Model Failure…New Papers Show Climate Models Unreliable…At Times “Near-Zero Performance”!

At the German Die kalte Sonne site here, Dr. Sebastian Lüning and Prof. Fritz Vahrenholt present another two recent papers showing that models are failing to simulate the climate and cannot be used to make prognoses.
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What are temperature prognoses really worth? Climate models fail completely in the all-important reality tests

[German text translated/edited by P Gosselin]

Climate models have had to take a lot of criticism lately. Neither were they able to predict the slowed warming of the last 15 years, nor are they able to reproduce the natural warm periods of the last few thousand years.

A team led by Christopher O’Reilly has checked over how well the most common climate models have reproduced the winter temperatures of the northern hemisphere over the past 100 years. The scientists were astonished to find the prognosis performance for the middle of the 20th century was almost zero. That’s a bitter setback. The models appear to be missing something. In view of the glaring deficits, is it really acceptable that policymakers to derive policy from such models and to make globally decisions based on them? What follow is the abstract of the paper, which appeared in June 2017:

Variability in seasonal forecast skill of Northern Hemisphere winters over the twentieth century
Seasonal hindcast experiments, using prescribed sea surface temperatures (SSTs), are analyzed for Northern Hemisphere winters from 1900 to 2010. Ensemble mean Pacific/North American index (PNA) skill varies dramatically, dropping toward zero during the mid-twentieth century, with similar variability in North Atlantic Oscillation (NAO) hindcast skill. The PNA skill closely follows the correlation between the observed PNA index and tropical Pacific SST anomalies. During the mid-century period the PNA and NAO hindcast errors are closely related. The drop in PNA predictability is due to mid-century negative PNA events, which were not forced in a predictable manner by tropical Pacific SST anomalies. Overall, negative PNA events are less predictable and seem likely to arise more from internal atmospheric variability than positive PNA events. Our results suggest that seasonal forecasting systems assessed over the recent 30 year period may be less skillful in periods, such as the mid-twentieth century, with relatively weak forcing from tropical Pacific SST anomalies.”

What follows is another example, one for the region of the tropical Pacific. In this paper Coats and Karnauskas found that the models here as well were remote from reality. The authors concluded that every model prognosis based on these models for the Pacific are hardly trustworthy. The paper appeared in the Geophysical Research Letters in October 2017:

Are Simulated and Observed Twentieth Century Tropical Pacific Sea Surface Temperature Trends Significant Relative to Internal Variability?
Historical trends in the tropical Pacific zonal sea surface temperature gradient (SST gradient) are analyzed herein using 41 climate models (83 simulations) and 5 observational data sets. A linear inverse model is trained on each simulation and observational data set to assess if trends in the SST gradient are significant relative to the stationary statistics of internal variability, as would suggest an important role for external forcings such as anthropogenic greenhouse gasses. None of the 83 simulations have a positive trend in the SST gradient, a strengthening of the climatological SST gradient with more warming in the western than eastern tropical Pacific, as large as the mean trend across the five observational data sets. If the observed trends are anthropogenically forced, this discrepancy suggests that state-of-the-art climate models are not capturing the observed response of the tropical Pacific to anthropogenic forcing, with serious implications for confidence in future climate projections. There are caveats to this interpretation, however, as some climate models have a significant strengthening of the SST gradient between 1900 and 2013 Common Era, though smaller in magnitude than the observational data sets, and the strengthening in three out of five observational data sets is insignificant. When combined with observational uncertainties and the possibility of centennial time scale internal variability not sampled by the linear inverse model, this suggests that confident validation of anthropogenic SST gradient trends in climate models will require further emergence of anthropogenic trends. Regardless, the differences in SST gradient trends between climate models and observational data sets are concerning and motivate the need for process-level validation of the atmosphere-ocean dynamics relevant to climate change in the tropical Pacific.”

There many indications showing the models are overheating.