In my post December 1986, I presented a histogram showing the GISS estimate of December 1986 minus the actual for GHCN stations in Europe and Russia. As noted, GISS under-estimated December 1986 for this region by a greater than 2 to 1 margin. The result was, when GISS combined multiple records for a single station, the stations with a cold estimate for December 1986 had their records artificially cooled pre-1987. By cooling the older record and leaving the current record unchanged, an enhanced warming trend was introduced.
I promised I would show other regions of the world in future posts. Therefore, in this post I present Africa, which essentially shows polar-opposite results from Europe / Russia.
In Africa, GISS tends to over-estimate December 1986 when combining records. Because the temperature is over-estimated, older records must be warmed slightly before they are combined with the present record. By introducing artificial warming in a past record, the overall trend through the present is cooled.
Following is a histogram showing the GISS estimate of December 1986 minus the actual for GHCN stations in Africa.
The implication is that the GISS algorithm introduces a cooling trend to most African records.
As can be seen in the next plot, however, the number of stations reporting temperature data in Africa drops off rather sharply before 1950. This means any warming of past records likely does not go very far back in time.
We need to peek backwards some and see how many of the “warmed” station records actually exist before 1950:
As can be seen from the table above, prior to 1950 the “cooled” stations tend to outnumber the “warmed” stations. In other words, from roughly 1950 to 1986, GISS artificially warms the African records, and prior to 1950 it artificially cools the records. Granted, we are not talking about a lot of stations here, but it does give one whiplash from all of the double-takes.
As was pointed out in several comments to December 1986, the average bias for that month, while negative, was not particularly large. Furthermore, the value would end up being divided by 36 or 48 in order to yield the adjustment amount. See here and here.
The same is of course true of Africa. The implication in both cases is that the net adjustment ends up being so small that we won’t see it at the global or perhaps even zonal level. This might indeed be true. Whether the trend is enhanced or not does not necessarily mean the trend is not there. At the macroscopic level the adjustment may not matter at all.
Nevertheless, I find it rather amusing / interesting / ironic that as I go back in time and look at the average bias adjustment of African stations, the cooled stations not only outnumber the warmed stations, but they far outweigh them when averaging the adjustment. This comes in spite of the fact that most of the records get the warming bias.
Here is what I mean: