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Convective available potential energy (CAPE) is an important index for storm forecasting. Recent versions (v15.2 and v16) of the Global Forecast System (GFS) predict lower values of CAPE during summertime in the continental United States than analysis and observation. We conducted an evaluation of the GFS in simulating summertime CAPE using an example from the Unified Forecast System Case Study collection to investigate the factors that lead to the low CAPE bias in GFS. Specifically, we investigated the surface energy budget, soil properties, and near-surface and upper-level meteorological fields. Results show that the GFS simulates smaller surface latent heat flux and larger surface sensible heat flux than the observations. This can be attributed to the slightly drier-than-observed soil moisture in the GFS that comes from an offline global land data assimilation system. The lower simulated CAPE in GFS v16 is related to the early drop of surface net radiation with excessive boundary layer cloud after midday when compared with GFS v15.2. A moisture-budget analysis indicates that errors in the large-scale advection of water vapor does not contribute to the dry bias in the GFS at low levels. Common Community Physics Package single-column model (SCM) experiments suggest that with realistic initial vertical profiles, SCM simulations generate a larger CAPE than runs with GFS IC. SCM runs with an active LSM tend to produce smaller CAPE than that with prescribed surface fluxes. Note that the findings are only applicable to this case study. Including more warm-season cases would enhance the generalizability of our findings. Significance Statement: Convective available potential energy (CAPE) is one of the key parameters for severe weather analysis. The low bias of CAPE is identified by forecasters as one of the key issues for the NOAA operational global numerical weather prediction model, Global Forecast System (GFS). Our case study shows that the lower CAPE in GFS is related to the drier atmosphere than observed within the lowest 1 km. Further investigations suggest that it is related to the drier atmosphere that already exists in the initial conditions, which are produced by the Global Data Assimilation System, in which an earlier 6-h GFS forecast is combined with current observations. It is also attributed to the slightly lower simulated soil moisture than observed. The lower CAPE in GFS v16 when compared with GFS v15.2 in the case analyzed here is related to excessive boundary layer cloud formation beginning at midday that leads to a drop of net radiation reaching the surface and thus less latent heat feeding back to the low-level atmosphere. [ABSTRACT FROM AUTHOR]

The Common Community Physics Package (CCPP) is a collection of physical atmospheric parameterizations for use in Earth system models and a framework that couples the physics to a host model's dynamical core. A primary goal for this effort is to facilitate research and development of physical parameterizations and experimentation with physics–dynamics coupling methods while simultaneously offering capabilities for use in numerical weather prediction (NWP) operations. The CCPP Framework supports configurations ranging from process studies to operational NWP as it enables host models to assemble the parameterizations in flexible suites. Framework capabilities include variability in scheme call order; ability to group parameterizations for calls in different parts of the host model, allowing intervening computation or coupling to additional components; options to call some parameterizations more often than others; and automatic variable transformations. The CCPP Framework was developed by the Developmental Testbed Center and is distributed with a single-column model that can be used to test innovations and to conduct hierarchical studies in which physics and dynamics are decoupled. It is also an integral part of the Unified Forecast System, a community-based, coupled, comprehensive Earth modeling system designed to support research and be the source system for the NOAA's operational NWP applications. Finally, the CCPP Framework is under various stages of adoption by a number of other models in the wider community. [ABSTRACT FROM AUTHOR]

The Common Community Physics Package (CCPP) is a collection of atmospheric physical parameterizations for use in Earth system models and a framework that couples the physics to a host model's dynamical core. A primary goal for this effort is to facilitate research and development of physical parameterizations and experimentation with physics-dynamics coupling methods, while simultaneously offering capabilities for use in numerical weather prediction (NWP) operations. The CCPP Framework supports configurations ranging from process studies to operational NWP as it enables host models to assemble the parameterizations in flexible suites. Framework capabilities include variability of scheme call order, ability to group parameterizations for calls in different parts of the host model allowing intervening computation or coupling to additional components, options to call some parameterizations more often than others, and automatic variable transformations. The CCPP Framework was developed by the Developmental Testbed Center and is distributed with a single-column model that can be used to test innovations and to conduct hierarchical studies in which physics and dynamics are decoupled. It is also an integral part of the Unified Forecast System, a community-based, coupled, comprehensive Earth modeling system designed to support research and be the source system for NOAA's operational NWP applications. Finally, the CCPP Framework is under various stages of adoption by a number of other models in the wider community. [ABSTRACT FROM AUTHOR]

In this paper the authors address one type of severe weather: strong straight-line winds. The case of a mesoscale convective system that developed in eastern Colorado on 12--13 May 1985 was studied. The system formed in the afternoon, was active until early morning, and caused strong winds during the night. A multiscale nonhydrostatic full physics simulation was performed to formulate a conceptual model of the main airflow branches of the system, and to gain understanding of the physical processes involved in the strong wind generation in this storm. Four telescopically nested grids covering from the synoptic-scale down to cloud-scale circulations were used. A Lagrangian model was employed to follow trajectories of parcels that took part in the updraft and downdraft, and balances of forces were computed along the trajectories. The strong nocturnal winds were caused by downdrafts reaching the surface and by a dynamically forced horizontal pressure gradient force. The most important branch of the downdraft had an "up--down" trajectory. Parcels originated close to the ground, were lifted up by a strong upward-directed pressure gradient force, and became colder than their surroundings as they ascended in a stable environment. Then, as they went through the precipitation shaft, they sank due to negative buoyancy enhanced by condensate loading. The upward pressure gradient force was partially related to midlevel perturbation vorticity in the storm. [ABSTRACT FROM AUTHOR]

After many years of independent development work that has led to largely incompatible model components among the different U.S. agencies, model unification has become a central effort of the near future. NOAA is engaged in the development of a Unified Forecast System (UFS) for addressing operational prediction at all scales, from hours to seasonal. Similarly, NCAR recently launched the SIMA (System for Integrated Modeling of the Atmosphere) project for WRF, MPAS and CESM. Often misunderstood, the term unification does not mean having a monolithic model to use for all applications but having a software infrastructure that permits the exchange of components between models. Model unification is a huge undertaking as it touches most, if not all, components of a modeling system. A central aspect in this process of unification is the interoperability of the physical parameterizations across the different models. In this context, the Global Model Test Bed (GMTB) with staff at NOAA's Global Systems Division (GSD) and at NCAR has been tasked to develop a collection of physical parameterizations and a software framework, called the Common Community Physics Package (CCPP), that facilitates the transition of innovations from the research community to operations to advance the UFS. The recent agreement made between NOAA and NCAR to jointly develop the CCPP framework places the CCPP framework in the heart of several of the U.S. flagship models as a single, standardized way to interface physics with models of the atmosphere (and other compartments of the Earth system). Additionally, NCAR is developing a new Model Independent Chemistry Module (MICM), which will employ the CCPP framework to connect a chemistry model to various community models.While the development of CCPP is centered around the NOAA and NCAR models SCM (GMTB single-column model), FV3 (Finite-Volume Cubed-Sphere), WRF (Weather Research and Forecasting model), MPAS (Model for Prediction Across Scales) and CESM (Community Earth System Model), the CCPP framework and the collection of physics and chemistry codes are becoming available to users and developers worldwide. This opens the door to a wider involvement of modeling communities and will accelerate the addition and transfer of physics improvements between these models, which is considered as a key factor for the success of NOAA's next generation global prediction system.In this contribution, we will provide a brief overview of the general concept of the CCPP, present the technical design and the requirements for parameterizations to be considered as CCPP-compliant, and describe the connection and integration of CCPP with the host model. We will also touch upon the challenges in designing a flexible modeling framework across different models while maintaining high computational performance. [ABSTRACT FROM AUTHOR]