Because the error will distribute around the true value, thus even with sampling errors you can still extract a signal, even a very weak one, if you have many samples.
But surely we have some which survived, or can manufacture using methods of the time to check.
Also, physics was in a pretty good state at the time, at least regarding temperature/length measurement. Surely the scientists of the time measured the bias.
> One possible reason for the lower temperature estimates today than in the past is the difference in thermometers or methods of obtaining temperature. To minimize these biases, we examined changes in body temperature by birth decade within each cohort under the assumption that the method of thermometry would not be biased on birth year.
I think that the assumption that the method of thermometry is not biased based upon birth year is probably correct.
Very.
Thermometer calibration occurs around known values. Like the melting point of ice and boiling point of water at STP. It’s possible for individual measurements to be off significantly, but long term trends like this cover a huge range of manufacturers so the calibration points would need to be shifting around.
I'll buy that equipment exists that can measure temperature extremely accurately, maybe we even base it on the Plank constant now too. But I don't buy for a minute that most thermometers, or anything close to that, are even on the same playing field. Nevermind thermometers from decades ago.
It varies in a range of about +5% to -5% of average pressure.
Anyway, I think people are vastly underestimating just how far scientists where calibrating things back then. Clock making for example cares deeply about the current temperature.
One additional caveat specific to ocean (or other large scale systems) property measurement is that, because of the scale, your data can be easily biased because your sensors are not uniformly or even globally deployed. That's increasingly less of a problem in earth science but for geologic data, both in time and space, we are quite liberal in interpolating/extrapolating based on very impactful and sometimes shakey assumptions. This is dangerous because it is very easy for bias from dogma to sneak in unintentionally and undetectably to produce results which may be far removed from truth.
This is possible if there were some systematic shift in instrumentation with measurement year, but it would be blunted by the extent to which different ages were being sampled at each year.
I agree though that it would be nice to have some information on instrumentation over time and how it relates to temperature measurement.
It's worth noting that the results have practical implications regardless of the explanation of the observed trends, though, which is it's commonly assumed normal body temperature has certain characteristics, without recognizing that that might have shifted in significant ways over time.
It's interesting to me personally because I've often observed my body temp when I'm feeling fine is usually just above 36 C. That doesn't sound like much but it becomes a bigger deal when deciding whether or not I have a significant fever. Some of that might just be individual variation, but this is suggesting there's cohort trends within that too.
You can have a very precise thermometer (repeated measures are tightly clustered) that isn’t accurate (deviates from true value).