Jan O. Haerter

Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models

AbstractFuture climate model scenarios depend crucially on the models’ adequate representation of the hydrological cycle. Within the EU integrated project Water and Global Change (WATCH), special care is taken to use state-of-the-art climate model output for impacts assessments with a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, given the systematic errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed for correcting climate model output to produce long-term time series with a statistical intensity distribution close to that of the observations. As observations, global reanalyzed daily data of precipitation and temperature were used that were obtained in the WATCH project. Daily time series from three GCMs (GCMs) ECHAM5/Max Planck Institute Ocean Model (MPI-OM), Centre National de Recherches Me...

Climate model bias correction and the role of timescales

Abstract. It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However, the improvements to the statistical properties of the data are limited to the specific timescale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily temperature values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made on the stationarity of the bias over the largest timescales. First, we point out several conditions that have to be fulfilled by model data to make the application of a statistical bias correction meaningful. We then examine the effects of mixing fluctuations on different timescales and suggest an alternative statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.

Targeted Bacterial Immunity Buffers Phage Diversity

ABSTRACT Bacteria have evolved diverse defense mechanisms that allow them to fight viral attacks. One such mechanism, the clustered, regularly interspaced, short palindromic repeat (CRISPR) system, is an adaptive immune system consisting of genetic loci that can take up genetic material from invasive elements (viruses and plasmids) and later use them to reject the returning invaders. It remains an open question how, despite the ongoing evolution of attack and defense mechanisms, bacteria and viral phages manage to coexist. Using a simple mathematical model and a two-dimensional numerical simulation, we found that CRISPR adaptive immunity allows for robust phage-bacterium coexistence even when the number of virus species far exceeds the capacity of CRISPR-encoded genetic memory. Coexistence is predicted to be a consequence of the presence of many interdependent species that stress but do not overrun the bacterial defense system.

Numerical simulations of layered and blended organic photovoltaic cells

We present results obtained from numerical simulations of organic photovaltaic cells as the donor–acceptor morphology evolves from sharply defined layers, to partial blends and finally homogeneous blends. As the mixing percentage increases, the exciton dissociation increases and the diffusion counter-current decreases, resulting in substantially greater short circuit currents but reduced open circuit voltages. Blended structures are more sensitive to mobility than layers due to recombination throughout the bulk. Our model indicates that solar power efficiencies greater than 10% can be achieved when the zero-field charge mobilities approach 10−3cm2∕Vs for partially blended structures.

Probing the precipitation life cycle by iterative rain cell tracking

intensities over Germany. We then combine this data set with surface temperature observations and synoptic observations to group tracks according to convective and stratiform conditions. Convective tracks show clear life cycles in intensity, with peaks shifted off-center toward the beginning of the track, whereas stratiform tracks have comparatively featureless intensity profiles. Our results show that the convective life cycle can lead to convection-dominating precipitation extremes at short time scales, while track-mean intensities may vary much less between the two types. The observed features become more pronounced as surface temperature increases, and in the case of convection even exceeded the rates expected from the Clausius-Clapeyron relation.

Intensification of convective extremes driven by cloud–cloud interaction

Convective precipitation may change in a changing climate. Large eddy simulations of convection with a realistic diurnal cycle suggest that interactions between convective systems and precipitation extremes are influenced by temperature.

Thermoelectric effects in a strongly correlated model for NaxCoO2

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 are 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 [Phys. Rev. B 73, 085117 (2006)] for the thermopower, Lorenz number, and the dimensionless figure of merit. Further, the thermopower is demonstrated to have a low to intermediate temperature enhancement when the sign of the hopping parameter t is switched from positive to negative for the geometrically frustrated lattice [A. P. Ramirez, in More Is Different, edited by N. P. Org and R. N. Bhatt (Princeton University Press, New Jersey, 2001), p. 255] considered.

Strong correlations produce the Curie-Weiss phase of NaxCoO2.

Within the t-J model we study several experimentally accessible properties of the 2D-triangular lattice system NaxCoO2, 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 approximately 0.7, we study the temperature dependent specific heat, magnetic susceptibility, and the dynamic Hall coefficient R_{H}(T,omega) as well as the magnetic field dependent thermopower. We find a crossover between two phases near x approximately 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 transport corrections to the Heikes-Mott formula, in a model situation where the sign of hopping is reversed from that applicable to NaxCoO2.

Statistical precipitation bias correction of gridded model data using point measurements

It is well known that climate model output data cannot be used directly as input to impact models, e.g., hydrology models, due to climate model errors. Recently, it has become customary to apply statistical bias correction to achieve better statistical correspondence to observational data. As climate model output should be interpreted as the space-time average over a given model grid box and output time step, the status quo in bias correction is to employ matching gridded observational data to yield optimal results. Here we show that when gridded observational data are not available, statistical bias correction can be carried out using point measurements, e.g., rain gauges. Our nonparametric method, which we call scale-adapted statistical bias correction (SABC), is achieved by data aggregation of either the available modeled or gauge data. SABC is a straightforward application of the well-known Taylor hypothesis of frozen turbulence. Using climate model and rain gauge data, we show that SABC performs significantly better than equal-time period statistical bias correction.

Dynamical thermal response functions for strongly correlated one-dimensional systems : Hubbard and spinless fermion t-V model

In this paper, we study the thermal response functions for two one-dimensional models, namely, the Hubbard and spinless fermion t-V model, respectively. By exactly diagonalizing finite sized systems, we calculate dynamical, electrical, thermoelectrical, and thermal conductivities via the Kubo formalism J. Phys. Soc. Jpn. 12, 570 1957. 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 in the kinetic energy operator. These frustrated systems are shown to have enhanced thermopower and Lorenz number at intermediate and low temperatures.