AcuuWeather meteorologist Joe Bastardi has a question about two datasets and asks: If it is darn warm, how come there is so much sea ice?

Bastardi asks a simple question: how can we have above normal temperatures in the Arctic and the Antarctic and continue to add to the global sea ice trend? After all we’ve been told by media stories that both the Arctic and the Antarctic continue to melt at a frenetic pace. But it looks like this year we’ll see another Arctic recovery as we’ve seen in 2008 and 2009.

Bastardi also wonders about something we routinely ask about here at WUWT: data adjustments. GISS seems to be stuck with Arctic positive anomaly, yet the sea ice isn’t cooperating. Of course just having a positive temperature anomaly doesn’t guarantee melt, but members of the public who are less discerning, who look at red hot color presentations like GISS puts out, usually can’t tell the difference.

For reference here are the images Joe uses in his presentation. I’m going to help out a bit too with some simple comparisons.

First The GISS Dec-Feb 2010 Global Surface Anomaly as Joe presents it in his video:

Source: http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2010&month_last=2&sat=4&sst=0&type=anoms&mean_gen=1203&year1=2010&year2=2010&base1=1951&base2=1980&radius=1200&pol=reg

Note that in the warmest places in the Arctic according to GISS, there are few if any land thermometers:

Above: map of GHCN2 land stations (thanks to commenter Carrick at Lucia’s)

Note the cross section of the GISS data, most of the warmth is at the Arctic where there are no thermometers. The Antarctic comes in a close second, though it has a few thermometers at bases on the perimeter of the continent plus a couple at and near the center. Note the flat plateaus are each pole.

The effects of interpolation become clearer when you do a 250 km map instead of 1200 km:

Source: http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2010&month_last=2&sat=4&sst=0&type=anoms&mean_gen=1203&year1=2010&year2=2010&base1=1951&base2=1980&radius=250&pol=reg

All of the sudden, the hot Arctic disappears. It disappears because there are no thermometers there as demonstrated by the cross section image which stops at about 80N.

Interestingly, the global surface anomaly also drops, from 0.80°C at 1200km of interpolation to 0.77°C with an interpolation of 250km.

One of the things that I and many other people criticize GISS for is the use of the 1951-1980 base period which they adopted as their “standard” base period. That period encompasses a lot of cool years, so anomalies plotted against that base period will tend to look warmer.

This famous GISS graph of surface temperatures from weather stations, shown worldwide in media outlets, is based on the 1951-1980 period:

Uncertainty bars (95% confidence limits) are shown for both the annual and five-year means, account only for incomplete spatial sampling of data.”] GISS doesn’t provide a utility to replot the graph above with a different base period on their webpage here http://data.giss.nasa.gov/gistemp/graphs/ but I can demonstrate what would happen to the GISS global maps using a different base period by using their plot selector here http://data.giss.nasa.gov/gistemp/maps/

Watch what happens when we use the same base period as the UAH satellite data, which is 1979-2009. The 1200km interpolated global temperature anomaly for Dec-Jan-Feb 2010 drops more than half to 0.38°C from 0.80°C. That number is not so alarming now is it? As for the graphic, the flaming red is still there in the same places because the anomaly map colors always stay the same, no matter what the absolute temperature scale is. In the first map with the 1951-1980 base period, the max positive anomaly was 6.4°C for 1200km and 8.8°C for 250km, while in the one below with the 1979-2009 base period the max positive anomaly of 7.1C If colors were assigned to absolute temperatures, this map would look cooler than it’s counterpart with the 1951-1980 base period.

Source: http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2010&month_last=2&sat=4&sst=0&type=anoms&mean_gen=1203&year1=2010&year2=2010&base1=1979&base2=2009&radius=1200&pol=reg

And here’s the 250km presentation, note that the global surface temp drops to 0.34°C

Source: http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2010&month_last=2&sat=4&sst=0&type=anoms&mean_gen=1203&year1=2010&year2=2010&base1=1979&base2=2009&radius=250&pol=reg

So it is clear, with the GISS anomaly presentation, you can look at it many different ways, and get many different answers. Who decides then which maps and graphs with what base periods and interpolations get sent out in press releases? Jim? Gavin?, Reto? Consensus over coffee at Monks?

The answer as to what base period GISS chooses in temperature anomaly maps to present to the public is easily answered by looking at their main page here: http://data.giss.nasa.gov/gistemp/

Here’s a thumbnail of the page, and the full size version of the second graph from the top, note the caption on the top of the graph:

Clearly, they prefer the base period of 1951-1980 as the default base period for the public presentation [as well as 1200 km smoothing] and by choosing that, the GISS results look a lot more alarming than they might be if a different base period was used, such as the 1979-2009 period used by UAH and RSS.

Anomalies can show anything you want based of choosing the base period. For example, a simple thought experiment. I could choose a base period from 11,000 years ago, during the last ice age, and plot maps and graphs of today’s temperatures against that base period. Would we see red? You betcha.

Here’s a graph that shows reconstructed northern hemisphere temps at the end of the last ice age 11k years ago, they were about 4.5°C cooler than today. Granted it’s not a global temp, but close enough for government work.

So if I used a 30 year slice of temperature 11,000 years before the present as a baseline period, our GISTEMP map would look something like this:

Obviously the map above is not an accurate representation, just a visual guesstimate. The more excitable who frequent here will likely cry foul at my abuse of the image. But it does illustrate how choices of colors and baseline periods can have a distinct effect on the final visual. Using a cold baseline period in the past (in this case 4.5°C globally cooler than the present) makes the present look broiling hot.

Anomalies are all about the starting choices made by people. Nature doesn’t give a hoot about anomalies. Generally, people don’t either. Imagine if your local TV weather forecaster gave tomorrow’s forecast in anomalies rather than absolute temperatures. He might say something like:

It’s going to be a hot one folks! Tomorrow we’ll have a high temperature that is 0.8C warmer than the 1951-1980 historical baseline for this city. Dress accordingly.

Useful isn’t it? Even more useful if he’s the weatherman in Svalbaard and people anticipating a heat wave go out in shorts and tank tops in mid February.

While anomalies are fine for illustrating many things, including temperature, bear in mind it’s all about the starting conditions chosen by the individuals doing the analysis. It’s all about choosing a baseline “normal”, which is subjective.

So when Joe Bastardi looks at the GISS map of the world, sees red, and wonders why we have a growing ice presence, the answer is in the choice of baseline and the choice of colors used to calculate and represent the anomaly.

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