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U.S. ECoS U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis A project of the NASA Earth System Enterprise Interdisciplinary.

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Presentation on theme: "U.S. ECoS U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis A project of the NASA Earth System Enterprise Interdisciplinary."— Presentation transcript:

1 U.S. ECoS U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis A project of the NASA Earth System Enterprise Interdisciplinary Science Program Ocean Carbon Biogeochemistry Workshop Woods Hole, MA, July 2006

2 U.S. ECoS Science Team Eileen Hofmann (ODU) project oversight, 1D modeling Marjorie Friedrichs (ODU) 1D modeling and data assimilation Chuck McClain (GSFC) project oversight, remote sensing data Sergio Signorini (GSFC) satellite data analysis Antonio Mannino (GSFC) carbon cycling Cindy Lee (SUNY-SB) carbon cycling Jay O’Reilly (NOAA) satellite data analysis Dale Haidvogel (RU) circulation modeling John Wilkin (RU) circulation modeling Katja Fennel (RU) biogeochemical modeling Sybil Seitzinger (RU) food web and nutrient dynamics Jim Yoder (URI) food web and nutrient dynamics Ray Najjar (PSU) oxygen data, climate modeling David Pollard (PSU) climate modeling

3 U.S. ECoS 1. What are the relative carbon inputs to the MAB and SAB from terrestrial run-off and in situ biological processes? 2. What is the fate of DOC input to the continental shelf from estuarine and riverine systems? 3. What are the dominant food web pathways that control carbon cycling and flux in this region? 4. Are there fundamental differences in the manner in which carbon is cycled on the continental shelves of the MAB and SAB? 5. Is the carbon cycle of the MAB and SAB sensitive to climate change? Goal: To develop carbon budgets for the U.S. east coast continental shelf (Mid-Atlantic Bight and South Atlantic Bight) Research Questions:

4 Outline of Presentation Theme 1: Development and implementation of circulation, biogeochemistry, and carbon cycling models for the east coast of the U.S. Theme 2: Data analysis effort – includes historical in situ measurements and satellite-derived data Theme 3: Limited field measurement effort Theme 4: Implementation of data assimilative models Theme 5: Interfacing circulation and biogeochemical models with climate models

5 Theme 1: Circulation and biogeochemical modeling Northeast North American shelf model (NENA)

6 Theme 1 : Circulation and biogeochemical modeling Simulated Salinity 4m August 2002 WOA98 Salinity 10m August North-south gradients agree, simulations produce mesoscale variability Wilkin, Haidvogel

7 Theme 1 : Circulation and biogeochemical modeling Hindcasts 2002 & onward Boundary forcing – cold bias in HyCOM solutions Tides make a difference: Georges Bank, reduced gradients Wilkin, Haidvogel

8 Theme 1 : Circulation and biogeochemical modeling NO 3 Chlorophyll Large detritus Organic matter N2N2 NH 4 NO 3 Water column Sediment Phytoplankton NH 4 Mineralization Uptake Nitrification Grazing Mortality Zooplankton Small detritus Aerobic mineralization Denitrification Fennel et al., in press, GBC No DOM yet

9 Theme 1 : Circulation and biogeochemical modeling Fennel et al., in press, GBC Sources and sinks of nitrogen Role of shelf denitrification

10 Theme 1 : Circulation and biogeochemical modeling Simulated annual air-sea flux of CO 2 Explicit inorganic carbon cycling Positive values indicate uptake by ocean Outer Mid-Atlantic Bight continental shelf is a sink for atmospheric CO 2 No net uptake off NJ due to outgassing during summer from upwelling Fennel

11 MAB atmospheric CO 2 uptake estimates DeGrandpre et al. (2002) ModelModel w/o DNF Total (Mt C yr -1 ) 1.0 ± 0.60.91.62 Inner Shelf (0-20 m) (mol C m -2 yr -1 ) 0.9 ± 0.630.381.1 Mid-shelf (20-50 m) (mol C m -2 yr -1 ) 1.6 ± 1.280.571.2 Outer Shelf (50-200 m) (mol C m -2 yr -1 ) 0.7 ± 0.070.911.2

12 Theme 2 : Satellite and in situ data analyses OC4v4Clark CarderGSM01 Intercomparison of Chlorophyll-a Algorithms: May 14, 2000 O’Reilly, Signorini, McClain First coastal intercom- parison Inner shelf differences

13 In situ productivity measurements Satellite productivity measurements Theme 2 : Satellite and in situ data analyses O’Reilly Phase good, models differ, models too high. SAB tough due to intrusions.

14 Annual PP, mean and ratio to mean O’Reilly

15 Max:min annual PP (1998- 2005) O’Reilly

16 Theme 2 : Satellite and in situ data analyses SAB variability Analyses of forcing functions and chlorophyll (response), 1998-2005 Top- size of North Atlantic Subtropical gyre (chl-based) Middle- Cape Fear River discharge Bottom- Chlorophyll Signorini, McClain

17 Theme 2 : Satellite and in situ data analyses Analyses of forcing functions and response at 3 sites Sea surface height anomaly (green) and NASG size (blue) May reflect seasonal migration of Gulf Stream front— offshore in spring, onshore in fall Signorini, McClain

18 SST trend Chl trend O’Reilly

19 Theme 2 : Satellite and in situ data analyses Analyses of World Ocean Database for study region: focus on MLD and dissolved O 2. Siewert, Najjar

20 Theme 2 : Satellite and in situ data analyses MLD based on ΔT = 0.2°C Siewert, Najjar

21 Theme 2 : Satellite and in situ data analyses MAB outer shelf annual cycles of the oxygen anomaly Siewert, Najjar 0-30 m 60-100 m 30-60 m

22 Theme 2 : Satellite and in situ data analyses MAB Sea-to-air oxygen flux Siewert, Najjar Inner Shelf Slope Outer Shelf Mid-Shelf

23 Themes 1 and 2 : Modeling and satellite analyses Fennel, Wilkin, O’Reilly, Signorini, McClain

24 Themes 1 and 2 : Modeling and satellite analyses Model-data comparisons Fennel, Wilkin, O’Reilly  Model crashes in summer (no tides)

25 Themes 1 and 2 : Modeling and satellite analyses Fennel, Wilkin, O’Reilly

26 Themes 1 and 2 : Modeling and satellite analyses Satellite-derived primary production (PP) using VGPM2 VGPM2 applied to NENA-simulated fields Modeled PP using NENA Fennel, Wilkin, O’Reilly

27 Themes 1 and 2 : Modeling and satellite analyses Model-data comparison Wilkin, O’Reilly

28 Theme 3 : Field measurements ODU cruises - one day, 8 hour cruise, 4 stations NIP – grid of stations, 3-4 day cruises Carbon, nutrients, chl a, pigments, absorb., … Estimate fluxes - model Algorithm development ARCHIVED SAMPLES 2002 to present Chesapeake Bay and adjacent coastal waters – ODU monthly cruises and NASA NIP (Mannino)

29 Theme 3 : Field measurements From cruises in Southern MAB, including lower Chesapeake Bay. 30 Mar – 1 Apr cruise  Spring conditions well mixed except where influenced by rivers. Mannino

30 Theme 3 : DOC & CDOM field measurements From cruises in Southern MAB, including lower Chesapeake Bay. Seasonal algorithms needed. Offset due to net community production of DOC and bleaching from spring to summer. Mannino

31 Themes 2 & 3 : Satellite and field measurements Mannino Aqua-MODIS-based CDOM* *Based on in situ a CDOM and in situ reflectance ratios

32 Themes 2 & 3 : Satellite and field measurements Aqua-MODIS-based DOC (  M) Mannino

33 Theme 4 : Biogeochemical data assimilation Developed a 1-D data assimilative ‘Modeling Testbed’ This framework includes: mixing, advection, diffusion, attenuation, sinking subroutines This framework requires: forcing fields: T, MLD, PAR, w, Kv boundary and initial conditions ecosystem model subroutine adjoint of ecosystem model subroutine biogeochemical data for evaluation/assimilation This framework will be used to: Perform parameter sensitivity/optimization analyses Test new parameterizations and formulations Compare multiple models at a single site Compare model performance at various sites

34 Theme 4 : Biogeochemical data assimilation 5 m 55 m115 m 3D 1D Comparison of simulated nitrate from 1D and 3D models at a site on MAB continental shelf Friedrichs

35 Theme 4 : Biogeochemical data assimilation 7 (of 18) parameters can be independently estimated Chl2C_m PhyIS PhyMR Vp0 ZooGR CoagR Sremin Identical Twin Numerical Experiments - Use SeaWiFS and in situ data Friedrichs

36 DOM modeling Jean-Noel Druon

37 1-D MAB results

38 Theme 5 : Climate Modeling How will coastal regions respond to climate change, and what are the feedbacks on the carbon cycle? Force the circulation/biogeochemical model with climate change scenarios: Present day scenario: 1980-2000 100 years later scenario: 2080-2100 Using RegCM3

39 Theme 5 : Climate Modeling Simulated precipitation Observed precipitation Pollard, Najjar Winter Summer

40 Theme 5 : Climate Modeling Six-hourly precipitation fields from a 10-year simulation using present conditions Pollard, Najjar

41 Summary U.S. ECoS Goal: To develop carbon budgets for the U.S. east coast continental shelf waters Circulation model shows observed features for SSS, SST. More evaluation (e.g., MLD) needed. Tides, BCs make a difference. Biogeochemical model captures chl variability. Chl too low in gyre. More tracer evaluation needed (e.g., oxygen) Denitrification significantly influences air-sea carbon flux in model. MAB air-sea flux agrees with observations. Satellite productivity algorithms give MAB results close to observed. Issues in SAB. Interannual variability and long-term trends in chl, PP, SST.

42 Summary U.S. ECoS Goal: To develop carbon budgets for the U.S. east coast continental shelf waters Riverine & gyre influences on chl seen in SAB. Field data have allowed development of CDOM and DOC products for MAB Model and satellite productivity issues need resolution. 1D models and data allow parameters for 3D models to be constrained. DOM poised to be included in 3D model. Regional climate model set up and ready for climate change runs

43 Summary U.S. ECoS Goal: To develop carbon budgets for the U.S. east coast continental shelf waters No component can do this by itself— synthesis approach Requires modeling effort coupled with satellite and in situ data analysis Ongoing effort—observationalists and modelers working together

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