Overview

The workshop consisted of invited plenary speakers and contributed talks and posters. The invited speakers were asked to review and encourage the discussion of the current state of research related to a particular topic with candid and critical comments. Session Chairs led end of session discussions assessing community consensus and future coordinated directions. The workshop culminated in a final summary discussion on what could be achieved by a joint effort, whether the community could develop a common framework in decadal variability, predictability and prediction research.

List of Particpants

Decadal SST Anomalies Confined To The North Pacific Subarctic Frontal Zone And Their Atmospheric Influences

B. Taguchi¹, H. Nakamura²,³, M. Nonaka³, N. Komori¹, A. Kuwano-Yoshida¹, K. Takaya³ and A. Goto⁴

(1) Earth Simulator, JAMSTEC, (2) Uni. Tokyo, (3) Res. Inst. Global Change, JAMSTEC, (4) Japan Met. Agency

Low Frequency Climate Responses Of ENSO And Solar Modulation On The Western North Pacific Fish Recruitment

Y.-H. Tseng¹, W.-N. Tzeng²,³, C.-H. Hsieh⁴, Y.-S. Han¹, C.--W. Chang⁵, C.-C. Hsu6, S. Jan⁴ and E. Di Lorenzo⁷

(1) Dept. Atmos. Sciences, National Taiwan University (NTU), (2) Dept. Life Science & Inst. of Fisheries Science, NTU, (3) Dept. Env. Biol. & Fisheries Science, National Taiwan Ocean University, (4) Inst. Oceanogr. & Inst. of Ecology and Evolutionary Biology, NTU, (5) Marine Biology Museum and Aquarium, Taiwan, (6) Earth Dynamic Center, Cheng-Kung University, (7) Georgia Insititute of Technology

Relationship Between Typhoon Activity In The Northeastern Pacific And The Upper-Ocean Heat Content On Interdecadal Timescales

Q. Liu¹ and W. Zhou²

(1) South China Sea Institute of Oceanology, Chinese Academy of Sciences, (2) Guy Carpernter Asia-Pacific Climate Impact Centre, City University of Hong Kong

On The Role Of The Solomon Sea In ENSO Decadal Modulation: A Preliminary Modeling Study

A. Melet¹, J. Verron¹, L. Gourdeau², W. Kessler³, and A. Koch-Larrouy

(1) LEGI/MEOM, (2) IRD/LEGOS, (3) NOAA/PMEL

An Analysis Of Climate Variability To Increase Of GHG Concentrations In CCSM3

Z.-Z. Hu¹, A. Kumar¹, B. Jha¹ and B. Huang²

(1) Climate Prediction Center, NCEP/NWS/NOAA, (2) George Mason University and COLA

Patterns Of Indian Ocean Sea Level Change In A Warming Climate

W. Han, G. A. Meehl, B. Rajagopalan, J. Fasullo, A. Hu, J. Lin, W. Large, J. Wang, X. Quan, L. Trenary, A. Wallcraft, T. Shinoda and S. Yeager

University of Colorado and NCAR

Decadal Climate Variability In A Coupled GCM FGOALS_g2.0

Y. Zhang¹,² and Y. Yu¹

(1) LASG, Insititute of Atmospheric Physics, (2) Graduate University of Chinese Academy of Sciences

Interannual To Decadal Modulations Of High Frequency Oceanic And Atmospheric Disturbances In The Kuroshio-Oyashio Interfrontal Zone Represented In A High Resolution CGCM With Ocean Data Assimilation

H. Tatebe¹, M. Ishii¹,², M. Kimoto³, T. Sakamoto¹, Y. Komuro¹ and T. Mochizuki¹

(1) JAMSTEC, (2) MRI, (3) University of Tokyo

Effect Of Atlantic Meridional Overturning Circulation On Tropical Atlantic Variability: A Regional Coupled Model Study

C. Wen¹, P. Chang², R. Saravanan³

(1) Wyle IS/CPC/NCEP/NOAA, (2) Dept. Oceanogr., Texas A&M University, (3) Dept. Atmos. Sciences, Texas A&M University

CCCma Decadal Prediction For CMIP5

W. Merryfield, W.-S. Lee, G. Boer, S. Kharin, J. Scinocca, G. Flato and J. Fyfe

CCCma, Environment Canada

Community Climate System Model (CCSM4) Decadal Prediction Experiments Initialized From Best-Estimates Of The Historical Ocean State Between 1970 and 2000

S. Yeager, G. Danabasoglu, J. Tribbia, J. Anderson, T. Hoar, N. Collins, K. Raeder, H. Teng and J. Hurrell

NCAR

The Response Of The Southern Ocean And Global Circulation To Decadal Strengthening Of Southern Hemisphere Winds: Mesoscale Eddies And Their Parameterization In Climate Models

R. Farneti¹, T. Delworth², T. Rosati², S. Griffies², and P. Gent³

(1) ICTP, (2) GFDL/NOAA, (3) NCAR

Atlantic MOC Variability In Decadal Climate Prediction Systems

H. Pohlmann¹, M. Balmaseda², N. Keenlyside³, D. Matei⁴, W. Muller⁴, P. Rogel⁵ and D. Smith¹

(1) Met Office Hadley Centre, (2) ECMWF, (3) IFM-GEOMAR, (4) MPI-M, (5) CERFACS

Multi-Decadal North Atlantic Variability Simulated In NEMO

J. Mecking, N. Keenlyside and R. Greatbatch

IFM-GEOMAR

Assessing The Decadal Variability and Predictability Of Climate In The GFDL Coupled Models

R. Msadek, T Delworth, K. Dixon and T. Rosati

NOAA/GFDL

Mechanisms And Impact Of Atlantic Multidecadal Variability

Y. Kushnir, M. Ting, N. Naik, C.-H. Li, I.-S. Kang*, R. Seager and M. Cane

Lamont-Doherty Earth Observatory, Columbia University, * On sabbatical from Seoul National University

The Role Of Ocean Dynamics In North Atlantic Tripole Variability 1951-2000

E. Schneider

George Mason University and COLA

Predictability Of Low-Frequency Regime Transitions In A Stochastically Forced Model
B. Nadiga¹ and T. O'Kane²

(1) Los Alamos National Laboratory, (2) CSIRO

On Initialization Of Realistic High-Resolution Ocean Models

B. Nadiga and P. Jones

Los Alamos National Laboratory

Varied Representation Of The Atlantic Meridional Overturning Across Multi-Decadal Ocean Reanalyses

E. Munoz¹, B. Kirtman², and W. Weijer³

(1) New Mexico Consortium, (2) RSMAS-University of Miami, (3) Los Almos National Laboratory

Impact Of Different Ocean Reanalyses On Decadal Climate Prediction

J. Kröger, W. Müller and J.-S. von Storch

MIP-M

Adequacy Of Observing Systems In Monitoring AMOC And North Atlantic Climate

S. Zhang, A. Rosati and T. Delworth

NOAA/GFDL

Coupled Ocean And Atmosphere Analysis By Assimilating Ocean Observation Data To A Coupled Model

Y. Fujii¹, T. Nakaegawa¹, S. Matsumoto², T. Yamanaka¹ and M. Kamachi¹

(1) Japan Meteorological Agency (JMA), Meteorological Research Institute, (2) JMA

Weakly Coupled Atmosphere-Ocean Data Assimilation: CAM-DART-POP

T. Hoar, S. Yeager, N. Collins, K. Raeder, J. Anderson, G. Danabasoglu, M. Vertenstein and J. Tribbia

NCAR

Multi-Model Analysis Of Upper Ocean Heat Content Indices

Y. Xue¹, M. Balmaseda², N. Ferry³, S. Good⁴, I. Ishikawa⁵, T. Boyer⁶, M. Rienecker⁷, T. Rosati⁸, Y. Yin⁹ and A. Kumar¹

(1) NOAA/NCEP, (2) ECMWF, (3) Mercator Ocean, (4) Met Office Hadley Centre, (5) Japan Meteorological Agency, (6) NOAA/NESDIS/NODC, (7) NASA/GSFC/GMAO, (8) NOAA/GFDL, (9) CAWCR/BoM

La Nina Events Before And After 1979 And Their Impact Over Southeastern South America, During Summer

G. Cazes-Boezio and S. Talento

Universidad de la Repiblica, Uruguay

Some recent examples of regional scale climate variability and change such as the prolonged drought in the southwestern U.S., increased Atlantic hurricane activity, changes in commercial fish production in the North Pacific and northern North Atlantic and the recent melting of the outlet glaciers on Greenland have raised awareness about climate change and its impact on society on decadal time scales, including amongst decision and policy makers. On these 10-30 year scales, regional variations in climate and their impacts largely represent natural, i.e., internal, variability of the climate system primarily driven by the slowly varying oceans, significantly affecting the anthropogenic (forced) climate change signals.

Decadal prediction is a new, but rapidly growing field. Some recent review articles (e.g., Meehl et al. 2009) as well as white papers (Hurrell et al. 2009; Latif et al. 2009; Balmaseda et al. 2009) detail the need for and usefulness of such decadal predictions, and outstanding issues and challenges with both observations and models. A unique aspect of the decadal prediction problem is that it represents a joint initial and boundary value problem. This implies that best possible initial conditions of the climate system need to be provided. The global ocean is the primary source of the longer-term temporal 'memory' of the climate system. Therefore, robust decadal predictability and prediction assessment require that the ocean be initialized using observational information, synthesized into appropriate initial conditions. A suite of coordinated decadal hindcast and prediction experiments for the period 1960-2035 are being carried out as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to improve our understanding of decadal climate variability and predictability. Results from these experiments, which partly are also initialized using ocean data or ocean syntheses, will be evaluated for the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5).

Observational examples of decadal variability include the Pacific Decadal Oscillation or Inter-decadal Pacific Oscillation (PDO/IPO) and the multidecadal variability in the Sea Surface Temperatures (SSTs) in the Atlantic Basin, usually referred to as the Atlantic Multidecadal Oscillation (AMO). Coupled general circulation models used in climate studies usually exhibit significant decadal variability / oscillation in their Atlantic Meridional Overturning Circulations (AMOCs). Furthermore, some studies show a broad resemblance between the observed and model simulated SST variability patterns in the North Atlantic that is usually associated with the AMOC variability. The link between the AMO and AMOC cannot be verified by the observations due to the lack of long-term AMOC records. Nevertheless, presence of such long-lived variability as depicted by either the PDO or AMOC forms the basis for decadal prediction studies. Because of its prominent role in the Earths climate system, the AMOC variability and its potential predictability have received much recent attention. Decadal variability and prediction exists in other oceans including the Southern Ocean, Indian and South Pacific Oceans, although lack of long-term observational data severely limits detection of the decadal signal in these regions.

Despite increasing number of studies, many important aspects of decadal variability and prediction remain controversial. For example, the amplitude and period of the AMOC variability differ considerably across ocean models and the associated SST variability patterns, magnitudes, and periods do not match the observational AMO properties in most models. This holds also for ocean models constrained by ocean observations and a detailed study is required as to determine why those differences remain and what observational data base is required to better constrain and understand them. Furthermore, understanding of decadal variability mechanisms is severely lacking. Some recent studies indicate that proper initialization of oceanic indices, e.g., the AMOC and the global upper-ocean heat content, is important for predictability of the climate system. However, robustness of such initialization approaches - attempting to accurately represent present-day low frequency variability in the ocean - across different models remains unclear.

The WGOMD has recently finalized an experimental protocol for the Coordinated Ocean-ice Reference Experiments (CORE-II) forced with interannually varying surface data sets for the period 1948-2007 from Large and Yeager (2008). The CORE-II hindcast simulations provide a highly anticipated framework to evaluate ocean model performance, to study mechanisms of ocean phenomena and their variability from seasonal to decadal timescales, to identify forced variability changes, and to develop mechanistic descriptions of observed climate variability and change. Furthermore, CORE-II experiments will serve as a useful direct comparison to observational studies, and they can be used to optimize the ocean observing systems for the present climate. The natural variability differences amongst models participating in CORE-II experiments will be interesting for understanding and evaluating the robustness of modeled ocean variability and the formation, propagation and decay of anomaly signals that has been observed during the 20th Century. Given the reliability of data assimilation prior to the Argo period is under question, initializing decadal predictions from CORE-II hindcast simulations without data assimilation can be an option. Similarly, anomalies can be extracted from the CORE-II climatology and then applied to the decadal prediction simulations.

An alternative approach is being followed by GSOP: The synthesis of all available ocean data sets by merging them over many years with ocean circulation models. Results of mathematically consistent approaches are dynamically self-consistent and can serve as a complementary basis to study the dynamics of ocean variability, to improve ocean and coupled models, to improve the observing system and to initialize coupled forecast models. GSOP performed now for several years an evaluation of existing ocean syntheses (Lee et al., 2009; Heimbach et al., 2009; Stammer et al., 2009). A next step includes the use of those syntheses for initialization, but especially also for studying ocean decadal variability. Part of those efforts needs to be to assess the adequacy of ocean syntheses for such studies as well as identifying and improving existing shortcomings.

Despite its prominent role in decadal variability and predictability, understanding of the underlying physical mechanisms of oceanic natural variability is clearly missing. As indicated above, so far many efforts have focused on the Atlantic Ocean, with the AMOC as a key player, although the Pacific Ocean also contains intriguing variability on the decadal time scales. There are of course significant difficulties with the decadal variability and prediction problem associated with a paucity of observational data, the long time scales involved, and ocean (and climate) model limitations. The CLIVAR WGOMD and GSOP are motivated to hold a joint workshop on decadal variability, predictability, and prediction, specifically focusing on the oceans role in understanding and modeling the decadal variability. In particular, we believe that the availability of the CORE-II hindcast simulations and the recent advances in ocean syntheses will be of significant help in addressing these issues.

The main goals of the workshop are:

To assess how well the ocean models and ocean syntheses reproduce observed decadal variability,

To understand and evaluate the robustness of simulated ocean internal variability,

To identify the underlying physical mechanisms in the ocean in decadal climate variability,

To evaluate the outcomes of the CMIP5 decadal prediction experiments.

References

Balmaseda, M.A. & Co-authors (2010). “Initialization for seasonal and decadal forecasts” in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306.

Heimbach, P. & Co-Authors (2010). "Observational Requirements for Global-Scale Ocean Climate Analysis: Lessons from Ocean State Estimation" in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306.

Hurrell, J. & Co-Authors (2010). "Decadal Climate Prediction: Opportunities and Challenges" in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306

Large, W.G., and S.G. Yeager, 2008: The global climatology of an interannually varying air sea flux data set. Climate Dynamics, doi:10.1007/s00382-008-0441-3, 24pp.

Latif, M. & Co-Authors (2010). "Dynamics of Decadal Climate Variability and Implications for its Prediction" in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306.

Lee, T. & Co-Authors (2010). "Ocean State Estimation for Climate Research" in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306.

Meehl, G.A., and Co-authors, 2009: Decadal prediction. Can it be skillful? BAMS, 90, 1467-1485.

Stammer, D. & Co-Authors (2010). "Ocean Information Provided through Ensemble Ocean Syntheses" in Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. & Stammer, D., Eds., ESA Publication WPP-306.

The following provides a list of topics and some key questions. We hope that the workshop participants will address these and other related questions in their presentations, posters, and discussions.

1. Observed decadal variability: What is the observed decadal variability in the climate system (observations and syntheses)? What are the observed climate impacts? What do the paleoclimate records show? What are the observed signals in the ocean? Are the present ocean observations adequate for decadal variability studies? What new observations are needed?

2. Predictability and state of the ocean models: Is there any predictability in the climate system? What are the sources of such predictability? What are the roles of natural and forced variability? Are the ocean models up to the task? What are the CORE-II hindcast simulations and ocean syntheses showing? How sensitive are small/regional changes to the ocean initial state? Are all the participating models in CORE-II reproducing the observed and synthesized variability robustly? How sensitive are the model results to model resolution? Are the ocean models robust in their internal variability? How is the internal variability affected by ocean model parameterization choices?

3. Physical Mechanisms: What are the sources of decadal variability? What determines the propagation and decay of decadal anomalies? What are the physical mechanisms in the ocean for decadal variability? How robust are these mechanisms? How are CORE-II experiments and ocean data assimilation improving our understanding of oceanic decadal variability mechanisms?

4. Initial conditions, predictions, and verification: What initialization techniques are used in the community? Are they robust in their outcomes across different models? What fields should be carefully initialized in the ocean? Can the CORE-II hindcast simulations be successfully used to initialize the ocean state for prediction experiments? Are they as useful as ocean syntheses? Is any one of the initialization approaches clearly superior to the others? What are the common verification techniques?

5. CMIP5 decadal prediction experiments: What do the early results show? Do the models agree? Is there any predictability? Are the ocean models capturing observed variability during the hindcast period? Do the hindcast experiments show that it is meaningful to run projection / prediction experiments?