ICON: Toward Vertically Integrated Model Configurations for Numerical Weather Prediction, Climate Predictions, and Projections
Wolfgang A. Müller, Barbara Früh, Peter Korn, Roland Potthast, Johanna Baehr, Jean-Marie Bettems, Gergely Bölöni, Susanne Brienen, Kristina Fröhlich, Jürgen Helmert, Johann Jungclaus, Martin Köhler, Stephan Lorenz, Andrea Schneidereit, Reiner Schnur, Jan-Peter Schulz, Linda Schlemmer, Christine Sgoff, Trang Van Pham, Holger Pohlmann, Bernhard Vogel, H. Vogel, Roland Wirth, Sönke Zaehle, Günther Zängl, Björn Stevens, Jochem Marotzke
Abstract
Abstract A wide range of important societal and economic applications on national and international levels strive for an integrated understanding and forecasting of weather and climate, at high spatial resolution ranging from days to decades. The global to regional model system Icosahedral Nonhydrostatic (ICON) has been applied to weather as well as to climate time scales with joint developments of the model infrastructure. However, ICON’s model configurations share the same dynamical core but differ substantially in their physical parameterization and the coupling of Earth system components, depending on whether they were designed for numerical weather prediction (NWP) or climate applications. Starting in 2020, a new modeling initiative has been launched as a joint project between climate modeling institutes and the Deutscher Wetterdienst. The initiative “vertically” integrates NWP, climate predictions, climate projections, and atmospheric composition modeling based on the ICON framework and targets a unified treatment of the respective subgrid-scale parameterizations. This initiative aims at the development of coupled model configurations of ICON to conduct operational weather and ocean forecasts for several days, climate predictions with time scales up to 10 years ahead as well as climate projections, and it provides a model baseline for joint research for NWP and climate. This paper illustrates the strategic direction of this modeling initiative, isolates key challenges, and reports on first results. Significance Statement For many years, numerical weather prediction and climate modeling were largely separated and only weakly interacting as they operated on vastly different spatiotemporal scales. This picture is changing because the trend of high-performance computing toward massively parallel computing architectures now allows high-resolution simulations for increasingly longer integration times. The global model Icosahedral Nonhydrostatic (ICON) has a common architecture for operational weather prediction and climate applications, but so far, they are configured only for the respective time scales. Here, we describe the way forward to formulate modeling configurations within the single modeling framework of ICON, for integrating a continuum of scales from weather to climate. This opens a new joint development space of basic research areas combining weather forecasts and climate research.