scholarly journals A Formal Analysis of the Feedback Concept in Climate Models. Part III: Feedback Dynamics and the Seasonal Cycle in a Floquet Analysis

2015 ◽  
Vol 72 (9) ◽  
pp. 3574-3596
Author(s):  
Alain Lahellec ◽  
Krista Reimer

Abstract 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.

2017 ◽  
Vol 114 (50) ◽  
pp. 13126-13131 ◽  
Author(s):  
Paulo Ceppi ◽  
Jonathan M. Gregory

Climate feedbacks generally become smaller in magnitude over time under CO2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO2. Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.


2013 ◽  
Vol 70 (12) ◽  
pp. 3940-3958 ◽  
Author(s):  
Alain Lahellec ◽  
Jean-Louis Dufresne

Abstract Climate sensitivity and feedback are key concepts if the complex behavior of climate response to perturbation is to be interpreted in a simple way. They have also become an essential tool for comparing global circulation models and assessing the reason for the spread in their results. The authors introduce a formal basic model to analyze the practical methods used to infer climate feedbacks and sensitivity from GCMs. The tangent linear model is used first to critically review the standard methods of feedback analyses that have been used in the GCM community for 40 years now. This leads the authors to distinguish between exclusive feedback analyses as in the partial radiative perturbation approach and inclusive analyses as in the “feedback suppression” methods. This review explains the hypotheses needed to apply these methods with confidence. Attention is paid to the more recent regression technique applied to the abrupt 2×CO2 experiment. A numerical evaluation of it is given, related to the Lyapunov analysis of the dynamical feature of the regression. It is applied to the Planck response, determined in its most strict definition within the GCM. In this approach, the Planck feedback becomes a dynamical feedback among others and, as such, also has a fast response differing from its steady-state profile.


2014 ◽  
Vol 71 (9) ◽  
pp. 3350-3375 ◽  
Author(s):  
Alain Lahellec ◽  
Jean-Louis Dufresne

Abstract 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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mulalo M. Muluvhahothe ◽  
Grant S. Joseph ◽  
Colleen L. Seymour ◽  
Thinandavha C. Munyai ◽  
Stefan H. Foord

AbstractHigh-altitude-adapted ectotherms can escape competition from dominant species by tolerating low temperatures at cooler elevations, but climate change is eroding such advantages. Studies evaluating broad-scale impacts of global change for high-altitude organisms often overlook the mitigating role of biotic factors. Yet, at fine spatial-scales, vegetation-associated microclimates provide refuges from climatic extremes. Using one of the largest standardised data sets collected to date, we tested how ant species composition and functional diversity (i.e., the range and value of species traits found within assemblages) respond to large-scale abiotic factors (altitude, aspect), and fine-scale factors (vegetation, soil structure) along an elevational gradient in tropical Africa. Altitude emerged as the principal factor explaining species composition. Analysis of nestedness and turnover components of beta diversity indicated that ant assemblages are specific to each elevation, so species are not filtered out but replaced with new species as elevation increases. Similarity of assemblages over time (assessed using beta decay) did not change significantly at low and mid elevations but declined at the highest elevations. Assemblages also differed between northern and southern mountain aspects, although at highest elevations, composition was restricted to a set of species found on both aspects. Functional diversity was not explained by large scale variables like elevation, but by factors associated with elevation that operate at fine scales (i.e., temperature and habitat structure). Our findings highlight the significance of fine-scale variables in predicting organisms’ responses to changing temperature, offering management possibilities that might dilute climate change impacts, and caution when predicting assemblage responses using climate models, alone.


2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.


2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Xia Feng ◽  
Paul Houser

In this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist of six water balance variables monitoring the mean conditions and extreme aspects of the changing water cycle. The variables include precipitation (P), evaporation (E), runoff (R), terrestrial water storage (dS/dt), moisture convergence flux (C), and atmospheric moisture content (dW/dt). Means are determined as the daily total value, while extremes include wet and dry extremes, defined as the upper and lower 10th percentile of daily distribution. Trends are assessed for annual and seasonal indicators at several different spatial scales. Our results indicate that significant changes have occurred in most of the indicators, and these changes are geographically and seasonally dependent. There are more upward trends than downward trends in all eighteen annual indicators averaged over the CONUS. The spatial correlations between the annual trends in means and extremes are statistically significant across the country and are stronger forP,E,R, andCcompared todS/dtanddW/dt.


2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.


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