Most global warming graphs are difficult to believe, even by the people who beleive them. The data are so dang variable and the precise and accurate climatic data is of such short time period and unequal distribution that long-term trends are awfully noisy. Whenever I see a smooth graph purporting to be weather data I say, "Right. Pass me the bong."

Personally, I place a lot more value on physical models than I do on statistical extrapolations. But even physical models are pretty darned imprecise, though getting more reliable at each iteration. The problem is like this: The first models were very simple convective/radiative models that didn't take ocean chemistry and geochemical processes into account. Mostly because the understanding was so limited that it made the models less reliable to include them. So folks started doing the geochemical, oceanographical and limnological grunt work. This resulted in more accurate physico-chemical modeling of the interaction between the atmosphere and the surface. But uh-oh, this also revealed feedback loops that adjust counter to global warming. Etc. The current models are full of positive and negative feedback loops and the various elemental fluxes are more and more accurately understood and verifiably predictive, within some error margin.

So if you look at the various global warming projections from the early runs in the 1980's to the most recent runs today you find considerable convergence along trajectories from the different modeling efforts over time. The variances within each of the models have declined and the variances between models have declined. They are converging to a narrowing set of trajectories.

Will there be surprises along the way? You bet. Study any complex process and eventually you'll get into feedback loops and strange attractors and other peculiar functions. At every announcement of these bits there will be some who lament the impending demise of life on Earth and others who say, "What, me worry?"

Take a longer view. Step back from the immediate field of argument and follow research trends. Get the raw data and graph it yourself. People can be wrong.

Maybe one of us idjits will see what the aigheads missed. That's how science advances.

B