Weather/climate models continue to suffer from systematic biases, many of which are related to missing or poorly represented physical processes and deficiencies in the underlying model physics. Process-based testing and evaluation (T&E) of physics are essential to identify and understand the causes of model errors/biases, and to improve the overall performance of a weather/climate model while ensuring that model adjustments/tuning can be justified on physical grounds. To advance the model physics and improve weather forecasting or climate predictive accuracy, reliability and lead times, this session aims to bring together scientists who work on a variety of numerical models (weather/climate, regional/global, coupled/uncoupled, deterministic/ensemble, etc.). It will focus on: 1) T&E of model physics, their interactions, and impacts on the overall performance of a model, and 2) applying process-based T&E to advance understanding of physical processes. Abstracts that apply hierarchical testing approaches and process-based verification and evaluation methods are particularly encouraged.