"It was already done"
Where's the paper?
"It was then followed by the manipulation of data that we saw NOAA do."
"Data manipulation" was preceded by switching from buckets dropped off ships to measuring temperature at the water intake to using buoys. I fault His Majesty's Navy for not starting with buoys 300 years ago, but things are what they are.
Also, manipulation was preceded by somebody reading something whenever to everybody recording everything using the exact same protocol. Sometimes, somebody even moved the location of the station, and that has to be corrected for. I fault Jefferson and Washington weather.gov , for failing to establish the protocol and funding for a coast-to-coast network, to be established by Lewis and Clark . But, it is what it is. You go to climate war with the weather network you have, not the one you wish you had.
Believe it or not, this moment of truth actually appeared in Judith Curry's deniloblog. I'm not sure why she let Zeke in, except so that now people can't say, "Everything in Curry is wrong"..
Understanding adjustments to temperature data
Posted on July 7, 2014 | 2,044 Comments
by Zeke Hausfather
This will be the first post in a three-part series examining adjustments in temperature data, with a specific focus on the U.S. land temperatures. This post will provide an overview of the adjustments done and their relative effect on temperatures. The second post will examine Time of Observation adjustments in more detail, using hourly data from the pristine U.S. Climate Reference Network (USCRN) to empirically demonstrate the potential bias introduced by different observation times. The final post will examine automated pairwise homogenization approaches in more detail, looking at how breakpoints are detected and how algorithms can tested to ensure that they are equally effective at removing both cooling and warming biases.
Why Adjust Temperatures?
There are a number of folks who question the need for adjustments at all. Why not just use raw temperatures, they ask, since those are pure and unadulterated? The problem is that (with the exception of the newly created Climate Reference Network), there is really no such thing as a pure and unadulterated temperature record. Temperature stations in the U.S. are mainly operated by volunteer observers (the Cooperative Observer Network, or co-op stations for short). Many of these stations were set up in the late 1800s and early 1900s as part of a national network of weather stations, focused on measuring day-to-day changes in the weather rather than decadal-scale changes in the climate.
Figure 2. Documented time of observation changes and instrument changes by year in the co-op and USHCN station networks. Figure courtesy of Claude Williams (NCDC).
Nearly every single station in the network in the network has been moved at least once over the last century, with many having 3 or more distinct moves. Most of the stations have changed from using liquid in glass thermometers (LiG) in Stevenson screens to electronic Minimum Maximum Temperature Systems (MMTS) or Automated Surface Observing Systems (ASOS). Observation times have shifted from afternoon to morning at most stations since 1960, as part of an effort by the National Weather Service to improve precipitation measurements.
All of these changes introduce (non-random) systemic biases into the network. For example, MMTS sensors tend to read maximum daily temperatures about 0.5 C colder than LiG thermometers at the same location. There is a very obvious cooling bias in the record associated with the conversion of most co-op stations from LiG to MMTS in the 1980s, and even folks deeply skeptical of the temperature network like Anthony Watts and his coauthors add an explicit correction for this in their paper.
Figure 3. Time of Observation over time in the USHCN network. Figure from Menne et al 2009.
Time of observation changes from afternoon to morning also can add a cooling bias of up to 0.5 C, affecting maximum and minimum temperatures similarly. The reasons why this occurs, how it is tested, and how we know that documented time of observations are correct (or not) will be discussed in detail in the subsequent post. There are also significant positive minimum temperature biases from urban heat islands that add a trend bias up to 0.2 C nationwide to raw readings.
Because the biases are large and systemic, ignoring them is not a viable option. If some corrections to the data are necessary, there is a need for systems to make these corrections in a way that does not introduce more bias than they remove...
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