The last
thing climate analysis needs is to attribute natural geologic occurrences, bad as they are, to the same causes as a warming climate.
Not exact matches
In general,
climate predictions are «best case»
analyses because
climate scientists (actually all scientists) do not include
things that they are not sure about.
I suspect many
things play a part in
climate analysis.
In general,
climate predictions are «best case»
analyses because
climate scientists (actually all scientists) do not include
things that they are not sure about.
One
thing that was not clear, was whether the
analysis, that involved both observed temperatures from the HadCRUT4 dataset and global
climate models, took into account the fact that the observations do not cover 100 % of Earth's surface (see RC post «Mind the Gap!»).
Climate Reference Network (CRN) and Soil Climate Analysis Network (SCAN) are a collection of climate monitoring stations which track, among other things, soil moisture and temperature at a series of
Climate Reference Network (CRN) and Soil
Climate Analysis Network (SCAN) are a collection of climate monitoring stations which track, among other things, soil moisture and temperature at a series of
Climate Analysis Network (SCAN) are a collection of
climate monitoring stations which track, among other things, soil moisture and temperature at a series of
climate monitoring stations which track, among other
things, soil moisture and temperature at a series of depths.
Spectral
analysis, unless properly understood may lead to very misleading conclusions, here are shown four essential
things one needs to be aware of all the time: On the other hand there are again unnoticeable data curiosities, this graph shows an unusual configuration within one of the top five temperature data sets used by the
climate scientists in their calculations, predictions and computer models.
The obvious
thing to do is to use regression
analysis to calibrate the
climate models forecasts.
No deeper
analyses, no retractions or amendments from grown understanding, no tangents into new problems, no bringing back of
things he learned from this work to other (non
climate) fields.
And the centerpiece of their «expert»
analysis about the «great»
things states are doing on
climate policy?
Dismissing the risks of global warming as «baseless and undisguised propaganda,» a John Birch Society blogger has pronounced that evidence for
climate change is «shoddy,» and that, on the basis of Bjorn Lomborg's (thoroughly discredited)
analysis, «a little warming wouldn't be such a bad
thing after all.»
By agglomeration is meant
things like the IPCC AR meta
analyses, or policy statement by the APS or the NRC on
climate.
Although it is from 2007 and hopefully
things are better now, try this from Kevin Trenberth, head of the
Climate Analysis Section at the USA National Center for Atmospheric Research occasionally a lead author of IPCC Scientific Assessments:
The first
thing to know about the new study authored by NOAA scientists about the global warming «slowdown» or «hiatus» over the past decade is that the new
analysis gets pretty deep into the details and will mainly be of interest to specialists who study
climate science.
About the only solid
thing I can say out of this
analysis is that if my numbers and logic are correct, then one of the fundamental equations of the current
climate paradigm is falsified...
My earlier research has concerned, among others
things, the use and the reliability of LES, the application of nonlinear time series
analysis on flow fields, and the inclusion of marine organic aerosol sources in global
climate models.