Dave in a comment on my Electra California post, a couple of posts below, said that Electra probably had missing data causing the yearly averages to be so bad and so varied. In that post, the readers of this blog will recall, I showed that there were changes of yearly temperature average of over 10 deg F. Dave thinks it is an artifact of missing data. So, I downloaded the monthly data from CO2science.org and here are the plots for each month, from 1960 to 1994 (all plots say 2006, but the data only goes to 1994). As you peruse each picture notice that post 1985 there are sharp spikes in the average monthly temperature. These spikes are what causes the spikes in the annual data. Note the size of these amazing temperature jumps in the raw data. The data is crap, yet this is what we are using to calculate how much the temperature has warmed. Note that there are no missing numbers, as Dave claims
Ok, we see the jumps in the monthly temperature. So, lets check to see if the night time temperatures are missing. If so, then the cooler minimums would be gone. They wouldn't be hot. What we find when we look at the minimum and maximum temperatures for the months which have these mysterious jumps of many degrees is that it affects both max and min temperature. Here are some examples. First again, July Mean. Notice in the 2 pictures below the mean that I have July min and max and the same two weird jumps in the later years are in both the max and the min.
Same thing for November. First the mean picture followed by the min and max. Same weird jump in temp affects all datasets.
Whatever the source of these jumps in the record, it is affecting not only the mean but also the maximum and minimum temperature. That says something environmental, something next to the thermometer is screwing up the reading. It isn't missing data as Dave says.
I say again, the data is crap. It can't be used for the purpose the Historical Climate network says it is used for, i.e. to measure the subtle change in the earth's global temperature. And if you think this data can be fixed, go look at the Chinese data here