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Decadal Predictability Framework for Climate Variations: WG Meeting Agenda

This agenda outlines the schedule and topics of the U.S. CLIVAR Decadal Predictability Working Group Meeting held on June 19, 2009. The meeting focuses on defining a framework to separate natural variability from anthropogenically forced variability on decadal time scales in order to assess predictability of climate variations in coupled models. Key discussions include methods for identifying predictability, white paper structure, and model experiment recommendations aimed at understanding decadal climate variability. The meeting aims to address challenges and future plans for quantifying additional predictability due to natural variations.

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Decadal Predictability Framework for Climate Variations: WG Meeting Agenda

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  1. Agenda for U.S. CLIVAR Decadal Predictability Working Group Meeting, June 19 2009 • 8:15 a.m. Coordination with other WGs (presentations +discussion) (1 hour 15 minute) • Coordination with US AMOC Science Team (Jim Carton)(30 minutes) • Input to WGCM on biases (Lisa Goddard)(30 minutes) • Coordinated decadal prediction experiments with NCAR Working Groups (Amy Solomon)(15 minutes) • 9:30 a.m. Break • 10:00 a.m. Involvement in upcoming workshops (presentations +discussion) (45 minutes) • Do we want to organize special sessions at any of these meetings? • Is there a good meeting that can overlap with a DPWG group meeting? • CLIVAR WGOM Workshop (Gokhan Danabasoglu)(20 minutes) • 8th DecVar Workshop, Oct 2009, Maryland (10 minutes) • 3) RSMAS workshop on " Predicting the climate of the coming decades" (Ben Kirtman)(15 minutes) • 10:45 p.m. Motivation for White Paper (30 minutes) • Discussion of purpose for the white paper and how it differs from the documents already in existence • Discussion of the proposed structure and sections. (Arun Kumar) • 11:15 p.m. White Paper Section 2 (30 minutes) • Discussion on physical basis for additional predictability due to • natural climate variations on decadal time-scales (Jim Carton and Ben Kirtman)

  2. 11:45 p.m.Lunch • 12:45 p.m. White Paper Section 3 (45 minutes) • Discussion on methods to identify additional predictability and noise due to natural climate variations • Matt Newman and Yochanan Kushnir) • 1:30 p.m.White Paper Section 4 (45 minutes) • Challenges. (Ichiro Fukumori and Clara Deser) • 2:15 p.m.Break • 2:45 p.m.White Paper Section 5 and general discussion (45 minutes) • Recommendations: Can the paper recommend a set of model experiments that • would help with this question (or what is proposed under the CMIP5 is adequate?) • (Jerry Meehl and Doug Smith) • 3:30 p.m. DPWG Business (30 minutes) • General discussion • Future plans (Assembling databases for metrics study) • Recommended timeline/scope of DecPred CMEP-type activities (David Legler) • 4:00 p.m.DPWG Meeting Adjourns

  3. Decadal Predictability Working Group Meeting Primary Objectives of the Working Group 1) To define a framework to distinguish natural variability from anthropogenically forced variability on decadal time scales for the purpose of assessing predictability of decadal-scale climate variations in coupled climate models. 2) To develop a framework for understanding decadal variability through metrics that can be used as a strategy to assess and validate decadal climate prediction simulations.

  4. Defining a framework to distinguish natural variability from anthropogenically forced variability on decadal time scales for the purpose of assessing and validating predictability of decadal-scale climate variations in coupled climate models. By first addressing: 1) On decadal timescales, where natural and forced variability (and trends?) are of the same order, what approaches can be used to separate natural decadal variability from anthropogenically forced decadal variations? How does the analysis depend on the chosen method? 2) How do we address the issue of potential projection and interaction between the natural and forced variability? 3) Do we have robust estimates of observed decadal variations to validate the models? …..With the ultimate goal of defining a framework to quantify additional predictability due to natural variations

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