«can causes to climate variability be deduced using differences that are «in the background noise» of the «system's» (thermometers + computer models
+ data selection + other) ability to measure with confidence?»
We carefully studied issues raised by skeptics: biases from urban heating (we duplicated our results using rural data alone),
from data selection (prior groups selected fewer than 20 percent of the available temperature stations; we used virtually 100 percent), from poor station quality (we separately analyzed good stations and poor ones) and from human intervention and data adjustment (our work is completely automated and hands - off).
These can arise from many technical issues,
including data selection, substandard temperature station quality, urban vs rural effects, station moves, and changes in the methods and times of measurement
On the scale of errors, there are blunders, there are errors, there is over
clever data selection, and there is ignorance.
Data sharing limitations to Tribal
Nations data selection and thematic content and how to better interpret Indian Lands and related rights are discussed in the framing questions.
A comparison of Australian mean temperature from a range of different datasets — including local and international datasets (which use different methods
of data selection, preparation and analysis) and both station - based and satellite data — is provided below (Figure 12).
We carefully studied issues raised by skeptics: biases from urban heating (we duplicated our results using rural data alone),
from data selection (prior groups selected fewer than 20 percent of the available temperature stations; we used virtually 100 percent), from poor station quality (we separately analyzed good stations and poor ones) and from human intervention and data adjustment (our work is completely automated and hands - off).
Well, for example, when we talked about «data collection» we told the class «how to keep a lab notebook» but we also discussed «
data selection» and «ownership of data.»
We could be very picky about
our data selection,» said Frank van Manen, team leader for the Interagency Grizzly Bear Study Team.
Data selection and triage are important techniques for large - scale data, which can drastically reduce the amount of data written to disk or transmitted over a network.
They managed to avoid bias in
their data selection, homogenization and other corrections.
Changes in distribution also has several causes but again
their data selection guaranteed a statistical bias.
As to why they should all cut off at 0.5 or 1C, this could also be an artifact of
data selection (periods with low positive climate sensitivities were rejected) or it could be that the analytical procedures are skewing the pdf.
The differences between the red and blue lines in this diagram show the differences due to
data selection, gridding and quality control.
The result is just an exercise in «splice artifacts, errors, and
data selection».