The sampling issue

Observations are generally a tricky thing. Not only are they a special kind of model, which tries to cover a sometimes very complicate laboratory experiment. Additionally they are also representing the truth, as far as we are able to measure it. As a consequence they play a really important part in science, but are in some fields hard to generate.

During the PALSEA2 meeting a question has come up in the context of the generation of paleo-climatic sea-level observations.

Assumed your ressources allow only two measurements, is it better when they be near towards each other or should they be far away.

In the heat of the discussion both sides were taken, but in the end the conclusion was the typical answer for such kind of questions: “it depends on what you want to measure”. Continue reading

All observations are models

Doing statistics between the two worlds of observations and model results lead often to the assumption that both are completely different things. There are the observations, where real people moved into the field, drilled, dug and measured and delivered the pure truth of the world we want to describe. In contrast to this, the clean laboratory of a computer, which takes all our knowledge and creates a virtual world. This world need not necessary have something to do with its real counterpart, but at least it delivers us nice information and visualisation. But this contrast between the dirty observations and the clean models is usually only something, which exists in our heads, in reality they are much more connected to each other.

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