November 2013 Russian “Hotspot” – Alarmists Are Overlooking Something

UPDATE:  Corrected the typo in Figure 3. 1988 now correctly reads 1989.

# # #

There’s lots of blogosphere chatter about the warm temperatures in Russia in November 2013.  In their global State of the Climate Report this month, NOAA stated:

According to Roshydromet, Russia observed its warmest November since national records began in 1891. Some areas of the Urals, Siberia, south of the Far East region, and on the Arctic islands in the Kara Sea had temperatures that were more than 8°C (14°F) higher than the monthly average.

NOAA even discussed the record warm temperatures on their global map here.

It might be true that Russian land surface air temperatures were at record levels for the month of November, but NOAA failed to present something that’s blatantly obvious in the data. In 1988, surface air temperature anomalies for much of Russia shifted upwards by more than 1 deg C.

The Russian “hotspot” stands out very clearly in the NOAA map presented in Figure 1.  Based on it, I’ve used the coordinates of 50N-70N, 30E-140E for the NOAA NCDC data, and the climate model outputs, presented in the following graphs. That region covers a major portion of Russia.

Figure 1

Figure 1

Figure 2 presents the NCDC land surface air temperature anomalies for the Russian “hotspot”, for the period of January 1920 to November 2013.  I’ve highlighted about when the shift occurred.  Before that shift, surface temperatures there warmed very little, if at all.  And after it, surface temperatures appear to have warmed, but not at an excessing rate. We’ll confirm that later.

Figure 2

Figure 2

The shift is much easier to see if we smooth the data with a 13-month filter, minimizing the visual impact of the monthly variations. In fact, with the aid of period average temperatures (the horizontal lines) and with some color-coding, the shift in 1988 becomes obvious. See Figure 3.  Based on the period-average temperatures before and after 1988, that climate shift raised Russian “hotspot” surface temperatures by about 1.1 deg C.

Figure 3c

Figure 3

MODEL-DATA COMPARISON BEFORE AND AFTER THE 1988 SHIFT

Figure 4 is a model-data comparison graph for the surface air temperature anomalies of the Russian “hotspot” for the period of January 1920 through December 1987.  Both the NCDC surface temperature data and the climate model outputs have been smoothed w/ 13-month running average filters. The climate models are the multi-model ensemble mean of the models stored in the CMIP5 archive, using the historic and RCP6.0 scenarios. The CMIP5 archive, as you’ll recall, was used by the IPCC for their 5th Assessment Report. And we discussed why we use the model mean in the post here.

Figure 4

Figure 4

NOTE:  The trends in Figures 4 and 5 are based on the “raw” data and model outputs, not the smoothed versions.

The models did a reasonable job of simulating the warming rate from 1920 to 1987.  In more than 65 years, they only overestimated the warming by about 0.23 Deg C.  But the models perform quite poorly for the period from January 1989 to November 2013. See Figure 5.  During this much-shorter 25-year period, the models overestimated the warming by more than 1.1 deg C.

Figure 5

Figure 5

Let’s state that again: the models overestimated the warming by more than 1.1 deg C over the most recent 25-year period.

Climate model failings at the regional levels are not unusual.  We discussed those failings in numerous posts over the past year and in my book Climate Models Fail.

WHAT CAUSED THE SHIFT?

The timing of the shift in the Russian surface temperatures is similar to the shift in Scandinavian surface air temperatures.  See the post here.   There we discussed that the shift in surface temperature was possibly a response to a shift in the sea level pressure and interrelated wind patterns associated with the Arctic Oscillation.

Additionally, see de Laat and Crok (2013) A Late 20th Century European Climate Shift: Fingerprint of Regional Brightening?  The authors argue that a shift in the North Atlantic Oscillation (similar to the Arctic Oscillation) in the late 1980s caused more sunlight to warm European surface temperatures in an apparent shift.  I would suspect that something similar occurred over Russia at that time as well.

CLOSING

Like other regions, a climate shift, not the long-term effects of manmade greenhouse gases, is responsible for a major portion of the warming that occurred over much of Russia.

And, of course, climate models performed poorly when attempting to simulate the warming that occurred there since the 1988 shift, overestimating the warming by a large amount.  So what else is new?

SOURCE

The NCDC surface temperature data and the CMIP5-archived climate model outputs are available through the KNMI Climate Explorer.

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About Bob Tisdale

Research interest: the long-term aftereffects of El Niño and La Nina events on global sea surface temperature and ocean heat content. Author of the ebook Who Turned on the Heat? and regular contributor at WattsUpWithThat.
This entry was posted in LSAT, Model-Data Comparison LSAT. Bookmark the permalink.

2 Responses to November 2013 Russian “Hotspot” – Alarmists Are Overlooking Something

  1. Bernie Hutchins says:

    Bob – Many thanks for your articles and books. I am awed by your ability to get your mind around so much data, and to instill your analysis with the “ominous ring of truth” to use a phrase from a former Physics professor of mine.

    When this article was on WUWT there was a question about your 13 month average, and I suggested a better way of doing this, which I have now written up and posted on my Electronotes website:
    http://electronotes.netfirms.com/AN401.pdf

    Briefly: Make it length 13 but make the end taps 1/2, and divide by 12. This solves the time shift problem and makes a perfect null at once-per-year.

    Quite likely it will be obvious to you that this works, but the app notes is there if you are curious. No significant difference to your analysis.

    Bernie

  2. Bob Tisdale says:

    Bernie, many thanks for the work you’ve put into this. I will likely stay with a standard running mean, primarily because it’s easy to reproduce and explain, but I may standardize on 12-month smoothing centered on the 6th month to avoid the possibility of a residual.

    Thanks again and happy holidays!!!!

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