The CVP Task Force on Tropical Pacific Biases seeks to enhance the representation of tropical Pacific climate variability in numerical climate and weather models by improving our understanding of the biases, processes, and climatology in that region. Convened by the Climate Variability and Predictability program of the NOAA Climate Program Office, this task force is a three-year endeavor that brings together scientists funded under a recent call for proposals to address these biases. The task force explicitly promotes communication amongst these researchers in order to increase sharing of research methods best practices, interoperability and reuse of data, and dissemination of improvements and ideas.

This task force will adhere to the following Terms of Reference:

  • The task force will be lead by one PI from the cohort of researchers funded under the tropical Pacific biases call, and will be supported by 2-3 co-leads from the cohort.
  • NOAA program management will facilitate the task force meetings and preparation of any outputs from the task force in collaboration with the lead and co-leads.
  • Participation in the Task Force is by invitation, with the core of the Task Force constituted by CVP-funded PIs.
  • The task force will be in place for the duration of the funded projects
  • Most of the work will be accomplished via remote meetings. Additionally, annual in-person meetings in Silver Spring, MD or Boulder, CO will be held in the second and third year.

Background

At present, climate models exhibit a number of errors in the tropical Pacific in fields such as sea surface temperature, wind velocity, and cloud microphysics. This leads to representations of the Earth system that are not realistic, thus degrading our ability to forecast weather and climate. For example, many models do not yet accurately simulate the correct placement of the Intertropical Convergence Zone (ITCZ) - a belt of clouds and precipitation near the equator - and in fact may produce two ITCZs at times when this is not realistic. This leads to models not representing natural variability modes such as El Niño and the Madden-Julian Oscillation well. These biases, in turn reduce prediction skill and lead to increased uncertainty in projections of future climate.

View the related FY14 Federal Financial Opportunity

View Funded Projects under this proposal call

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