205 research outputs found
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. 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
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