Ocean dynamics and marine ecosystems: Simula3ng the impact of climate change

Transcription

1 Ecole Théma3que La Rochelle Juin Climate, Oceans and Ecosystems Ocean dynamics and marine ecosystems: Simula3ng the impact of climate change Laurent Bopp IPSL / LSCE, CNRS CEA UVSQ, Gif sur YveJe Laurent Bopp 15 Juin 2012 Marine Ecosystems

2 Ocean physics / chemistry over the past 100y Warming of the ocean (+0.8 C since 1900 in surface waters) changes in ocean dynamics more stra3fica3on? Surface Ocean Temperature ( C) Surface Ocean ph more acidic ( ph : 0.1 over the last 50y) 2

3 Ocean physics / chemistry over the past 100y 3 IPCC, 2007

4 Poten3al impacts on marine ecosystems? Light & Nutrient Marine Produc3vity Phytoplankton / Zooplankton Carbon Cycle Other cycles (N 2 O, DMS, ) Ocean Dynamics 4 Marine Ecosystems

5 Poten3al impacts on marine ecosystems? Light & Nutrient Marine Produc3vity Phytoplankton / Zooplankton Carbon Cycle Other cycles (N 2 O, DMS, ) Ocean Dynamics 5 Marine Ecosystems Models used to represent lower trophic levels Model evalua3on Impact of climate change on marine primary produc3vity Towards upper trophic levels

6 Models used to represent lower trophic levels

7 Models used to represent lower trophic levels Geochemical PO 4 3- One equa3on to represent all marine ecosystems: Export Produc3on = f(temp). f(light). PO 42 / Ks+PO 4 Integrated in General Circula3on Models Particles Euphotic Layer ( m) HAMOCC, Maier Reimer et al. 7

8 Models used to represent lower trophic levels Geochemical NPZD PO 4 3- PO 4 3- Phyto Dissolved Zoo Particles Particles Euphotic Layer ( m) Fasham et al. 8

9 Models used to represent lower trophic levels Geochemical NPZD Temperature / Growth Rate (Eppley, 1972) PO 4 3- PO 4 3- Phyto Particles Dissolved Particles Zoo Growth Rate Euphotic Layer ( m) Fasham et al. Température ( C) 9

10 Models used to represent lower trophic levels Geochemical NPZD Dynamical Green Ocean PO 4 3- PO 4 3- Phyto NH 4 + NO 3 - PO 4 3- Si Iron Phyto 1 Phyto 2,. Dissolved Zoo D.O.M MicroZoo Meso Zoo Particles Particles P.O.M Euphotic Layer ( m) Small Ones Big Ones 10 (Le Quéré et al.)

11 Models used to represent lower trophic levels PISCES Model (Aumont et Bopp, 2006) 24 state variables 5 nuutrients: NH 4, NO 3, PO 4, Fe, Si Input of nutrients: Rivers (all) Atmosphere (Fe, Si, P, N) Sediment (Fe) 2 Phytoplankton 2 Zooplankton: Diatoms / Nano Pico Micro / Meso Zoo Redfield for C:N:P Si/C, Fe/C, & Chl/C variables

12 Models used to represent lower trophic levels PISCES Model PISCES in NEMO (Madec 2008) Global Configura3on (ORCA 2 ORCA 0.5) Regional Configura3ons (e.g. MED12) MBG component of climate models IPSL CNRM (MétéoFrance)

13 Models used to represent lower trophic levels Surface Chlorophyll (mg/m3) simulated by NEMO PISCES (0.5 ) for year 2007

14 Model Evalua3on Surface Chlorophyll (mg/m3) SeaWifs ( ) Model 14

15 Model Evalua3on PHYSAT (Alvain et al.) 2 phytoplankton groups: diatoms picophytoplankton PISCES 15

16 Model Evalua3on

17 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons (Schneider et al. 2008) Centennial Variability of Produc3vity / Sediment Core Data (Mariop et al. 2012)

18 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons Strong link between PP anomalies & climate variability (Schneider et al. 2008) (Behrenfeld et al. 2006)

19 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons (Schneider et al. 2008) 1). PP / Stra3fica3on rela3onship 2). Correla3ons local PP vs. Stra3fica3on index Schneider et al

20 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons Centennial Variability of Produc3vity / Sediment Core Data (Mariop et al. 2012) NAtl (kyr BP) (Bond and Lop, 1995)

21 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons Centennial Variability of Produc3vity / Sediment Core Data ~40 carojes : modifica3ons de la produc3vité (Mariop et al. 2012) 21

22 Model Evalua3on Interannual Variability of Produc3vity / Satellite Observa3ons Centennial Variability of Produc3vity / Sediment Core Data Data / Model comparison IPSL CM4 / PISCES (HEINRICH LGM) (Mariop et al. 2012) 22

23 Climate Change impact on Marine Produc3vity

24 Climate Change impact on Marine Produc3vity Bopp et al years, 1xCO 2 à 2xCO 2 IPSL CM2 NPZD Δ Produc3on (%) 10 24

25 Climate Change impact on Marine Produc3vity Simulation P3ZD-OPA-LMD 30 gc m -2 an -1 Zonal Mean (2xCO 2-1xCO 2 ) - 30 gc m -2 an % +30 % Global Decrease (-5 / -10 %), but opposition between low and mid/high latitudes 25

26 Climate Change impact on Marine Produc3vity Changes in Net Primary Produc3vity driven by climate change Rela3ve Change in NPP from 2005 to 2100 (RCP85 scenario) IPSL CM5A LR IPSL CM5A MR MPIM ESM MIROC ESM MIROC ESM CHEM CanESM2 HadGEM2 ES HadGEM2 CC A global decrease of NPP by 5 to 18% in 2100

27 Climate Change impact on Marine Produc3vity Rela3ve Change in NPP from 2005 to 2100 (RCP85 scenario, model mean, %) Hatched regions: when >75% of the models agree on the sign of change Large regional contrasts: 50% in N. Atl, 20% in the tropics, increase in the SO

28 Climate Change impact on Marine Produc3vity Changes in Net Primary Produc3vity driven by climate change: Drivers Sarmiento et al. 1998, Bopp et al. 2001, Doney et al. 2006

29 Climate Change impact on Marine Produc3vity La stratification de l océan augmente (P3ZD-OPA-LMD) Elements nutritifs -5 to 10 % La saison de croissance augmente > +10 days Augmentation de la surface des gyres Opposition hautes / basses latitudes 29 1xCO 2 2xCO 2-1xCO 2

30 Climate Change impact: Phytoplankton communi3es Modifica3on de la taille du phytoplancton : diatomées nano/pico phytoplancton (4xCO 2 1xCO 2 ) IPSL PISCES Changement de la propor3on rela3ve de diatomées (Bopp et al. 2005) 30

31 Climate Change impact: Phytoplankton communi3es Modifica3on de la fixa3on d azote atmosphérique : Cyanobactéries (Boyd and Doney, 2002) 31

32 Towards upper trophic levels

33 Towards upper trophic levels Offline coupling: IPSL PISCES SEAPODYM (Lehodey et al. 2010) PISCES (T, O2, Phytoplankton) SEAPODYM Bigeye Tuna

34 Towards upper trophic levels Offline coupling: IPSL PISCES SEAPODYM (Lehodey et al. 2010) WTP: West Tropical Pacific ETP : East Tropical Pacific Main drivers: Temperature : habitat, spawning, mortality, Oxygen : habitat Food availability

35 Towards upper trophic levels Towards Online Coupling: PISCES APECOSM (Aumont Maury Bopp et al.) ANR MACROES ( )

36 Towards upper trophic levels Towards Online Coupling: PISCES APECOSM (Aumont Maury Bopp et al.) The ecosystem is divided into 3 Open Ocean Pelagic Communi3es (OOPC) 0 day night Epipelagic community day x,y Depth distribu3on is constrained by light, oxygen, food and temperature N. O. Handegard pers. com. Migratory community Mesopelagic community Each OOPC is divided into n size classes z

37 Towards upper trophic levels PISCES APECOSM : : Preliminary RCP85 results (see talk by S. Dueri for more details) Nanophytoplankton rela3ve change Diatoms rela3ve change La3tude Time (1850 to 2100) Microzooplankton rela3ve change Mesozooplankton rela3ve change LOWER TROPHIC 15% drop of total biomass in 2100 compared to preindustrial values Large disparity among plankton func3onal types: Phyto : 8%, Diatoms : 16%, Microzoo : 20%, Mesozoo : 20%.

38 Towards upper trophic levels PISCES APECOSM : : Preliminary RCP85 results (see talk by S. Dueri for more details) Total biomass rela3ve change Epipelagic biomass rela3ve change La3tude Time (1850 to 2100) Migratory biomass rela3ve change Mesopelagic rela3ve change UPPER TROPHIC 23% drop of total biomass in 2100 compared to preindustrial values Large disparity among communi3es: Epipelagic : 22%, Migratory : 8%, Mesopelagic : 30%

39 Towards upper trophic levels IPSL model 1. Sensi3vity E2E model 2. Retroac3ons 3.Fishing scenarios? ANR MACROES

40 Perspec3ves Model Spread? Mul3 model analysis is necessary / required as rou3nely performed in the climate modelling / IPCC WG1 community Some es3mate of uncertain3es

41 Perspec3ves Model Spread? Mul3 model analysis is necessary / required as rou3nely performed in the climate modelling / IPCC WG1 community Some es3mate of uncertain3es Stock et al Spa3al resolu3on? IPCC class global models: horizontal resolu3on ~ 1 2 higher resolu3on vs. zoom version vs. Regional? Ver3cal velocity, Oregon Coast, GFDL model (70km vs 17 km)

42 Perspec3ves Model Spread? Spa3al resolu3on? Internal variability? Climate simula3ons: difficult to use for the next decade or so ( ) as internal variability tends to dominate on these 3me scales?

43 Perspec3ves Model Spread? Spa3al resolu3on? Internal variability? Some decadal predic3ons with climate models in IPCC AR5 PP in North Atlan3c simulated by IPSL PISCES Decadaly smoothed control run (over , with ini3aliza3on procedure) Do models have some previsibility skills for NPP evolu3on? 10 members Ensemble mean Séférian et al. in prep 50 ans

44 Perspec3ves Feedbacks? Biogeochemistry Climate Carbon Climate coupling via air sea carbon fluxes IPCC, 2007

45 Perspec3ves Feedbacks? Biogeochemistry / Ecosytems Climate via air sea carbon fluxes biophysical retroac3ons in the ocean Ocean albedo? Heat Trapping? Bio mixing Turbulence? Lengaigne et al. 2009

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