Predictability, Predictions, and Applications Interface Panel

The Predictability, Predictions, and Applications Interface (PPAI) Panel's mission is to foster improved practices in the provision, validation and uses of climate information and forecasts through coordinated participation within the US and international climate science and applications communities. The Panel is comprised of up to 12 experts from the scientific community, each serving a 4-year term. New panelists are selected annually by the Scientific Steering Committee based on nominations submitted through an open call for new members each fall/winter.


Predictability, Predictions, and Applications Interface (PPAI) Panel
Member name Institution Term through
Andy Wood, Co-chair National Center for Atmospheric Research Dec. 2020
Zhuo Wang, Co-chair University of Illinois at Urbana-Champaign Dec. 2021
Emily Becker NOAA Climate Prediction Center/Innovim Dec. 2019
Mona Behl University of Georgia  Dec. 2020 
Robert Burgman Florida International University Dec. 2019
Adam Clark NOAA National Severe Storm Lab Dec. 2019
Naresh Devineni The City College of New York Dec. 2022
Qinghua Ding University of California, Santa Barbara Dec. 2022
John Nielsen-Gammon Texas A&M University Dec. 2019
Matthew Newman University of Colorado/NOAA Earth System Research Center Dec. 2021
Haiyan Teng National Center for Atmospheric Research Dec. 2022
Hailan Wang NASA Goddard Space Flight Center/Science Systems and Applications, Inc. Dec. 2021


Terms of Reference

  • Review, prioritize, and coordinate US research plans to understand predictability of the oceans and climate on sub-seasonal, seasonal-to-interannual, decade-to-century and longer time scales.
  • Advise US CLIVAR on research priorities, gaps, and milestones to advance ocean and climate predictions and projections through improved evaluation, and better quantification and communication of skill and uncertainty.
  • Advocate for new funding opportunities and national and international activities to advance in prediction and predictability research, understand user needs, and develop decision support capabilities.
  • Coordinate US CLIVAR efforts to communicate with operational and decision-making communities on improved understanding of ocean and climate phenomena and predictability and on implementation of this understanding in their activities.
  • Liaise with other US CLIVAR panels and Working Groups to ensure predictability, prediction, and applications are part of their efforts.