Chemistry Across Multiple Phases (CAMP): A Novel Flexible Treatment for Multiphase Chemistry in Atmospheric Models
Despite decades of study, aerosol impacts still contribute the largest uncertainty in climate projections. One of the reasons is the complexity of aerosols in the atmosphere and the challenges that this introduces when it comes to representing aerosols in chemical transport models. Progress in the identification of increasingly complex aerosol processes have resulted in an advanced understanding of the evolution of atmospheric systems, but have also introduced a level of complexity that few atmospheric models were originally designed to handle. To improve models, new insights from laboratory experiments and field studies need to be incorporated, but this process is severely hampered by archaic legacy codes. What is needed now is a flexible modeling framework for multiphase chemistry that integrates physicochemical processes easily, rapidly, and efficiently on state-of-the-art computing platforms. In a collaborative effort with the Barcelona Supercomputing Center and the National Center of Atmospheric Research, Professor Riemer and her lab are developing the Chemistry Across Multiple Phases (CAMP) model. CAMP is designed to be:
- portable: useable as a stand-alone library able to interact with any model’s internal configuration, including how it represents aerosol systems.
- flexible: fully run-time configurable chemical mechanisms requiring no changes to the source code or re-compilation of the model.
- self-contained: solves the complete chemical system, including gas-and condensed-phase reactions and phase transfer as a single kinetic system.
CAMP will take high-level mechanism descriptions and automatically execute them efficiently within host models ranging from highly-detailed particle-resolved aerosol representations to simplified representations for use in global earth-system models. This will allow modelers to try out new chemistry and assess their impacts at scale. Furthermore, the ultra-detailed simulations will be the ideal benchmark to quantify the errors in global-scale aerosol models, which is increasingly important as global models push the spatial resolution down towards the kilometer scale.