One of the statistical tools that the Climate Prediction Center uses for monthly and longer period forecasting is called the "Optimum Climate Normals", which is simply how temperatures and precipitation have averaged in the past 10 years (15 for precipitation) compared to normal. This is potentially important because most longer term forecasts are made in reference to some "normal".
Here's a plot Fairbanks 1981-2010 normal monthly temperatures along with how the past 10 years (Mar 2003-Feb 2012) compare. Due to the very short period (10 years), I've included the decadel mean and median, which in some cases (e.g. January and October) are substantially different; this is an artificant that one extreme value can have on the mean in such a small sample.
As you can see, in the past decade January and March and November have averaged significantly below the 30 year normal, while September and especially October have averaged above.
How does this look if we standardize the differences (multiplied by 10 so scale is the same as the first chart), so that we account for the fact that temperatures have much wider ranges in winter than summer:
So now we see that the decline in January temperatures is not so spectacular (but March still is), but the recent warmth in May and August through October really stands out. This is a nice illustration of the power of standarization when the there are big differences in the variance in the data through the year.