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Intro to Biogeochemical Modeling Ocean & Coupled Keith Lindsay, NCAR/NESL/CGD NCAR is sponsored by the NaEonal Science FoundaEon

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Page 1: Intro&to&Biogeochemical&Modeling& Ocean&&&Coupled&Intro&to&Biogeochemical&Modeling& Ocean&&&Coupled& Keith&Lindsay,&NCAR/NESL/CGD& NCARis&sponsored&by&the&Naonal&Science&Foundaon&

Intro  to  Biogeochemical  Modeling  Ocean  &  Coupled  

Keith  Lindsay,  NCAR/NESL/CGD  

NCAR  is  sponsored  by  the  NaEonal  Science  FoundaEon  

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Lecture  Outline  

1)  Large  Scale  Ocean  Biogeochemical  Features  2)  Techniques  for  Modeling  Biological  ProducEvity  3)  Skill  Assessment  4)  Global  Carbon  Cycle  5)  Summary  

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NO3  (a  nutrient),  O2  (dissolved  gas)  Along  Pacific  Transect  

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DIC  (~CO2)  Along  Same  Pacific  Transect  

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Takahashi  Air-­‐Sea  CO2  Gas  Flux  

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Primary  Processes  Governing  DistribuEon  of  Nutrients,  O2,  Carbon,  etc.  

•  Biological  ProducEvity  in  EuphoEc  Zone  –  Consumes  Nutrients  &  Inorganic  Carbon  –  Produces  Organic  MaZer  &  O2  

•  Export  of  Organic  MaZer  out  of  EuphoEc  Zone  –  Sinking  ParEcles  (e.g.  detritus,  CaCO3  shells,  …)  –  CirculaEon  of  Suspended  MaZer  

•  RemineralizaEon  of  Organic  MaZer  –  ‘reverse’  of  producEvity,  consumes  O2  

•  General  CirculaEon  – AdvecEve  Transport  –  Lateral  &  VerEcal  Mixing  

•  Temperature  Dependent  Air-­‐Sea  Gas  Exchange  

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Other  Processes,  Smaller  Global  Impact,  Locally  Significant  

•  Atmospheric  Nutrient  DeposiEon  – Fe,  N,  P,  …  

•  Sedimentary  Burial  •  Riverine  Inputs  

•  Nitrogen  FixaEon  – Conversion  of  dissolved  N2  gas  into  NH4  

•  DenitrificaEon  – ConsumpEon  of  NO3  during  remineralizaEon  

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Large  Scale  Ocean  Carbon  Cycle  

DIC  Diss.  Inorganic    C    DOC  Diss.  Organic  C    PIC  Part.  Inorganic  C    POC  Part.  Organic  C    Figure  courtesy  PMEL  

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What  is  an  NPZD  model?  

N  Nutrient      nitrate,  ammonium,      phosphate,  silicate,  iron,  etc.  

P  Phytoplankton      photosynthesizers  

Z  Zooplankton      grazers  

D  Detritus    Canonical  Example  Fasham,  Ducklow,  McKelvie,  Journal  of  Marine  Research,  Vol.  48,  pp.  591-­‐639,  1990.    Many  more  variaEons  are  used…  

Fasham  model  diagram  from  www.gotm.net  

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How  do  you  esEmate  parameters  and  funcEonal  forms?  

•  Laboratory  &  field  incubaEons  – P-­‐I  curves  – Nutrient  uptake  curves  

•  Tune/OpEmize  against  field  data  •  Previous  Models  

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Plankton  FuncEonal  Types  (PFTs)  

•  Categorize  plankton  species  by  how  they  funcEon  and  use  representaEve  types/groups  

•  Example  definiEon  from  Le  Quéré  et  al.,  Global  Change  Biology,  Vol.  11,  pp.  2016-­‐2040,  2005.  – Explicit  biogeochemical  role  – Biomass  and  producEvity  controlled  by  disEnct  physiological,  environmental,  or  nutrient  requirements  

– Behavior  has  disEnct  effect  on  other  PFTs  – QuanEtaEve  importance  in  some  region  of  the  ocean  

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Skill  &  Portability  in  12  Different  NPZD  models  Friedrichs  et  al.,  JGR-­‐Oceans,  2007.  

(b)  Simple  models  do  just  as  well  as  more  complex  models  when  tuned  for  specific  sites.  (c)  More  complex  models  do  beZer  at  mulEple  sites  with  single  parameter  sets.  (d)  More  complex  models  perform  beZer  at  different  sites  when  tuned  for  one  site.  

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Doney  et  al.    (J.  Mar.  Systems,  2009)  

CCSM  BEC  model  

Moore,  Doney,  Lindsay,  Global  Biogeochemical  Cycles,  2004.    

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Primary  Features  of  CESM1  BEC  Model  

•  Nutrients:  N,  P,  Si,  Fe  •  4  Plankton  FuncEonal  Groups  –  3  Autotrophs,  1  Grazer  –  Implicit  coccolithophores  –  24  tracers  in  CESM  1.0,  1.1  –  27  tracers  in  CESM  1.2  

•  Fixed  C:N:P  raEos  in  plankton  •  Variable  Fe:C,  Si:C,  Chl:C  raEos  

•  Numerous  enhancements  introduced  in  CESM  1.2  –  Reduce  excessively  large  OMZ  bias  

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Known  Gaps  in  Ocean  BGC  in  CESM1-­‐(BGC)  

•  CalcificaEon  &  CaCO3  remineralizaEon  rates  are  independent  of  CO3  saturaEon  state  

•  No  riverine  inputs  of  BGC  tracers  – Prescribed  datasets  introduced  in  1.2  

•  No  sediment  model  – Loss  to  sediments  introduced  in  1.2  

•  No  treatment  of  BGC  in  sea-­‐ice  

•  Focus  in  on  lower  trophic  levels  

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Model  ValidaEon:  Examples  of  Data  Sets  

•  Macronutrients  (PO4,  NO3,  SiO3)  and  O2  from  World  Ocean  Atlas  

•  DIC,  ALK  from  GLODAP  Analysis  •  pCO2  and  CO2  Flux  assembled  by  Takahashi  •  Surface  Chl  measured  by  satellite  •  ProducEvity  esEmated  from  satellite  •  JGOFS  study  sites  •  HOTS  &  BATS  Emeseries  

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Air-­‐sea  CO2  Flux  

Doney  et  al.  (Deep-­‐Sea  Res.  II,  2009)  

model  

observaEons  

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Satellite  Ocean  Color  Comparison  

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Known  Challenges  

•  OpEmize  BGC  model  parameters  – FuncEonal  group  approach  increases  uncertainty  of  parameters  (i.e.  mulEple  species,  with  different  characterisEcs,  are  clumped  together)  

– Don’t  want  to  overtune  too  much  to  compensate  for  biases  in  physical  model  

•  Given  BGC  model  parameters  and  physical  circulaEon,  generate  balanced  BGC  state  – Need  to  deal  w/  diurnal  to  millenial  Emescales  – Using  Newton-­‐Krylov  for  this  is  a  work  in  progress  

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Large  Scale  Global  Carbon  Cycle  

Figure  courtesy  PMEL  

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Land  &  Ocean  CO2  Fluxes  from  CESM1-­‐BGC  

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Same  plot  with  Fixed  ATM  CO2  

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CO2  Seasonal  Cycle  

Lindsay  et  al.,  2012,  J  Climate,  submiZed  

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CO2  Response  to  ENSO  

Mauna  Loa,  Hawaii   Point  Barrow,  Alaska  

Lindsay  et  al.,  2012,  J  Climate,  submiZed  

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Land  &  Ocean  Uptake  of  Fossil  Fuel  Emissions  

Friedlingstein  et  al,  J.  Climate,  2006  

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Impact  of  Climate  Change  on  this  Uptake  

Friedlingstein  et  al,  J.  Climate,  2006  

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Summary  •  Large  scale  ocean  biogeochemical  features  are  determined  

by  handful  of  processes  •  ‘Perfect’  ecosystem  model  doesn’t  exist,  many  

simplificaEons  need  to  be  made.  Improving  models  is  ongoing  research.  ScienEfic  quesEons  guide  this  process.  

•  Atmospheric  CO2  couples  land  and  ocean  carbon  cycles,  explaining  some  correlaEon.  Climate  variability  does  as  well.  Atmospheric  CO2  observaEons  are  valuable  constraint  on  models.  

•  Land  &  ocean  uptake  of  anthropogenic  CO2,  parEcularly  sensiEvity  to  climate  change  is  ongoing  research.  Modern  models  show  considerable  spread  for  land  results.  

•  PracEcal  Notes  are  available  and  will  be  presented  in  Land/BGC  breakout