Quantifying Errors in Modeled Aerosol Effects on Climate from Numerical Approximations of Particle Distributions
DescriptionFor the past two decades, atmospheric aerosol has been the largest source of inter-model variability in radiative forcing among climate simulations. Climate-relevant aerosol properties depend critically on the distribution in size, shape, and chemical composition of particle populations that evolve in time as they are transported through Earth’s atmosphere. However, tracking such particle-level details is computationally impractical for large-scale, long-running climate simulations. Instead, aerosol modules in Earth System Models necessarily simplify the representation of particle characteristics, leading to errors in climate-relevant aerosol properties that have not been well quantified. Here we present a framework for using particle-resolved simulations of aerosol-cloud-chemistry interactions to quantify structural errors from the numerical representation of particle populations. Particle-resolved models track per-particle composition among evolving aerosol populations and are, therefore, not subject to many of the numerical errors that plague reduced aerosol schemes. In addition to quantifying error in reduced aerosol schemes, we will introduce an approach for using these detailed particle-resolved simulations to train surrogate models that account for the impact of unresolved particle characteristics on predictions of climate-relevant properties and uncertainty in those predictions.
TimeMonday, June 2617:30 - 18:00 CEST
Climate, Weather and Earth Sciences