Steven Mosher says:

Some folks seem to be confused by my position, and Anthon’y post aims at fiinding agreement.

So, Let me state some things clearly

My position
1. Averaging Absolutes as goddard does is not the best method to use especially when records are missing.
A) it’s not the best method to calculate a global average
B) its not the best method to Assess the impact of adjustments.
2. IF you choose a method that requires long continuous records then you have to adjust for station changes
A) changes in location
B) changes in TOBS
C) changes in instrument.
3. The alternative to adjusting (#2) is to slice stations.
A) When a station moves, its a new fricking station because temperature is a function of SITING
B) When the instrument changes, its a new fricking station
C) when you change the time of observation, its a new station.
4. Another alternative to 2 is to pre select stations according to criteria of goodness.

On #1. The method of averaging absolutes is unreliable. Sometimes it will work, sometimes it will give you biases in both directions. deciding which method to use should be done with a systematic
study using synthetic data. This is not a skeptic versus warmist argument. This is a pure method

On #2. This approach means that every adjustment you do will be subject to examination. You
will never ever get them all correct. Since adjustment codes are based on statistical models
you might be right 95% of the time, 5% you will be wrong. there are 40000 stations. Go figure
5% of that.

On # 3. This is my preferred approach versus #2. Why? because when the station changes its a new station. Its measuring something different. The person who changed my mind about this
was Willis. I used to like #2.

on #4 Im all for it. However, the choice of station rating must be grounded in field test.
Actual field test of what makes a site good and what disqualifies a site. Site rating needs to be objective ( based on measurable properties ) and not merely visual inspection. Humans need to taken out of rating or strict rating protocals must be established and tested.

Now, let the personal attacks commence. or you can look at 1-4 and say whether you agree or disagree.

Endogenous [Feedbacks] and Exogenous [Forcings] are a bit user defined.
To my way of thinking turning the light up or down, ie the sun increasing or decreasing output or moving towards or away from the earth is an obvious exogenous forcing.
Having an eclipse of the earth during the day turns off 100 million Hiroshima atomic bombs of heat during a typical 3 minute eclipse. enough eclipses [21.3] and we would solve our purported energy imbalance.
Other exogenous sources are harder to understand eg background radiation from the Universe.
One might allow volcanoes grudgingly along with the fact that the earth gives some small radiative forcing from its core heat.
The rest is all endogenous as far as I am concerned.
The soots, methane, water come from natural sources and variations as does CO2.
Plants absorb the most CO2 but also produce the most CO2 when they rot or are burnt as coal. Humans producing CO2 is as natural as cows producing methane. The earth has a great inbuilt capacity to stay normal despite the minute efforts of humans.
The sea has been the same alkalinity for over a billion years. It is kept that way by the relatively infinite constant amounts of water and minerals. Why is the Ph where it is? Because it cannot go anywhere else given the substrate composition


angech (Comment #131480)  at Blackboard

but you still have goddarians out there.
Only a complete munchkin would argue that we should use the “raw” data in deference to quality controlled data. Steve Goddard is that munchkin, and it’s not surprising to see his surrogates here making the same stupid arguments here.

I repeat, I am not interested in Goddard or waiting for him.
Calling him a munchkin is a really good argument, Carrick, Thanks for including that brilliant riposte.Better than Tamino when on a losing argument.
Using raw data, real data, in deference to quality controlled model inferred “data”? [lets call it gloop] is better?
Note there are no tree rings or proxies in real data.
Lets note that all data is adjusted [rounded] at some level by a person or program.
There is nothing wrong with this and rounding can go up as well as down Mosher, it evens out.
Real data by a thermometer is pretty accurate. It was taken on the day, it was written down, it is still amazingly extant in “the true original value, it must be retrieved from DSI-3210?.

Now to correct some minor subterfuge.
The first USHCN datasets .
defined a network of 1219 stations in the contiguous United States.
24 of the 1,218 stations (about 2 percent) have complete data from the time they were established.
The initial USHCN daily data set contained a 138-station subset of the USHCN.
Even though there is supposed to be a network of 1218 stations from which the model is derived for most of its life since 1987 USHCN has used variations on a smaller critical subset to issue its temperature model, roughly the 138/1218 or 10 % of the stations [do not get picky on my maths].
Steven said “USHCN version 1 data comprise about 5% of station months, generally in the earliest years of the station records.”
This is not correct, if referring to USHCN which he seems to be though he may mean USHCN compared to all US CONUS.
“Monthly values calculated from GHCN-Daily are merged with the USHCN version 1 monthly data to form a more comprehensive dataset of serial monthly temperature and precipitation values for each HCN station”
Err no , USHCN is supposed to be worked out from its 1218 stations, infilled by surrounding non recognized stations when data is missing and then this is incorporated into GHCN, smaller to larger, not using the world data to fool the American data, surely, please.
I understand the reams of data , Steve, so when you josh around telling the less able people like myself to go and do the work that a highly trained person like yourself found almost too hard it is not even comedic, just sad and not helpful.
Lets have real history and explain we use models for science, but they are not real.