Response maxima in modulated turbulence

Isotropic and homogeneous turbulence driven by an energy input modulated in time is studied within a variable range mean-field theory. The response of the system, observed in the second order moment of the large-scale velocity difference D(L,t)=>~Re(t)^2$, is calculated for varying modulation frequencies w and weak modulation amplitudes. For low frequencies the system follows the modulation of the driving with almost constant amplitude, whereas for higher driving frequencies the amplitude of the response decreases on average 1/w. In addition, at certain frequencies the amplitude of the response either almost vanishes or is strongly enhanced. These frequencies are connected with the frequency scale of the energy cascade and multiples thereof.Comment: 11 pages, 6 figure

Projections of the Transient State-Dependency of Climate Feedbacks

When the climate system is forced, e.g. by emission of greenhouse gases, it responds on multiple time scales. As temperatures rise, feedback processes might intensify or weaken. Current methods to analyze feedback strength, however, do not take such state dependency into account; they only consider changes in (global mean) temperature and assume all feedbacks are linearly related to that. This makes (transient) changes in feedback strengths almost intangible and generally leads to underestimation of future warming. Here, we present a multivariate (and spatially explicit) framework that facilitates dissection of climate feedbacks over time scales. Using this framework, information on the composition of projected (transient) future climates and feedback strengths can be obtained. Moreover, it can be used to make projections for many emission scenarios through linear response theory. The new framework is illustrated using the Community Earth System Model version 2 (CESM2).Comment: main text: 11 pages, 4 figures, 1 table Supporting Information: 14 pages, 17 figures, 1 table, 8 movie

Multivariate Estimations of Equilibrium Climate Sensitivity from Short Transient Warming Simulations

One of the most used metrics to gauge the effects of climate change is the equilibrium climate sensitivity, defined as the long-term (equilibrium) temperature increase resulting from instantaneous doubling of atmospheric CO$_2$. Since global climate models cannot be fully equilibrated in practice, extrapolation techniques are used to estimate the equilibrium state from transient warming simulations. Because of the abundance of climate feedbacks - spanning a wide range of temporal scales - it is hard to extract long-term behaviour from short-time series; predominantly used techniques are only capable of detecting the single most dominant eigenmode, thus hampering their ability to give accurate long-term estimates. Here, we present an extension to those methods by incorporating data from multiple observables in a multi-component linear regression model. This way, not only the dominant but also the next-dominant eigenmodes of the climate system are captured, leading to better long-term estimates from short, non-equilibrated time series.Comment: Main Text (10 pages, 4 figures) plus Supporting Information (36 pages, 18 figures, 1 table

AMOC Stabilization Under the Interaction With Tipping Polar Ice Sheets

Several large-scale components of the climate system may undergo a rapid transition as critical conditions are exceeded. These tipping elements are also dynamically coupled, allowing for a global domino effect under global warming. Here we focus on such cascading events involving the Greenland Ice Sheet (GIS), the West Antarctica Ice Sheet (WAIS) and the Atlantic Meridional Overturning Circulation (AMOC). Using a conceptual model, we study the combined tipping behavior due to three dominant feedbacks: the marine ice sheet instability for the WAIS, the height-surface mass balance feedback for the GIS and the salt-advection feedback for the AMOC. We show that, in a realistic parameter range of the model, a tipping of the WAIS can inhibit cascading events by preserving the AMOC stability

Three-phase coexistence with sequence partitioning in symmetric random block copolymers

We inquire about the possible coexistence of macroscopic and microstructured phases in random Q-block copolymers built of incompatible monomer types A and B with equal average concentrations. In our microscopic model, one block comprises M identical monomers. The block-type sequence distribution is Markovian and characterized by the correlation \lambda. Upon increasing the incompatibility \chi\ (by decreasing temperature) in the disordered state, the known ordered phases form: for \lambda\ > \lambda_c, two coexisting macroscopic A- and B-rich phases, for \lambda\ < \lambda_c, a microstructured (lamellar) phase with wave number k(\lambda). In addition, we find a fourth region in the \lambda-\chi\ plane where these three phases coexist, with different, non-Markovian sequence distributions (fractionation). Fractionation is revealed by our analytically derived multiphase free energy, which explicitly accounts for the exchange of individual sequences between the coexisting phases. The three-phase region is reached, either, from the macroscopic phases, via a third lamellar phase that is rich in alternating sequences, or, starting from the lamellar state, via two additional homogeneous, homopolymer-enriched phases. These incipient phases emerge with zero volume fraction. The four regions of the phase diagram meet in a multicritical point (\lambda_c, \chi_c), at which A-B segregation vanishes. The analytical method, which for the lamellar phase assumes weak segregation, thus proves reliable particularly in the vicinity of (\lambda_c, \chi_c). For random triblock copolymers, Q=3, we find the character of this point and the critical exponents to change substantially with the number M of monomers per block. The results for Q=3 in the continuous-chain limit M -> \infty are compared to numerical self-consistent field theory (SCFT), which is accurate at larger segregation.Comment: 24 pages, 19 figures, version published in PRE, main changes: Sec. IIIA, Fig. 14, Discussio

Effect of Plankton Composition Shifts in the North Atlantic on Atmospheric pCO2

Marine carbon cycle processes are important for taking up atmospheric CO2 thereby reducing climate change. Net primary and export production are important pathways of carbon from the surface to the deep ocean where it is stored for millennia. Climate change can interact with marine ecosystems via changes in the ocean stratification and ocean circulation. In this study we use results from the Community Earth System Model version 2 (CESM2) to assess the effect of a changing climate on biological production and phytoplankton composition in the high latitude North Atlantic Ocean. We find a shift in phytoplankton type dominance from diatoms to small phytoplankton which reduces net primary and export productivity. Using a conceptual carbon-cycle model forced with CESM2 results, we give a rough estimate of a positive phytoplankton composition-atmospheric CO2 feedback of approximately 60 GtCO2/°C warming in the North Atlantic which lowers the 1.5° and 2.0°C warming safe carbon budgets

Cascading transitions in the climate system

We introduce a framework of cascading tipping, i.e. a sequence of abrupt transitions occurring because a transition in one subsystem changes the background conditions for another subsystem. A mathematical framework of elementary deterministic cascading tipping points in autonomous dynamical systems is presented containing the double-fold, fold–Hopf, Hopf–fold and double-Hopf as the most generic cases. Statistical indicators which can be used as early warning indicators of cascading tipping events in stochastic, non-stationary systems are suggested. The concept of cascading tipping is illustrated through a conceptual model of the coupled North Atlantic Ocean – El Niño–Southern Oscillation (ENSO) system, demonstrating the possibility of such cascading events in the climate system.</p

Fragmented tipping in a spatially heterogeneous world

Many climate subsystems are thought to be susceptible to tipping—and some might be close to a tipping point. The general belief and intuition, based on simple conceptual models of tipping elements, is that tipping leads to reorganization of the full (sub)system. Here, we explore tipping in conceptual, but spatially extended and spatially heterogenous models. These are extensions of conceptual models taken from all sorts of climate system components on multiple spatial scales. By analysis of the bifurcation structure of such systems, special stable equilibrium states are revealed: coexistence states with part of the spatial domain in one state, and part in another, with a spatial interface between these regions. These coexistence states critically depend on the size and the spatial heterogeneity of the (sub)system. In particular, in these systems the crossing of a tipping point not necessarily leads to a full reorganization of the system. Instead, it might lead to a reorganization of only part of the spatial domain, limiting the impact of these events on the system's functioning