Andrew Revkin asked me to provide comments on this article of his where the National Climatic Data Center was asked to respond to Watts et al 2012:

A Closer Look at Climate Studies Promoted Before Publication

Here is what I sent to him:

My comments on Thorne’s response are pretty simple.

They still refuse to get out of the office, to examine firsthand the condition of the network and try to come up with hands on approaches for dealing with station inhomogeneity, but instead focus of trying to spot patterns in data and massage it. In my view this is the wrong approach and the reason that we are in this polarization today. We are conducting a grand experiment, and like any scientific experiment, you have to carefully watch how the data is being measured in the experiment environment, or problems will invalidate the measurement. If Climate Science operated under the same rules as Forensic Science, the compromised data would be tossed out on its ear. Instead, we are told to accept it as fully factual in the court of public opinion.

Until I came along with Watts 2009, they really weren’t looking closely at the issue. The SurfaceStations photography forced them into reaction mode, to do two things.

1. Close the worst USHCN stations, such as Marysville, CA (the station that started it all), Tucson, AZ (the University Science Dept/Weather Service Office that had the USHCN weather station in the parking lot), and Ardmore, OK (the USHCN station on the street corner). There are many others that have been closed.

If they are able to correct the data gathering problems back in the office with algorithms, why do they need to close these stations? Additionally, if they think they can get good data out of these stations with the myriad of adjustments they perform, why did they need to spend millions of dollars on the new Climate Reference Network commissioned in 2008 that we never hear about?

According to communications I received from Texas State Climatologist John Nielsen-Gammon, the National Weather Service is developing plans to eliminate up to half of all COOP network stations (of which USHCN is a subset) as a potential cost-cutting measure.

Some possible reasons: (1) not central to the core mission of the NWS; (2) poor data quality; (3) too much of a public relations headache with people putting embarrassing photographs online.

I would argue not for removal of bad stations, but rather for the replacement of bad stations with well-sited stations, with simultaneous overlapping data collection so that biases can be both measured directly and permanently eliminated. I don’t see anything in what they are doing with Thorne that addresses this. To me, all they are doing is trying to put lipstick on a pig.

2. Attack me without publishing an appropriate paper intended for peer review first, such as the ghost authored “Talking points” memo issued by NCDC’s Dr. Thomas Peterson, who wouldn’t put his name on it, yet circulated it to every NOAA manager and the press. If the data from these stations is so strong, and the adjustments and corrections so valid, why the cloak and dagger approach?

Note, that in the Thorne response, they carefully avoided saying anything about station siting, preferring instead to focus on data manipulations. From my viewpoint, until they start worrying about the measurement environment in which our grand global experiment is being measured, all they are doing is rearranging data without looking at and learning from the environment and history that created it.

Perhaps they should follow the advice of the General Accounting Office report that backed up my work:

GAO-11-800 August 31, 2011, Climate Monitoring: NOAA Can Improve Management of the U.S. Historical Climatology Network Highlights Page (PDF) Full Report (PDF, 47 pages) Accessible Text Recommendations (HTML)

Finally, let’s spend a few moments looking at another network in the USA that doesn’t seem to suffer from the same sorts of magnitude of issues. The U.S. Population-Adjusted Temperature Dataset (PDAT) developed by Dr. Roy Spencer, which better handles UHI.

The following plot shows 12-month trailing average anomalies for the three different datasets (USHCN, CRUTem3, and ISH PDAT)…note the large differences in computed linear warming trends (click on plots for high res versions):

Where’s the warming?

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