The Model Diagnostics Task Force is constituted to develop, coordinate, and implement process-based model evaluation metrics and a metrics framework in National modeling center metrics packages, leveraging ongoing efforts at the modeling centers toward advancing model evaluation and development capabilities.

This Task Force is constituted of researchers whose projects were successfully evaluated as part of the FY15 competition held by NOAA’s Modeling, Analysis, Predictions, and Projections program on the topic of Process Oriented Metrics. This competition was motivated by a number of factors, including community interest in moving beyond performanceoriented metrics toward processoriented metrics, ongoing efforts to develop next-generation climate and Earth system models, evolving plans for CMIP, and a need to link model development and evaluation efforts across modeling centers. Nine projects were selected as a result of the competitive process, including eight focused on developing metrics and one that will develop metrics as well as define a direction and framework for the overall effort.

Task Force Function and Implementation

This Task Force will initiate its activities in October 2015 and will have a duration of three years. It is expected that researchers who were selected through the NOAA competitive process will participate actively in this Task Force helping to build an integrative processoriented metrics framework serving NOAA and other modeling centers. Task Force membership may also include affiliates, elected by Task Force leadership, who are not supported by MAPP funding but whose expertise and work are relevant to achieving the goals of this task force. The Task Force will coordinate with other relevant ongoing diagnostic efforts including emerging community processoriented metrics efforts such as the WCRP/WGCM Metrics Panel, PCMDI’s UVCDAT effort, and the EMBRACE ESMValTool project.

The Task Force will connect all of the funded investigators and other invitees. Beyond enhancing communication between investigators, expectations of this group include contribution by the individual projects to the development and implementation of the collective effort with a focus on implementing a cohesive metrics framework, open documentation of the efforts, and a focus on maximizing the community utility of metrics and the metrics framework. It is expected the main group will have monthly teleconferences and consider inperson meetings, as appropriate.


As of Spring 2017, the Task Force has developed a functional Application Program Interface (API) for the metrics package, which is documented here. The linked document also describes the overall status of the effort as of April 2017. The API is python based and designed to be flexible such that metrics coded in different non-proprietary software packages can be integrated into the API.

MAPP Task Force Concept and Terms of Reference


Lead: Eric Maloney, Colorado State University
Co-Lead: Yi Ming, NOAA Geophysical Fluid Dynamics Laboratory
Co-Lead: Andrew Gettelman, National Center for Atmospheric Research
Co-Lead: Aiguo Dai, University at Albany


Relevant MAPP Program PIs and selected additional invitees.
To view the full Participants list, please visit the Participants page.


To view the full list of Projects, please click here.

News & Events

UPDATED: FY18 Federal Funding Opportunities for Climate and Societal Interactions 17 January 2018

UPDATED: FY18 Federal Funding Opportunities for Climate and Societal Interactions

The three competitions would fund interdisciplinary research on planning and preparedness to extreme weather and climate.
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New line of information could help predict the storms’ future strength

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Water Resources Dashboard: November Webinar Recordings 19 December 2017

Water Resources Dashboard: November Webinar Recordings

Missed November's webinars? Watch them here.
New research unlocks the door for better predictability up to 7 months ahead 13 December 2017

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In many parts of North America, a fluctuating air-pressure pattern that enhances or blocks the storm-steering jet stream, called the Arctic Oscillation (AO), explains more variability in the weather than a primary influencer called the El Niño-Southern Oscillation (ENSO). However, the AO’s prediction skill has been known to be limited, until now.

New research finds extreme thunderstorms could increase with warming temperatures in tropics and subtropics 13 November 2017

New research finds extreme thunderstorms could increase with warming temperatures in tropics and subtropics

Some of the world’s most intense thunderstorms, associated with destructive impacts like high winds, large hail, and flash floods, occur in the tropical and subtropical regions, including parts of the southern U.S. However, scientists have been uncertain about how such storms will respond in the context of warming temperatures.



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