It is important to stress that the databank is a release of fundamental data holdings — holdings which contain myriad non-climatic artefacts arising from instrument changes, siting changes, time of
observation changes etc..
Not exact matches
My
observation is that many theologians,
etc., don't
change their minds, but if they do they are hesitant to admit it.
In summary, it is important to KNOW YOUR DOG -
OBSERVATION - watch out for any
changes in behaviour, demeanour
etc. - these may indicate that something is not quite as it should be.
Future emails will include: the difference between contrails / vapour trails and Stratospheric Aerosol Injection
observations on covert atmospheric spraying (their tactics have
changed in the last few weeks — this has been noticed globally) who is controlling the spraying — who are «they» much of the northern hemisphere is burning — California, Canada, Siberia (2,000 mile smoke clouds), Sweden
etc..
Revisionist and / or «still consistent with
observations»: in terms of
changing the assumptions,
changing the amount of time necessary for a pause to be significant,
changing tack to OHC, comparing real earth to the spread of all models,
etc..
It costs little to field the
observations — the satellites and the radars, the surface in situinstruments,
etc. to monitor conditions and their
changes; to assimilate the data into variety of numerical models, to run these and form ensemble averages; to disseminate the findings.
It becomes a model when you try and describe the
observation mathematically, so as to be able to extrapolate what happens when a variable
changes (ie the amount of water, thickness of the pot, the duration of the heat source,
etc.).
«All of the information» surely includes knowledge gained from paleoclimate, modeling,
observations of ongoing climate
change, understanding of physical processes,
etc..
First
observation is the local universe hasn't
changed much, same old beetle and ruler, no obvious macro impacts like a large foot etc
etc..
Anomalies provide a useful way of salvaging temperature records corrupted by problems of station loss, relocation,
changing observation times
etc. etc..
It is because both contain stations like Las Vegas that have been compromised by
changes in their environment, that station itself, the sensors, the maintenance, time of
observation changes, data loss,
etc..
The same could be done with time of
observation changes, station moves,
etc..
However,
observations show that during the last 1 million years, the strongest climate signal is the 100,000 year cycle», and «Observations show climate behaviour is much more intense than the calculated variations», and»... No reason for this change has been established&r
observations show that during the last 1 million years, the strongest climate signal is the 100,000 year cycle», and «
Observations show climate behaviour is much more intense than the calculated variations», and»... No reason for this change has been established&r
Observations show climate behaviour is much more intense than the calculated variations», and»... No reason for this
change has been established»,
etc..
Where
observations are plentiful and span the variability, the reanalysis field is close to what actually happened (for instance, horizontal components of the wind), but where the output field is only indirectly related to the assimilated
observations (rainfall, cloudiness
etc.), the
changes and variability are much more of a product of the model.