EM

They added the bucket corrections to SST (well according to the Real Climate post) but there's an old thread on here that puts doubt on that correction. It was posted by me and John Kennedy got involved. It's also a good example of science versus engineering. I can't say if the correction was "enough" if that's the word. The temperature may have to be adjusted even more.

The bucket correction assumes a model where relative humidity is the key factor. They performed experiments in 1948 and then again 1991 on ships but with no continuous improvement or characterisation in subsequent years or any obvious prolonged lab campaigns. There is also the problem of the process of measurement. A wet finger in the air as to how long buckets were left is used and there is no consideration of the complicated interplay between thermometer and bucket.

As I said then, this is okay in a science paper as you have to allow some assumptions. But it's not okay in an official temperature record where it affects policy and can be considered a "national standard". You have to painstakingly demonstrate you understand the process. The tolerance i.e. uncertainty should be larger in the meantime as a precaution (as in this is how the Precautionary Principle should be used). It's currently stated at 0.1 degrees. That has come only from using a statistical model of the process.

This is important. The model is of the whole process not just how the bucket cools, which in itself looks to have an uncertainty of around 0.15 degrees C when compared to the students' measurements.

Nothing really came after that thread but at least it's here for posterity.

Plus one last thing, I've noticed you have said before and are saying here in a roundabout way that measurements can be averaged so that uncertainties reduce. It's how the temperature anomalies are often quoted to 0.1 degrees C uncertainty. This only occurs when individual measurements or even samples of measurements can be reduced to a normal distribution (with zero or fixed bias) behaviour. It's in the Met Office papers and is at times a best case assumption that is made. They made the same assumption with bucket corrections.

Problem is that engineers are all too familiar with sensor drift and the headaches. If you don't know how your measurement varies over the lifetime of the instrument then uncertainties become discontinuous and only in very long stretches of time do they approximate normal distributions (as in Central Limit Theorem).

If you can engineer low uncertainty and have other ways to correct for drift, as is the case with using orbital dynamics to help correct satellite view factors, along with onboard calibration, then it helps. Otherwise it's high tolerance time.

EM

Yes that example you linked to is correct. But only because the individual components are discrete units. You can't have half a beetle.

A temperature measurement is not a discrete measurement but can be considered a distribution. Knowledge of uncertainty and how it varies over time becomes important. If you have a process then it becomes even more important to understand what can cause the largest uncertainty.

Uncertainty that is discontinuous i.e sensor jumps, means discrete statistics as above can't be used so easily. That's why the Met Office tries to get measurements to follow the normal distribution model. It makes the calculations easier. Doesn't mean that's what happens. It's an assumption for the sake of the science but one that needs to be watched closely.

EM

Jobs, tenure, professorships and funding in science all come out of a reputation for high quality research, so professional reputation is hard won and zealously protected. Competition is also intense. Poor practice, faking or distorting data gets you rusticated very quickly.

There was great annoyance here when I suggested that engineers were less than perfect. Kindly give scientists the same professional courtesy you demand for yourselves.

I think you misunderstand what I wrote. The assumptions the Met Office make are clear in the paper, for example 2 minutes for the water to sit or words to that effect. But that is an assumption, a best case. Also it is normal to simply assume that errors can be random and to restate this at the end. That's scientific practice. I didn't invent it. If the conditions are such that those assumptions are relatively correct then the conclusions stand. If not then the conclusions don't. Again go and read the Met Office papers or other climate papers.

For engineering you simply ask the question "can we afford to assume that?" The real world implications demand time consuming characterisation. Pure science doesn't often do this because once the idea is out there someone else can test it. That's not a criticism, that's just how the process works.