U.S. AMOC Program atlanticmoc

1. U.S. AMOC Program www.atlanticmoc.org A U.S. interagency program with a focus on AMOC monitoring and prediction capability NASA Earth Science Division Satellite data analyses, modeling and space-based observations NOAA Climate Program Office Observing systems, monitoring, climate modeling NSF Geosciences program Process studies, models, and observations

2. U.S. AMOC Scientific Objectives • The design and implementation of an AMOC monitoring system • An assessment of AMOC’s role in the global climate • An assessment of AMOC predictability Program Organization: Science Team Chair: B. Johns (prev. S. Lozier) Task Teams: 1. AMOC Observing System Implementation and Evaluation (Chair: Susan Lozier; Vice-chair: Patrick Heimbach) 2. AMOC State, Variability, and Change (Chair: Josh Willis; Vice-chair: Rong Zhang) 3. AMOC Mechanisms and Predictability (Chair: Gokhan Danabasoglu; Vice-chair: Young-Oh Kwon) 4. Climate Sensitivity to AMOC: Climate/Ecosystem Impacts (Chair: Ping Chang; Vice-chair: Yochanon Kushnir) Executive Committee: Science Chair + Task Team chairs/vice-chairs + U.S. Clivar rep.

3. Research Highlights

4. AMOC Variability in the Subtropical Atlantic (RAPID-MOCHA 26.5N)

5. AMOC Variability in the Subtropical Atlantic (RAPID-MOCHA 26.5N) Courtesy of Bill Johns

6. Relationship of Ocean Heat Transport to AMOC Variability Mean heat transport: 1.33 PW At 26.5°N, the RAPID-MOCHA array now provides continuous ocean heat transport estimates of unprecedented accuracy. The mean value of 1.33 PW, larger than most previous estimates, is associated with a mean MOC strength of 18.5 Sv. This provides a precise definition of the relationship between MOC and heat transport variability, an important benchmark for climate model evaluation. Mean MOC:18.5 Sv Correlation: 0.94 Sensitivity: 0.06 PW/Sv Courtesy of Bill Johns

7. AMOC Variability Derived from ARGO and Altimetry ARGO data and altimetry can be combined to monitor AMOC variability at latitudes where the boundary circulations are weak (example: 41°N). ARGO-altimetry correlations provide an extended record back to 1993, suggesting a weak increasing trend of AMOC for the last two decades. MOC at 41ºN Courtesy of Josh Willis

8. Pathways of Meridional Circulation in the North Atlantic Ocean Surface drifter tracks show significant changes since year 2000 in the path of the surface currents associated with the North Atlantic Current. Surface drifter tracks entering (cyan) and leaving (magenta) the region (30-50W, 35-45N): during 1991-2000, top, and during 2001-2006, bottom. Courtesy of Sirpa Hakkinen

9. Export Pathways from the Subpolar North Atlantic RAFOS floats launched from the subpolar gyre do not follow the DWBC continuously. Observations and modeling results show that eddy-driven flow creates an important interior pathway for newly-ventilated waters. Courtesy of Susan Lozier

10. Meridional Coherence and Propagation of AMOC Variations Due to the existence of interior pathways, AMOC anomaly propagates with advection time scale, resulting in a several-year time lead between subpolar and subtropical AMOC variations. AMOC variations associated with changes in the NADW formation have significant Meridional Coherence in density space in GFDL CM2.1 (Zhang, 2010) and in the high resolution coupled model GFDL CM2.5 (Zhang et al. 2011).

11. Impact of Nordic Sea Overflow in a High Resolution Global Coupled Model (GFDL CM2.5) Control Experiment (Weak Overflow, Expanded SPG) Perturbed Experiment (Strong Overflow, Contracted SPG) Zhang et al. 2011

12. Sensitivity of AMOC Variability to Parameterized Nordic Sea Overflows in CCSM4 The inclusion of parameterized Nordic Sea overflows in the ocean component of the CCSM4 results in dramatically reduced variance of the AMOC on decadal and longer timescales compared to a control CCSM4 simulation without this parameterization. Courtesy of Gokhan Danabasoglu

13. Impact of Nordic Sea Overflow Parameterization on Decadal Prediction in GFDL CM2.1 Courtesy of Tony Rosati

14. Implement Enhanced AMOC Observing Systems in the South Atlantic and Subpolar North Atlantic OSNAP SAMOC

15. Courtesy of Susan Lozier

16. Courtesy of Susan Lozier

17. Courtesy of Susan Lozier

18. Annual air-sea carbon dioxide flux (positive out) using gridded data from Takahashi et al. (2009). What are the mechanisms controlling CO2 uptake in the subpolar North Atlantic and how do they vary on seasonal and interannual time scales? How does ocean physics, particularly the AMOC, constrain this uptake? The North Atlantic is a strong sink for atmospheric carbon dioxide (Takahashi et al., 2009) and it dominates storage of anthropogenic carbon in the ocean (Sabine et al., 2004). On an annual basis the Atlantic as a whole accounts for 41% of the global air-sea CO2 flux and nearly half of this flux occurs north of 50° N (Figure 1). This high flux is driven by a combination of the AMOC and a strong, annual cycle of net community production (NCP) (Schuster and Watson, 2007; Kortzinger et al., 2008). The AMOC drives northward flow of warm surface waters. As these waters cool, they absorb additional CO2 and then leave the surface as deep waters form. Courtesy of Susan Lozier

19. Summary • OSNAP addresses a high priority of the U.S. AMOC program. • OSNAP will enable answers to fundamental questions regarding ocean overturning. • OSNAP leverages existing measurement systems. • OSNAP has garnered significant international interest and collaboration. • OSNAP is a multi-disciplinary observing program that will investigate physical constraints on biogeochemistry, marine ecosystems and the cryosphere. Courtesy of Susan Lozier

20. SAMOC: South Atlantic Meridional Overturning Circulation – Future observing system AMOC 2010 Annual Report

21. US AMOC Program near term priorities: 1. Assessing the meridional coherence of AMOC changes should be a continued focus of prognostic models, state estimation models, and enhancement of the AMOC observing system. The design of monitoring systems for the time varying strength of the AMOC in the subpolar North Atlantic and subtropical South Atlantic should be completed this year and implemented during 2012. The importance of deep temperature and salinity measurements (i.e. deep ARGO) in monitoring AMOC variability should also be assessed. 2. Assimilation modeling efforts should focus on reaching a consensus on the variability of the AMOC over the past few decades, and on placing realistic uncertainty bounds on these estimates. It is important that we understand the uncertainties of existing estimates and the accuracies required to detect climatically important AMOC-related changes. 3. Studies aiming to develop fingerprinting techniques to better characterize AMOC variability by combining model simulations with observations should be further encouraged and supported. Particular focus should be on understanding the linkage between AMOC variability and SST variability, both from a diagnostic and mechanistic viewpoint. 4. Further study is required to understand the teleconnections between AMOC/North Atlantic SST and climate variability elsewhere, and the physical mechanisms of these teleconnections. Targeted studies of the impact of AMOC variability on sea ice, ocean ecosystems, sea level changes around the Atlantic Basin, and the exchange of carbon between the atmosphere and ocean are also needed.

22. US AMOC Program near term priorities (con’t): 5. Further effort needs to be directed toward understanding AMOC variability mechanisms and the model dependencies of these variability mechanisms. To address this issue, a detailed comparison study for the AMOC mechanisms should be coordinated among modeling groups. A focused effort is also needed to develop a synthesis of existing observations, including synthesis of proxy data, to discriminate various model-based proposed mechanisms against the observational data. 6. The meridional heat transport (MHT) carried by the AMOC provides the main connection to the climate system. Therefore it is important to explore AMOC and MHT relationships in various models (forward, assimilation, non-eddy-resolving, eddy-resolving) in comparison with observational data being generated by the program, to understand the reasons for differences, or biases, in the relationship between model AMOC intensity and MHT in available models. 7. In coordination with the near-term prediction experiments being conducted by modeling centers for the IPCC AR5, an inter-comparison study should be performed to investigate the robustness of AMOC predictions among simulations using various models. These efforts should seek collaboration with the U.S. CLIVAR Decadal Predictability Working Group as well as the International CLIVAR Working Group on Ocean Model Development and Global Synthesis and Observational Panel.

23. Steps We are Taking to Meet the 7 Near-Term Priorities • The implementation of SAMOC and OSNAP • Initial planning for workshops on: • AMOC "fingerprint“. Developing capabilities for reconstruction of past AMOC variations through the syntheses of various AMOC fingerprints, using both model simulations and observations, includiing Holocene proxy records.  • (ii) AMOC variability mechanisms. Understanding AMOC variability mechanisms and the model dependencies of these mechanisms. A detailed comparison study for the AMOC mechanisms should be coordinated among modeling groups. We are planning next year’s USAMOC meeting for Boulder in May/June, which will be mainly a US PI meeting, and a 2013 joint RAPID/USAMOC international meeting like the 2011 joint meeting in Bristol, UK.

25. Task Team 2 - Model-based observing system assessment • Complete observing system evaluation for subpolar N. Atlantic and S. Atlantic • Quantify impact of deep measurements in the interior North Atlantic (deep ARGO, full depth gliders) • Develop observing systems capable of examining meridonal coherence of the AMOC and associated elements, including forcing functions. • Developing plans for putting judicious posterior error estimates on AMOC strength and variability estimates derived from ocean state estimation models. • Develop coordinated activity (including model development and observing system sensitivity studies) to examine special physics region such as high-latitude sinking regions. • Develop coordinated activity to examine water-mass transformation associated with AMOC and related air-sea interaction using modeling and assimilation systems. • Understand the reasons for differences - or biases- in the relationship between model MOC intensity and MHT in available models, as compared to observations. • Evaluate robustness of AMOC fingerprint in different models and consistency with observed fingerprint.

26. Task Team 3 - Climate Impacts • Understanding the link between AMOC and SST variability: Study and better define the interaction between AMOC and upper ocean properties: SST, salinity, heat content. Understand the mechanisms of AMOC influence on SST and the possible role of upper ocean anomalies on generating (predictable) AMOC variability. There is a need to determine the phase relationships between the overturning circulation, the strength of the horizontal gyres, and the subsequent impact on SST. • Robustness of AMOC/AMV impacts and connecting impact studies to societal needs: While the number of studies on AMOC/AMV impact on world (particularly Northern Hemisphere) climate has increased and broadened, more should be done to establish the robustness of these links, understanding their cause, and comparing them to other long-term changes in climate, forced and natural. It is important to link these impact studies to societal needs and if relevant to actual sectoral decisions (e.g., in water resources, coastal infrastructure, health, and ocean resource management). This will help focus impact research and lead to tangible benefits from AMOC research. • Strengthen links to other related CLIVAR/WCRP activities: This will raise the profile of U.S. AMOC research and help in exchange of important information and stimulate progress. This goal can be achieved through U.S. CLIVAR, the International CLIVAR Atlantic Implementation Panel, and through communication with individual program committees, nationally and internationally.

27. Task Team 4 -AMOC Mechanisms and Predictability • Study AMOC and NHT relationships in models (forward, assimilation, eddy- permitting) in comparison with the RAPID data • Inter-comparison of near-term prediction experiments (AR5) to investigate robustness of model simulations • Inter-comparison of hindcast ocean-only and ocean-ice coupled simulations forced with the CORE-II inter-annual data sets to assess the robustness of model simulations under specified forcing • Develop new observations & synthesis of existing observations to discriminate against proposed mechanisms, including synthesis of proxy data • Study impact of model biases, e.g., Gulf Stream and North Atlantic Current paths, on AMOC variability and predictability • Focus studies between modeling groups for AMOC mechanisms • Identify “best” initialization practices for decadal prediction simulations • Investigate impacts of high resolution (0.1°) on AMOC variability • Identify standard metrics (CLIVAR DVWG?)

28. AMOC 2010 Annual Report

29. Red lines: Boundary monitoring partially implemented. The two red lines are (i) the German Labrador Sea Exit array, which would need to be extended both to near-surface and inshore on the shelf, and (ii) the Ellett Line, which needs improved temporal and spatial measurement density. O-SNAP OSNAP design elements Green line: Site of past boundary monitoring: not presently in the water. The green line is the location of the UK DWBC and French EGC arrays, in the water between 2004 and 2008. Some engineering development is required to enable robust shelf monitoring here. Proposed seaward termination of this line is the planned OOI Irminger Sea Global-Scale Node (GSN) at 60°N, 39°W. Blue line: Approximate location of a possible Mid-Atlantic Ridge array. Yellow lines: Ocean regions to be monitored by “soft” arrays, comprising of a mixture of gliders, floats, possibly deep T/S moorings, BPRs and bottom current meters. The observing design for the interior is currently being studied to assess the mix of instrumentation that can most efficiently accomplish the needed spatial and temporal coverage.

30. AMOC Program Lead P.I.’s (40 funded projects) Molly Baringer (NOAA.AOML) Amy Bower (WHOI) James Carton (U. Maryland) Ping Chang (Texas A&M) Ruth Curry (WHOI) Tom Delworth (GFDL) Kathleen Donohue (URI) Sirpa Hakkinen (NASA/GSFC) George Halliwell (NOAA/AOML) Gordon Hamilton (U. Miami) Bill Johns (U. Miami) Terry Joyce (WHOI)   Igor Kamenkovich (U. Miami) Kathy Kelly (U. Washington) Craig Lee (U. Washington) Tong Lee (JPL) Jonathan Lilly (NWRA) Timothy Liu (JPL) Susan Lozier (Duke) Jay McCreary (SOEST/IPRC) Vikram Mehta  (CRCES) Chris Meinen (NOAA/AOML) Peter Minnett (U. Miami) Peter Rhines (U. Washington) Uwe Send (Scripps)   C.K. Shum (OSU)    Fiamma Straneo (WHOI) John Toole (WHOI) Josh Willis (JPL)  Carl Wunsch (MIT) Xiao-Hai Yan (U. Delaware) Jiayan Yang (WHOI) Gokhan Danabasoglu (NCAR) Mike McPhaden (NOAA/PMEL) Young-Oh Kwon (WHOI) Patrick Heimback (MIT)   Shenfu Dong (NOAA/AOML) Yochanon Kushnir (LDEO) Rong Zhang (GFDL)