The monthly temperature values in over 4000 CRUTEM3 stations have all been continuously changed, and it is these changes alone that have resulted in transforming the 16 year long hiatus in global warming into a rising temperature trend. But all these changes have only affected temperatures AFTER 1998.
The last IPCC assessment in 2013 showed a clear pause in global warming lasting 16 years from 1998 to 2012 – the notorious hiatus. As a direct consequence of this AR5 estimates of climate sensitivity were reduced and CMIP5 models appeared to clearly overestimate trends. Following the first release of HadCRUT4 in 2012 the ‘headline’ that followed was that 2005 and 2010 were now marginally warmer than 1998. This was the first dent in removing the hiatus. Since then each new version of H4 has showed further incremental warming trends, such that by 2019 the hiatus has now completely vanished. Anyone mentioning it today is likely to be ridiculed by the climate science community. So how did this reversal happen within just 7 years? I decided to find out exactly why the post 1998 temperature record changed so dramatically in such a short period of time.
In what follows I always use the same algorithm as CRU for the station data and then blend that with the Hadley SST data. I have checked that I can reproduce exactly the latest HadCRUT4.6 results based on the current 7820 stations from CRU merged with HadSST3. Back in 2012 I downloaded the original station data from CRU – CRUTEM3. I have also downloaded the latest CRUTEM4 station data.
Figure 1 compares the latest HadCRUT4.6 results with the last version of HadCRUT3.
I had assumed that the reason for the apparent trend change was because CRUTEM4 had added many new weather stations in the Arctic (removing some in S.America as well), while additionally the SST data had also been updated (HadSST2 moved to HADSST3). However, as I show below, my assumption simply isn’t true.
To investigate I recalculated a ‘modern’ version of HadCRUT3 by using only the original 4100 stations (used by CRUTEM3) from CRUTEM4 station data. The list of these stations are defined here. I then merged these with both the older HadSST2 and HADSST3 to derive annual global temperature anomalies. Figure 2 shows the result. I get almost exactly the same values as the full 7820 stations in HadCRUT4. It certainly does not reproduce HadCRUT3 !
This result provides two conclusions.
- Modern CRUTEM3 stations give a different result to the original CRUTEM3 stations.
- SST data is not responsible for the difference between HadCRUT4 and HadCRUT3