Analysis of the AMSR-E data on Arctic Ice
Guest post by Dr Tony Berry, 4th October 2009
The Arctic Ice extent prepared IARC-JAXA demonstrates the cyclical annual trend of freezing and thawing in the Arctic. It is clear that the cycles vary from year to year and it has been suggested that the data supports the hypothesis that AGW is responsible for a long term decline in Arctic ice although recent data has shown a recovery in the Arctic ice extent.
The raw data provide daily IARC-JAXA shows trend nicely but it is difficult to carry out comparative analysis and examine long term trends. Therefore I have calculated average monthly ice extent for each complete month from July 2002 and used this to prepare rolling averages for the data. NOTE: there are gaps in the daily data of up to 11days especially during 2002 to 2004. In these cases the gaps have been filled in using linear interpolation; I do not believe that this has affected the monthly averages in any significant way. The resulting data is as follows:-
For all graphs and tables, click them to obtain larger images.
These data contain a number of interesting observations. All the lowest ice extent figures are contained in three clusters: January-June 2006, November and December 2006 and July to September 2007. By contrast all the highest figures, bar one, are found in 2002/2003. Looking at the monthly averages over the whole period it is remarkable how little variation (Std.Dev<3%) there is apart from the period July to October. This is illustrated by the following graph
Using the above data to compute monthly 12 month rolling averages shows some very interesting trends. Considering just the period July 2003 (the first 12 month average) to September 2007 this shows the following trend:-
It is apparent that there appears to be a strong correlation between the average ice extent and time as illustrated by the high correlation coefficient (0.9232). You might have concluded in September 2007 that this was indeed strong evidence that long term warming was taking place and you might also be concerned that it appeared to accelerating in the later months. This is just the conclusion that our AGW “friends” have reached assuming that these data can be extrapolated. However, when you consider the later data you might change your mind as show by the next graph covering the period September 2007 to September 2009 which shows the following trend:-
These data show an entirely different picture. Whilst there is still a strong trend between the average ice extent and time (correlation coefficient 0.9185) it is precisely in the opposite direction!
These two graphs illustrate the folly of assuming that correlations are a proxy for understanding the underlying science and can be used to make predictions of the future. In fact these sorts of correlations are useful in understanding what has happened in the past and might be used as a starting point to identify the science but have little or no value in making long term projections. You can’t drive safely down the highway by looking in the rear view mirror!
The trend over all the data is as follows:-
The fitted polynomial is of no significance other than it fits the data best with a good correlation coefficient (0.8982). The curve, as one might expect, does predict the period, by differentiation, when the lowest recorded ice extent occurred – between the 16th and 18th of September 2007. This picture is also carried forward in a two year rolling average:-
Again I don’t believe that the polynomial itself is of any significance other than to illustrate trends. However, this analysis does highlight that there would appear to be something unusual about the period January 2006 and October 2007 when all the lowest ice extents occurred. This has quite a large effect on the graphical data which shows much larger swings during this period. It is also interesting that the graphical data seems to show short term cycles which is particularly apparent again over the period 2006-2007.This latter phenomenon might be an artifact of the analysis or the data but might be worth further investigation.
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But I think it is possible that the past can predict the future. We just need to input enough data to allow the possibility of statistically discovering predictability within an acceptable significance level. Just like they do with the PDO statistical models.
“You can’t drive safely down the highway by looking in the rear view mirror!”
How ironic, the IPCC using a binocular (computer modelling) to drive, and refuse to see what has happened in the past. Their binocular has a build in colour filter when you turn it around or try to use it near site (present).
I have been trying to make the same point over at CA for a while. People keep saying that 2009’s ice, while the minimum is greater than recent past minima, still brings the “trend” down. I have been trying to get across the notion that yeah, that might be true. And the trend from 25,000 years ago is down too. But there is a new trend of if you measure since 2007, the trend is up. Trends change. There are at least three different trends visible since 1979. One flat, one steady down with a drastic down during the wind anomaly of 2007, and then a trend up in recovery.
Oh, and so far I expect 2010 to be near 2006 levels.
Saw this today, dated August 2008;
http://www.watoday.com.au/environment/as-the-ice-gives-way-a-great-arctic-mystery-may-be-solved-20080803-3pa9.html
I wonder what the current state of the site is?
Exactly how did you calculate the rolling average, for July 09 as an example?
Correlation to a smoothed function is pointless.
Various climate studies fall apart on that point.
It is visible here as well: except the 2007 and 2008 summer extremes, the trend looks reversed: http://blog.sme.sk/blog/560/195013/arcticamo.jpg
To built whole warmmongering on single 30 year trend, ts ts ts…
MikeN (23:02:47) “Correlation to a smoothed function is pointless.”
False, but interpretation differs.
Funny that Sunspots seem to move in the same manner
“”Juraj V. (23:47:04) :
To built whole warmmongering on single 30 year trend, ts ts ts…””
Right. Who started it?
Rather than correlate against time, it would be interesting if someone correlated ice extent versus wind direction. The ice extent seems unrelated to the Arctic temperature; the Danish temperature record doesn’t seem to show an abnormally warm Arctic in 2007. When the ice gets blown out of the Arctic into the North Atlantic, that’s when the melting gets going.
Remember, the CO2 makes the wind heavier, so it blows the ice more. 😉
HarryG (00:49:14) :
Funny that Sunspots seem to move in the same manner
Yeah: more spots, more ice…
Phil
Exactly how did you calculate the rolling average, for July 09 as an example?
The rolling average is the average for the period June 2008 to July 2009. Just labelled July 2009 for convenience. This is calculated from the monthly averages in the initial table
From this one can see that applying deterministic rules to Arctic Sea ice is at best not helpful. Even looking at the AMSR-E Ice trend graphic it is possible to sea that the ice extent for any given month is no indication of what the trend will be. Perhaps it might be possible to get a five day forecast as with the weather, using Air Pressure, Wind strengths and directions, Air & Water temps. It is patently clear that just using ice extent or ice thickness is not useful to forecast for where the ice will be next with any precision. So far the prediction that less multi-year ice will lead to less summer ice is not holding up.
In addition the affect of polar ice on global climates may be dependant on many factors, so that at any time Polar ice can be:
(a) A driver of surrounding climates
(b) Driven by surrounding climates
(c) Independent of surrounding climates
For example consider that this year ice extent in Antarctica was greater than ever, while Australia experienced a winter heat wave. Which is driving which?
Pamela Gray (22:17:15) :
But I think it is possible that the past can predict the future. We just need to input enough data to allow the possibility of statistically discovering predictability within an acceptable significance level. Just like they do with the PDO statistical models.
I think you are right but there is a tendency to over extend projections and yes it does depend on the amount and quality of the data. I would be happy to predict say one or two points into the future i.e I think October 09 and November 09 will continue to support the trends in the graphs but I don’t think it is reasonable to project years into the future without a clear understanding of the underlying science
Tony Berry
Well…
The most recent warm leg of the PDO pretty well coincides with the satellite record of polar ice. If polar ice extent trends are driven by changes in cloud cover that follow (or cause) the PDO cycles… The Arctic sea ice extent should exhibit a declining trend and Antarctic sea ice extent should exhibit an increasing trend during the warm phase of the PDO. And guess what happened from 1979-2007?
Arctic sea ice extent declined while Antarctic sea ice extent expanded.
Now that the PDO is negative, low cloud cover is increasing, “global” temperatures are cooling and Arctic sea ice extent is growing… Antarctic sea ice extent should start declining.
So, within a few months to a few years, the Gorebots’ predictions of an imminently ice-free summer Arctic will be replaced by predictions of an imminently ice-free summer Antarctic.
Eventually, the scientific community (and hopefully the public) will figure out that the “climate Cassandra” predictions are essentially nothing more than spending the daylight hours predicting night and then spending the nights predicting imminent mornings… With each dawn and dusk being the latest unprecedented climate catastrophe.
Each and every change in the PDO since the end of the Little Ice Age has resulted in a media (and scientific) frenzy… Fire and Ice: Journalists have warned of climate change for 100 years, but can’t decide weather we face an ice age or warming
Maybe, this time… The Gorebots’ cries of “wolf” will be exposed for the fraud that it has been for more than 100 years. Then they’ll move on to the next bit of carbon fraud: Ocean Acidification.
I think the Spam filter might have just grabbed my last comment.
Doesn’t the monthly average ice extent by year graph establish essentially no trend for the period since 2002?
Pamela, you’re right……… Unless our system is chaotic, and this is highly probable…
In the study noted below The authors confirmed that the Arctic
warmed during the 1970–2008 period by a factor of two to
three times faster than the global mean but the reasons was not be entirely anthropogenic but due to the AMO pattern. Watch for the ice to come back as the AMO returns to the cool or negative mode
Here is what they said: in the opening paragraph.
Understanding Arctic temperature variability is essential
for assessing possible future melting of the Greenland ice
sheet, Arctic sea ice and Arctic permafrost. Temperature trend
reversals in 1940 and 1970 separate two Arctic warming
periods (1910–1940 and 1970–2008) by a significant 1940–
1970 cooling period. Analyzing temperature records of the
Arctic meteorological stations we find that (a) the Arctic
amplification (ratio of the Arctic to global temperature trends)
is not a constant but varies in time on a multi-decadal time
scale, (b) the Arctic warming from 1910–1940 proceeded
at a significantly faster rate than the current 1970–2008
warming, and (c) the Arctic temperature changes are highly
correlated with the Atlantic Multi-decadal Oscillation
(AMO) suggesting the Atlantic Ocean thermohaline
circulation is linked to the Arctic temperature variability on
a multi-decadal time scale.
http://www.lanl.gov/source/orgs/ees/ees14/pdfs/09Chlylek.pdf
OT–
when is Spencer’s September UAH anomoly due?
Thanks for the stats and info. Good stuff.
Slightly OT … just a sample of spin doctoring sea ice stats by the eco crowd.
A few weeks ago up here in Canackistan (Canadia…one of the colonies ☺ ) there was a media item in which some eco-weenie had conceded that sea ice had indeed gone up a wee bit, BUT (he went on to say) “…the sea ice if the past 12 months was below the 1970 to 2000 average.” And naturally most people think that is BAD.
But golly gee, [given a normal distribution] approx. one half of the annual sea ice areas (from 1970 to 2000) were also below the average for the period. Folks don’t get stats with natural systems.
Great set of graphs. Thank you for taking the time.
Clive
Alberta, Canada
Dave Middleton (04:50:42) ,
Very well put. All we are seeing is sea ice responding exactly as it should to the strong influences on climate of the PDO.
Nice to have someone look at these graphs that have become a daily fodder.
Does Dr Berry have an affiliation he can share with us; so we know where he’s from; no biggie, just curiosity.
What has interested me Dr Berry in the last few weeks has been watching the 2009 refreeze take off and the apparently stall, so that it recrossed below the 2005 curve, and looks to cross below the 2008 curve.
Meanwhile the DMI arctic temperature graph has those two quite striking upticks; and that leads me to query whether that temperature stall is a direct cause of the ice slowing down; or for that matter might the causal relationship be the other way round ?
We read a lot of talk about the climate effect on the Arctic ice; but what about the Arctic ice effect on the climate.
Anyhow Dr Berry, if you have some insights on what has been happening the last few weeks since the refreeze started; there’s at least one person here interested ; not that I want to distract from your longer term studies you report here.
George
Wouldn’t it make more sense to fit the curves against harmonic functions of some sort? That might have some sort of plausible predictive value. If we use a line we get the oceans boiling away in a few years — if we use a higher order polynomial we will all freeze…