The more things change, the more they stay the same.
GISS reports updates to the surface temperature analysis regularly (here). In the last year, for example, there has been a change to use of USHCN v2 data for US stations (November 2009), and most significantly the change to using satellite ‘nightlights’ for global evaluation of the urban status of stations in January 2010. The effects checked against previous versions (NASA Draft paper) state that the major change of using ‘nightlights’ results overall in a very small change in global average temperatures. Here, for example are the small differences between January and March 2010 in the GISS Land-Ocean Temperature Index as a result of the ‘nightlights’ changes:
These differences are tiny. This was a change of the land data and the globe is 70% ocean; sea surface temperature is more stable that land temperatures. Looking at land temperatures only, the change still small but it is five times what we saw above:
The changes alter the overall temperature trend by no more than <0.01°C/century, and it bothered me that there is so little change overall. I couldn’t quite put my finger on why until I looked at it in detail. [Peter O’Neill has discussed (here) a number of concerns with the accuracy of locations used and I’ll leave thoughts on that to another day.] Prior to this change only US stations were adjusted using a brightness index, and urban classification for the rest of the world relied on very outdated population figures. Surely, I thought, this change would have had a more noticeable effect. Looking at data for the two hemispheres separately shows up slightly greater change. GISS also publishes data by latitude zone, and the change really does show up in some of the zones. Here’s what the current data split out by latitude zone looks like:
The change by latitude band is interesting. There is almost no change at higher latitudes (Canada, Russia, Northern and Central Europe) but substantial change between 44N and 44S, almost exclusively in older data, prior to 1940. This is not a great surprise actually (more on correction of urban temperatures in a moment).
The differences run to +/- 0.4°C (and these are still averages for each latitude band), but all these zonal changes add up to the average difference (red line) in Figure 2 – there is a lot of ‘cancelling out’ that is masked by the averaged data. At individual locations the changes can be huge and this can be seen in the figure below where location-based anomalies are up to +/- ~3.0°C.
[I almost didn’t notice that the data in Figure 5 was for 1900-2009 only.
The mask on the graph left for data 1880-1900 gives a clue. The most extreme changes are prior to 1900; these are likely to affect a very few stations due to the lesser global data coverage at that point.
What would the anomaly scale in Figure 5 look like if they were included? ]
It amazes me that such profound local changes have ‘no overall effect’, although with the structure of the GIStemp programme I can see how this can be. At one level I do not have a problem with this, but on another level is extremely frustrating. This change is intended to render more accurate the classification of rural and urban stations, and therefore which data records are adjusted for Urban Heat Island correction, and which are rural stations that contribute adjustment. Since the UHI correction is done by warming past temperatures, it is the past that is more substantially changed. Herein lies my problem with it. GIStemp uses only a single designation of the station metadata which is not time dependant. It makes no distinction between ‘what is’ now and ‘what was’ in the past. So a station classified as urban now is regarded as always urban (even if it was rural in the past), UHI correction is applied and this is not a problem. But this does mean that the historical part that was rural, can no longer take part in the correction of other urban stations, and the programme has to reach out further and further to find stations that can do the adjusting (with less and less accuracy).
Looking at the designations of the stations by the new methods (here) and comparing the unadjusted and homogenised stations data (here) there seem to be many ‘quirks’ between what is adjusted and what is not, and this does not always match with the Urban/Semi-urban/Rural classifications listed. I suspect there are many ‘issues’ still being worked out.
My ultimate concern is that the changes really only visibly affect the older temperatures. Once again, we are rewriting the past for comparison with the present and it takes a lot of effort to get this right, which means it is all too easy for gross errors and misrepresentations to slip through. Think about it. GISS is just papering over the cracks with this one.