Climate CO2 Sensitivity Overestimated
It is well known that carbon dioxide cannot directly account for the observed increase in global temperature over the past century. This has led climate scientists to theorize that many feedback relationships exists within the climate system, serving to amplify the impact of rising CO2 levels. One of these is the impact of rising temperature on the ability of the ecosystem to absorb CO2. The temperature sensitivity of ecosystem respiratory processes (referred to as Q10) is a key determinant of the interaction between climate and the carbon cycle. New research, recently published in the journal Science, shows that the Q10 of ecosystem respiration is invariant with respect to mean annual temperature, and independent of the analyzed ecosystem type. This newly discovered temperature insensitivity suggests that climate sensitivity to CO2 is much smaller than assumed by climate models.
Climate sensitivity is generally given as how much temperature rise would result from a doubling of atmospheric CO2 levels. Using IPCC figures for radiative forcing, a doubling of CO2 would lead to a temperature rise of about half a degree (see “Another Look at Climate Sensitivity”). Yet the UN IPCC Fourth Assessment Report (AR4) gives a much higher value for climate sensitivity. It claims a 2°C to 4.5°C rise for a CO2 doubling, or from four to nine times higher than what is see in the real climate system. Why? Climate models assume that there are large positive feedbacks as Earth warms. Among these feedbacks is the impact of rising temperature on emission and absorption of CO2 by Earth's biota.
Accurately predicting future levels of atmospheric CO2 requires a clear understanding of how land and atmosphere exchange CO2. Each year, photosynthesizing land plants remove (fix) one in eight molecules of atmospheric CO2. Land plants and soil organisms return a similar amount of the dreaded greenhouse gas. The balance between removal and respiration determines whether terrestrial ecosystems are a net carbon sink or source. Two papers in the August 13, 2010, issue of Science bring a new understanding of land-atmosphere CO2 exchange.
The terrestrial carbon cycle.
In “Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate,” Christian Beer et al. estimate total annual terrestrial gross primary production (GPP) in an approach more solidly based on data than previous approximations. Terrestrial GPP is the largest source of global carbon exchange. It drives many ecosystem functions, such as respiration and growth. Food, fiber, and wood production from plants are all part of terrestrial GPP. Moreover, GPP is one of the major processes controlling land-atmosphere CO2 exchange.
The researchers used a combination of observation and calculation to estimate that the total GPP by terrestrial plants is around 122 billion tons per year. In part, the capacity of terrestrial ecosystems acts to offset human CO2 emissions, which total around 7 billion tons annually. Thirty-two percent of this uptake occurs in tropical forests, and precipitation controls carbon uptake in more than 40% of vegetated land. Here is how Beer et al. sum up their findings:
After four decades of research on the global magnitude of primary production of terrestrial vegetation, we present an observation-based estimate of global terrestrial GPP. Although we arrive at a global GPP of similar magnitude as these earlier estimates, our results add confidence and spatial details. The large range of GPP results by process-oriented biosphere models indicates the need for further constraining CO2 uptake processes in these models. Furthermore, our spatially explicit GPP results contribute to a quantification of the climatic control of GPP. Complementing theoretical or process-oriented results about climatic limitations of GPP, our observation-based results now constitute empirical evidence for a large effect of water availability on primary production over 40% of the vegetated land (Fig. 3A) and up to 70% in savannahs, shrublands, grasslands, and agricultural areas. Our findings imply a high susceptibility of these ecosystems’ productivity to projected changes of precipitation over the 21st century, but a robustness of tropical and boreal forests. Results of current process models show a large range and a tendency to overestimate precipitation-associated GPP (Fig. 3B). Most likely, the association of GPP and climate in process-oriented models can be improved by including negative feedback mechanisms (e.g., adaptation) that might stabilize the systems.
Shown above, in figure 3 taken from the paper, the percentage of vegetated land surface (A) and corresponding GPP (B) that is controlled by precipitation, depending on the chosen threshold for the partial correlation coefficients that signal a control of GPP by a climate factor. The blue areas represent the range of data-driven estimates using different climate sources. This is compared to the range of process-oriented model results in red. Purple shows the overlapping area. The thick lines represent the medians of both ranges. See the article for details.
The most important statement from Beer et al. is that last line: “Most likely, the association of GPP and climate in process-oriented models can be improved by including negative feedback mechanisms (e.g., adaptation) that might stabilize the systems.” Instead of a positive feedback as is widely assumed in climate models, they suggest that the feedback should be reduced and may even be negative. There are even signs that the climate system adapts and self regulates. None of these factors are used in the IPCC's models.
In the second report, “Global Convergence in the Temperature Sensitivity of Respiration at Ecosystem Level,” Mahecha et al. assess how ecosystem respiration (R) is related to temperature over week-to-month and longer annual time scales, and find a potentially important but difficult-to-interpret relationship. Attempting to understand the sensitivity of respiratory processes to temperature, they approximated the sensitivity of terrestrial ecosystem respiration to air temperature (Q10) across 60 FLUXNET sites. The authors expand on their motivation:
Quantifying the intensity of feedback mechanisms between terrestrial ecosystems and climate is a central challenge for understanding the global carbon cycle and a prerequisite for reliable future climate scenarios. One crucial determinant of the climate–carbon cycle feedback is the temperature sensitivity of respiratory processes in terrestrial ecosystems, which has been subject to much debate. On the one hand, empirical studies have found high sensitivities of soil respiration to temperature, with values of Q10 (here an indicator of the sensitivity of terrestrial ecosystem respiration to air temperature) well above 2. Dependencies of Q10 values on mean temperatures have been attributed to the acclimatization of soil respiration, among other factors. On the other hand, global-scale models often make use of globally constant Q10 values of 2 or below to generate carbon dynamics consistent with global atmospheric CO2 growth rates. Nonetheless, several models have directly included empirical dependencies of the parameterization of respiratory processes to environmental dynamics. This inclusion is questionable, given that single-site studies have indicated that factors seasonally covarying with temperature can confound the experimental retrieval of the intrinsic temperature dependence of respiration.
The investigators report that the week-to-month scale sensitivity is stable across sites varying in mean temperature, but annual sensitivity varies markedly from cold to warm ecosystems. Overall, they found an empirically inferred Q10 of approximately 1.4 at the ecosystem level. “These results reconcile the empirical evidence with findings that the global carbon cycle can be well modeled only with an ecosystem level sensitivity of Q10 < 2,” Mahecha et al. conclude. “Moreover, our results may partly explain recent findings indicating a less pronounced climate–carbon cycle sensitivity than assumed by current climate–carbon cycle model parameterizations.”
Ecosystem respiration is influenced by many complex factors (see figure below). Land plant and microbe respiration of CO2 into the atmosphere can be increased (yellow) or reduced (red) by a wide range of processes that enhance or limit metabolic processes, operate over varying time scales, and go beyond direct temperature effects on physiology [figure below expanded from M. Reichstein & C. Beer, J. Plant Nutr. Soil Sci. (abstract)]. This new work indicates that previously used estimates were erroneous and model representations overly simplistic.
Complex factors influence carbon dioxide respiration.
The combined impact of these two papers is yet another blow to the validity of current computer models. Previous assumptions about the absorption and production of CO2 by terrestrial plants under changing conditions are in error. These new results imply that rising CO2 levels will not cause the temperature increases predicted by existing computer models. In an accompanying perspective article, Peter B. Reich, an environmental biologist at the University of Minnesota, summed up the implications of these papers:
Regardless of the difficulty of interpreting the processes underlying these numbers, the findings are important. Beer et al.'s value for GPP is our best and most broad-based estimate, despite its uncertainty. Mahecha et al.'s results are important because they suggest that, at week-to-month scales, R's relationship to temperature converges at a Q10 of 1.4 across many varied ecosystems. Their work also reduces fears that respiration fluxes may increase strongly with temperature, accelerating climate change. They also add to studies indicating that simple assumptions about respiration-temperature relations can lead to problematic models. It is not yet clear, however, whether and how their findings can be used in climate models.
More plainly put, making simplifying assumptions about nature has led to an over estimation of carbon dioxide's impact on temperature. As experienced modelers will tell you, simplifying assumptions can be the death of any simulation. Here is more proof that the climate models used by the IPCC and other climate researchers don't have a chance in hell of getting future climate change correct. The closer science looks at the real world processes involved in climate regulation the more absurd the IPCC's computer driven fairy tale appears. Instead of blithely modeling climate based on hunches and suppositions, climate scientists would be better off abandoning their ivory towers and actually measuring what happens in the real world.
Be safe, enjoy the interglacial and stay skeptical.