Model-Data Comparison: Alaska Land Surface Air Temperatures

Mainstream media and climate alarmist websites have been publishing a lot of nonsense about record and near-record surface temperatures in Alaska over the past few weeks.

Near-record? Yup. Near-record. On June 25^th, Sophia Rosenbaum penned the NBC News article Alaska sweating through brutal blast of heat. But right at the top of the page is a photo of smiling bikini-clad residents sunbathing at the lakeshore. Doesn’t look that brutal to me. Later, she notes:

In Fairbanks, the “near-record temperatures” are expected Wednesday and Thursday to clock in at 91 degrees.

Temperatures above 90 are extremely rare in Alaska. Fairbanks has only experienced 90 or above 14 times since in 109 years. The record in Fairbanks is 95 degrees set back in 1915.

If the record was set in 1915, why would anyone be worried about Alaskans receiving the gift of sunbathing weather? Let them enjoy it in peace.

To give Sophia Rosenbaum credit, she ends her article on a high note, by concluding there are differences of opinion about the cause of the heat wave:

A large northward bulge in the jet stream is to blame, consensus shows. Why that has occurred is more hotly debated. Some scientists tie the jet stream’s odd behavior on climate change. Others don’t make the connections directly, instead seeing random weather or long-term cycles at work. And even more scientists are taking a wait-and-see approach.

I wonder if Sophia Rosenbaum dropped by Steve Goddard’s blog and found the past newspaper articles about the high Alaska temperatures in the 1930s and in the 1950s.

The author of a SkepticalScience post, on the other hand, is not that well balanced…in his news roundup.

It’s easy to see when and why Alaskan surface air temperatures warmed. Based on linear trends of the recently released CRUTEM4 data, land surface air temperature anomalies were relatively flat in Alaska from 1900 to 1975, and from 1977 to present, they’re flat again. Between those two periods was the Pacific Climate Shift of 1976, which, in effect, raised Alaska land surface air temperature anomalies in the neighborhood of 1 deg C. See Figures 1 and 2.

Figure 1

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Figure 2

(Note: We discussed the 1976 Pacific Climate Shift in the Blog Memo to John Hockenberry Regarding PBS Report “Climate of Doubt”.  That phenomenon occurred across the entire East Pacific Ocean, effectively raising the sea surface temperatures of 33% of the surface of the global oceans almost 0.17 deg C…in one year. See the graph here.)

As you’ll note in Figure 1, in addition to the one in 1976, there appear to be other shifts in the land surface air temperature anomalies of Alaska, like in 1911 and 1934, and possibly 1957 and 2001. Between the shifts, surface air temperatures decay, gradually cooling after each shift, except for the recent period, when surface temperatures are cooling quite drastically. Unfortunately, the UKMO CRUTEM4 data lags a few months at the KNMI Climate Explorer.

So, how well do climate models simulate Alaska land surface temperature anomalies? The outputs of the climate models stored in the CMIP5 archive are also available through the KNMI Climate Explorer, though you may have to sign in to access them. For the period of 1900 to 1975, the climate model performance is kind of good (relative to the most recent 35 years). The difference in the observed trend in Alaska surface temperature anomalies from 1900 to 1975 and the trend of all the ensemble members of the climate models stored in the CMIP5 archive (models used for the upcoming IPCC AR5) is only about 0.06 deg C per decade, with the models showing warming and the data showing no warming.

Figure 3

However, according to the models, if manmade greenhouse gases were responsible for the warming, Alaska land surface air temperature anomalies should have warmed about 1.4 deg C since 1977, based on the linear trend. See Figure 4. But land surface air temperatures in Alaska have not warmed since 1977, also based on the linear trend. In fact, over the past couple of years, Alaskan surface air temperatures have been dropping rapidly.

Figure 4

STANDARD BLURB ABOUT THE USE OF THE MODEL MEAN

We’ve published numerous posts that include model-data comparisons. If history repeats itself, proponents of manmade global warming will complain in comments that I’ve only presented the model mean in the above graphs and not the full ensemble. In an effort to suppress their need to complain once again, I’ve borrowed parts of the discussion from the post Blog Memo to John Hockenberry Regarding PBS Report “Climate of Doubt”.

The model mean provides the best representation of the manmade greenhouse gas-driven scenario—not the individual model runs, which contain noise created by the models. For this, I’ll provide two references:

The first is a comment made by Gavin Schmidt (climatologist and climate modeler at the NASA Goddard Institute for Space Studies—GISS). He is one of the contributors to the website RealClimate. The following quotes are from the thread of the RealClimate post Decadal predictions. At comment 49, dated 30 Sep 2009 at 6:18 AM, a blogger posed this question:

If a single simulation is not a good predictor of reality how can the average of many simulations, each of which is a poor predictor of reality, be a better predictor, or indeed claim to have any residual of reality?

Gavin Schmidt replied with a general discussion of models:

Any single realisation can be thought of as being made up of two components – a forced signal and a random realisation of the internal variability (‘noise’). By definition the random component will uncorrelated across different realisations and when you average together many examples you get the forced component (i.e. the ensemble mean).

To paraphrase Gavin Schmidt, we’re not interested in the random component (noise) inherent in the individual simulations; we’re interested in the forced component, which represents the modeler’s best guess of the effects of manmade greenhouse gases on the variable being simulated.

The quote by Gavin Schmidt is supported by a similar statement from the National Center for Atmospheric Research (NCAR). I’ve quoted the following in numerous blog posts and in my recently published ebook. Sometime over the past few months, NCAR elected to remove that educational webpage from its website. Luckily the Wayback Machine has a copy. NCAR wrote on that FAQ webpage that had been part of an introductory discussion about climate models (my boldface):

Averaging over a multi-member ensemble of model climate runs gives a measure of the average model response to the forcings imposed on the model. Unless you are interested in a particular ensemble member where the initial conditions make a difference in your work, averaging of several ensemble members will give you best representation of a scenario.

In summary, we are definitely not interested in the models’ internally created noise, and we are not interested in the results of individual responses of ensemble members to initial conditions. So, in the graphs, we exclude the visual noise of the individual ensemble members and present only the model mean, because the model mean is the best representation of how the models are programmed and tuned to respond to manmade greenhouse gases.

CLOSING

We can add Alaskan land surface air temperatures to the variables that the IPCC’s climate models cannot simulate. In recent months we’ve also illustrated and discussed that the climate models stored in the CMIP5 archive for the upcoming 5^th Assessment Report (AR5) cannot simulate observed:

Daily Maximum and Minimum Temperatures and the Diurnal Temperature Range

Hemispheric Sea Ice Area

Global Precipitation

Satellite-Era Sea Surface Temperatures

Global Surface Temperatures (Land+Ocean) Since 1880

And we recently showed in the post Meehl et al (2013) Are Also Looking for Trenberth’s Missing Heat that the climate models used by Meehl et al (2013) show no evidence that they are capable of simulating how warm water is transported from the tropics to the mid-latitudes at the surface of the Pacific Ocean, so why should we believe they can simulate warm water being transported to depths below 700 meters without warming the waters above 700 meters?

TITLE FOR UPCOMING BOOK

Many thanks to all who have suggested titles for my upcoming book about the extremely poor performance of climate models being used by the IPCC for their 5^th Assessment Report.

I’ve been toying with another title based on a comment I recently made on the thread of a WUWT post by easy-to read, always-informative Willis Eschenbach.

As I’m writing a model-data post or when I come across an alarmist webpage tolling the life-as-we-know-it death knell while referring to a climate model study, I’m reminded of an early scene from “Young Frankenstein”. In it, a medical student asks, “But what about your grandfather’s work, sir?”

Dr. Fredrick Frankenstein cries out in reply, “My grandfather’s work was doo-doo!” See the YouTube clip here.

So right now, the working title is Climate Models are Doo-Doo, with the subtitle An Illustrated Overview of IPCC Climate Model Incompetence. And for the cover art I’m thinking a cartoon by Josh with Barack Obama asking, “But what about climate models?”, and a cranky old pensioner replying, “Climate Models are Doo-Doo!” Maybe with Obama feeding billions of dollars to a mainframe that looks like the Frankenstein monster and a diverging model-data graph of global temperatures behind the frazzled Billy Connolly-looking pensioner.