Homogenisation adjustments (corrections) made to raw temperature records has grabbed my attention. Those waiting for my post on The Sun will have to wait a while. Roger sent me his spread sheet with about 900 carefully logged temperature records and I was eager to compare these records from 2006 with those being used today. In the past, GISS temp used raw temperature records from GHCN V2 but in 2011 changed to using homogenised records GHCN v3.1 as described in the NASA FAQ page (see the Q&A relating to recent “scandal” at the end of the page). That reply also points to the archived version of GHCN V2 and so it is possible to run many checks comparing V2 data with homogenised V3.1 data. An example of deducting V3.1 temperatures from V2 temperatures is shown below for Sydney. It should be clear why this grabbed my attention. Homogenisation has warmed the past by 1˚C and adjusted virtually all the data.
It has been argued that Paul Homewood got lucky stumbling upon a handful of adjusted records in S America and that there is no wider issue. Roger’s records tell a different story but I wanted to find out for myself how widespread the adjusted records are and spent the morning comparing V2 with V3.1 records selecting stations pretty well at random though I biased selection to stations with long records. In his earlier post Roger observed that about 600 N hemisphere raw temperature records were closely aligned with GISS temp that uses homogenised data. The raw southern hemisphere records, however, did not suggesting that homogenisation introduces more bias in the bottom half of the world. Hence, I have only looked at S hemisphere records in this post. 11 pairs of records are shown below the fold that show highly variable degrees of adjustment.
All stations have visible adjustments. I didn’t keep count, but estimate that about 50% of the stations I looked at had only small adjustments while the remainder which are presented below have significant adjustments. This is certainly not an issue isolated to a handful of stations in Central America. The first station below (Santa Cruz) is included as a station that shows no / only small adjustments. The other 10 stations all show significant adjustments. In each pair of charts the GHCN V2 raw record is shown above the homogenised GHCN V3.1 record.
Santa Cruz Ae. V2 top, version 3.1 bottom. This is about as good as it gets where the effect of homogenisation is hard to spot. But even here the spike down around 1940 has been homogenised out of the data. Unadjusted top, adjusted bottom.
Capetown S Africa. The longest record in V2 begins in 1880 and has two marked discontinuities around 1910 and 1960. The V3.1 record with the same reference number (141688160000) begins in 1943. The warm past has been eliminated and the pre-1960 data appreciably cooled which creates a warming trend. Unadjusted top, adjusted bottom.
Pamplemousses is on Mauritius. At first glance the V3.1 homogenisation has removed the warming trend in V2. But take a look at the Y-axis scale. V2 data ranges from 22.2 to 24.0˚C. The version 3.1 data ranges from 23 to 24.4˚C. A significant amount of warmth has been added. Unadjusted top, adjusted bottom.
Pretoria S Africa. The warming trend of V2 has been totally removed by homogenisation. This could be to correct for urban warming? This has been achieved by warming the past and not by cooling the present. Again look at the big difference on Y-axis scales. Unadjusted top, adjusted bottom.
Durban S Africa. The V2 record begins in 1880 and has a major cooling around 1940 that may be associated with a change in environment. The version 3.1 record has the same name but different ID number begins in 1950. Again, like Capetown the warm past is simply eliminated. Unadjusted top, adjusted bottom.
Buenos Aires, Argentina. The V2 data shows a clear warming trend that again may reflect urban warming that is partly removed by homogenisation. For some reason the pre-1900 data, that look perfectly reasonable, are dropped. Note Y-axis scale again, the past has been warmed. Unadjusted top, adjusted bottom.
Punta Tortuga Chile. The V2 and V3.1 data are not recognisable as being the same record. Enough said. Unadjusted top, adjusted bottom.
Punta Arenas, S Chile. The V2 data is flat to gently cooling. The homognenised data is gently warming. Note how the post 1900 spike down has been moved to become a pre 1900 spike. Unadjusted top, adjusted bottom.
Faraday is in the deep south of S America. V2 shows a clear warming trend that is removed by homogenisation. But look at the Y axis scale. The original is -1 to -8˚C, the V3.1 is 0 to -6˚C. It looks like a couple of degrees has been added. Again, these are not recognisable as the same records – different trend and different scale. But the spikes show they are based on the same data. Unadjusted top, adjusted bottom.
Hokitika airport, N Island New Zealand. V2 is basically a flat trend. V3.1 introduces a warming trend. Look at the pre-1910 data which has wholesale been moved down by about 1 degree. Unadjusted top, adjusted bottom.
Onslow, NW Australia. The original data shows a gentle warming. The homogenised data has appreciably cooled the past and introduced significant recent warming. Unadjusted top, adjusted bottom.
- Most / all records are adjusted, some more than others
- Sometimes a warming record is flattened. Other times a flat record turned into a warming record. I did not come across a flat or warming record turned into cooling.
- A common adjustment is to cool the distant past.
- Some records, for example Faraday have simply had temperature added – approaching 3˚C.
- Durban and Capetown have had a warm distant past deleted (this may be valid).
It is maintained that homogenisation does not significantly distort the global temperature record although it has added about 0.3˚C warming, mainly through cooling the distant past. If homogenisation makes such little difference, why do it? This simply serves to sow suspicion in sceptical minds. Whilst at one level I can accept the need to correct records where a justifiable cause is identified and understood. I find it equally hard to accept that automated wholesale adjustment is justified. I would like to hear the physical science explanation for adjustments made to the Sydney record posted up top.