Tag Archives: Climate Models

Climate modeler groupthink

groupthink

  • n.
    The act or practice of reasoning or decision-making by a group, especially when characterized by uncritical acceptance or conformity to prevailing points of view.
  • n.
    A process of reasoning or decision-making by a group, especially one characterized by uncritical acceptance or conformity to a perceived majority view.
  • n.
    decision making by a group (especially in a manner that discourages creativity or individual responsibility)

“Climate science has no system of checks and balances.  The people who write climate models are the same ones who evaluate themselves, and then journalists parrot what the modelers say, and refuse to print any other opinions.” click here

General circulation climate models (GCMs) are unreliable and arbitrary

Patrick Frank. Propagation of Error and the Reliability of Global Air Temperature Projections. Front. Earth Sci., 06 September 2019 https://doi.org/10.3389/feart.2019.00223

The reliability of general circulation climate model (GCM) global air temperature projections is evaluated for the first time, by way of propagation of model calibration error. An extensive series of demonstrations show that GCM air temperature projections are just linear extrapolations of fractional greenhouse gas (GHG) forcing. Linear projections are subject to linear propagation of error. A directly relevant GCM calibration metric is the annual average ±12.1% error in global annual average cloud fraction produced within CMIP5 climate models. This error is strongly pair-wise correlated across models, implying a source in deficient theory. The resulting long-wave cloud forcing (LWCF) error introduces an annual average ±4 Wm–2 uncertainty into the simulated tropospheric thermal energy flux. This annual ±4 Wm–2simulation uncertainty is ±114 × larger than the annual average ∼0.035 Wm–2 change in tropospheric thermal energy flux produced by increasing GHG forcing since 1979. Tropospheric thermal energy flux is the determinant of global air temperature. Uncertainty in simulated tropospheric thermal energy flux imposes uncertainty on projected air temperature. Propagation of LWCF thermal energy flux error through the historically relevant 1988 projections of GISS Model II scenarios A, B, and C, the IPCC SRES scenarios CCC, B1, A1B, and A2, and the RCP scenarios of the 2013 IPCC Fifth Assessment Report, uncovers a ±15 C uncertainty in air temperature at the end of a centennial-scale projection. Analogously large but previously unrecognized uncertainties must therefore exist in all the past and present air temperature projections and hindcasts of even advanced climate models. The unavoidable conclusion is that an anthropogenic air temperature signal cannot have been, nor presently can be, evidenced in climate observables.

We’ve known for decades that climate models are unreliable for making climate projections; Will NASA, NOAA, NCAR and IPCC refund the US taxpayer money they wasted trying to use climate models to make future global warming scenario projections and catastrophic claims?

“NASA has conceded that climate models lack the precision required to make climate projections due to the inability to accurately model clouds.” click here

The US surface temperature record includes fabricated values inserted in place of”data” (actual measurements)

IPCC climate model projections are unreliable

“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.”

In other words, the IPCC method is fraught with great uncertainties and much guesswork.

“This puts serious doubt on whatever conclusion that could be drawn from model projections,” the two professors write.” ” click here

Climate models calculate the future too hot (no tricks)

“Climate models have such large deficits in the depiction of events in the tropical Pacific that they are globally incorrect in determining the response to the forcing and systematically overestimate the sensitivity to the forcing (according to Seager et al, and Dong et al).” click here

GCM-models over estimate climate sensitivity

J. KAUPPINEN AND P. MALMI, NO EXPERIMENTAL EVIDENCE FOR THE SIGNIFICANT ANTHROPOGENIC CLIMATE CHANGE. 

In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a very large change for the contribution of the green house gases in the observed temperature. This is the reason why IPCC has to use a very large sensitivity to compensate a too small natural component. Further they have to leave out the strong negative feedback due to the clouds in order to magnify the sensitivity. In addition, this paper proves that the changes in the low cloud cover fraction practically control the global temperature. click here