Not exact matches
Some studies have attempted to
estimate the statistical relationship between
temperature and
global sea level seen in the period for which tide gauge records exist (the last 2 - 3 centuries) and
then, using geological reconstructions
of past
temperature changes, extrapolate backward («hindcast») past sea - level changes.
It's incredibly hypocritical
of global warming denialists to whine that compilations
of global temperature anomaly like GISTEMP have large distances between recording stations and this makes them an inaccurate
estimate of global anomaly and
then we have a
global warming denialist extraordinaire, Roberts, claim that a SINGLE locality, Central England, can provide an adequate
estimate of global anomaly.
If the GHG -
temperature link is on the low end
of the range
of estimates (1.5 C to 4.5 C per doubling),
then global warming will not be a significant problem.
The SkyShares model enables users to relate a target limit for
temperature change to a
global emissions ceiling; to allocate this emissions budget across countries using different policy rules; and
then uses
estimated marginal abatement costs to calculate the costs faced by each country
of decarbonising to meet its emissions budget, with the costs for each country depending in part on whether and how much carbon trading is allowed.
If a substantial fraction
of all the weather stations from around the world have been affected by urbanization bias,
then this could have introduced an artificial warming trend into the «
global temperature trend»
estimates.
We
then used this new
estimate of unforced variability to aid in our interpretation
of observed
global mean
temperature variability since 1900.
So, they didn't actually simulate sea level changes, but instead
estimated how much sea level rise they would expect from man - made
global warming, and
then used computer model predictions
of temperature changes, to predict that sea levels will have risen by 0.8 - 2 metres by 2100.
Then, it might be possible to make some meaningful
estimates of long - term
global temperature trends from the weather records.
The principal work
of climate modeling is to take a complete census
of all
of these factors,
estimate the sizes and trajectories
of their various effects, and
then add them up to
estimate future
global temperatures.
Then using an
estimate of 14.0 C for the
global temperature average
of the 20th century, 12 - month absolute
temperatures were calculated from the calculated 12 - month average anomalies.
The effects
of this uneven sampling are being investigated and quantified in several ways, for example by
estimating «true»
global - mean
temperatures from the complete fields generated by satellite observations, blends
of satellite and in situ data, or climate models, and
then sampling these fields using the actual (incomplete) observed data coverage (see chapter 9).
The physics
of the climate system are input into very detailed climate models, which can
then estimate how the
global temperature will respond to various forcings.
Since
then, a growing number
of surface
temperature measurement stations worldwide, coupled with improved methods for correcting for biases induced through urban heat island effects and other station siting and operational issues, have allowed for the development
of accurate
global temperature estimates.
Since
then, significant improvements in methodology, a vast increase in the available stations, and the inclusion
of marine data have greatly improved
estimates of global temperatures.
Each group
then uses its chosen subset to create
estimates of how
global temperatures have changed over time and how they may change in the future.
So I
estimate that if we followed IEO2011 / RCP8.5 out to 2035, and
then stabilized our forcing, we would eventually arrive at an average
global temperature increase
of 2.4 ºC.
The Sun was
then about 0.25 percent dimmer, and the reduction in solar brightness produced an
estimated drop
of about 0.5 degrees Celsius (0.9 degrees Fahrenheit) in the
global mean
temperature.