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Regional and Coastal Circulation Modeling: California Current System

Regional and Coastal Circulation Modeling: California Current System. Art Miller Scripps Institution of Oceanography. ECOFOR Workshop Friday Harbor, WA September 7-10, 2012. Regional and Coastal Circulation Modeling: California Current System.

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Regional and Coastal Circulation Modeling: California Current System

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  1. Regional and Coastal Circulation Modeling: California Current System Art Miller Scripps Institution of Oceanography ECOFOR Workshop Friday Harbor, WA September 7-10, 2012

  2. Regional and Coastal Circulation Modeling: California Current System The physical-biological observational datasets motivate many modeling studies with a Unifying Scientific Motivation: How do changes in surface forcing (heat fluxes, wind stresses) alter stratification, upwelling cells and mesoscale eddy statistics and the consequent upward nutrient fluxes and subsequent biological response?

  3. Regional and Coastal Circulation Modeling: California Current System Brief Review of Two Classes of Modeling: 1) Long-term climate hindcasts - Deterministic: Explain observed changes in forced physical structures - Stochastic: Identify relations among variables and input forcing 2) Data assimilation runs - Enhance observations in space and time for process diagnostics - Initialize predictions of eddies and forced components

  4. Regional and Coastal Circulation Modeling: California Current System Brief Review of Two Classes of Modeling: 1) Long-term climate hindcasts - Deterministic: Explain observed changes in forced physical structures - Stochastic: Identify relations among variables and input forcing

  5. Examples of deterministic CCS hindcasting - Curchitser et al. 2005 used a basin-scale hindcast to show that The 2002 cold/fresh anomaly in the northeast Pacific was due to enhanced mixing during the preceding winter in the center of the Alaska gyre - Hermann et al. 2009 used a regional and basin-scale model to isolate remotely from locally drivensea level and current ENSO variability in the CCS and ACS regions - Rykaczewski and Dunne 2010 used a global greenhouse-gas forced run to predict that nitrate and primary production will increase in the CCS due to differences in subduction and age of upwelled waters

  6. Coastal upwelling regions controlled by PDO and NPGO Di Lorenzo et al., GRL, 2008

  7. Model Adjoint backward runs of passive tracer in upwelling zone: Reveal how weaker upwelling winds cause shallower coastal upwelling cell Adjoint runs of passive tracer in upwelling zon: Surface warming causes shallower coastal upwelling cell Negative PDO Phase Positive PDO Phase Surface layer transport into coastal upwelling zone Less nutrient flux to surface Mid-depth (150m) transport into coastal upwelling zone More nutrient flux to surface (Chhak and Di Lorenzo, 2007)

  8. Regional and Coastal Circulation Modeling: California Current System Brief Review of Two Classes of Modeling: 2) Data assimilation runs - Enhance observations in space and time for process diagnostics - Initialize predictions of eddies and predictable forced components

  9. Near-Real-Time CCS Data Assimilation by UC, Santa Cruz Broquet et al. (2009) 7-day fits using mostly surface data with ROMS @ 10km May 2, 2012

  10. SCCOOS 3DVar ROMS model (JPL-UCLA) Yi Chao et al. Surface CODAR is a key variable Daily updates with 1km resolution every 6 hrs 72-hour forecasts executed daily

  11. Data Assimilation “Fits” for April 2002 and 2003 - Strong constraints over 30-day periods allows diagnosis of 4D physical processes that help explain the large disparity in sardine spawning Offshore spawning, fewer eggs: La Nina Nearshore spawning, many eggs: El Nino Data includes: T-S (CalCOFI, Argo, CUFES), SLH (AVISO), SST (AVHRR) Song et al., 2012, JGR

  12. Data Assimilation Model Fits: (1) Quantifying TransportStronger offshore transport and upwelling in 2002Weaker offshore transport and stronger convergence in 2003 Red: Egg densityGrey Scale Arrows: Surface Currents Song et al., 2012, JGR

  13. Data Assimilation Model Fits: (2) QuantifyingUpwelling SourcesAdjoint tracer model (run backwards) for source waters (boxes) of surface ocean2002 source waters in offshore spawning area transported from more productive upwelled surface water near the coast Orange indicates location of water 30 days before arriving in BOX Song et al., 2012, JGR

  14. Data Assimilation Model Fits: (2) QuantifyingUpwelling SourcesAdjoint tracer model (run backwards) for source waters (boxes) of surface ocean2003 source waters in nearshore spawning area transported from more productive deep waterin the central California Current Orange indicates location of water 30 days before arriving in BOX Song et al., 2012

  15. Regional and Coastal Circulation Modeling: California Current System Brief Review of Two Classes of Modeling: 1) Long-term climate hindcasts - Deterministic: Explain observed changes in forced physical structures - Stochastic: Identify relations among variables and input forcing 2) Data assimilation runs - Enhance observations in space and time for process diagnostics - Initialize predictions of eddies and forced components

  16. ECOFOR Workshop Thanks!

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