Use of Lexan Petri-type long dishes instead of growth tubes for clock mutants

Use of Lexan Petri-type long dishes instead of growth tubes for clock mutant

Domestic heating behaviour and room temperatures: Empirical evidence from Scottish homes

In this paper, we describe patterns of residential heating based on data from 255 homes in and around Edinburgh, Scotland, UK, spanning August 2016 to June 2018. We describe: (i) the room temperatures achieved, (ii) the diurnal durations of heating use, and (iii) common diurnal patterns of heating behaviour. We investigate how these factors vary between weekdays and weekends, over the course of the year, by external temperature, and by room type. We compare these empirical findings with the simplifying assumptions about heating patterns found in the UK’s Standard Assessment Procedure (SAP), a widely-used building energy performance model. There are areas of concurrence and others of substantial difference with these model assumptions. Indoor achieved temperatures are substantially lower than SAP assumptions. The duration and timings of heating use vary substantially between homes and along lines of season and outdoor temperature, whereas the SAP model assumes no such variation. Little variation is found along the lines of weekday vs. weekend, whereas the SAP model assumes differences, or between living space and other rooms, consistent with the SAP. The results are relevant for those interested in how SAP assumptions regarding household heating behaviours and achieved indoor temperatures concur with empirical data

The diversity of repression: measuring state repressive repertoires with events data

Tactical repertoires of mobilization and repression play an essential role in understanding dynamics of political violence, yet existing quantitative approaches focus primarily on intensities or counts of repressive actions. We focus instead on the diversity of repression, and demonstrate a novel method of measuring repertoires of state repression using event data. We show that more repressive states are likely to employ more diverse repertoires of repression, rather than specializing narrowly in particularly coercive tactics. We demonstrate that, globally, repertoires of state repression are growing less diverse over time. Finally, in the Online appendix, we model repertoires of repression across countries and over time, finding evidence of broader repertoires during protest and civil war, but narrower under democratic regimes and international human rights treaties

A study of the deep structure of the energy landscape of glassy polystyrene: the exponential distribution of the energy-barriers revealed by high-field Electron Spin Resonance spectroscopy

The reorientation of one small paramagnetic molecule (spin probe) in glassy polystyrene (PS) is studied by high-field Electron Spin Resonance spectroscopy at two different Larmor frequencies (190 and 285 GHz). The exponential distribution of the energy-barriers for the rotational motion of the spin probe is unambigously evidenced at both 240K and 270K. The same shape for the distribution of the energy-barriers of PS was evidenced by the master curves provided by previous mechanical and light scattering studies. The breadth of the energy-barriers distribution of the spin probe is in the range of the estimates of the breadth of the PS energy-barriers distribution. The evidence that the deep structure of the energy landscape of PS exhibits the exponential shape of the energy-barriers distribution agrees with results from extreme-value statistics and the trap model by Bouchaud and coworkers.Comment: Final version in press as Letter to the Editor on J.Phys.:Condensed Matter. Changes in bol

Ocean ensemble forecasting. Part I: Ensemble Mediterranean winds from a Bayesian hierarchical model

A Bayesian hierarchical model (BHM) is developed to estimate surface vector wind (SVW) fields and associated uncertainties over the Mediterranean Sea. The BHM–SVW incorporates data-stage inputs from analyses and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and SVW retrievals from the QuikSCAT data record. The process-model stage of the BHM–SVW is based on a Rayleigh friction equation model for surface winds. Dynamical interpretations of posterior distributions of the BHM–SVW parameters are discussed. Ten realizations from the posterior distribution of the BHM–SVW are used to force the data-assimilation step of an experimental ensemble ocean forecast system for the Mediterranean Sea in order to create a set of ensemble initial conditions. The sequential data-assimilation method of the Mediterranean forecast system (MFS) is adapted to the ensemble implementation. Analyses of sample ensemble initial conditions for a single data-assimilation period in MFS are presented to demonstrate the multivariate impact of the BHM–SVW ensemble generation methodology. Ensemble initial-condition spread is quantified by computing standard deviations of ocean state variable fields over the ten ensemble members. The methodological findings in this article are of two kinds. From the perspective of statistical modelling, the process-model development is more closely related tophysicalbalances than inpreviousworkwithmodels for the SVW.Fromthe ocean forecast perspective, the generation of ocean ensemble initial conditions via BHM is shown to be practical for operational implementation in an ensemble ocean forecast system. Phenomenologically, ensemble spread generated via BHM–SVW occurs on ocean mesoscale time- and space-scales, in close association with strong synoptic-scale wind-forcing events. A companion article describes the impacts of the BHM–SVW ensemble method on the ocean forecast in comparisons with more traditional ensemble methods

Ocean ensemble forecasting. Part II: Mediterranean Forecast System response

This article analyzes the ocean forecast response to surface vector wind (SVW) distributions generated by a Bayesian hierarchical model (BHM) developed in Part I of this series. A new method for ocean ensemble forecasting (OEF), the socalled BHM-SVW-OEF, is described. BHM-SVW realizations are used to produce and force perturbations in the ocean state during 14 day analysis and 10 day forecast cycles of the Mediterranean Forecast System (MFS). The BHM-SVW-OEF ocean response spread is amplified at the mesoscales and in the pycnocline of the eddy field. The new method is compared with an ensemble response forced by European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EEPS) surface winds, and with an ensemble forecast started from perturbed initial conditions derived froman ad hoc thermocline intensified random perturbation (TIRP) method. The EEPS-OEF shows spread on basin scales while the TIRP-OEF response is mesoscale-intensified as in the BHM-SVW-OEF response. TIRP-OEF perturbations fill more of the MFS domain, while the BHM-SVW-OEF perturbations are more location-specific, concentrating ensemble spread at the sites where the ocean-model response to uncertainty in the surface wind forcing is largest

Better Nonlinear Models from Noisy Data: Attractors with Maximum Likelihood

A new approach to nonlinear modelling is presented which, by incorporating the global behaviour of the model, lifts shortcomings of both least squares and total least squares parameter estimates. Although ubiquitous in practice, a least squares approach is fundamentally flawed in that it assumes independent, normally distributed (IND) forecast errors: nonlinear models will not yield IND errors even if the noise is IND. A new cost function is obtained via the maximum likelihood principle; superior results are illustrated both for small data sets and infinitely long data streams.Comment: RevTex, 11 pages, 4 figure

Modeling dynamic controls on ice streams: a Bayesian statistical approach

This is the published version, also available here: http://dx.doi.org/10.3189/002214308786570917.Our main goal is to exemplify the study of ice-stream dynamics via Bayesian statistical analysis incorporating physical, though imperfectly known, models using data that are both incomplete and noisy. The physical–statistical models we propose account for these uncertainties in a coherent, hierarchical manner. The initial modeling assumption estimates basal shear stress as equal to driving stress, but subsequently includes a random corrector process to account for model error. The resulting stochastic equation is incorporated into a simple model for surface velocities. Use of Bayes' theorem allows us to make inferences on all unknowns given basal elevation, surface elevation and surface velocity. The result is a posterior distribution of possible values that can be summarized in a number of ways. For example, the posterior mean of the stress field indicates average behavior at any location in the field, and the posterior standard deviations describe associated uncertainties. We analyze data from the 'Northeast Greenland Ice Stream' and illustrate how scientific conclusions may be drawn from our Bayesian analysis

Ocean Ensemble Forecasting, Part II: Mediterranean Forecast System Response

This paper analyzes the ocean forecast response to surface vector wind (SVW) distributions generated by a Bayesian Hierarchical Model (BHM) developed in Part I (Milliff et al., 2009). A new method for Ocean Ensemble Forecasting (OEF), so-called BHM-SVW-OEF, is described. BHM-SVW realizations are used to produce and force perturbations in the ocean state during 14-day analysis and 10-day forecast cycles of the Mediterranean Forecast System (MFS). The BHM-SVW-OEF ocean response spread is amplified at the mesoscales and pycnocline of the eddy field. The new method is compared to an ensemble response forced by ECMWF Ensemble Prediction System (EEPS) surface winds, and to an ensemble forecast started from perturbed initial conditions derived from an ad hoc Thermocline Intensified Random Perturbation (TIRP) method. The EEPS-OEF shows spread at the basin scales while the TIRP-OEF response is mesoscale intensified as in the BHM-SVW-OEF response. TIRP-OEF perturbations fill more of the MFS domain while the BHM-SVW-OEF perturbations are more location-specific, concentrating ensemble spread at the sites where the ocean model response to uncertainty in the surface wind forcing is largest. The BHM-SVW-OEF method offers a practical and objective means for producing short-term forecast spread by modeling surface atmospheric forcing uncertainties that have maximum impact at the ocean mesoscales