cloud-resolving modeling; climate change; climate modeling; graphics processing units; high-performance computing; extreme events; convection-resolving modeling; heavy precipitation; droughts
Bader Robin, Sprenger Michael, Ban Nikolina, Radisuhli Stefan, Schar Christoph, Ganther Tobias (2019), Extraction and Visual Analysis of Potential Vorticity Banners around the Alps, in IEEE Transactions on Visualization and Computer Graphics
, 26, 259-269.
Belušić Andreina, Prtenjak Maja Telišman, Güttler Ivan, Ban Nikolina, Leutwyler David, Schär Christoph (2018), Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models, in Climate Dynamics
, 50(11-12), 4455-4480.
Fuhrer Oliver, Chadha Tarun, Hoefler Torsten, Kwasniewski Grzegorz, Lapillonne Xavier, Leutwyler David, Lüthi Daniel, Osuna Carlos, Schär Christoph, Schulthess Thomas C., Vogt Hannes (2018), Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0, in Geoscientific Model Development
, 11(4), 1665-1681.
Berthou Ségolène, Kendon Elizabeth J., Chan Steven C., Ban Nikolina, Leutwyler David, Schär Christoph, Fosser Giorgia (2018), Pan-European climate at convection-permitting scale: a model intercomparison study, in Climate Dynamics
Schneider Tapio, Teixeira João, Bretherton Christopher S., Brient Florent, Pressel Kyle G., Schär Christoph, Siebesma A. Pier (2017), Climate goals and computing the future of clouds, in Nature Climate Change
, 7, 3-5.
Arteaga Andrea, Fuhrer Oliver, Hoefler Torsten, Schulthess Thomas (2017), Model-Driven Choice of Numerical Methods for the Solution of the Linear Advection Equation, in Procedia Computer Science
, 108, 1542-1551.
Giorgi Filippo, Torma Csaba, Coppola Erika, Ban Nikolina, Schär Christoph, Somot Samuel (2016), Enhanced summer convective rainfall at Alpine high elevations in response to climate warming, in Nature Geoscience
, 9(8), 584-589.
Leutwyler David, Fuhrer Oliver, Lapillonne Xavier, Lüthi Daniel, Schär Christoph (2016), Towards European-Scale Convection-Resolving Climate Simulations, in Geoscientific Model Development Discussions
Leutwyler David, Fuhrer Oliver, Lapillonne Xavier, Lüthi Daniel, Schär Christoph (2015), Continental-Scale Climate Simulation at Kilometer-Resolution
, ETH-Zürich, Zürich.
Leutwyler David, Fuhrer Oliver, Lapillonne Xavier, Lüthi Daniel, Schär Christoph (2015), Winter storm Kyrill in a Continental-Scale Convection-Resolving Climate Simulation
, ETH-Zürich, Zürich.
Leutwyler David, Lüthi Daniel, Ban Nikolina, Fuhrer Oliver, Schär Christoph, Evaluation of the convection-resolving climate modeling approach on continental scales, in Journal of Geophysical Research: Atmospheres
Schär Christoph, Ban Nikolina, Fischer Erich M., Rajczak Jan, et al., Percentile indices for assessing changes in heavy precipitation events, in Climatic Change
The development of weather and climate models has made rapid progress in recent years. With the progress of high-performance computing (HPC), the computational resolution of such models will continue to be refined in the next decades. This development offers exciting prospects. From a climate science perspective, a further increase in resolution will make it possible to base such models on a set of equations that is much closer to first principles. In particular, at horizontal resolutions of a few kilometers, the models become cloud resolving and start to explicitly represent the dynamics of deep convective and thunderstorm clouds without the help of semi-empirical parameterizations. This development corresponds to an important quantum jump in climate modeling. It allows reducing some of the key uncertainties in the current generation of climate models, yields an improved representation of the water cycle including the drivers of extreme events (heavy precipitation events, floods, droughts, etc.), and enables more sophisticated climate-change scenarios with better guidance for impact assessment and climate change adaptation measures.From a computer science perspective, this strategy poses major challenges. First, emerging hardware architectures increasingly involve the use of heterogeneous many-core architectures consisting of both CPUs and accelerators (e.g., GPUs). The efficient exploitation of such architectures requires a paradigm shift and has only just started. Second, with increasing computational resolution, the models’ output becomes unbearably voluminous and long-term storage prohibitively expensive. Ultimately, there is no way around conducting the analysis online rather than storing the model output, and performing model reruns (i.e., repeat simulations for refined analysis). These developments pose new challenging computer science questions, which need to be addressed before an efficient exploitation of new hardware systems becomes feasible.The current proposal is a pilot project in this area. Our overarching objective is to develop a continental-scale cloud-resolving climate modeling capability for the next generation of high-performance computing (HPC) architectures. The target set-up for this development is a horizontal resolution of 2 km, 60 to 90 computational levels in the vertical, and a computational domain covering the whole of Europe. The project will start with a GPU-enabled prototype of the COSMO model, which has been developed in a successful collaboration between MeteoSwiss, CSCS, and ETH. This prototype is the first of its kind and it provides an ideal opportunity to tackle emerging issues in an interdisciplinary collaboration between climate and computer scientists. The project will not generate any new climate change scenarios, but it will develop a modeling framework that may be used for such purposes.The project is organized into four subprojects: Subproject A will assess how to efficiently exploit heterogeneous many-core computing architectures for weather and climate models. This will involve addressing key questions such as the relative costs and benefits of higher-order numerical accuracy versus higher spatial resolution. Subproject B will explore the virtualization of climate simulations from a computer science perspective. It addresses the critical question of computational versus mass-storage loads, and develops an online analysis platform for high-resolution models. The primary scientific objectives of subprojects C and D relate to the water cycle in the European summer season. Subproject C will perform, validate and analyze cloud-resolving climate simulations over Europe, and subproject D will exploit the new level of virtualization using Eulerian and Lagrangian perspectives for the online analysis of synoptic features and water transport. Tight interactions between all partners are essential in this strongly interdisciplinary project, in order to jointly develop an innovative and powerful system for climate simulations, which enables addressing a range of scientific questions related to the atmospheric water cycle and extreme events.