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This article introduces a new decomposition of climate feedback mechanisms based on their characteristic times. As the last of a series of three, it complements the first two parts by Lahellec and Dufresne to give a comprehensive review of climate feedbacks that will help to ensure consistency between practice and theory. In Parts I and II, analysis of the climate response to perturbations at the large spatial scales and time scales necessary to obtain linearity restricted the characterization to the slow components of the response. This part incorporates the fast mechanisms' impact on the climate feedbacks, bringing the seasonal cycle into the analysis. Thanks to the Floquet theory, the authors could extend the formal framework of Parts I and II to incorporate the fast mechanisms. An illustration of the formal results with a simple 1D model highlights a clear distinction between the role of fast (intraseasonal) and slow (decadal) feedbacks, with an application to the water-cycle feedback of Part II. The same implementation of the Gâteaux difference in LMDZ, the GCM of LMD, as in Part II is used for comparing results with the authors' toy model. This comparison essentially validates the Floquet decomposition obtained with the toy model: the fast component linked to precipitation is contributing negatively to the water-cycle feedback while the slow component is building up the positive feedback. The comparison also provides further insight on the sensitivity of models' precipitation to climate warming. [ABSTRACT FROM AUTHOR]

Climate analysis is greatly simplified in perturbation analysis when filtered anomalies show linear behavior. In the first part (part I) of this two-part analysis, the formal tangent linear system (TLS) that handles linear behavior was used to demonstrate the strict equivalence between feedback and sensitivity analysis but at the cost of reducing the generality of its application to GCMs. In this second part, the full feedback analysis is introduced from the application of the so-called regression method of Gregory et al. The authors give a complete example of its use in the global analysis of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) abrupt 4×CO2 and ramp experiments. A simple 1D model with only two ocean layers is shown to be able to explain the slow climate warming of the next century. An extension of the formal results in part I allows a new perturbation method to be designed in GCMs to determine the TLS in models. A series of illustrations demonstrates the advantages of implementing such a method in GCMs. [ABSTRACT FROM AUTHOR]

Abstract: An increase in transportation costs impacts the welfare of households living on the outskirts of the city more than the other inhabitants and, in the short term, limited housing supply stops them from moving toward the center. Over a longer period, however, urban adjustments cancel out this inequality: (1) in the center, rent level rises because of higher demand, inducing investment in additional housing and increasing city density; (2) on the outskirts, housing demand decreases until rent level decreases and compensates for higher transportation expenditures. Inertia in housing supply and household re-locations leads, therefore, to the development of spatial inequalities. To investigate this issue, we built a dynamic model that reproduces urban transitions in monocentric cities, and enables quantifying in continuous time their spatialized consequences. Applied to the implementation of a transportation tax, the model suggests that a rapid implementation would induce (i) higher welfare losses than can be inferred from traditional models and (ii) major redistributive effects throughout the city. Finally, the model suggests that an early and progressive implementation is to be preferred to late and aggressive action. These results challenge current assessment methods of climate change stabilization strategies and show that it is essential to take into account urban dynamics and inequalities in the design of climate policy. [Copyright &y& Elsevier]

The concept of feedback has been used by several authors in the field of climate science to describe the behavior of models and to assess the importance of the different mechanisms at stake. Here, a simple 1D model of climate has been built to analyze the water vapor feedback. Beyond a static quantification of the water feedback, a more general formal definition of feedback gain based on the tangent linear system is introduced. This definition reintroduces the dynamical aspect of the system response to perturbation from Bode's original concept. In the model here, it is found that, even though the water vapor static gain proves consistent with results from GCMs, it turns out to be negative for time scales below 4 yr and positive only for longer time scales. These results suggest two conclusions: (i) that the water vapor feedback may be fully active only in response to long-lived perturbations; and (ii) that the water vapor feedback could reduce the natural variability due to tropospheric temperature perturbations over short time scales, while enhancing it over longer time scales. This second conclusion would be consistent with studies investigating the influence of air–sea coupling on variability on different time scales. [ABSTRACT FROM AUTHOR]