CRU’s Arctic fix

New Stations Kyrgyzstan

How 2005 & 201o got “ranked” the warmest years.

The new temperature data from  CRUTEM4 has added 628 new weather stations, including strangely enough over 50 from Kyrgyzstan. Most  of these stations are in far northern latitudes. There are none in the Southern Hemisphere. The general perception is  that the greenhouse effect is a global phenomenon and  all parts of the world will experience  “climate change”. However GISS, UAH and Hadcrut trends show recent larger increases in the Arctic.  Antarctica on the other hand shows little sign of any warming. The Arctic is surrounded by land masses and this is precisely where the vast majority of  the new station data have been added by CRU. CRUTEM4 has significantly increased sampling across the (still very cold) Arctic borders. The best way to see this is through the effect it has on global average temperatures. I will ignore  all the counter-arguments as to why  “global” temperatures cannot be shown. These are the temperatures to which  the station anomaly measurements refer and  reflect their geographic distribution. Figure 1 shows the area averaged temperatures for CRUTEM3 compared to CRUTEM4.

Fig 1: CRUTEM4 and CRUTEM3 annual average temperatures. Note how including the arctic stations has reduced the average temperatures in the northern hemisphere. Note also temperature spike in 2009.

The effect of adding so many Arctic stations is to essentially  drop the average temperatures in the northern hemisphere by up to 1-2 degrees C. This is accentuated during  recent years where more of the stations have data. What effect does all this have on the temperature anomalies ? The anomalies for CRUTEM4 will naturally tend to increase slightly over CRUTEM3 for two reasons.

1. The addition of stations in an area which is already known to show  strong warming will lead to  a higher global average anomaly as  available grid points get filled in preferentially there.

Concentration of grid points and land masses close to the North Pole

2. The density of grid points in a 5×5 degree grid increase rapidly as we get closer to the poles. In fact if you stand near  the north pole and simply walk around it you will then pass through 75 grid points. This means that there are far more grid points available in which to place new stations than for example at the equator. Furthermore because there is so much land area close to the north pole there are stations nearby unlike at the south pole. It is true that the area averaging does weight according to  latitude. However CRUTEM4 has filled as many grid points as possible just near the north pole. It is clear that this is the explanation as to why  the post 1998 anomalies have increased sufficiently for 2010 to become the “warmest year”, although within errors this is anyway meaningless. A detailed comparison of the anomalies after 1994  is shown in Figure 2.

Fig 2: Detailed comparison of temperature anomaly results from CRUTEM4 and CRUTEM3.

To look further into this  I compared missing grid points between CRUTEM3 and CRUTEM4. A missing grid point is simply one single 5×5 cell which does not contain any stations. There are 2592 cells in a 5×5 degree world grid of which perhaps 65% contain just ocean. If all available land points were covered with stations then there would be an ideal minimum of  ~1700 missing cells. Figure 3 shows the actual number of missing cells per year (and month) for CRUTEM3 and CRUTEM4.

Figure 3: Missing cells versus year for CRUTEM3 and 4. Note spike in 2009.

The geospatial changes can be seen in more detail by comparing the ratio of sampled cells from the tropics (LAT < 25) with those at large latitudes (LAT >25) – see Figure 3.

Fig3: Ratio of sampled cells from the Tropics (LAT<25) and higher latitudes

CRUTEM4 accentuates further the sampling bias away from the Tropics.  It is pretty clear that  oversampling of  the arctic region  leads to an  increase in the “global” temperature anomaly, as is now “measured” with CRUTEM4.  However,  it should be remembered when reading various press releases and news headlines that  the error on  a single annual anomaly value is ~ 0.1 deg.C , so statistically it is meaningless to state that 2010 is warmer than 1998 or vice versa.

P.S. I wonder what is the real origin of  the spike in 2009?  Why did  so many of the new arctic stations suddenly  disappear that year ?

About Clive Best

PhD High Energy Physics Worked at CERN, Rutherford Lab, JET, JRC, OSVision
This entry was posted in AGW, Climate Change, climate science, Science and tagged , , . Bookmark the permalink.

9 Responses to CRU’s Arctic fix

  1. P. Solar says:

    Clive, in view of their past misdeeds I don’t trust UEA’s CRU any further than I can throw them. However, I think it is important to assess what they do with and open, critical mind, not to* assume* they are rigging the results before starting.

    “The new temperature data from CRUTEM4 has added 628 new weather stations, including strangely enough over 50 from Kyrgyzstan. ”

    Where is Kyrgyzstan and why is that “strange”?

    One of the big problems was under representation of these high N latitudes. This addition could potentially be a big improvement. It may also be useful in showing how misleading Hansen’s speculative polar extrapolations are.

    One key feature you don’t seem to notice in your haste to blast CRU is that this release shows considerably less NH and global warming post 1980. That may be very important.

    The 2009 peak looks like there is some quality control problem. I’m surprised they published something with such an obvious anomaly unless they deal with it explicitly in the paper and maintain it is real. You are correct to point this out, it looks problematic.

    If you want to look at “ranking” this spike does not explain 2005, you should be looking at the way 1920-1940 got cooled rather than the end of the record.

    Keep digging.

    • Clive Best says:

      I didn’t intend to give the impression that CRU had somehow “fiddled” the result. I suspect they may have been under pressure to bring the anomalies into line with GISTemp and NCDC, and therefore added stations . My main point is that by concentrating on filling grid points at high latitudes, rather than in Africa and South East Asia, the global anomaly will not be fully representative. There are still many empty grid points in Africa. Since in addition, we know that the Arctic has shown greater warming in recent years then this geographic bias will tend to increase the global anomaly slightly.

      The Kyrgyzstan story is just a joke. If you look at the world map of new stations here , you will see a large cluster of new stations around Kyrgyzstan. I have no idea of the reason. Turns out many of them are at high altitude and rather cold.

      I think the biggest problem is under-representation of stations in Africa and around the tropics, rather than the Arctic. It is deceptive looking at mercator type projections and linear lat,lon grids. The is a much larger swath of empty land area in Africa and the tropics than in the Arctic.

      What you say about the full timespan from 1900-2010 is true. However, overall the difference between CRUTEM3 and CRUTEM4 looks to be well within statistical errors. There are anyway systematic problems with the early data. The way the monthly normals are calculated can effect the “anomalies”.

      The ranking was done by the MET office who gave a press release that changed the ranking of yearly temperatures – so 2010 is 0.01 +- 0.1 deg.C warmer than 1998 – which would fail the A-level statistics exam.

  2. P. Solar says:

    PS. Once the result is area weighted, more samples should be better as long as they have proper QC. I don’t think that you have “shown” as you claim that high lats are “over-sampled”. what does that even mean? Neither do I think you have shown

    fig 3 does not seem to show what you think. (Lat25) is 65 degrees!

    How about plotting (lat65) ??

    • Clive Best says:

      I was thinking of a sphere. The surface area of the Earth covered by LAT= +25 to -25 is roughly the same as that covered by 2*(LAT 90-25). In addition it corresponds more or less to the Tropics.

      Regarding the area weighting – yes if done properly it should not matter. However sometimes there is just one station inside a single grid point, covering 1000’s of km^2.

      • P. Solar says:

        Clive, I did not realise your <25 was calculated on area, fair enough, I withdraw my comment on that.

        "Since in addition, we know that the Arctic has shown greater warming in recent years then this geographic bias will tend to increase the global anomaly slightly. "

        I still don't get your point. If there is area weighting there is no "bias" . All the extra stations can do is remove any spurious bias due to extrapolation and in-filling. As you point out this region is reckoned to warm more than others so getting more real data in there will _prevent_ bias not induce it.

        'I didn’t intend to give the impression that CRU had somehow “fiddled” the results'

        I would not be too shy about that. They have shown they have not problem with "hiding" data they find inconvenient and laugh amongst themselves about doing so.

        The added warming through out the last 10 years and slight pull down on 1998 looks like more of the same to me.

        If you can't fix the model , fix that data !!

        • Clive Best says:

          I still don’t get your point. If there is area weighting there is no “bias” . All the extra stations can do is remove any spurious bias due to extrapolation and in-filling.

          Actually they DON’T do any extrapolation or infilling at all! Grid points with no data are ignored and are left out of the global anomaly! I have their software so I am sure of this. As a result most of the Sahara, whole swathes of Africa and Asia are simply ignored. So by adding stations only in the Arctic they have increased slightly recent global anomalies but as a consequence the NH area averaged temperature has dropped by 1 deg. C.

  3. P. Solar says:

    Oh , WP is a crock of shit. The last post contained less-than and greater-than signs so it has screwed it up completely.

    My point is that you are not comparing comparable bands , try plotting lat .lt. 25 and lat .gt. 65

  4. Clive Best says:

    WP can be frustrating with any mathematical symbols !

    I am beginning to think there could be an inverse correlation between surface humidity and temperature anomaly. Arctic air has very low water vapor content, as does the Sahara. Both regions show more warming than humid tropical regions. This implies a slightly negative feedback from water vapor with CO2 forcing. See also this.

  5. I’m new to your posts but will read with interest as time permits. Thanks for writing these. The lunar post on climate was quite interesting, along with this one. I’m curious if you have noted, as I do, that satellite reanalysis temperature data covers the full surface of the planet for 40 years. This coverage does appear to reflect warming in the northern hemisphere but cooling in the southern one. And amplification for each polar section. The ECMWF data, for example, is already extensively ground-truthed. So there is no point it seems to produce official temperature statements based on arbitrary collections of land surface data, while ignoring the satellite data. It does seem deliberate in my view, and I sometimes cringe when reading reports of NASA GISS, or BEST results as if they were from satellite observations.

    Moreover, I’ve done spot checks on Antarctic station temperature data, and they don’t align with expectations from pressure data. Here’s an example at my site.

    I’m working with a team of other scientists on stability analyses of global climate trends including winds, temperatures, atmospheric moisture, divergence of latent heat, CO2, and ozone. These are complemented by streamflow records and of course Solar records, along with separate exercises on evaporation and stable isotopes and some attention to surface upwelling of dissolved inorganic carbon along with ocean pH and other trends. Accordingly, I’ve helped to build a large set of datasets that are often featured at my site and in peer reviewed literature such as this paper at Nature Scientific Reports on Covid and climate and pollen.

    You are always welcome to communicate and ask questions or offer suggestions. Just email me and I’ll forward my work email. Cheers, Mike W.

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