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Pacific vs. Indian Ocean warming: How does it matter for global and regional climate change?

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NOAA Photo Library. Global Mean Surface Air Temperature DJF. Global Mean Precipitation DJF. A: Opposing Temperature and Precipitation Sensitivity to Tropical SSTs ... – PowerPoint PPT presentation

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Title: Pacific vs. Indian Ocean warming: How does it matter for global and regional climate change?


1
Pacific vs. Indian Ocean warmingHow does it
matter for global and regional climate change?
  • Joseph J. Barsugli
  • Sang-Ik Shin
  • Prashant D. Sardeshmukh
  • NOAA-CIRES Climate Diagnostics Center
  • Boulder, Colorado

NOAA Photo Library
2
Q How does it matter for global (DJF) climate
change?
A Opposing Temperature and Precipitation
Sensitivity to Tropical SSTs across 110E
3
Q How does it matter for regional (NH
Wintertime) climate change?
A Opposing PNA and NAO Sensitivity to Tropical
SSTs across 110-120E, with PNA emphasizing the
central and eastern Pacific more.
4
  • Method and Context (How did we get these plots
    and why do we believe them?)
  • Understanding Opposing T, p sensitivity
  • Seasonal cycle in T, p sensitivity
  • PNA and NAO sensitivity with application to 50
    year trend.

5
SST Patch Experiments with NCAR CCM3.10
1 K 0.5K
  • 43 SST anomaly patches total. 2K maximum
    anomaly
  • Indo-Pacific
  • 32 ensemble members (16 Warm, 16 Cold)
  • 18 month runs (2 winters, 1 summer)
  • Atlantic
  • 40 ensemble members (20 warm, 20 Cold)
  • 25 month runs
  • Climatology
  • 100 year fixed climo-SST run

6
Comparison of the present study to Barsugli and
Sardeshmukh, 2002
Atmosphere GCM
  • NCAR CCM3.10 w/CCM3.6 physics
  • T42, 18 level resolution
  • Default parameter values for current climate
  • Smoothed Topography (as in CAM2)
  • CCM3 vs. NCEP MRF9
  • Larger patch area in Indo-Pacific.
  • 2K vs. 1.5K peak SST anomaly.
  • Seasonal cycle vs. perpetual January
  • All Tropical oceans vs. Indo-pacific only.

7
Green Function approximation
  • Think of this as an empirical linearization
    about a given climate.
  • For a grid of T, or for a set of patches this
    becomes
  • Note the Area Factor. This means that the
    grid-independent Green Function (and sensitivity)
    has units of
  • Indo-Pacific Patches 12 SSTU
    Atlantic Patches 7.5 SSTU

8
Barsugli and Sardeshmukh, 2002
9
Simmons, Wallace, and Branstator, 1983
  • Barotropic vorticity forcing
  • nodal line for Pacific target? This is similar
    to patterns in Branstator et al, 1985 from
    explicit Green function approach.
  • Hmmm, what about the forcing of North Atlantic.
  • Newman and Sardeshmukh, 1998. Strong seasonal
    dependence of sensitivity.

10
Ting and Sardeshmukh, 1993
  • Linear Baroclinic Model. Deep heating.
  • Remote response switches sign across 120E.
  • Little remote response near nodal line at 120E.
  • Local (rotational) response moves with forcing
  • Heating is used as forcing, not SST.
  • Nodal line not found when GFDL model basic state
    is used.

11
  • Hoerling et al. (2004). Indian ocean SSTs force
    50 year trend in North Atlantic NAO-like
    pattern. Found in 3 models.
  • Branstator(2004) Circumglobal Waveguide Pattern
    responds more to forcing at the date line than to
    forcing at 150 W. The latter forcing results in
    a more isolated PNA pattern.

12
Temperature and Precipitation Sensitivity
13
(No Transcript)
14
Composite Surface Air Temperature
Indian Ocean
West Pacific Ocean
15
Composite Precipitation
Indian Ocean
West Pacific Ocean
16
Indian Ocean Patch Composite
Surface Latent Heat Flux
U-Wind Stress
V-Wind Stress
500 hPa Omega
17
W. Pacific Ocean Patch Composite
Surface Latent Heat Flux
U-Wind Stress
V-Wind Stress
500 hPa Omega
18
Precipitation Sensitivity Seasonal Cycle
DJF
MAM
JJA
SON
ANNUAL
19
Surface Temperature
20
850 hPa Temperature
21
Annual Mean Temperature at different levels
22
NAO, PNA and Trends
23
NAO and PNA sensitivity
- NAO
PNA
PNA MRF9
24
PNA in detail
25
1950-1999 Trend in 500 hPa Z NCEP
Reanalysis
Atlantic Sector
Pacific Sector
26
Z500 trend from CCM3
TOGA and GOGA
Fixed SST Trend Pattern
27
Projection of Z500 trend onto each patch
experiment
TOTAL TREND
PAC
ATL
28
Pattern Correlation
29
Conclusions
  • There is opposing sensitivity to SST anomalies
    across longitude 110E for global mean
    temperature and precipitation. E.g. warm SST
    anomalies in most of the Tropical Indian Ocean
    lead to a global mean cooling of the surface (
    mainly land), cooling at 850 mb, and a reduction
    in global mean precipitation.
  • The opposing temperature sensitivity is confined
    to the DJF season and is largest in the northern
    continents. The opposing sensitivity for
    precipitation is evident all year, and there is
    an additional area of negative sensitivity in the
    Eastern Pacific, south of the Equator.
  • There is opposing sensitivity to SST anomalies
    across the same nodal line for the NAO and PNA
    pattern. Compared to the NAO, the PNA shows more
    sensitivity to SSTs at and east of the dateline.
  • Therefore, the relative warming of the Indian and
    West Pacific warm pools will have a large impact
    on both global and (Northern Hemisphere) regional
    response to Tropical SST changes in DJF.
    Prediction (or past and paleo- reconstruction)
    of this broad spatial pattern of SST change is
    essential to get the global and regional picture
    correct.

30
Conclusions
  • Because the nodal line was seen in BS2002 and
    earlier, more idealized dynamical studies, we
    believe it to be a robust structure in the
    atmosphere of dynamical origin. The temperature
    sensitivity follows from the circulation
    anomalies. However, the origin of the coincident
    nodal line in Tropical precipitation remains
    uncertain.
  • The Tropical Atlantic SSTs are generally more
    influential in JJA for the global mean
    quantities.
  • The full picture of Tropical-Extratropical
    interaction is a) more complicated than just
    ENSO, but not that much more complicated 2-3
    regions do pretty well to capture the changes
    that have a big global impact.
  • Prashant will elaborate on the big picture at
    tomorrows talk.
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