Enhancement of primary production at greater resolved scales Results from the Greenseas project

1. Enhancement of primary production at greater resolved scales Results from the Greenseas project 45th International Liège Colloquium 13 – 17 May 2013 Liège, Belgium W McKiver, M Vichi, T Lovato, A Storto, S Masina

2. The greenseas project 9 partners, led by NERSC, Bergen GreenSeasemploys a combinationofobservation data, numericalsimulations and a cross-disciplinarysynthesistodevelop a high quality, harmonized and standardized plankton and plankton ecology long time-series, data inventory and information service

3. Questions and aims • Global plankton data are sparse and the usageofbiogeochemical data formodelassessmentraisesseveralquestions: • Do in situ data have enough signal to allow extrapolation? • What are the limits of model assessment given the available data? • Are rates and process measurements more evanescent than stock data? • Can we efficiently use mesoscale features from satellite products? • On the modelling side, advances in computationaltechnologyhas led to more complicatedmodels at greaterspatial and temporalresolution. More details can beproducedbut the production costs are high. • Herewe focus on a directcomparisonbetween a OBGCM used at twodifferentresolutions: • LO-RES –2degreeresolution • HI-RES –¼degreeresolution

4. The Model: PELAGOS • PELAgicBiogeochemistryfor Global OceanSimulation (Vichi et al., 2007a,b; Vichi and Masina 2009) • Global oceanimplementationof a couplingbetweem: • BiogeochemicalFluxModel (BFM): Biomassbased continuum descriptionoflower trophic levelsthrough a set ofdifferentialequationsthatsolves the dynamicalstoichiometryoffluxesofC, N, P, Si and Fe amongselectedbiologicalfunctionalgroups • NEMO OceanModel (v3.4): Primitive equationsformomentum, temperature, salinitywith LIM2 Seaicemodel, (Madec et al., 1998) • Modelisimplemented on ORCA grid at both2degree and ¼degreeresolutionwith the samebiogeochemicalparameterizations

5. Biogeochemical Flux Model (BFM) http://bfm-community.eu • Stoichiometric biomass-basedmodel, with a unifiedtheorybuilt on the conceptofChemicalFunctionalFamilies • Allowstodescribelower trophic levelsbyimplementinganynumberoffunctionalgroups and constituents • Standard pelagicsetting: • C,N,P,Si,Fe,O,Alk • 3phytoplanktongroups • 3zooplanktongroups • 1bacterioplankton • Open source code online: • http://bfm-community.eu

6. Biogeochemical Flux Model (BFM) http://bfm-community.eu Some theory: Vichi et al. 2007 (JMS)

7. ORCA2 vs ORCA025 • HorizontalGrid182 x 149 1442 x 1021 • Vertical Levels31 50 • TimeStep96 mins 18 mins • BFM: 57 Pelagic state variableswith full diagnostics • Largecomputingpower ~ 900 cores. Largememoryrequirementsfor HI-RES, 850 GB • Largestoragerequirement, approx 18 GB output pertimeunit

8. Experimental setup • Simulationsperformed at ORCA2 (LO-RES) and ORCA025 (HI-RES)resolutionwithsameatmospheric forcings from ERA-interim (on-line interpolation) • LO-RES modelrunfor 30 years • HI-RES physicsrunfor4years, thencoupledto the biogeochemicalmodelusing the biogeochemicalvariablesinterpolatedfrom the LO-RES experimenttoinitialize. January and Juneinitializations. • Thenboth LO- and HI-RES models are runfor6monthsstoringevery8days • Ourresultswillmainly focus on the Atlantic and SouthernOceanwhichis are well-knownregionswithlargemodelbiases • Presentfirst the physicaldrivers and thenexaminetheir impact on the marine biogeochemicalsystem (and relatedproblems!)

9. Physical Drivers: Mean EKE/Wind Stress • Momentumis put into the system through the wind-stress. • Boththe LO-RES and HI-REScasesconverts a certainamountofthisintokineticenergy. • Herewe show the ratioof the total averageTurbulentKinetic Energy and the Wind Stress forboth the LO-RES (blue) and HI-RES (red) experiments. • The HI-RESexperimenthasmuchhigher TKE.

10. Ratio of Vertical to Horizontal motion LO-RES HI-RES • As a qualitative indicatorof the relative importanceof the verticalmotionswe show the averagedvertical-to-horizontalvelocityratios. • Overallverticalmotions are muchstronger in HI-RES case as the mesoscaleisresolved

11. Mixed Layer Depth: Seasonal cycle Tropical Atlantic North Atlantic Southern Ocean • LO-RES ---de BoyerMontegut et al. 2004 --- • HI-RES ---Hosoda et al (Argo) 2010 --- • MLD ismuchdeeper in the HI-RES • Particularlystrong difference in the SouthernOcean • Overallthe physicsisverydifferent in the twocases, howdoesthis impact the biology?

12. Evolutionafter3months (March) LO-RES (initialfor HR) HI-RES Seawifs LO-RES

13. SST [degC] (March)

14. Net PhytoplanktonGrowth Rate [mg C/m3/d] (March) Overall enhancement of coastal production

15. SurfaceChl [mg/m3] (March) Overall enhancement of coastal chl

16. Temperature section [degC] (March) MLD

17. Net production [mg C/m3/d] and Chlorophyll [mg/m3] Note the change of units! This decoupling is a consequence of variable chl:C!

18. Example timeseries (summertowinter) on the APF • LO-RES –2degHI-RES –¼deg

19. Ironcycle [umol/m3] isnotbalanced at Hi-Resscales Scale is 5 times larger!

20. Summary • Performedsimulations at twodifferentresolutions • Clearlyhigherresolutionenhancesthe mesoscalefeatureshavingan impact on the marine plankton • Enhancedgrowth in coastalregions, whilegrowthis first enhanced and thensuppressed in the SouthernOcean • Notallparameterizations are resolutiondependentasbiogeochemicalfeaturesget (visually) better (more physics, more details). However, “loophole” parameterizationsas in the Fe case are more dangerousas remineralization parameters are scale dependent • Thisis just the modelling side. Assessmentphasehasstarted. • Chainofrestarts: whathappens in the HI-RES beyond the adjustmentphase? Isthereconvergence? • Howmuchresolvedscales are needed? Can some intermediate resolutionaddress the costissuewhileprovidingbetterphysics? Future work

21. Thanks