OK, acknowledging that Goddard made some analysis errors, I am still left with some uneasiness about the actual data, and why it keeps changing. For example, Jennifer Marohasy has been writing about Corrupting Australian’s temperature record.
In the midst of preparing this blog post, I received an email from Anthony Watts, suggesting that I hold off on my post since there is some breaking news. Watts pointed me to a post by Paul Homewood entitled Massive Temperature Adjustments At Luling, Texas. Excerpt:
So, I thought it might be worth looking in more detail at a few stations, to see what is going on. In Steve’s post, mentioned above, he links to the USHCN Final dataset for monthly temperatures, making the point that approx 40% of these monthly readings are “estimated”, as there is no raw data.
From this dataset, I picked the one at the top of the list, (which appears to be totally random), Station number 415429, which is Luling, Texas.
Taking last year as an example, we can see that ten of the twelve months are tagged as “E”, i.e estimated. It is understandable that a station might be a month, or even two, late in reporting, but it is not conceivable that readings from last year are late. (The other two months, Jan/Feb are marked “a”, indicating missing days).
But, the mystery thickens. Each state produces a monthly and annual State Climatological Report, which among other things includes a list of monthly mean temperatures by station. If we look at the 2013 annual report for Texas, we can see these monthly temperatures for Luling.
Where an “M” appears after the temperature, this indicates some days are missing, i.e Jan, Feb, Oct and Nov. (Detailed daily data shows just one missing day’s minimum temperature for each of these months).
Yet, according to the USHCN dataset, all ten months from March to December are “Estimated”. Why, when there is full data available?
But it gets worse. The table below compares the actual station data with what USHCN describe as “the bias-adjusted temperature”. The results are shocking.
In other words, the adjustments have added an astonishing 1.35C to the annual temperature for 2013. Note also that I have included the same figures for 1934, which show that the adjustment has reduced temperatures that year by 0.91C. So, the net effect of the adjustments between 1934 and 2013 has been to add 2.26C of warming.
Note as well, that the largest adjustments are for the estimated months of March – December. This is something that Steve Goddard has been emphasising.
It is plain that these adjustments made are not justifiable in any way. It is also clear that the number of “Estimated” measurements made are not justified either, as the real data is there, present and correct.
Watts appears in the comments, stating that he has contacted John Nielsen-Gammon (Texas State Climatologist) about this issue. Nick Stokes also appears in the comments, and one commenter finds a similar problem for another Texas station.
Homewood’s post sheds light on Goddard’s original claim regarding the data drop out (not just stations that are no longer reporting, but reporting stations that are ‘estimated’). I infer from this that there seems to be a real problem with the USHCN data set, or at least with some of the stations. Maybe it is a tempest in a teacup, but it looks like something that requires NOAA’s attention. As far as I can tell, NOAA has not responded to Goddard’s allegations. Now, with Homewood’s explanation/clarification, NOAA really needs to respond….
(H/T to Climate Realist ~ See WUWT and Hockey Schtick for more)