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Home » Metrics for general circulation model biases in extratropical cyclone clouds and precipitation: evaluating their skill and identifying processes to be improved

Metrics for general circulation model biases in extratropical cyclone clouds and precipitation: evaluating their skill and identifying processes to be improved

“The general circulation models that participate in the CMIP5 exercise exhibit cloud and precipitation biases in the midlatitudes, a region where extratropical cyclones play an active role. This in turn causes long-term biases for the prediction of average and extreme precipitation events, as well as the global energy balance. It is thus paramount to better understand which processes in the models contribute to these biases and provide a set of metrics to help in their evaluation.

As such, the objective of this project is to create a set of process-oriented metrics to evaluate model ability to produce realistic extratropical cyclones. These metrics encompass the characteristics of the storms on the planetary, synoptic and frontal scales. The metrics are designed to inform on model skill in accurately representing the large-scale and the cyclone-
scale dynamics, as well as the cyclone moisture content, temperature, cloud and radiation fields and precipitation. Furthermore, the proposed analysis methods will help identify the limitations of current parameterization schemes.

This project is based on a set of tools that the team has developed over the years that use model gridded outputs to: (a) locate and track extratropical cyclones, (b) locate the warm and cold fronts, (c) measure cyclone-local characteristics through the use of compositing techniques and (d) use conditional subsetting to identify the sensitivity of cyclone cloud and precipitation to changes in dynamics and thermodynamics. It also combines a comprehensive set of satellite observations and reanalysis output using both state-of-the-art and innovative approaches to assess models beyond the simple map-to-map comparison. The metrics will provide (1) a measure of a model’s ability to reproduce the atmospheric conditions within the storms, and (2) the model’s ability to predict the right response in cloud and precipitation to changes in atmospheric conditions. Furthermore, specific metrics are designed to inform on the reliability of components of the model that directly participate in the formation of clouds and precipitation, namely their convection, cloud and boundary layer schemes.

The outcome of the project will be a package of numerical codes that generate the process-based metrics proposed herein and compare them with reference metrics. The reference metrics are a series of storm-specific observations and reanalysis products that we will generate. Additionally, in our work we will test the process-based metrics using output from the GCMs participating in CMIP5. Both the numerical code for the metrics analysis and the data for the reference metrics will be made freely accessible via NOAA-CREST website.

The project directly addresses the objectives of the NOAA MAPP-Process-Oriented Evaluation of Climate and Earth System Models and Derived Projections (ID 2488569) call, namely to “develop and integrate process-oriented metrics into U.S. modeling centers’ diagnostic packages to support the evaluation and development of next-generation climate and Earth system models”. This project fits within NOAA’s long term goal of “Climate Adaption and Mitigation” by addressing their objective of “Improved scientific understanding of the changing climate system and its impacts” and “Assessments of current and future states of the climate system”.”

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