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WP 4: Climate Change
and Ocean Acidification
2nd Annual MeetingParis, 14-16 May 2012MACROES
WP4: Climate Change and Ocean Acidification
WP4 main objectives:
--- Use the MACROES modelling framework to study the effects of anthropogenic emissions (greenhouse gases, aerosols) through climate change and ocean acidification on the marine ecosystems (incl. fish ressources)
--- A particular emphasis will be given to the identification and characterization of the feedbacks between the different (natural) systems considered here (climate, biogeochemical cycles, marine ecosystems)
WP4 structure:
--- 4.1 Impact of CC and OA on marine ecosystems: end-to-end--- 4.2 Retroactions in the coupled system
- Top-down control from higher to lower trophic levels- Biophysical coupling through heat trapping and bio-induced turbulence
--- 4.3 Impact of CC and OA on marine ecosystems: biodiversity
WP4: Climate Change and Ocean Acidification
Les « drivers » : productivité marine, acidification, dé-oxygénation
Les premières simulations avec IPSL-CM / PISCES-APECOSM
A venir cette année…
Climate Change impact on surface chlorophyll
250
450
650
850
6.0
3.0
0.0
RCP8.5RCP6.0RCP4.5RCP2.6Historical
T (°C)
Chl de surface (mgChl/m3)
0.15
0.17
0.19
Premiers Résultats avec CM5
CO2, T et chlorophylle de surface
Biogeochemical Drivers
• Changes in Net Primary Productivity driven by climate change
Biogeochemical Drivers
• Changes in Net Primary Productivity driven by climate change
Net Primary Productivity as simulated by 8 CMIP5 models
IPSL-CM5A-LR IPSL-CM5A-MR MIROC-ESM-CHEM
MIROC-ESM HadGEM2-ESHadGEM2-CC
MPI-ESM
CanESM2
IPSL-CM5
IPSL-CM5 Biogéochimie Marine : Séférian et al. in pressComparaison des modèles IPCC – CMIP5 / Productivité marine :Kidston et al. in prep
IPSL-CM5A-LRIPSL-CM5A-MRMPIM-ESMMIROC-ESMMIROC-ESM-CHEMCanESM2HadGEM2-ESHadGEM2-CC
Biogeochemical Drivers
• Changes in Net Primary Productivity driven by climate change
A global decrease of NPP by -5 to -18% in 2100
Relative Change in NPP from 2005 to 2100 (RCP85 scenario)
Biogeochemical Drivers
• Changes in Net Primary Productivity driven by climate change
Relative 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
Biogeochemical Drivers
• Changes in pH / Ocean Acidification
Biogeochemical Drivers
• Changes in pH / Ocean Acidification
RCP4.5
RCP8.5
Orr et al. in prep
IPSL-CM5A-LR, IPSL-CM5A-MR, HadGEM2-ES, HadGEM2-CC, MPIM-ESM, MIROC-ESM, MIROC-ESM-CHEM, CanESM
Consistent decrease in pH from several CMIP5 models
RCP45: -0.3RCP85: from -0.4 to -0.8 in 2300 !
Biogeochemical Drivers
• Changes in pH / Ocean Acidification
RCP4.5
RCP8.5
Aragonite / Calcite undersaturation reached at the surface in polar oceans
Implications on calcification / trophic food webs?
[CO32-]
Biogeochemical Drivers
• Changes in pH / Ocean Acidification
RCP4.5
RCP8.5
Increase in C/N ratios of organic matter (Riebesell et al. 2008)
Implications on food “quality” ?
(Tagliabue et al. 2011)
Biogeochemical Drivers
• Changes in Oxygen / Desoxygenation
Biogeochemical Drivers
• Changes in Oxygen / Desoxygenation
Stramma et al. 2008
Observed increase of hypoxic waters in the Eq. Pacific
O
2 (
mo
l/L)Changes in [O2] (micromol/L) (5-model mean, SRES-A2) : 0 m
Biogeochemical Drivers
• Changes in Oxygen / Desoxygenation
Large decrease of O2 in surface waters: solubility-driven
Hatched regions: when >75% of the models agree on the sign of change
(IPSL-CM4, UVIC, CSM1.4, CCSM3, BCM-C)
O
2 (
mo
l/L)Changes in [O2] (micromol/L) (5-model mean, SRES-A2) : 200 m
Biogeochemical Drivers
• Changes in Oxygen / Desoxygenation
Consistent at mid/high lat but models do not agree in the tropics !
Hatched regions: when >75% of the models agree on the sign of change
Towards coupled climate & end-to-end ecosystem modelling
Towards Online Coupling: PISCES-APECOSM
Towards coupled climate & end-to-end ecosystem modelling
PISCES-APECOSM :: Preliminary RCP85 results (see talk by S. Dueri for more details)
Nanophytoplankton relative change Diatoms relative change
Microzooplankton relative change Mesozooplankton relative change
15% drop of total biomass in 2100 compared to preindustrial values
Large disparity among plankton functional types:Phyto : -8%, Diatoms : -16%, Microzoo : -20%, Mesozoo : -20%.
Latit
ude
Time(1850 to 2100)
LOWER TROPHIC
Towards coupled climate & end-to-end ecosystem modelling
PISCES-APECOSM :: Preliminary RCP85 results
Latit
ude
Time(1850 to 2100)
Total biomass relative change Epipelagic biomass relative change
Migratory biomass relative change Mesopelagic relative change
23% drop of total biomass in 2100 compared to preindustrial values
Large disparity among communities:Epipelagic : -22%, Migratory : -8%, Mesopelagic : -30%
UPPER TROPHIC
Etapes / Stratégie pour le WP4 End-to-End
Etape 1M12 : Simulations “offline” sur 1860-2100 (RCP8.5)
IPSL-CM ( PISCES APECOSM ) M18 : Analyse de l’impact du CC (et OA) sur les écosystèmes
Etape 2
M24: Mise en place de PISCES-APECOSM dans IPSL-CM (biomixing) M24 : Importance du top-down control dans un contexte de CC
IPSL-CM ( PISCES APECOSM )
Etape 3M42: Simulations “offline” sur 2000-2100 (biodiversité)
IPSL-CM PISCES-APECOSM-DEB/Biodiv (?)M48: Analyse de ces simulations
En
co
urs
Climatic scenarios:Climatic scenarios:
Governance scenarios:Governance scenarios:
IPSL model
3.Fishing scenarios ?
E2E model
2. Retroactions
1. Sensitivity (acidification ?)
Towards coupled climate & end-to-end ecosystem modelling
Some issues: spatial resolution, internal variability, model spread
Model Spread? : use of CMIP5 models ?
Spatial resolution? : towards higher resolution (global) / regional configurations ?
Internal variability?
Climate simulations: difficult to use for the next decade or so (2010-2030) asinternal variability tends to dominate on these time-scales
?
Some issues: spatial resolution, internal variability, model spread
Model Spread?
Spatial resolution?
Internal variability?
10 members
Ensemble mean
Decadaly-smoothed control run
50 ansSéférian et al. in prep
-Some decadal predictions with climate models in IPCC-AR5
(over 2000-2030, with initialization procedure)
-Do models have some previsibility skills for marine productivity evolution?
PP in North Atlantic simulated by IPSL-PISCES