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Climate Variability and Change in the U.S. GLOBEC
Regions as Simulated by the IPCC Climate Models:
Ecosystem Implications
PIs: Antonietta Capotondi, University of Colorado/NOAA
Mike Alexander, NOAA
Nick Bond, University of Washington/PMEL
Enrique Curchitser, Rutgers University
As stated in the AO (2007):
‘As the culmination of a series of solicitations for the U.S. Global
Ocean Ecosystem Dynamics Program (U.S. GLOBEC), this solicitation
seeks a broader understanding of climate impacts on marine
ecosystems that builds upon findings from the three regional U.S.
GLOBEC studies: the Northwest Atlantic, the Northeast Pacific, and
the Southern Ocean.’
Observational studies, and studies that use models forced with
observations can address the climate-ecosystem interaction over
time periods, typically a few decades or less, which may be too short
to draw conclusions that are statistically significant.
In the presence of climate change it is also important to understand
how climate impacts on ecosystems may evolve in the future.
Long climate models simulations of present and future climate
scenarios can be very useful.
Intergovernmental Panel for Climate Change (IPCC)
climate models
Most recent generation of climate models from 23 modeling centers around the
world, used in support of the IPCC Assessment Report 4 (AR4).
A set of present day and future climate simulations have been completed by all the
models, and the output is archived at PCMDI.
Simulations:
•Pre-industrial control simulations
•20th century
•Climate change scenarios
IPCC models
Pros in using the models:
•Models are global, so that all three GLOBEC regions can be
examined
•They provide complete information of both oceanic, atmospheric and
ice fields (e.g. T, S, U,V are available at each horizontal and vertical
grid points), and the fields are consistent with each other, so that
physical mechanisms and processes can be examined.
•IPCC simulations (control, 20th century, and future climate) are at
least 100 yrs long, so that results have statistical confidence.
Cons:
•Model resolution is low
•Degree of realism is variable
Can coarse resolution models be useful to understand
regional processes relevant for the ecosystem?
Global climate models can help identify the large-scale patterns of climate
variability. Regional processes are often related to the large-scale patterns.
Pycnocline depth (h) difference : P2 -P1
P2=1977-1997
P1=1958-1975
NCOM ~2.4 resolution
h difference ROMS 19km-13km grid spacing
SSH difference ROMS
Capotondi et al., JGR, 2009
What about eddy processes?
Proposal questions
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Does the present generation of climate models show connections
between large-scale low-frequency wind forcing variations and ocean
circulation changes in the three GLOBEC areas similar to those we
believe exist in nature? Can we use the models to provide larger
statistical confidence in those relationships?
Based on the most reliable models, will the influence of climate upon
processes in the GLOBEC regions change in the next one to two
centuries?
How successful can statistical downscaling be for relating variations at
the regional (ecosystem) scale to large-scale climate forcing? Can we
identify specific variables that are amenable to statistical downscaling?
Processes (present-day)
Northeast Pacific
Gulf of Alaska:
• Mean upper ocean structure and circulation (use observations and SODA for
validation)
• Leading modes of SST variability (PDO, “Victoria Mode”/NPGO), and their
connection with atmospheric forcing (Ekman pumping), gyre circulation and
pycnocline depth variations
California Current System (CCS)
• Variations in intensity of the North Pacific Current (NPC) and connection with the
NPGO
• Upwelling index based on alongshore winds or large-scale pressure patterns:
Connection with modes of SST variability
• Variations in T and S properties along the California Coast, and relationship with
upwelling and large-scale gyre variations.
Processes (present-day)
Northwest Atlantic:
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Variations in Labrador Current (LC),
and relationship with basin-scale
Ekman pumping, Subpolar gyre
circulation strength, and NAO.
Changes in Labrador Sea Water
(LSW) formation (from changes in
MLD, Holland et al. 2006)
Variations in T and S south of
Newfoundland, and relationship with
the LC and Gulf Stream transports.
Variations in Arctic outflow.
Processes (present-day)
Southern Ocean:
•
•
Examine winds, ocean currents, Ekman
drift, water properties, ocean heat
transport, ice concentration and
thickness.
Most important mode of variability is the
Southern Annular Mode (SAM) defined as
the leading EOF of SLP. ENSO can also
be important.Positive SAM is associated
with a poleward displacement of the
westerlies.
Leading EOF of winter SLP north of 9N (a), and south
of 9S (b) (from Hall and Visbeck (2002)
Positive SAM is associated with poleward displacement of the
westerlies, leading to northward Ekman drift south of the mean axis
of the winds, and southward drift north of the mean axis, resulting
in downwelling at ~45S, and upwelling offshore of Antarctica.
Climate change scenarios
B1: CO2 concentration ~550 ppm in 2100
A1B: CO2 concentration ~700 ppm in 2100
QuickTime™ and a
TIFF (U ncompressed) decompressor
are needed to see thi s picture.
A2: CO2 concentration ~820 ppm in 2100
Multi-model means of surface warming for
the 20th century and different climate
change scenarios
Meehl et al., Bull. Amer. Meteor. Soc.,
2007
Diagnostics: Mean conditions + Variability
Downscaling: array of methods used to obtain finescale information from a relatively coarse-resolution
global climate models.
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Develop statistical models based on a ROMS (10km, 60 vertical levels)
hindcast (1958-present), and test different techniques for different
environments.
Use the latest version of the SODA ocean analysis as an independent
test of the statistical models
Apply the statistical relationship to the IPCC output in both present-day
and future climate scenarios.
Modes of climate variability in the North Pacific
PDO
“Victoria
Mode”
Di Lorenzo et al., GRL, 2008
Bond et al., GRL, 2003
Modes of variability in the North Pacific
GFDL_CM21, 500 yrs
GFDL_CM20, 500 yrs
Modes of variability in the North Pacific
NCAR_CCSM3, 500 yrs
UKMO_HadCM3, 340 yrs
Modes of variability in the North Pacific
CSIRO, 380 yrs
CCCMA, 400 yrs