manfredi manizza sio/ucsd [email protected] testing ocean biogeochemical models with atmospheric...
TRANSCRIPT
Manfredi ManizzaSIO/UCSD
Testing ocean biogeochemical models with atmospheric observations of Oxygen and
Argon in the Southern Hemisphere
In collaboration with :R. Keeling, M. Mazloff, S. Gille, J. Sprintall (SIO)
C. Nevison (CU Boulder)D. Menemenlis (JPL)
Outline
1) Introduction : oceanic O2 seasonal cycle
2) Ocean Processes, Atm. Observations, and Theory
3) Methods : Theory, New Metrics & Models 4) Results and Conclusions
Seasonal O2 cycle in the upper ocean
Strong coupling between physics andbiogeochemical processes at seasonal time-scale.
Seasonal gain and loss of buoyancy of thethe water column drives O2 vertical distribution
Seasonal changes in O2 vertical distribution impacts seasonal cycle of air-sea fluxes
Air-sea O2 gas flux : seasonal cycle
Thermal Net Comm. Prod. Thermal Ventilation
O2 Flux = 1-Thermal + 2-NCP + 3-Ventilation
Spring - Summer Autumn - Winter
(Nevison et al., 2012; Manizza et al., In Press)
Classic O2 Flux metric : Seasonal Net Outgassing
SNO according to Garcia & Keeling (2001)
SNO(t) = Flux_month(t) - Flux_annual_average
MITgcm 2.8 by 2.8 + eco. model; Manizza et al., Tellus B, 2012, In Press
O2 seasonal cycle in models
Naegler et al., Tellus B, 2007
OCMIP modelsGK 2001 climatology depends on wind and HF products and empirical relations with heat flux.
In GK 2001 wind and heat fluxesuse ECMWF products.
Use of Atmos. Obs. & APO
APO = O2 + 1.1 * CO2 (Severinghaus, 1995)
Atmospheric Potential Oxygen
- O : C = 1.1 ratio in Land Plant photosysnthesis
APO tells us about atmopsheric O2 changes driven by oceanic processes ONLY.
Evaluating ocean bgc models
Naegler et al., Tellus B, 2007
Use of Atmospheric Transport Model (ATM)to translate air-sea fluxes into atmos. [gas]
ATM can introduce an error that canImpact the evaluation of the results
MAIN QUESTION :
Can we try to bypass the use of ATMto test our model and performance onthe seasonal cycle of air-sea fluxes ?
Different ATMs can generate different Results when forced by same fluxes.
Seas. Cycle of APO, Ar & N2 from stations
Cold Bay La Jolla
Cape Grim
Palmer Station
Same phasing (driven by Heat Fluxes)
Difference in seasonal amplitude
Difference in amplitde is due to :1) NCP in warm seasons (outgassing)2) Ventilation in cold seasons (ingassing)
δAr/N2
APO
Scripps Network of Atmospheric Stations
O2 and Ar : same solubilty in seawater
Seas. Cycle of APO, Ar & N2 from stations
Scripps Network of Atmospheric Stations Cold Bay La Jolla
Cape Grim
Palmer Station
δAr/N2
APO
A_(APO) / A_(Ar/N2) = 3-4
How to relate the ratio to oceanicprocesses and test models ?
Focus on the Southern Hemisphere
New metric to test on models
RHS of main equation is equivalent to the slope of the time-integrated fluxesof O2 and Argon in the ocean :
==> NEW METRIC TO DIRECTLY TEST OCEAN MODELS WITHOUT USE OF ATM
= 3-4 (Amplitude of observed ratios)
= 50-60 (Expected value of the new metric)
Ocean bgc models to test
PlankTOM10 : Global configured, 0.5 – 2.0 Horizontal resolution Embedded into NEMO3 + LIM sea-ice model Ecosystem dynamics with 10 PFTs, nuts+Fe+light limitation. O2 and CO2 cyclesAr and N2 fluxes computed according to Jin et al., 2007 (Heat Flx)3 Runs : NCEP, ECMWF, JPL Winds. (Le Quere et al., 2010)
MITgcm : Southern Ocean region (northern limit of 30 S), 1/6 degSea-Ice Model DIC package, PO4, Fe, light limitation O2 and CO2 cycleAr, N2, and O2-Thermal explicit tracers (plus N2O cycle)NCEP forcing , open boundary conditions
Results I – Time- Integrated Fluxes
30-45 S 45 – 55 S 55-80 S 40- 60 S
PlanktOM10 – JPL 65.7 50.3 25.2 50.9
PlanktOM10 – NCEP 61.7 47 34 49.3
PlanktOM10 - ECMWF 61.9 48.9 35 50.4
MITgcm – NoFe 23.6 47.4 106 52.1
MITgcm – Fe
Results II – Cross check with ATM
A_(APO) / A_(Ar/N2) = 3-4
A_(APO) / A_(Ar/N2) = 2.2 – 2.4
Atmospheric Stations
ATM runs (PlankTOM10)
Mismatch still remains due to the use of the ATM with its uncertainty associated with the misrepresentation of atmospheric circulation/physics.
Results III – Metric Latitudinal Variations
F_O2 / F_Ar ~ 50
F_O2(Th) /F_Ar ~ 20-25
Modeled metric (Total O2) varies latitudinally
Modeled metric (Thermal O2 ONLY)does not vary latitudinally
1) Latitudinal variations of metric O2/Ar could be due to different biogeochemical regimes in the Southern Ocean
2) Second metric O2(Th)/Ar can also be used for testingphysical models (NSF-funded project using ECCO solutions)
Conclusions
Possible other applications of this metric : evaluating next generation of IPCC models in their ocean bgc components (project funded by NASA)
Comparison with model results shows the potential of the new metric to evaluate the O2/Ar seasonal cycle of bgc models although the latitudinal factor plays a role.
ATM runs confirm that even if the metric/model agreement is good the amplitude ratios do not agree : back to original problem of the use of ATM....
Can this new metric also be used as indirect test for ECCOsolutions for the thermal-only part (project funded by NSF – Chem. Oc.) ?? Use of O2-Th/Ar ratio, for physics only.
More to do with ECCO & ECCO-3
2 – Using subdomain of SOSE-like set-up to explain the chlorophyll transition from west to east of the Drake Passage (Pending NASA funding)
1 – Interannual variations of O2/Ar in the global ocean (NSF Funded, collaborationwith P. Heimbach)
3 – The impact of future climate warming on the Arctic Ecosystem by using 18 Km regional Arctic Ocean set-up with Darwin model (Pending NFS approval, collaboration with U. Laval, Canada)
4 – The impact of melt ponds on the productivity of Western Arctic Ocean with Subregional region Arctic set-up with Darwin code (Pending NFS approval, collaboration with G. Mitchell (SIO), M. Kahru (SIO), N. Bates (BIOS))
6 – The impact of aeolian Fe supply to the biogeochemistry of the Southern Oceanusing SOSE-like se-tup & Bling (led by Amato Evan at SIO, to be submitted to NSF)
5 – Assessing the Net Community Production of the Arctic Ocean with a future network of atmospheric observations (Pending NSF funding, in collaboration with R. Keeling and Cindy Nevison)