frédéric maps & marina chifflet
DESCRIPTION
Influence of Climate Variability and Change on the Ecosystems of the Sub-Arctic Inland Seas of Canada : A modeling approach. Frédéric Maps & Marina Chifflet. Ongoing monitoring programs (visited weekly to yearly). Hudson Bay : MERICA visited yearly - PowerPoint PPT PresentationTRANSCRIPT
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Influence of Climate Variability and Change on the Ecosystems of the Sub-Arctic Inland Seas of Canada :
A modeling approach.
Frédéric Maps&
Marina Chifflet
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Ongoing monitoring programs(visited weekly to yearly)
SatelliteMonitoring
(ex. SeaWIFS)
Gulf of St LawrenceGulf of St Lawrence: Atlantic Zone Monitoring Program
fixed stations visited weekly to monthly, and sections visited twice in the year (spring and autumn)
T, S, dissolved oxygen, fluorescence, chlorophyll a, nutrients, zooplankton abundance
Thermographs
Hudson BayHudson Bay: MERICAvisited yearly
moorings, T, S, dissolved oxygen, fluorescence, chlorophyll a, nutrients, zooplankton, benthos,
fishes larvae
Sea-ice observations
(CIS)
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Sea ice
snow
SWLW
FIO, QIO, M IOPhysical Ocean:
Water level, currents, temperature, salinity, turbulent energy and dissipation
Tides
Runoff
FAO, QAO, MAO
FAI, QAI, M AI
(OBS orOGCM)
Atmosphere: temperature, winds, clouds, dewpoint, pressure, precipitation
CRCM / GEM
GCM GCM
Coupler
coupled climate - sea-ice - ocean - ecosystem - biological models
Ice algae
Secondary productioncopepods population model
Primary productionNPZD modelKrill aggregation
vertical behaviour
model
Harmful algae
growth and vertical
behaviour model
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Prognostic hindcast solutionfor domain-averaged salinity & temperature profiles, and sea ice volume
Salinity
Observation
Model
Time (years)
Sea ice volume
Temperature
sea-ice – ocean circulation model
Saucier et al., in prep
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Comparison with annual temperature and salinity indicesin depth ranges
Salinity Temperature (oC)
: 0-30 m 30-100 m 100-200 m 0-30 m 30-100 m 100-200 m
MOD
OBS
Depth range
sea-ice – ocean circulation model
Saucier et al., in prep
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Sea surface salinity Sea surface temperature (oC)
sea-ice – ocean circulation model
Saucier et al., in prep
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Simulation with air temperature + 2oC (stabilization experiment)
Domain-averaged salinity & temperature profiles, and sea ice cover & volume. Anomalies ( solution - standard run)
sea-ice – ocean circulation model
Sea ice cover concentration
Current climate … + 2oC
Saucier et al., in prep
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Simulated nitrate and chlorophyll a 1997
coupled ecosystem – sea-ice ocean circulation model
Le Fouest et al., 2005Chifflet et al., in prep
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coupled ecosystem – sea-ice ocean circulation model
Le Fouest et al., 2005
Comparisons to satellite-derived fields:chl a synoptic events
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coupled ecosystem – sea-ice ocean circulation model
Le Fouest et al., submitted
Comparisons to satellite-derived fields:St. Lawrence discharge effect
model satellite
AVHRR
SeaWIFS
SeaWIFS
SST
Chl a
kCDOM
vs
Chl a
3rd – 6th of August 1998
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April 1997 April 1998 April 1999
Interannual variability : ice cover vs chlorophyll a
Monthly mean ice cover %
Monthly mean chl. a mg/m2
coupled ecosystem – sea-ice ocean circulation model
3 different ice cover for the 3 years 3 different patterns for the spring bloom
Chifflet et al., in prep
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Gulf
bloom max : end April – end May bloom max : April max bloom : April – end Mai
bloom max : end May – end August bloom max : end May – Sept. bloom max : May – Sept.
coupled ecosystem – sea-ice ocean circulation model
Interannual variability : chlorophyll a bloom
1997 1998 1999
Estuary
mgChla m-3
• ice concentration: determinant effect on the bloom timing• bloom in the estuary later than in the gulf• spring bloom in 1999: early and long, as it was observed• autumnal blooms in 1998 & 1999, but not in 1997, as it was observed on Seawifs images
Chifflet et al., in prep
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1997 1998 1999
Annual integrated production - gC/m2/an
Mean winter nitrate concentration (mmolN m-2)
coupled ecosystem – sea-ice ocean circulation model
Interannual variability in primary production
Chifflet et al., in prep
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Winter 1998/1999
coupled ecosystem – sea-ice ocean circulation model
Chifflet et al., in prep
no major differences of irradiance
nutrients fluxes in the St. Lawrence estuary and the north-western region
Temperature profile at Rimouski station
tides / storms during the winter ?
Flow of nutrients at Québec city
low freshwater runoff in Nov-Dec 98 & Jan-Feb 99:North Atlantic water entrance in the St. Lawrence estuary = rich in nutrients ?
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1997 1998 1999
Spring
Fall
Observed vs simulated nitrate concentration
predicted
observed
coupled ecosystem – sea-ice ocean circulation model
Chifflet et al., in prep
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1997 1998 1999
Spring
Fall
Observed vs simulated chlorophyll a biomass
predicted
observed
coupled ecosystem – sea-ice ocean circulation model
Chifflet et al., in prep
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Ch
la m
od
èle
(m
gC
hla
.m-3)
101
100
10-1
10-2
Chla observée (mgChla.m-3) Chla observée (mgChla.m-3)
101
100
10-1
10-2
Ch
la m
od
èle
(m
gC
hla
.m-3)
10-2 10-1 100 101 10-2 10-1 100 101
10-2 10-1 100 101 10-2 10-1 100 101
101
100
10-1
10-2
101
100
10-1
10-2
Ch
la m
od
èle
(m
gC
hla
.m-3)
Ch
la m
od
èle
(m
gC
hla
.m-3)
Chla observée (mgChla.m-3) Chla observée (mgChla.m-3)
Spring
C/N et C/Chla constants C/N variable
C/Chla variableC/N et C/Chla
variables
RMS=0,46 mgChla.m-3
MRD= -216,0 %
Ratio=3,16
RMS=0,69 mgChla.m-3
MRD= -421,7%
Ratio=5,22
RMS=0,31 mgChla.m-3
MRD= -111,7%
Ratio=2,11
RMS=0,68 mgChla.m-3
MRD= -367,5 %
Ratio=4,67
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Ch
la m
od
èle
(m
gC
hla
.m-3)
101
100
10-1
10-2 Chla observée (mgChla.m-3) Chla observée (mgChla.m-3)
101
100
10-1
10-2
Ch
la m
od
èle
(m
gC
hla
.m-3)
10-2 10-1 100 101 10-2 10-1 100 101
10-2 10-1 100 101 10-2 10-1 100 101
Ch
la m
od
èle
(m
gC
hla
.m-3)
Ch
la m
od
èle
(m
gC
hla
.m-3) 101
100
10-1
10-2
101
100
10-1
10-2 Chla observée (mgChla.m-3) Chla observée (mgChla.m-3)
Autumn
C/N et C/Chla constants C/N variable
C/Chla variableC/N et C/Chla
variables
RMS=0,49 mgChla.m-3
MRD= -95,49 %
Ratio=1,96
RMS=0,45 mgChla.m-3
MRD= -74,29%
Ratio=1,74
RMS=0,44 mgChla.m-3
MRD= -4,39%
Ratio=0,95
RMS=0,43 mgChla.m-3
MRD= -11,12 %
Ratio=1,11
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Conclusions
• Detailed regional climate models can predict the synoptic to interannual variability of the general sea ice - ocean circulation
• Fully coupled ecosystem model predict also the synoptic to interannual variability, especially primary production variability and nutrients concentration. Principal results:
• high spatial and temporal variability: heterogeneous entity• ice cover: determinant effect on the spring bloom timing• pre-conditioning of the bloom during the winter? impact of synoptic
events? role of the estuary and north-western region?
Future steps
• Improvement of the ecosystem model: St. Lawrence discharge of nutrient, C/chla, C/N, remineralization, carbon cycle, sulfur cycle…
• Operational reanalyses of physical and biogeochemical fields for forcing / coupling to upper trophic levels
• Climate change scenarios and seasonal forecasting
In situ data used for initial and boundaries conditions
Validation: in situ data and satellite images
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The team
Principal investigators F. Saucier physical modelB. Zakardjian coupled physical-ecosystem model
Post-docM. Chifflet NPZD model – Gulf of St. LawrenceZ.-P. Mei carbon cycle – Hudson BayM. Sourrisseau krill model, harmful algae model – Gulf of St. Lawrence
PhDM. Defossez physical model – Hudson BayJ. Fauchot harmful algae model – Gulf of St. LawrenceV. Le Fouest NPZD model – Gulf of St. LawrenceF. Maps copepods population model – Gulf of St. LawrenceV. Sibert sea-ice algae and NPZD models – Hudson BayG. Smith physical model – Gulf of St. Lawrence
Research assistantsJ. Caveen, F. Roy, S. Senneville
CollaboratorsM. Gosselin, P. Larouche, D. Lavoie, D. LefaivreS. Plourde, Y. Simard, M. Starr