Climate change models over estimate climate change

Here is a link to a paper at www.nature.com.

Climate models are most impressive to those who do not understand their limitations, e.g., the media, climate alarmists, politicians, and even some climate scientists.

The paper "Earth system models underestimate carbon fixation by plants in the high latitudes"  is an example of one of their limitations.

Here are some excepts.  My comments are in italics.
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ABSTRACT

Most Earth system models agree that land will continue to store carbon due to the physiological effects of rising CO2 concentration and climatic changes favoring plant growth in temperature-limited regions. But they largely disagree on the amount of carbon uptake. The historical CO2 increase has resulted in enhanced photosynthetic carbon fixation (Gross Primary Production, GPP), as can be evidenced from atmospheric CO2 concentration and satellite leaf area index measurements. Here, we use leaf area sensitivity to ambient CO2 from the past 36 years of satellite measurements to obtain an Emergent Constraint (EC) estimate of GPP enhancement in the northern high latitudes at two-times the pre-industrial CO2 concentration (3.4 ± 0.2 Pg C yr−1). We derive three independent comparable estimates from CO2 measurements and atmospheric inversions. Our EC estimate is 60% larger than the conventionally used multi-model average (44% higher at the global scale). This suggests that most models largely underestimate photosynthetic carbon fixation and therefore likely overestimate future atmospheric CO2 abundance and ensuing climate change, though not proportionately.

FROM THE METHODS SECTION

Dimension reduction using principal component analysis

The drivers GDD0 and atmospheric CO2 concentration vary co-linearly due to the radiative effect of increasing CO2 concentration in the NHL. Thus, it is problematic to conduct an accurate factor separation in terms of their respective contribution to increase in LAImax. However, the co-linearity suggests that a large amount of the signal is shared. Therefore, we conduct a PCA to apply dimension reduction.

Principal Components Analysis is a purely statistical procedure with little relation to the physics of climate change.  It is widely used in Finance.  One Nobel Prize winner once referred to the "factors" it provides as follows. "factors" are things you pull out of your A__."  Statistical models can be powerful and extremely useful, but they are not a substitute for physics.  Climate models often are based on or rely on statistical models - be forewarned.