Conclusions The quantitative dynamical fitting procedure has been tested successfully for CalCOFI hydrographic data by adjusting temperature and salinity initial conditions for July 1997 (68% error variance reduction) and February 1998 (36% error variance reduction). The alongshore current reversal observed in the Southern California Bight has been qualitatively simulated using observed initial conditions from February 1998, evolving boundary conditions from NCEP's ocean analysis, and atmospheric forcing from NCEP's atmospheric analysis. The 3D NPZD ecosystem model has been qualitatively tested for February 1998 using frozen physical fields to obtain a balanced initial state and subsequent evolving physical fields as 3D time-dependent forcing. Ongoing Work · Further develop a qualitative and quantitative procedure for fitting observed 3D biological fields (SeaWiFS chl-a and CalCOFI nitrate, chl-a and zooplankton) for February · Examine the dynamical and ecosystem balances that hold in the model’'s evolving fields (reconstructed by the inverse) and assess their consistency with other model studies. · Forecast independent data in subsequent CalCOFI hydrographic and ADCP surveys, TOPEX datasets and SeaWiFS observations to determine predictive timescales in the various regions of the Southern California Bight. Publications Di Lorenzo, E., A.J. Miller, D.J. Neilson, B.D. Cornuelle, and J.R. Moisan, 2004: Modeling observed California Current mesoscale eddies and the ecosystem response, International Journal of Remote Sensing, 25 (7-8), Miller, A.J., E. Di Lorenzo, D.J. Neilson, B. Cornuelle, and J.R. Moisan, 2000: Modeling CalCOFI observations during El Nino: Fitting physics and biology. CalCOFI Reports, 41, Modeling the biological response to the eddy-resolved circulation in the California Current Emanuele Di Lorenzo GaTech, Atlanta, GA Arthur J. Miller SIO, La Jolla, CA John R. Moisan NASA GSFC/Wallops Bruce D. Cornuelle SIO, La Jolla, CA Douglas J. Neilson SIO, La Jolla, CA Abstract Over fifty years of hydrographic and other physical and biological data have been collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI) in the California Current System. The coarse sampling (70 km), however, has precluded definitive study of the dynamics controlling eddies in the system. In recent years, additional data from ADCP upper ocean currents, satellite altimetry of sea level, ocean color by SeaWiFS and other variables has been contemporaneously sampled. This study is aimed at using these data to test model dynamics, understand ecosystem processes and eventually to assess predictive timescales. Model skill is quantified by the model-data mismatch (rms error) during the fitting interval. The physical fields are used to drive a 3D NPZD-type model constrained by sub-surface chlorophyll-a (Chla), nitrate and bulk zooplankton from CalCOFI and surface Chl-a from SeaWiFS. February 98 : Model Velocity [cm/sec] Poleward Coastal Current April 98 : Model Velocity [cm/sec] Southward Coastal Current Test Case: Fit of February 1998 El Nino Cruise The circulation pattern observed during the CalCOFI cruise was characterized by a strong coastal northward current. The low-salinity core of the California Current was located unusually far offshore. Two month later in the April 98 cruise the jet of the California Current was found inshore and the coastal countercurrent was absent and replaced by a southward flow. Here we present a model simulation in this same period. After inverting for the initial condition for the month of February 98 we integrated the model forward and forced it using weekly wind stresses from the Leetmaa Ocean Analysis (from CDC/NOAA). Qualitatively the model captured the changes in the current as shown in the figure In April there was a well developed southward current. CalCOFI Chl-a (in situ obs.) How do we fit the physical data? (inverse method strategy) 1. Adjust only initial state, boundary conditions and physical forcing 2. Minimize weighted misfits and correction to initial state 3. Reduce size of problem by limiting corrections to largest/eddy space scales using basis functions 4. Determine the sensitivity matrix with set of perturbation runs of the non-linear model, invert it assuming linearity, test degree of non-linearity and repeat process iteratively NPZD Ecosystem Model * Phytoplankton * Zooplankton * Ammonia * Nitrate * Small Detritus * Large Detritus * Chlorophyll Source/sink coupling terms computed following Fasham et al. strategy. Test model with SeaWiFS chlorophyll, and sub- surface CalCOFI data (chlorophyll, nitrate, bulk/acoustic zooplankton). Choose/fit parameters to allow a steady-state ecosystem response to frozen physical forcing. Disallow periodic or aperiodic ecosystem behavior. Allow ecosystem and physical model to evolve from that initial to qualitative test strategy. Scientific Issues Can a dynamical eddy-resolving ocean model fit a non-synoptic 3-week survey of all the available physical data? If so, then the resulting time-dependent 3D reconstruction of the evolving flow fields can be used in three ways. * Diagnose eddy dynamics - baroclinic/barotropic instabilities - coastline/topographic influences - atmospheric forcing effects * Determine predictive timescales - deep ocean eddies - shelf/slope eddies - atmospheric-forced surface fields * Drive ecosystem response - fit part of biology controlled by physics - diagnose ecosystem balances - determine ecosystem predictive timescales Data Sources Our effort has relied heavily on the fifty year CalCOFI data record. In addition, datasets collected within the last ten years: ADCP, Topex and Drifters, are also been utilized. For our July 1997 test case, we plotted these datasets over our model domain as shown here with the model’s ETOPO5-derived bathymetry. CalCOFI Dynamic Height (obs.) SeaWiFS Chl-a (satellite obs.)Chl-a (model average) February 1998 Fit The physical field reconstruction of the Feb 98 CalCOFI hydrographic data are here used to drive the 3D ecosystem model. Day 1 corresponds to the equilibrated (steady state) biology after 45 days of frozen physical field forcing. Day 15 corresponds to the evolving physical fields driving the ecosystem model from Day 1 initial conditions. TemperaturePhytoplankton Zooplankton TemperaturePhytoplankton Zooplankton DAY 15 (Feb ) DAY 1 (23 Jan 1998) SeaWiFS Chla Average Fields (23 Jan 1998 – 14 Feb 1998) SeaWiFS Chla Free-Surface (model average)