Digital Diatribes

A presentation of data on climate and other stuff

April 2008 Update on Global Temperature Trends, Part 1

Posted by The Diatribe Guy on April 9, 2008

You can find the GISS temperature anomaly table here.

The March temperature anomaly came in at a value of 81 (1 = .01 degrees Celsius from the average of the base period of 1950-1980). 

This value is surprising in a few different ways.  First of all, the mere magnitude of the jump is significantly higher than normal.   The increase from the February anomaly is 48 (February had originally come in as a value of 31, but has been re-stated to be 33).

I am going to present a series of posts with different data analyses on the GISS temperature anomalies.   But I first want to address this leap in the GISS anomaly.   It is interesting to note that the UAH (University of Alabama Huntsville) and the RSS (Remote Sensing Systems of Santa Rosa) track temperature anomalies as well.   These three sources, along with the HadCRUT anomaly data are the four major sources drawn from.   HadCRUT has not released their data yet, but UAH and RSS have – in fact they released it prior to the GISS data.

Please click on the “Watts Up With That” link on the right of my page to see the presentation of the data from these two sources.  Both showed only a small increase in the March anomaly compared to February.   In fact, the increase was so small, that translating the same relative increase to the GISS data, the expected anomaly would have been around 40.   Needless to say, such a digression from these other two sources in the GISS data leads to questions, the main one being “why?”   It will be interesting to see the HadCRUT data.

I had been keeping tabs on the NOAA weekly temperature anomalies throughout March.   While these are unofficial, they are a good general guide to regional temperature anomalies.   It is easy to forget that other lands exist when you’re in Wisconsin and winter does not seem to want to end.  In fact, we received 4 inches of snow yesterday.  I want spring!    But for those keeping tabs, we knew that Eastern Europe, the Middle East, and Northern Asia had positive temperature anomalies.   Therefore, despite the cold weather in the U.S. and Canada, the UAH and RSS data was not all that surprising, and seemed about right.  Warm weather in one area offset cold weather in another.   The gut check works.

Then comes along the GISS data.   It is simply bizarre.   The explanation of a warm Asia may explain an increased anomaly, but relative to the other measures it does not explain why GISS shows an increase of nearly half a degree Celsius when the two other measures show an increase of a tenth of a degree Celsius.   All three would account for the Asiatic warmth in March, so something else is going on here.

One of my tasks now is to dig into the differences between the measurements.  I plan on that being my next post.   My simple understanding up until now is that GISS is different because it considers the poles.   I could accept this explanation if the anomaly diverges somewhat, but the amount of divergence here seems unsatisfactory for that explanation.   Plus, if you boil it down to region, it is the Northern Hemisphere that went through  the roof in the GISS regional data, so we can’t even seem to blame Antarctica.   Are we really to believe that the North Pole in and of itself was so warm in March that it accounted for a 0.4 C adjustment on a global basis over the other measures?    The gut check does not work here.

Now, I openly admit that I have purposely not become involved in the fine details of the differences between all the temperature measures.  This will be a learning exercise for me.   But, as an actuary, I am trained to question outliers in the data.  Barring a similar surprise from HadCRUT, GISS is clearly an outlier.   This demands a better understanding of the data.

OK, I’ve said my piece on that.   We’ll revisit the details once I’ve looked into them a bit more.   Now, let’s just look at the data as it stands, understanding the questions behind it.

The March anomaly of 81is the highest anomaly since February 2007.  It is tied for the third highest March anomaly on record.  The latest 12-month average anomaly is now 63.4, which is higher than the previous 12-month value of 62.8, since the March 2007 anomaly was 74.   An anomaly of 81 is the 13th highest anomaly on record for ALL months since January 1880.   So, while I really am trying to maintain an objective focus on the data, it is simply difficult for me to grasp these results given my own anecdotal observations, given a continuing La Nina that everyone agrees exists, given the NOAA weekly temperature anomalies (which, by the way, showed negatvie Sea Surface anomalies as well), and given the results of the other indices.    But I shall try to maintain my focus.   (As an aside, the GISS data has long been under the critical eye of skeptics, because this is not the first time such anomalies have surfaced.   Check Watts for different discussions on some of the issues with the averaging of temperatures, which adjust temperature history.   Plus, their lead researcher – affectionaltely referred to as Hansen – is known to be a proponent of Anthropogenic Global Warming.   I would not say he massages the data because I have no basis for such an assertion.  Some have suggested it, however, and I only note it here as a point that has arisen in the debate about global temperature trends.   It is unfortunate that we cannot have a consistent basis of objective measurement that is widely agreed upon by AGW proponents and AGW skeptics alike).

Now, let’s take a closer look at this significant jump from February to March.   The anomaly jump of 48 represents an average anomaly in March that was 0.48 C higher than February.   I thought I woould look at the history of differences in magnitude from one month to another with an absolute value of at least 48 to see how unusual this is.

The first thing to note is that there has not been an increase in the anomaly from one month to another this high since January to February 2000.  So, this is the largest such jump in over eight years.   It was pointed out on another board that, perhaps not coincidentally, that was another La Nina year.  The last positive jump that actually met or exceeded this magnitude was November to December 1939!  So, in this light, the magnitude of the jump is pretty remarkable.

I decided to note all the incidents of a jump in either direction of at least 48.   As I went through this, I found the results very interesting.   Allow me to bore you with the list.   See if you notice what I did…

Month-to-month anomaly differences:
Feb to March 2008: +48
Jan to Feb 2000: +48
May to June 1984: -55
Feb to March 1960: -72
Dec 1939 to January 1940: -53
Nov to Dec 1939: +52
Mar to Apr 1935: -54
Jan to Feb 1935: +54
Jan to Feb 1932: -62
Nov to Dec 1929: -57
Dec 1920 to Jan 1921: +55
Nov to Dec 1917: -53
Jul to Aug 1917: -48
Jun to Jul 1917: +56
Mar to Apr 1906: +52
Feb to Mar 1905: +70
Sep to Oct 1898: -48
Jan to Feb 1898: -58
Oct to Nov 1896: -54
Dec 1894 to Jan 1895: -51
Oct to Nov 1893: -55
Jan to Feb 1893: +73
Dec 1892 to Jan 1893: -101
Feb 1891 – Mar 1891: +59
Dec 1890 – Jan 1891: -50
Mar – Apr 1888: +59
Nov – Dec 1887: +51
Oct – Nov 1887: -51
Feb – Mar 1887: +57
Oct – Nov 1886: +67
Dec 1885 – Jan 1886: -82
Nov – Dec 1885: +61
Oct – Nov 1885: -54
Mar – Apr 1884: -49
Nov – Dec 1883: +52
May – Jun 1883: +56
Feb – Mar 1883: +51
May – Jun 1882: -53
Mar – Apr 1882: -59
Dec 1881 – Jan 1882: +51
Jun – Jul 1881: +81
May – Jun 1881: -107
Dec 1880 – Jan 1881: -50

Now, I probably wouldn’t have had to list all those to make the point, but by my count, we have 4 anomalies that moved a value of 48 from one month to the next in the last 68 years. But then look at what the data shows. There were five such occurrences in the decade of the 1930s, 2 occurrences in the 1920s, 3 occurrences in the previous decade (all in 1917), 2 in the decade before that. Then things really go bonkers. There are 9 such anomalies in the 1890s and 18 occurrences in the 1880s, with at least one such occurrence in every year of that decade except in 1889.

Seeing these numbers, I ran a standard deviation by decade of the temperature anomalies. The 1880s had a standard deviation of 32.02. The 1890s show a standard deviation of 26.66. 1900-1909 have a standard deviation of 19.75, and the 1910s a standard deviation of 22.96. Starting with the anomalies of the 1920s, the standard deviation starts too fluctuate from a low of 14.75 in the 1940s to a high of 20.44 in the 1990s, with the most recent ten-year period showing a value of 16.79.

I present this more as a point of interest, rather than to draw any particular conclusion. It seems reasonable to believe that the further back we go, the less reliable the numbers are. This could be due to both an increase in techological ability to measure temperature as well as an increase in coverage (meaning less estimation in more recent data). So, at some level, there must be a certain amount of garbage (I suppose a nicer term is “noise”) in the older data. This directly speaks to how reliable this older data is. And if called into question, it shortens our observed time period of good data. The other possibility is that the data is reliable, but temperatures actually did fluctuate a lot more during that time period. But it has been suggested to me that one of the impacts of climate change is that we can expect more “extremes.” The suggestion that we are undergoing climate change in the more recent period, and the further suggestion that such climate change means a larger swings in “extremes” seem like contradictory positions given the temperature anomaly data.

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9 Responses to “April 2008 Update on Global Temperature Trends, Part 1”

  1. amaduq01 said

    mm

  2. […] April 2008 Update on Global Temperature Trends, Part 1 […]

  3. […] April 2008 Update on Global Temperature Trends, Part 1 […]

  4. your media said

    Have you fund that the increasing temps in europe force the artic air into the Americas?

  5. Diatribical Idiot said

    I do not know the mechanism by which part of the world was warm and how that related to the cooler part of the world. Clearly, observing the NOAA regional climate data from week to week showed a warmth in that part of the world. How that did or did not related to the cooler areas, I don’t know.

  6. Bob said

    Can leap year have an effect on the March data? Dropping the coldest day (Feb.29th) and adding the warmest day at the end of the Month that would normally be April 1st?
    (at least in the northern hemisphere)

  7. Diatribical Idiot said

    I would doubt that the effect would be all that discernible. As you point out, this would be a Northern Hemisphere impact,p erhaps, but when looking globally it should be offset by the Southern Hemisphere temps.

    But then we should expect to see a corresponding increase in February as it pick up the extra day at the end (warmest). Plus, noting that the trend from year to year is in increments of quarter-days actually makes the additional day only 3/4 a day different from 3 years ago, and 3/8 different from average. Finally, the impact of this additional day gets averaged out over the entire 31 days.

    The warmth in Asia was really the driver for March. My biggest issue with GISS is its deviation from the other measures, and not the fact that there was a higher anomaly. The others seem much more reasonable, given the fact that ocean surface temps just don’t fluctuate that much from month to month, and there was still La Nina, and a majority of the globe is water. The huge jump just doesn’t make a lot of sense. (Noted that the above are Land temps, but the global temps showed the same thing)

  8. […] April 2008 Update on Global Temperature Trends, Part 1 […]

  9. […] […]

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