A number of observational studies indicate that carbon sequestration by terrestrial ecosystems in a world with an atmosphere richer in carbon dioxide and a warmer climate depends on the interactions between the carbon and nitrogen cycles. However, most terrestrial ecosystem models being used in climate-change assessments do not take into account these interactions. Here we explore how carbon/nitrogen interactions in terrestrial ecosystems affect feedbacks to the climate system using the MIT Integrated Global Systems Model (IGSM) and its terrestrial ecosystems submodel, the Terrestrial Ecosystems Model (TEM). We use two versions of TEM, one with (standard TEM) and one without (carbon-only TEM) carbon/nitrogen interactions. Feedbacks between climate and the terrestrial carbon cycle are estimated by comparing model response to an increase in atmospheric CO2 concentration with and without climate change. Overall, for small or moderate increases in surface temperatures, the terrestrial biosphere simulated by the standard TEM takes up less atmospheric carbon than the carbon-only version, resulting in a larger increase in atmospheric CO2 concentration for a given amount of carbon emitted. With strong surface warming, the terrestrial biosphere simulated by the standard TEM may still become a carbon source early in the 23rd century.

Our simulations also show that consideration of carbon/nitrogen interactions not only limits the effect of CO2 fertilization in the absence of climate change, but also changes the sign of the carbon feedback with climate change. In the simulations with the carbon-only version of TEM, surface warming significantly reduces carbon sequestration in both vegetation and soil, leading to a positive carbon-cycle feedback to the climate system. However, in simulations with standard TEM, the increased decomposition of soil organic matter with higher temperatures releases soil nitrogen to stimulate plant growth and carbon storage in the vegetation that is greater than the carbon lost from soil. As a result, sequestration of carbon in terrestrial ecosystems increases, in comparison to the fixed climate case, and the carbon cycle feedback to the climate system becomes negative for much of the next three centuries.

We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of climate sensitivity is 2.0 to 5.0 K. The net aerosol forcing strength for the 1980s has 90% bounds of -0.70 to -0.27 W/m2. The rate of deep-ocean heat uptake corresponds to an effective diffusivity, Kv, with a 90% range of 0.04 to 4.1 cm2/s. Second, we estimate the effective climate sensitivity and rate of deep-ocean heat uptake for 11 of the IPCC AR4 AOGCMs. By comparing against the acceptable combinations inferred by the observations, we conclude that the rate of deep-ocean heat uptake for the majority of AOGCMs lie above the observationally based median value. This implies a bias in the predictions inferred from the IPCC models alone. This bias can be seen in the range of transient climate response from the AOGCMs as compared to that from the observational constraints.

We present a method for constraining key properties of the climate system that are important for climate prediction (climate sensitivity and rate of heat penetration into the deep ocean) by comparing a model's response to known forcings over the twentieth century against climate observations for that period. We use the MIT 2D climate model in conjunction with results from the Hadley Centre's coupled atmosphere–ocean general circulation model (AOGCM) to determine these constraints. The MIT 2D model, which is a zonally averaged version of a 3D GCM, can accurately reproduce the global-mean transient response of coupled AOGCMs through appropriate choices of the climate sensitivity and the effective rate of diffusion of heat anomalies into the deep ocean. Vertical patterns of zonal mean temperature change through the troposphere and lower stratosphere also compare favorably with those generated by 3-D GCMs. We compare the height–latitude pattern of temperature changes as simulated by the MIT 2D model with observed changes, using optimal fingerprint detection statistics. Using a linear regression model as in Allen and Tett this approach yields an objective measure of model-observation goodness-of-fit (via the residual sum of squares weighted by differences expected due to internal variability). The MIT model permits one to systematically vary the model's climate sensitivity (by varying the strength of the cloud feedback) and rate of mixing of heat into the deep ocean and determine how the goodness-of-fit with observations depends on these factors. This provides an efficient framework for interpreting detection and attribution results in physical terms. With aerosol forcing set in the middle of the IPCC range, two sets of model parameters are rejected as being implausible when the model response is compared with observations. The first set corresponds to high climate sensitivity and slow heat uptake by the deep ocean. The second set corresponds to low sensitivities for all magnitudes of heat uptake. These results demonstrate that fingerprint patterns must be carefully chosen, if their detection is to reduce the uncertainty of physically important model parameters which affect projections of climate change.

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Different atmosphere-ocean general circulation models produce significantly different projections of climate change in response to increases in greenhouse gases and aerosol concentrations in the atmosphere. The main reasons for this disagreement are differences in the sensitivities of the models to external radiative forcing and differences in their rates of heat uptake by the deep ocean. In this study, these properties are constrained by comparing radiosonde-based observations of temperature trends in the free troposphere and lower stratosphere with corresponding simulations of a fast, flexible climate model, using techniques based on optimal fingerprinting. Parameter choices corresponding either to low sensitivity, or to high sensitivity combined with slow oceanic heat uptake are rejected. Nevertheless, a broad range of acceptable model characteristics remains, such that climate change projections from any single model should be treated as only one of a range of possibilities.