Where are we with the Decadal Climate Prediction Project (DCPP)?

Transcription

1 Where are we with the Decadal Climate Prediction Project (DCPP)? G.J. Boer* Canadian Centre for Climate Modelling and Analysis Barcelona May 2016 *(and the DCPP Panel)

2 Where does a decadal climate fit? day-week week-year year -decade decade-century Weather forecasting Sub-seasonal Decadal Seasonal climate (WGSIP) Climate Simulation (WGCM)

3 Antecedent CMIP5 decadal component Decadal Climate Prediction Panel the development and support of both the science and practice of decadal prediction the provision of an archive of decadal prediction information for research and applications to provide advice on CMIP5 practicalities drift adjustment every year initial conditions data priorities.

4 CMIP5 decadal prediction component Has had a positive affect on research and offers promise for applications: many investigations and publications based on results input to Chapter 11 IPCC AR5 foster interest and activity in decadal prediction

5 The Shock, Drift and Bias Struggle global mean T Some climate modellers shocked and adrift due to the behaviour of their initialized climate predictions Very basic bias correction method described by Anon in WCRP report Importance of ameliorating shock and drift and adjusting for residual drift remains an important aspect of decadal prediction

6 The Shock, Drift and Bias Struggle adjusting for mismatch in trend

7 Shock, Drift and Bias Questions How to identify causes of shock, drift and bias? How avoid and/or ameliorate shock, drift and bias? How to adjust results to lessen the effects of shock, drift and bias in decadal prediction skill (and are there optimum approaches)?

8 Predictability and skill of annual mean T global and local predictability and skill mechanisms determining skill total forced internal importance of initialization vs external forcing deep ocean processes etc. predictability and skill as a function of forecast range - difference between and r may offer: guidance on mechanisms hope for improvement Results depend on reasonably successful bias adjustment

9 Some things we learned from the CMIP5 decadal prediction component need long sequence of ensembles of historical forecasts with many start dates needed for drift adjustment for statistical stability of results to provide historical skill assessment calibration of forecasts.. annual, multi-annual skill for temperature, not so much for precipitation initial condition skill dominates for several years then dies away leaving skill from forced component skill varies a great deal geographically skill higher over N. Atlantic than N. Pacific disconnect between potential and actual skill low skill over Southern Ocean multi-model aspects importance of general availability of results importance of coordinated multi-model experiments

10 Where are we organizationally with the DCPP? 1st International Workshop on Seasonal to Decadal Prediction (Toulouse, May 2013) DCPP development (2014) MiKlip/SPECS/DCPP/CLIVAR meeting (Feb 2015) review of common interests, actions Component C specifications CMIP6 Basic DCPP design agreed to by Panel Development of detailed description of the three Components DCPP data retention table to CMIP (Feb 2015) Final DCPP design to CMIP (Mar 2015) CMIP6 endorsement of the DCPP (April 2015) Aspen Workshop (June 2015) latest results wrt decadal prediction/predictability/mechanisms adjustments to DCPP specifications special attention to Component C

11 Where are we organizationally with the DCPP? GMD paper submitted (March 2016) JSC/WMAC meeting (April 2016) Approval of a WCRP Grand Challenge on Near Term Climate Prediction Lack of approval for WG on Decadal Climate (WGDC) or equivalent SPECS/PREFACE/WCRP Workshop on Initial Shock, Drift, and Bias Adjustment in Climate Prediction (now) DCPP Panel Meeting (next)

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13 WCRP Grand Challenge! Concept Note accepted and Grand Challenge approved by JSC White paper under development One goal is WMO annual/multi-annual forecasts (as currently done for seasonal forecasts) DCPP results and Grand Challenge depend on reasonably successful bias avoidance and/or adjustment

14 Broad interests in decadal climate variability and prediction WGSIP research and development leading toward operational annual, multi-annual forecasts IPCC Focus on decadal variability and predictability Ocean aspects, initialization Grand Challenge of Near Term Climate Prediction Coordinated experimentation including scenarios, decadal prediction. CLIVAR Forced climate change and natural variability CMIP Sub-seasonal to (inter)annual prediction WGCM Near term climate a focus of AR5 Chapter 11 and expected to be an important contribution to AR6 DCPP Decadal climate prediction project currently reports to WGSIP and WGCM, is an endorsed CMIP MIP and has connections to all groups CMIP WGCM Grand Challenge WGSIP Grand Challenge CLIVAR

15 Where does a decadal climate fit? WGNE WGSIP DecadalWGCM Climate (WGDC) Despite the absence of a WGDC, shock, drift and bias apply across all timescales and are (perhaps) most critical at seasonal/decadal timescales

16 Where are we with CMIP?

17 Organized by the DCPP Panel

18 Near-Term Climate Prediction A B C

19 DCPP Experiment Table

20 Component A: New hindcast results Annual mean temperature new approaches to drift amelioration and adjustment Forced plus internally generated components Internally generated component

21 B: Ongoing multi-model forecasts Temperature anomalies for 2016 (based on bias-adjusted results)

22 C:Response to AMV+/AMV-

23 C: Response to PDV+/PDV-

24 C: Volcanic effects on prediction (bias adjusted)

25 DCPP data aspects Earth System Grid (ESG) data approach Data widely available Large archive of hindcast data for analyses of all kinds including of shock, drift and bias adjustment case studies, mechanisms consequences of resolution, initialization, ensemble size etc. combination, calibration and multi-model approaches

26 CMIP Panel timeline and the DCPP Comp B:Forecasts Comp A:Hindcasts Comp C: Studies

27 Summary First organized multi-model effort in decadal prediction for CMIP5 leads to the DCPP Broad interest in decadal variability and prediction across WCRP and elsewhere DCPP proposed, adopts CMIP6 infrastructure, and becomes endorsed component Grand Challenge approved by JSC Active aspects for the DCPP component of CMIP6: finalize Component C forcing specifications finalize data treatment foster participation and analysis Many ongoing scientific aspects of end-to-end climate prediction deserve attention (shock and drift, initialization and ensemble generation, resolution, post processing..) Potential contribution to applications including the GFCS Importance of shock, drift amelioration and bias adjustment to progress

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29 (Hindcasts) (Forecasts)