Common Community Physics Package: Fostering Collaborative Development in Physical Parameterizations and Suites
Lígia Bernardet, Lisa Bengtsson, P. Alex Reinecke, Fanglin Yang, Man Zhang, Kyle Hall, James D. Doyle, Matus N. Martini, Grant Firl, Lulin Xue
Abstract
Abstract The Common Community Physics Package (CCPP) is a state-of-the-art infrastructure designed to facilitate community-wide development of atmospheric physics parameterizations, support their interoperability among different modeling centers, and enable the transition of research to operations in NWP and climate modeling. The CCPP consists of two elements: the Physics (a repository of parameterizations) and the Framework (an infrastructure for interfacing the parameterizations with host models). The CCPP is a community resource: Its latest release has 23 primary parameterizations, which can be organized into six supported suites. It is distributed with a single-column model to facilitate physics development and experimentation. The Developmental Testbed Center provides support to users and developers. A key aspect of the CCPP is its interoperability, that is, its ability to be used by multiple host models. This enables synergistic collaboration among groups dispersed over various institutions and working on various models. In this article, we provide an overview of the CCPP and how it is being used in two leading modeling systems. The CCPP is part of the Unified Forecast System (UFS), is included in the NOAA operational Hurricane Analysis and Forecast System (HAFS) version 1, and is slated for use in all upcoming NOAA global and limited-area UFS applications for operations. Similarly, the CCPP has been integrated into the Navy Environmental Prediction System Using a Nonhydrostatic Engine (NEPTUNE) model and is undergoing testing for the upcoming transition to operations. These experiences make physics interoperability a reality and open the doors for much broader collaborative efforts on ESM development. Significance Statement Physical parameterizations are a key component of numerical weather and climate prediction models, as they are responsible for the representation of processes such as clouds and precipitation. We created a package that allows numerical models with different complexities to use the same set of physical parameterizations to enable opportunities for careful comparisons between models and more efficient collaborations among modeling groups. We streamlined the software management software to make it straightforward for a distributed community to collaborate. Our work is mature, and the package is now being used operationally by the National Weather Service, experimentally by the U.S. Navy, and routinely in the research community. This opens the door for wider community collaboration and potential gains in predictive skill.