Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers’ model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.
The mesoscale eddies of which parameterization is needed in coarse‐resolution ocean models include not only the transient eddies akin to baroclinic instability but also the stationary eddies associated with topography. By applying a modified Lorenz‐type decomposition to the eddy‐permitting Southern Ocean State Estimate, we show that the stationary mesoscale eddies contribute a significant part to the total eddy kinetic energy, eddy enstrophy, and the total eddy‐induced isopycnal thickness and potential vorticity fluxes. We find that beneath middepth (about 1000 m) the upgradient eddy fluxes, or so‐called “negative” eddy diffusivities, are mainly attributed to the stationary mesoscale eddies, whereas the remaining transient eddy diffusivity is positive, for which the Gent and McWilliams (1990) parameterization scheme applies well. A quantitative method of measuring the anisotropy of eddy diffusivity is presented. The effect of stationary mesoscale eddies is one of major sources responsible for the anisotropy of eddy diffusivity. We suggest that an independent parameterization scheme for stationary mesoscale eddies may be needed for coarse‐resolution ocean models, although the transient eddies remain the predominant part of mesoscale eddies in the oceans.
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