The Black-Scholes equation [above] that was the mathematical justification for the trading that plunged the world's banks into catastrophe is a simple cousin to the derivative equations used in climate models.
Yet that's the task climate science and climate modelers are tasked with. Huge sums of money and maybe even the survival of our species may turn on the projections of this branch of science which attempts to describe the unimaginably complex climate with simple models. The global warming projections contained in the IPCC's Fourth Assessment Report (AR4) include carbon cycle feedbacks. Authors of AR4, however, noted that scientific understanding of carbon cycle feedbacks was poor.
Yesterday we touched the uncertainty of clouds and aerosols that are difficult to represent in climate models. Today we'll take on a few of the most notable negative feedbacks, all of them are debates about the values given to them when used as parameters in the various types of climate models.
The most hotly debated by physicists is Blackbody Radiation This negative feedback comes from the Stefan–Boltzmann law which says that the amount of infrared radiation from the Earth back into space increases with the fourth power of the temperature of Earth's surface and atmosphere [its absolute temperature]. Proponents and opponents of the consensus agree it exists, but widely disagree on both its initial and subsequent values. It's far beyond the scope of this post or my math skills to go into more detail but a great place to follow the ongoing and evolving arguments of both groups on blackbody radiation, and many other important climate debates, is Judith Curry's influential website, Climate Etc
Next up, Net Primary Productivity which is the increased CO2 sequestration as plants photosynthesis increases in response to increasing concentrations of CO2 and rising temperatures. This too is accepted by both encampments as true broadly speaking however the opponents attach much larger numbers and significance to it [see below]. Opponents often claim that this effect is why CO2 and temperature readings correlate so strongly over the geologic record as we'll talk more about more in a future post on historic and geologic time frame climate graphing.
Then there's the Lapse Rate a term used to describe measurements of the rate of temperature change with height that are very sensitive to small errors in observations, making it difficult to establish whether the models agree with observations. As you'd suspect proponents think they agree well, opponents think the diverge wildly and thereby throw off the models projections.
Followed by Le Chatelier's Principle which states that -the chemical equilibrium of the Earth's carbon cycle will shift in response to anthropogenic CO2 emissions. The primary driver of this is the ocean. Basically, if a chemical system at equilibrium, like our oceans, experiences a change in concentration, temperature, volume, or partial pressure, then the equilibrium shifts to counteract the imposed change and a new equilibrium is established. Opponents say this proves that the oceans will therefore absorb more CO2 in the future to compensate for increased atmospheric CO2 until new equilibrium is established.
Finally, my personal favorite, Chemical Weathering. In the chemical weathering process carbon dioxide in the atmosphere dissolves in rainwater to form carbonic acid, which dissolves rocks and then flows into the oceans. The process was recognized as being one of the major carbon sinks on million-year timescales, but considered as insignificant on timescales of a century. Many experts now agree that this weathering process which stores around 0.3 billion tons of atmospheric carbon in rivers and in the oceans every year
should play a significant role in future climate change models.
Climate modeling scientists at UBC found that when the amount of atmospheric CO2 rose from 355 ppmv at the end of the twentieth century to 560 ppmv by 2100, the Mackenzie River basin [the area being modeled in their study] responded by capturing 50% more atmospheric CO2 through chemical weathering. 40% of this increase is directly linked to climate change (higher temperatures and rainfall accelerate mineral dissolution), while the remaining 60% is put down to changing vegetation activity: higher atmospheric CO2 levels reduce evapotranspiration in plants, which intensifies circulation of water in soils. The increased circulation speeds up chemical weathering of rocks. The sensitivity of this flux to climate change would then be equivalent to the flux related to the terrestrial biosphere (vegetation, soil, humus, etc).
This one example of the how complex interaction between just two of the variables - 'net primary productivity' and chemical weathering - produced non-linear feedback result shows that our climate is still far beyond our ability to project its future via modeling. The the next post we'll take a look at the positive feedback mechanisms who's effects are also either poorly understood by or totally ignored by climate modeling.
