I'm voting in the 2.5-2.75 slot.

The method I used is the same as the one I posted here :

http://neven1.typepad.com/blog/2013/07/problematic-predictions-2.htmlMethod briefly explained again :

I take 3 variables known in June : (snow-cover in June, SIE in June, and SIA in June) that I think best represent how much

**energy **is getting absorbed into the Arctic, and thus should serve as good predictors for later state of the ice (including predictions about area and extent in September).

I then run linear regression (and essentially principal component analysis) to determine the parameters for these variables that obtain the best correlation over the past years data.

Don't want to go back too far, since before 2000, the state of the Arctic was very different than now (and thus resp, and thus no combination of parameters obtains a correlation better than simple extrapolation of trends.

But with 3 variables, I need at least 10 data points or so, or else I will surely be 'over fitting'.

I found that going back to 2002 works well and seems to be representative to how well the Arctic responds to these 3 variables.

For SIA daily minimum, the formula for energy that gives the best correlation over the past 12 years or so is this one (june_area normalized (to 1.0) :

june energy = 0.38 * june_snowcover - 1.57 * june_extent + 1.0 * june_area ;

*************** Linear Regression Analysis *****************

11 years analysed (2002-2012) :

Mean energy -6.289610 Mean ice cover 3.466049

SD energy 0.660019 SD ice cover 0.622146

** Correlation (R): 0.990791 **

Beta(slope delta-icecover/delta-energy) 0.933936

Alpha (ice-cover at energy 0) 9.340144

ice cover = 9.340144 + 0.933936 * energy

*************** Prediction and confidence intervals *****************

2002: energy -5.78, area 9.13, extent 11.70, predict 3.94, final 4.03, delta 0.09

2003: energy -5.59, area 9.05, extent 11.77, predict 4.12, final 4.14, delta 0.02

2004: energy -5.27, area 9.19, extent 11.52, predict 4.42, final 4.28, delta -0.13

2005: energy -5.63, area 8.74, extent 11.30, predict 4.08, final 4.09, delta 0.01

2006: energy -5.85, area 8.34, extent 11.06, predict 3.87, final 4.02, delta 0.14

2007: energy -6.78, area 8.15, extent 11.50, predict 3.01, final 2.92, delta -0.09

2008: energy -6.77, area 8.53, extent 11.37, predict 3.02, final 3.00, delta -0.02

2009: energy -6.38, area 8.92, extent 11.47, predict 3.38, final 3.42, delta 0.05

2010: energy -6.72, area 8.02, extent 10.83, predict 3.07, final 3.07, delta 0.01

2011: energy -6.73, area 8.20, extent 10.99, predict 3.05, final 2.90, delta -0.15

2012: energy -7.69, area 7.71, extent 10.97, predict 2.16, final 2.23, delta 0.07

# -2013: energy -7.33, area 8.57, extent 11.58, **predict 2.50,** final ?

Standard Deviation for de-trended prediction : **0.084**

Note the amazing correlation factor R of 0.99, and resulting Standard Deviation on the prediction of only 84 k km^2.

Now, gotta take that SD with a grain of salt, since I included all known data in the analysis.

So I ran the entire process again, this time excluding individual years and then see how well this method can predict SIA that it did not know about. With that method, I get R=0.987 and resulting SD of about 100 k km^2. Which is still remarkably good and much better than straight line extrapolations of area and extent alone.

Which brings my prediction for 2013 SIA to 2.4 - 2.6.

No slot for that, but my got feeling is that 2013 will go to the high end of this range, so vote into the 2.5-2.75 slot.

Sorry for the long post, but after many experiments, I'm getting some confidence in this method.

We'll see in September if the Arctic agrees

)