Two European professors
wrote that the IPCC projections
of future warming are based
on huge unknowns.
Projections of the future
of the world’s climate
are very unreliable,
according to Samuel Furfari,
Professor at the Free University
of Brussels, and Henri Masson,
Professor (Emeritus),
University of Antwerpen.
The (NASA) GISS
Surface Temperature
Analysis (GISTEMP v4)
is an estimate of global
surface temperature change,
often used by climate scientists
for their reports to the media.
This estimate is computed
using data files from
NOAA GHCN v4 (land stations),
and ERSST v5 (ocean areas).
In June 2019, the number
of land stations was 8,781
in the GHCNv4 unadjusted
dataset; but in June 1880,
that figure was a mere
281 stations, the two
professors wrote.
Professors Furfari
and Masson write:
“The climate system,
and the way
IPCC represents it,
is highly sensitive
to tiny changes
in the value
of parameters
or initial conditions and
these must be known
with high accuracy.
But this is not the case.”
“This puts serious doubt
on whatever conclusion
that could be drawn
from model projections.”
Opening the door to:
“fake conclusions”
… “manipulations”.
Masson and Furfari
say that IPCC scientists
ignore that climate change
occurs with cyclic behavior,
and that linear trend lines
applied to (poly-)cyclic data
of period similar
to the length
of the time window
considered,
open the door
to any kind of
fake conclusions,
if not manipulations,
aimed to push
one political agenda
or another.
“Until very recently,
these (sea surface)
temperatures have been
only scarcely reported,
as the data for SST
(Sea Surface Temperature)
came from vessels
following a limited number
of commercial routes,”
report Masson and Furfari.
The gaping data holes
mean scientists
are free to guess
whatever numbers
they want.
IPCC projections result from
mathematical models
which need to be calibrated
by making use of data
from the past.
The accuracy of calibration data
is of paramount importance,
as the climate system
is highly non-linear, and this
is also the case for the
(Navier-Stokes) equations
and (Runge-Kutta integration)
algorithms used in the
IPCC computer models.
The spatial coverage
of the data
is highly questionable,
as is the temperature
over the oceans,
representing 70%
of the Earth surface,
is mostly neglected or
“guesstimated”.
The number and location
land surface weather stations
have also considerably changed
over time, inducing biases
and fake trends.
The global temperature anomaly,
is obtained by spatially averaging
local temperature anomalies.
Local anomalies are the comparison
of present local temperatures
to the averaged local temperature
calculated over a previous
fixed reference period of 30 years,
changing each 30 years (1930-1960,
1960-1990, etc.).
The concept of local anomaly
is highly questionable,
due to biases and false trends
when the “measurement window”
is shorter than at least 6 times
the longest period detectable
in the data; which is unfortunately
the case with temperature data.
It is highly recommended
to abandon
the IPCC concept
of a single global average
temperature anomaly,
and to focus on
local climate data.
A change in a local climate,
is a physically meaningful concept,
because local climates are those
in which people actually live !