For me, this gets at the fundamental problem with addressing climate change: the discrepancy between what our eyes are telling us and what we know from the research that we just can't see -- under the ocean, in the atmosphere, across huge regions too big to comprehend visually.
And if you haven't already noticed, the internet is loaded to the gills with commenters ready to call out the slightest discrepancy on climate change reporting.
After they manufactured a problem by exaggerating the discrepancy between mainstream climate model simulations and temperature observations, and ignored the relevant scientific research on that issue, Monckton and colleagues created their own "irreducibly simple climate model" with built-in assumptions based on circuit design rather than the physics of the Earth's climate system.
More photosynthesis is good, but can a 16percentt discrepancy slow down climate change?
The skeptics point to some genuine discrepancies between the climate models and what's actually happened; they're probably right in criticizing the United Nations' I.P.C.C. for not paying enough attention to the impact of solar variations on the Earth's climate.
But others, notably fuller inclusion of evaporation and condensation processes in atmospheric dynamics (the 'biotic pump'), offer elegant insights and, if integrated into more comprehensive models, may resolve some of the discrepancies plaguing current climate models.
"However, the size of this slowdown and the discrepancy between observations and climate simulations may be less than previously thought.
Two experiments of the palaeoclimate simulations with different land surface of modern and palaeo-vegetations have been designed to test the discrepancies of simulated LGM climate with in precipitation and P E fields.
Inefficient mitigation of excessive heat is attributed to the discrepancy between the scope of climate research and conventional planning practice.
This does not address the discrepancy between fundamental and realized climate space, but it ensures that one's top models are in a reasonable range of complexity.
