arctic minimum 2007 a climate model perspective
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Arctic Minimum 2007 A Climate Model Perspective. Only 2 of ~20 models have any ensemble members that can keep up with 1979-2006 trend Faster than Forecast? Stroeve et al 2007. What makes these two special? Do models ever have 1 year decline as great as - PowerPoint PPT PresentationTRANSCRIPT
Arctic Minimum 2007 A Climate Model Perspective
What makes these two special?
Do models ever have 1 year decline as great as observed from September 2006 to 2007?
Is there evidence for tipping points in models?
What controls sea ice sensitivity in models?
Only 2 of ~20 models have any ensemblemembers that can keep up with 1979-2006 trend
Faster than Forecast? Stroeve et al 2007
Low extent models tend to retreat faster (N)
5 models with ITD tend to retreat faster (Y), but with considerable spread
April
(mid-21st minus late 20th c)
(Y!)
TREND in atmospheric heat flux is negligiblein the two models (N!)
(Don’t know how much variability it explains)
Cloud TRENDS are not unusual in thetwo models (N)
Ice thickness in the late 20th c is high in the two models (N)
red = observationscolors = 7 SRES A1B runs w/ CCSM3black = ensemble mean
Holland, Bitz, & Tremblay 2006T85 (1.4 deg) in atmosphere and land0.5-1 deg in ocean and sea ice
1) Increase in absorbed shortwave 2) Increase in Ocean Heat Transport through Fram Strait Two strong positive feedbacks?
Ocean Transport
Absorbed Sunlight
CCSM3 Single Year Decline at Least as Big
as Observed in 2007
CCSM3 2001-2050 A1B Scenario - 7 Runs
Even with TRENDskew is positive, though probably not significant
4 X in 350 years the drop is as big as observed
in 2006-2007
In any decade
Obs
erve
d 20
06-2
007
Histogram of 1 yr September Sea Ice Change
red = observationscolors = 7 SRES A1B runs w/ CCSM3black = ensemble mean
Same runs only smoothed
A1B Scenario
A1B Scenario
2000 Commitment
2020 Commitment
2030 Commitment
Histogram of 400 yr CCSM3 1990s Control
No significant skewso positive and negative
1 year changes are equally likely
Histogram of 1 yr September Sea Ice Change
Histogram of 320 yr CCSM3 Pre-Industrial Contol
Variance is ~2/3 of modern(Because thickness is
~50% greater)
Histogram of 1 yr September Sea Ice Change
Autocorrelation of 400 yr CCSM3 1990s Control
September ice cover
observed
R=0.5 (0.7 skipping 2 outliers) Correlation Coefficient of linear trend 2004-2035 and mean from 1980-1999 Model uncertainty grows
Climate Models from IPCC AR4 (CMIP3)
Trends in sea ice thickness depend
on the mean state
R=-0.86
Model uncertainty shrinks
all Feedbacks - ∆H No Ice-Albedo
Feedback - ∆H0
“GAIN”G= ∆H / ∆H0 = 1.25 (on average)
∆H Sea Ice Thickness Change from doubling CO2
Summary
Two models that keep up with forecast have unusually high increase in ocean heat transport
Sea ice anomalies like 2007 occur about 1% of the time in 21st century CCSM3 runs. Anomalies are not negatively skewed and there is little memory. Anomalies increase in size as ice thins.
Sea Ice albedo feedback causes sea ice to thin 10-30% faster
Although positive, the feedback is not large enough to cause much uncertainty in thickness prediction
Instead model errors are probably more a function of error in the mean state. (Present day thickness spread in AR4 models is 1-3m)
For a blackbody Earth-like planet
∆To ≈ 1.2 K
= feedback factor
= gain
Now with additional physical processes
∆T = ∆To + f ∆T
When CO2 has been doubled
September Ice Extent in one ensemble member
Holland, Bitz, and Tremblay, 2006
A1B Scenario with CCSM3
106 km2
SeptemberConcentration
4
2
0
-2
-4hPa
5
2.5
0
-2.5
-5hPa
CCSM3 JJA Composite 2007 JJA Reanalysis
Sea Level Pressure
Cloud anomalies toosee Culather et al for more details