Climate processes

Abstract:

Abstract Next-generation high-resolution (km-scale) climate models promise unprecedented accuracy in climate projections, but realizing their potential requires robust methods to quantify how well simulations align with real-world observations. Average-based metrics conventionally used for climate model evaluation ignore the physics encoded in the fine-scale structures of km-scale simulations. To overcome this limitation, we propose a novel, statistically principled evaluation methodology based on the likelihood function of a generative image model. Our method provides a continuous similarity metric derived from the likelihood distribution of observation and simulation snapshots, which can redefine the evaluation, intercomparison, and parameter tuning of high-resolution climate models. We demonstrate the applicability and interpretability of this method by evaluating convective clouds simulated by two state-of-the-art global km-scale models, using their outgoing infrared radiation fields. This work establishes a scalable pathway toward observation-based evaluation of next-generation climate simulations.

Abstract:

<jats:p>Abstract. We present a new limited-area version of the aerosol–climate modeling system ICON coupled to HAM-lite. This new version is capable of simulating anthropogenic and natural aerosols and their climate effects in specific target regions. We demonstrate its flexibility and applicability through three case studies covering distinct aerosol regimes and processes: air pollution episodes in Central Europe, the emission and transport of sea salt aerosol in the Atlantic Arctic, and the simultaneous formation of smoke and desert dust plumes during the 2019–2020 Australian bushfire season. These case studies show the ability of the model to capture the regional-scale patterns and diurnal variability of the predominant aerosol types. They also indicate, however, systematic biases related to the simplified representation of aerosol emission, microphysics, and chemistry. The insights that we gained from these regional simulations will guide future developments of HAM-lite.</jats:p>