How well do we understand and evaluate climate change feedback processes?

Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.

Diagnostic analysis of atmospheric moisture and clear-sky radiative feedback in the Hadley Centre and Geophysical Fluid Dynamics Laboratory (GFDL) climate models

The interannual variability of the hydrological cycle is diagnosed from the Hadley Centre and Geophysical Fluid Dynamics Laboratory (GFDL) climate models, both of which are forced by observed sea surface temperatures. The models produce a similar sensitivity of clear-sky outgoing longwave radiation to surface temperature of ∼2 W m−2 K−1, indicating a consistent and positive clear-sky radiative feedback. However, differences between changes in the temperature lapse-rate and the height dependence of moisture fluctuations suggest that contrasting mechanisms bring about this result. The GFDL model appears to give a weaker water vapor feedback (i.e., changes in specific humidity). This is counteracted by a smaller upper tropospheric temperature response to surface warming, which implies a compensating positive lapse-rate feedback.

Granger causality of coupled climate processes: Ocean feedback on the North Atlantic oscillation

This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

Proposed design for an ultrasonic optical force-feedback microphone

We discuss a novel approach that would lead to the development of an ultrasonic optical force-feedback measurement microphone.

Plant species and functional group effects on abiotic and microbial soil properties and plant-soil feedback responses in two grasslands

1 Plant species differ in their capacity to influence soil organic matter, soil nutrient availability and the composition of soil microbial communities. Their influences on soil properties result in net positive or negative feedback effects, which influence plant performance and plant community composition. 2 For two grassland systems, one on a sandy soil in the Netherlands and one on a chalk soil in the United Kingdom, we investigated how individual plant species grown in monocultures changed abiotic and biotic soil conditions. Then, we determined feedback effects of these soils to plants of the same or different species. Feedback effects were analysed at the level of plant species and plant taxonomic groups (grasses vs. forbs). 3 In the sandy soils, plant species differed in their effects on soil chemical properties, in particular potassium levels, but PLFA (phospholipid fatty acid) signatures of the soil microbial community did not differ between plant species. The effects of soil chemical properties were even greater when grasses and forbs were compared, especially because potassium levels were lower in grass monocultures. 4 In the chalk soil, there were no effects of plant species on soil chemical properties, but PLFA profiles differed significantly between soils from different monocultures. PLFA profiles differed between species, rather than between grasses and forbs. 5 In the feedback experiment, all plant species in sandy soils grew less vigorously in soils conditioned by grasses than in soils conditioned by forbs. These effects correlated significantly with soil chemical properties. None of the seven plant species showed significant differences between performance in soil conditioned by the same vs. other plant species. 6 In the chalk soil, Sanguisorba minor and in particular Briza media performed best in soil collected from conspecifics, while Bromus erectus performed best in soil from heterospecifics. There was no distinctive pattern between soils collected from forb and grass monocultures, and plant performance could not be related to soil chemical properties or PLFA signatures. 7 Our study shows that mechanisms of plant-soil feedback can depend on plant species, plant taxonomic (or functional) groups and site-specific differences in abiotic and biotic soil properties. Understanding how plant species can influence their rhizosphere, and how other plant species respond to these changes, will greatly enhance our understanding of the functioning and stability of ecosystems.