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Jan O. Haerter

Publications and source records attributed to Jan O. Haerter.

At least 19 recordsLinked to original sources

Self-organized quantization and oscillations on continuous fixed-energy sandpiles

Atmospheric self-organization and activator-inhibitor dynamics in biology provide examples of checkerboard-like spatio-temporal organization. We study a simple model for local activation-inhibition processes. Our model, first introduced in the context of atmospheric moisture dynamics, is a continuous-energy and non-Abelian version of the fixed-energy sandpile model. Each lattice site is populated by a non-negative real number, its energy. Upon each timestep all sites with energy exceeding a unit threshold re-distribute their energy at equal parts to their nearest neighbors. The limit cycle dynamics gives rise to a complex phase diagram in dependence on the mean energy $μ$: For low $μ$, all dynamics ceases after few re-distribution events. For large $μ$, the dynamics is well-described as a diffusion process, where the order parameter, spatial variance $σ$, is removed. States at intermediate $μ$ are dominated by checkerboard-like period-two phases which are however interspersed by much more complex phases of far longer periods. Phases are separated by discontinuous jumps in $σ$ or $\partial_μσ$ - akin to first and higher-order phase transitions. Overall, the energy landscape is dominated by few energy levels which occur as sharp spikes in the single-site density of states and are robust to noise.

cond-mat.stat-mech

DiuSST: A conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive SST

The diurnal variability of sea surface temperature (SST) may play an important role for cloud organization above the tropical ocean, with implications for precipitation extremes, storminess, and climate sensitivity. Recent cloud-resolving simulations demonstrate how imposed diurnal SST oscillations can strongly, and delicately, impact mesoscale convective organization. In spite of this nuanced interaction, many idealized modeling studies of tropical convection either assume a constant, homogeneous SST or, in case of a responsive sea surface, represent the upper ocean by a slab with fixed thickness. Here we show that slab ocean models with constant heat capacity fail to capture the wind-dependence of observed diurnal sea surface warming. To alleviate this shortcoming, we present a simple, yet explicitly depth-resolved model of upper-ocean temperature dynamics under atmospheric forcing. Our modular scheme describes turbulent mixing as diffusion with a wind-dependent diffusivity, in addition to a bulk mixing term and heat fluxes entering as sources and sinks. Using observational data, we apply Bayesian inference to calibrate the model. In contrast with a slab model, our model captures the exponential reduction of the diurnal warming amplitude with increasing wind speed. Further, our model performs comparably to a more elaborately parameterized diurnal warm layer model. Formulated as a single partial differential equation with three key tuning parameters, the model is suitable as an interactive numerical boundary condition for idealized atmospheric simulations.

physics.ao-ph

The diurnal path to persistent convective self-aggregation

Clustering of tropical thunderstorms constitutes an important climate feedback because it influences the heat radiated to space. Convective self-aggregation (CSA) is a profound modelling paradigm for explaining the clustering of tropical oceanic thunderstorms. However, CSA is hampered in the realistic limit of fine model resolution when cold pools -- dense air masses beneath thunderstorm clouds -- are well-resolved. Studies on CSA usually assume the surface temperature to be constant, despite realistic surface temperatures varying significantly between night and day, even over the sea. Here we mimic oscillating surface temperatures in cloud resolving numerical experiments and show that, in the presence of a diurnal cycle, CSA is enabled by high resolutions. We attribute this finding to vigorous combined cold pools emerging in symbiosis with mesoscale convective systems. Such cold pools suppress buoyancy in extended regions ($\mathbf{\sim 100}$ km) and enable the formation of persistent dry patches. Our findings help clarify how the tropical cloud field forms sustained clusters under realistic conditions and may have implications for the origin of extreme thunderstorm rainfall and tropical cyclones.

physics.ao-ph

How weakened cold pools open for convective self-aggregation

In radiative-convective equilibrium (RCE) simulations, convective self-aggregation (CSA) is the spontaneous organization into segregated cloudy and cloud-free regions. Evidence exists for how CSA is stabilized, but how it arises favorably on large domains is not settled. Using large-eddy simulations (LES), we link the spatial organization emerging from the interaction of cold pools (CPs) to CSA. We systematically weaken simulated rain evaporation to reduce maximal CP radii, $R_{\text{max}}$, and find reducing $R_{\text{max}}$ causes CSA to occur earlier. We further identify a typical rain cell generation time and a minimum radius, $R_{\text{min}}$, around a given rain cell, within which the formation of subsequent rain cells is suppressed. Incorporating $R_{\text{min}}$ and $R_{\text{max}}$, we propose a toy model that captures how CSA arises earlier on large domains: when two CPs of radii $r_{i,j}\in[R_{\text{min}},R_{\text{max}}]$ collide, they form a new convective event. These findings imply that interactions between CPs may explain the initial stages of CSA.

physics.ao-ph

Convective Self-Aggregation as a Cold-Pool Driven Critical Phenomenon

Convective self-aggregation is when thunderstorm clouds cluster over a constant temperature surface in radiative convective equilibrium. Self-aggregation was implicated in the Madden-Julian Oscillation and hurricanes. Yet, numerical simulations succeed or fail at producing self-aggregation, depending on modeling choices. Common explanations for self-aggregation invoke radiative effects, acting to concentrate moisture in a sub-domain. Interaction between cold pools, caused by rain evaporation, drives reorganization of boundary layer moisture and triggers new updrafts. We propose a simple model for aggregation by cold pool interaction, assuming a local number density $ρ(\mathbf{r})$ of precipitation cells, and that interaction scales quadratically with $ρ(\mathbf{r})$. Our model mimics global energy constraints by limiting further cell production when many cells are present. The phase diagram shows a continuous phase transition between a continuum and an aggregated state. Strong cold pool-cold pool interaction gives a uniform convective phase, while weak interaction yields few and independent cells. Segregation results for intermediate interaction strength.

nlin.AO

Circling in on Convective Organization

Cold pools (CPs) contribute to convective organization. However, it is unclear by which mechanisms organization occurs. By using a particle method to track CP gust fronts in large eddy simulations, we characterize the basic collision modes between CPs. Our results show that CP interactions, where three expanding gust fronts force an updraft, are key at triggering new convection. Using this, we conceptualize CP dynamics into a parameter-free mathematical model: circles expand from initially random points in space. Where two expanding circles collide, a stationary front is formed. However, where three expanding circles enclose a single point, a new expanding circle is seeded. This simple model supports three fundamental features of CP dynamics: precipitation cells constitute a spatially interacting system; CPs come in generations; and scales steadily increase throughout the diurnal cycle. Finally, this model provides a framework for how CPs act to cause convective self-organization, clustering, and extremes.

nlin.AO

Tracking the Gust Fronts of Convective Cold Pools

It is increasingly acknowledged that cold pools can influence the initiation of new convective cells. Yet, the full complexity of convective organization through cold pool interaction is poorly understood. This lack of understanding may partially be due to the intricacy of the dynamical pattern formed by precipitation cells and their cold pools. Additionally, how exactly cold pools interact is insufficiently known. To better understand this dynamics, we develop a tracking algorithm for cold pool gust fronts. Rather than tracking thermodynamic anomalies, which do not generally coincide with the gust front boundaries, our approach tracks the dynamical cold pool outflow. Our algorithm first determines the locus of the precipitation event. Second, relative to this origin and for each azimuthal bin, the steepest gradient in the near-surface horizontal radial velocity $v_r$ is employed to determine the respective locus of the cold pool gust front edge. Steepest $v_r$-gradients imply largest updraft velocities, hence strongest dynamical triggering. Results are compared to a previous algorithm based on the steepest gradient in temperature --- highlighting the benefit of the method described here in determining dynamically active gust front regions. Applying the method to a range of numerical experiments, the algorithm successfully tracks an ensemble of cold pools. A linear relation emerges between the peak rain intensity of a given event and maximal $v_r$ for its associated cold pool gust front --- a relation found to be nearly independent of the specific sensitivity experiment.

physics.ao-ph

Diurnal Self-Aggregation

Convective self-aggregation is a modelling paradigm for thunderstorm organisation over a constant-temperature tropical sea surface. This setup can give rise to cloud clusters over timescales of weeks. In reality, sea surface temperatures do oscillate diurnally, affecting the atmospheric state. Over land, surface temperatures vary more strongly, and rain rate is significantly influenced. Here, we carry out a substantial suite of cloud-resolving numerical experiments, and find that even weak surface temperature oscillations enable qualitatively different dynamics to emerge: the spatial distribution of rainfall is only homogeneous during the first day. Already on the second day, the rain field is firmly structured. In later days, the clustering becomes stronger and alternates from day-to-day. We show that these features are robust to changes in resolution, domain size, and surface temperature, but can be removed by a reduction of the amplitude of oscillation, suggesting a transition to a clustered state. Maximal clustering occurs at a scale of $\mathbf{l_{max}\approx 180\;km}$, a scale we relate to the emergence of mesoscale convective systems. At $\mathbf{l_{max}}$ rainfall is strongly enhanced and far exceeds the rainfall expected at random. We explain the transition to clustering using simple conceptual modelling. Our results may help clarify how continental extremes build up and how cloud clustering over the tropical ocean could emerge much faster than through conventional self-aggregation alone.

physics.ao-ph

A statistical model for isolated convective precipitation events

To study the diurnal evolution of the convective cloud field, we develop a precipitation cell tracking algorithm which records the merging and fragmentation of convective cells during their life cycles, and apply it on large eddy simulation (LES) data. Conditioning on the area covered by each cell, our algorithm is capable of analyzing an arbitrary number of auxiliary fields, such as the anomalies of temperature and moisture, convective available potential energy (CAPE) and convective inhibition (CIN). For tracks that do not merge or split (termed "solitary"), many of these quantities show generic, often nearly linear relations that hardly depend on the forcing conditions of the simulations, such as surface temperature. This finding allows us to propose a highly idealized model of rain events, where the surface precipitation area is circular and a cell's precipitation intensity falls off linearly with the distance from the respective cell center. The drop-off gradient is nearly independent of track duration and cell size, which allows for a generic description of such solitary tracks, with the only remaining parameter the peak intensity. In contrast to the simple and robust behavior of solitary tracks, tracks that result from merging of two or more cells show a much more complicated behavior. The most intense, long lasting and largest tracks indeed stem from multi-mergers - tracks involved in repeated merging. Another interesting finding is that the precipitation intensity of tracks does not strongly depend on the absolute amount of local initial CAPE, which is only partially consumed by most rain events. Rather, our results speak to boundary layer cooling, induced by rain re-evaporation, as the cause for CAPE reduction, CIN increase and shutdown of precipitation cells.

physics.ao-ph

Noise-Induced Polarization Switch in Single and Multiplex Complex Networks

The combination of bistability and noise is ubiquitous in complex systems, from biological to social interactions, and has important implications for their functioning and resilience. We analyze a simple three-state model for bistability in networks under varying unbiased noise. In a fully connected network increasing noise yields a collapse of bistability to an unpolarised state. In contrast, in complex networks noise can abruptly switch the polarization state in an irreversible way. When two networks are combined through increasing multiplex coupling, one is dominant and progressively imposes its state on the other, offsetting or promoting the ability of noise to switch polarization. Our results show that dynamical correlations and asymmetry in dynamical processes in networks are sufficient for allowing unbiased noise to produce abrupt irreversible transitions between extremes, which can be neutralized or enhanced by multiplex coupling.

nlin.AO

Intensification of convective extremes driven by cloud-cloud interaction

In a changing climate, a key role may be played by the response of convective-type cloud and precipitation to temperature changes. Yet, it is unclear if precipitation intensities will increase mainly due to modified thermodynamic forcing or due to stronger convective dynamics. In gradual self-organization, convective events produce highest intensities late in the day. Tracking rain cells throughout their life cycles, we find that interacting events respond strongly to changes in boundary conditions. Conversely, events without interaction remain unaffected. Increased surface temperature indeed leads to more interaction and higher precipitation extremes. However, a similar intensification occurs when leaving temperature unchanged but simply granting more time for self-organization.Our study implies that the convective field as a whole acquires a memory of past precipitation and inter-cloud dynamics, driving extremes. Our results implicate that the dynamical interaction between convective clouds must be incorporated in global climate models to describe convective extremes and the diurnal cycle more realistically.

physics.ao-ph

Food web assembly rules

In food webs, many interacting species coexist despite the restrictions imposed by the competitive exclusion principle and apparent competition. For the generalized Lotka-Volterra equations, sustainable coexistence necessitates nonzero determinant of the interaction matrix. Here we show that this requirement is equivalent to demanding that each species be part of a non-overlapping pairing, which substantially constrains the food web structure. We demonstrate that a stable food web can always be obtained if a non-overlapping pairing exists. If it does not, the matrix rank can be used to quantify the lack of niches, corresponding to unpaired species. For the species richness at each trophic level, we derive the food web assembly rules, which specify sustainable combinations. In neighboring levels, these rules allow the higher level to avert competitive exclusion at the lower, thereby incorporating apparent competition. In agreement with data, the assembly rules predict high species numbers at intermediate levels and thinning at the top and bottom. Using comprehensive food web data, we demonstrate how omnivores or parasites with hosts at multiple trophic levels can loosen the constraints and help obtain coexistence in food webs. Hence, omnivory may be the glue that keeps communities intact even under extinction or ecological release of species.

q-bio.PE

The expert game -- Cooperation in social communication

Large parts of professional human communication proceed in a request-reply fashion, whereby requests contain specifics of the information desired while replies can deliver the required information. However, time limitations often force individuals to prioritize some while neglecting others. This dilemma will inevitably force individuals into defecting against some communication partners to give attention to others. Furthermore, communication entirely breaks down when individuals act purely egoistically as replies would never be issued and quest for desired information would always be prioritized. Here we present an experiment, termed "The expert game", where a number of individuals communicate with one-another through an electronic messaging system. By imposing a strict limit on the number of sent messages, individuals were required to decide between requesting information that is beneficial for themselves or helping others by replying to their requests. In the experiment, individuals were assigned the task to find the expert on a specific topic and receive a reply from that expert. Tasks and expertise of each player were periodically re-assigned to randomize the required interactions. Resisting this randomization, a non-random network of cooperative communication between individuals formed. We use a simple Bayesian inference algorithm to model each player's trust in the cooperativity of others with good experimental agreement. Our results suggest that human communication in groups of individuals is strategic and favors cooperation with trusted parties at the cost of defection against others. To establish and maintain trusted links a significant fraction of time-resources is allocated, even in situations where the information transmitted is negligible.

cs.SI

Communication dynamics in finite capacity social networks

In communication networks structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and dynamics, a generic model, based on the local interaction between nodes, is considered for the communication in large social networks. In agreement with data from a large human organization, we show that the flow is non-Markovian and controlled by the temporal limitations of individuals. We confirm the versatility of our model by predicting simultaneously the degree-dependent node activity, the balance between information input and output of nodes and the degree distribution. Finally, we quantify the limitations to network analysis when it is based on data sampled over a finite period of time.

physics.soc-ph

The Hall Number, Optical Sum Rule and Carrier Density for the $t$-$t'$-$J$ model

We revisit the relationship between three classical measures of particle number, namely the chemical doping $x$, the Hall number $x_{hall}$ and the particle number inferred from the optical sum rule $x_{opt}$. We study the $t$-$t'$-$J$ model of correlations on a square lattice, as a minimal model for High $T_c$ systems, using numerical methods to evaluate the low temperature Kubo conductivites. These measures disagree significantly in this type of system, owing to Mott Hubbard correlations. The Hall constant has a complex behavior with several changes of sign as a function of filling $x$, depending upon the model parameters. Thus $x_{hall}$ depends sensitively on $t'$ and $J$, due to a kind of quantum interference.

cond-mat.str-el

Dynamical thermal response functions for strongly correlated one-dimensional systems

In this article we study the thermal response functions for two one-dimensional models, namely the Hubbard and spin-less fermion $t$-$V$ models. By exactly diagonalizing finite sized systems we calculate dynamical electrical, thermoelectrical, and thermal conductivities via the Kubo formalism. The thermopower (Seebeck coefficient), Lorenz number, and dimensionless figure of merit are then constructed which are quantities of great interest to the physics community both theoretically and experimentally. We also geometrically frustrate these systems and destroy integrability by the inclusion of a second neighbor hop. These frustrated systems are shown to have enhanced thermopower and Lorenz number at intermediate and low temperatures.

cond-mat.str-el

Thermoelectric effects in a strongly correlated model for Na$_x$CoO$_2$

Thermal response functions of strongly correlated electron systems are of appreciable interest to the larger scientific community both theoretically and technologically. Here we focus on the infinitely correlated t-J model on a geometrically frustrated two-dimensional triangular lattice. Using exact diagonalization on a finite sized system we calculate the dynamical thermal response functions in order to determine the thermopower, Lorenz number, and dimensionless figure of merit. The dynamical thermal response functions is compared to the infinite frequency limit and shown to be very weak functions of frequency, hence, establishing the validity of the high frequency formalism recently proposed by Shastry for the thermopower, Lorenz number, and the dimensionless figure of merit. Further, the thermopower is demonstrated to have a low to mid temperature enhancement when the sign of the hopping parameter $t$ is switched from positive to negative for the geometrically frustrated lattice considered.

cond-mat.str-el

Strong Correlations Produce the Curie-Weiss Phase of Na$_{x}$CoO$_2$

Within the t-J model we study several experimentally accessible properties of the 2D-triangular lattice system Na$_x$CoO$_2$, using a numerically exact canonical ensemble study of 12 to 18 site triangular toroidal clusters as well as the icosahedron. Focusing on the doping regime of $x\sim0.7$, we study the temperature dependent chemical potential, specific heat, magnetic susceptibility and the dynamic Hall coefficient $R_H(T,ω)$ as well as the magnetic field dependent thermopower. We find a crossover between two phases near $x \sim 0.75$ in susceptibility and field suppression of the thermopower arising from strong correlations. An interesting connection is found between the temperature dependence of the diamagnetic susceptibility and the Hall-coefficient. We predict a large thermopower enhancement, arising from {\em transport corrections} to the Heikes-Mott formula, in a model situation where the sign of hopping is reversed from that applicable to Na$_x$CoO$_2$.

cond-mat.str-el