Climate forcing of C. finmarchicus populations of the North Atlantic WHOI PIs: D. McGillicuddy and P. Wiebe UConn PI: A. Bucklin Rutgers PIs: D. Haidvogel.

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Presentation transcript:

Climate forcing of C. finmarchicus populations of the North Atlantic WHOI PIs: D. McGillicuddy and P. Wiebe UConn PI: A. Bucklin Rutgers PIs: D. Haidvogel and J. Levin

Project Objectives Determine the mechanisms that control the abundance and distribution of C. Finmarchicus in the North Atlantic Begin by exploring the seasonal cycles of animal abundance and the circulation Use genetic data to estimate the rates of population exchange between gyres, and compare with model estimates Investigate interannual to decadal variability (compare high- NAO and low-NAO states) Produce multi-decadal hindcast (1950s-present)

Three-Gyre Conceptual Model for C. Finmarchicus Bucklin et al., 2000; Wiebe, 2001 Null hypothesis: C. Finmarchicus populations in the three gyres are independent and self-sustaining

Datasets C. Finmarchicus: CPR data (C 5 and C 6, surface) C. Finmarchicus: Other GLOBEC programs Ocean color (SeaWIFS; proxy for food availability) Various datasets to force the circulation model (SODA, CORE-2, etc.) C. Finmarchicus: Genetic analysis

Data from the Continuous Plankton Recorder Planque et al. (1997) Feb Mar Apr May Jun Jul Aug Sep Climatological C. finmarchicus distributions

Models and Methods North Atlantic implementations of ROMS - Non-eddy-resolving (~40 km)  Adjoint inversions - Eddy-resolving (~10 km)  Gangopadhyay et al. C. Finmarchicus population dynamics model - 13-stage life cycle model (egg – adult) - diapause cued by food availability / photoperiod Adjoint data assimilation - adjust control paramters to best fit Calanus data - “best” inversion used to infer mechanisms, exchange rates Quantitative skill assessment - cross-validation (run inversions excluding 1 mo of CPR)

F i : molting flux F i (T,Chl) computed (Campbell et al. 2001) R: sources of N 3 Inferred (monthly) μ i : mortality Inferred (monthly) C i off-bank Inferred (initial conditions) N 3 N 4 N 5 N 6 C 1 C 2 C 3 C 4 C 5 C 6 R μ N4 μ N5 μ N6 μ C1 μ C2 μ C3 μ C4 μ C5 μ C6 Li, X., McGillicuddy, D.J., Durbin, E.G., and P.H. Wiebe, Deep-Sea Research II, 53 (23-24), , doi: /j.dsr C. Finmarchicus Model (Phase IVB version; to be extended to full 13-stage model in this project)

Adjoint Assimilation Procedure [Control parameter: spatially variable (3D), stage-specific mortality rate]

Underway: Climatological North Atlantic ROMS simulation Grid has 20 to 170 km resolution, region of interest has resolution within 40 km. Time step – half hour. Northern boundary at Bering Strait. Southern boundary curved at 20 to 50 deg South. Southern BC – radiation with nudging for 3d fields. Chapman for SSH, Flather – for batoropic velocity. Northern BC – closed. Initialized with Levitus 05 January climatology for T and S, and SODA January mean for velocity and SSH. Southern BC – Levitus 05 monthly climatology for TS, and SODA monthly mean for velocity and SSH. Atmospheric forcing from CORE corrected normal year analysis (obtained from fields). River input is from CORE; it is imposed as surface fresh water input. Current run – 2 years. Nudging towards T and S climatology is applied. Strong nudging of T at surface until sea ice sub-model is turned on; weak nudging of salinity. Paul Budgell (2008)

Free Surface Elevation and Velocity (2 yrs)

Surface Velocity

Temperature and Salinity (December, 250 m)

Temperature and Salinity (December, 1000 m)

Temperature cross-section (December)

Salinity cross-section (December)

Next Objectives Synthesize GLOBEC data - Stage resolution - Vertical distribution Integrate Calanus model with ROMS Test Inversion - Low-res ROMS, seasonal forcing - CPR C 6 data - Spatially variable source/sink (molting flux / mortality) Use the genetic data to estimate the rate of population exchange between gyres Extensions to ROMS - Turn on sea ice sub-model in low-res version - Develop hi-res version with COSINE sub-model  Avijit