Process-oriented analyses aid model improvement of physical-process representation and ultimately reduce uncertainty in future climate projections and improve weather forecasts. Knowledge from domain experts are captured within these diagnostics, and modeling groups often require cohesive analysis packages to accelerate progress. Studies are encouraged that engage in process-oriented analysis of observations and model ensembles from co-ordinated intercomparison projects such as CMIP6, as well as process modeling efforts that help inform these analyses. Studies targeting processes that span atmospheric, oceanic, land-surface, cryospheric, and biospheric phenomena across a range of time and space scales are welcome. Contributions detailing diagnostics designed for inclusion in model development cycles, examples of model improvement efforts in dialogue with such diagnostics, or those that identify gaps in our current suite of diagnostics are particularly welcome. Additionally, the session will overview code frameworks to organize process-oriented diagnostics—contributions that complement these are also welcome.