is linked to large-scale circulation changes, namely a weakening of the AEJ and an intensification of the Tropical Easterly Jet.

Evidence is presented, based on an ensemble of climate change scenarios performed with a global general circulation model of the atmosphere with high horizontal resolution over Europe, to suggest that the end-of-century anthropogenic climate change over the North Atlantic–European region strongly projects onto the positive phase of the North Atlantic Oscillation during wintertime. It is reflected in a doubling of the residence frequency of the climate system in the associated circulation regime, in agreement with the nonlinear climate perspective. The strong increase in the amplitude of the response, compared to coarse-resolution coupled model studies, suggests that improved model representation of regional climate is needed to achieve more reliable projections of anthropogenic climate change on European climate.

The EC-EARTH model is a global, coupled climate model that consists of the separate components IFS for the atmosphere and NEMO for the ocean that are coupled using the OASIS coupler. EC-EARTH was ported and run on the Curie system. Different configurations, using resolutions from T159 (approx. 128km) to T799 (approx 25km), were available for benchmarking. Scalasca was used to analyze the performance of the model in detail. Although it was expected that either the I/O or the coupling would be a bottleneck for scaling of the highest resolution model, that is clearly not, yet, the case. The IFS model uses two MPI_Alltoallv calls per timestep that dominate the loss of scaling at 1024 cores. Using the OpenMP functionality in IFS could potentially increase scalability considerably, but this does not yet work on Curie. Work is ongoing to make MPI_Alltoallv more efficient on Curie. It is expected that I/O and/or coupling does become a bottleneck when IFS can be scaled further than 2000 cores. Therefore, the OASIS team increased the scalability of OASIS dramatically with the implementation of a radically different approach, showing less than 1% overhead at 2000 cores. The scalability of NEMO was improved during an earlier PRACE project. The I/O subsystem in IFS is described and is probably not easily accelerated unless it is being rewritten and uses a different file format.