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Currently available satellite active fire detection products from the VIIRS and MODIS instruments on polar-orbiting satellites produce detection squares in arbitrary locations. There is no global fire/no fire map, no detection under cloud cover, false negatives are common, and the detection squares are much coarser than the resolution of a fire behavior model. Consequently, current active fire satellite detection products should be used to improve fire modeling in a statistical sense only, rather than as a direct input. We describe a new data assimilation method for active fire detection, based on a modification of the fire arrival time to simultaneously minimize the difference from the forecast fire arrival time and maximize the likelihood of the fire detection data. This method is inspired by contour detection methods used in computer vision, and it can be cast as a Bayesian inverse problem technique, or a generalized Tikhonov regularization. After the new fire arrival time on the whole simulation domain is found, the model can be re-run from a time in the past using the new fire arrival time to generate the heat fluxes and to spin up the atmospheric model until the satellite overpass time, when the coupled simulation continues from the modified state., Comment: 9 pages, VII International Conference on Forest Fire Research, Coimbra, Portugal, November 17-20, 2014

Fuel moisture has a major influence on the behavior of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content observations from remote automated weather stations (RAWS) into a time-lag fuel moisture model. RAWS are spatially sparse and a mechanism is needed to estimate fuel moisture content at locations potentially distant from observational stations. This is arranged using a trend surface model (TSM), which allows us to account for the effects of topography and atmospheric state on the spatial variability of fuel moisture content. At each location of interest, the TSM provides a pseudo-observation, which is assimilated via Kalman filtering. The method is tested with the time-lag fuel moisture model in the coupled weather-fire code WRF-SFIRE on 10-hr fuel moisture content observations from Colorado RAWS in 2013. We show using leave-one-out testing that the TSM compares favorably with inverse squared distance interpolation as used in the Wildland Fire Assessment System. Finally, we demonstrate that the data assimilation method is able to improve fuel moisture content estimates in unobserved fuel classes., Comment: 28 pages

In this study, we describe how WRF-Sfire is coupled with WRF-Chem to construct WRFSC, an integrated forecast system for wildfire and smoke prediction. The integrated forecast system has the advantage of not requiring a simple plume-rise model and assumptions about the size and heat release from the fire in order to determine fire emissions into the atmosphere. With WRF-Sfire, wildfire spread, plume and plume-top heights are predicted directly, at every WRF timestep, providing comprehensive meteorology and fire emissions to the chemical transport model WRF-Chem. Evaluation of WRFSC was based on comparisons between available observations to the results of two WRFSC simulations. The study found overall good agreement between forecasted and observed fire spread and smoke transport for the Witch-Guejito fire. Also the simulated PM2.5 (fine particulate matter) peak concentrations matched the observations. However, the NO and ozone levels were underestimated in the simulations and the peak concentrations were mistimed. Determining the terminal or plume-top height is one of the most important aspects of simulating wildfire plume transport, and the study found overall good agreement between simulated and observed plume-top heights, with some (10% or less) underestimation by the simulations. One of the most promising results of the study was the agreement between passive-tracer modeled plume-top heights for the Barker Canyon fire simulation and observations. This simulation took only 13h, with the first 24h forecast ready in almost 3h, making it a possible operational tool for providing emission profiles for external chemical transport models., Comment: 28 pages, 12 figures

Fuel moisture is a major influence on the behavior of wildland fires and an important underlying factor in fire risk. We present a method to assimilate spatially sparse fuel moisture observations from remote automatic weather stations (RAWS) into the moisture model in WRF-SFIRE. WRF-SFIRE is a coupled atmospheric and fire behavior model which simulates the evolution of fuel moisture in idealized fuel species based on atmospheric state. The proposed method uses a modified trend surface model to estimate the fuel moisture field and its uncertainty based on currently available observations. At each grid point of WRF-SFIRE, this information is combined with the model forecast using a nonlinear Kalman filter, leading to an updated estimate of fuel moisture. We demonstrate the effectiveness of the method with tests in two real-world situations: a region in Southern California, where two large Santa Ana fires occurred recently, and on a domain enclosing Colorado., Comment: 4th Fire Behavior and Fuels Conference Raleigh, North Carolina, USA, February 18 - 22, 2013

A single-mirror small-size (1M-SST) Davies-Cotton telescope has been proposed for the southern observatory of the Cherenkov Telescope Array (CTA) by a consortium of scientific institutions from Poland, Switzerland, and Germany. The telescope has a 4 m diameter reflector and will be equipped with a fully digital camera based on Geiger avalanche photodiodes (APDs). Such a design is particularly interesting for CTA because it represents a very simple, reliable, and cheap solution for a SST. Here we present the design and the characteristics of the mechanical structure of the 1M-SST telescope and its drive system. We also discuss the results of a finite element method analysis in order to demonstrate the conformance of the design with the CTA specifications and scientific objectives. In addition, we report on the current status of the construction of a prototype telescope structure at the Institute of Nuclear Physics PAS in Krakow., Comment: In Proceedings of the 33rd International Cosmic Ray Conference (ICRC2013), Rio de Janeiro (Brazil). All CTA contributions at arXiv:1307.2232

The Cherenkov Telescope Array (CTA) is the next generation very high energy gamma-ray observatory. It will consist of three classes of telescopes, of large, medium and small sizes. The small telescopes, of 4 m diameter, will be dedicated to the observations of the highest energy gamma-rays, above several TeV. We present the technical characteristics of a single mirror, 4 m diameter, Davies-Cotton telescope for the CTA and the performance of the sub-array consisting of the telescopes of this type. The telescope will be equipped with a fully digital camera based on custom made, hexagonal Geiger-mode avalanche photodiodes. The development of cameras based on such devices is an RnD since traditionally photomultipliers are used. The photodiodes are now being characterized at various institutions of the CTA Consortium. Glass mirrors will be used, although an alternative is being considered: composite mirrors that could be adopted if they meet the project requirements. We present a design of the telescope structure, its components and results of the numerical simulations of the telescope performance., Comment: In Proceedings of the 33rd International Cosmic Ray Conference (ICRC2013), Rio de Janeiro (Brazil). All CTA contributions at arXiv:1307.2232

Atmospheric pollution regulations have emerged as a dominant obstacle to prescribed burns. Thus, forecasting the pollution caused by wildland fires has acquired high importance. WRF and SFIRE model wildland fire spread in a two-way interaction with the atmosphere. The surface heat flux from the fire causes strong updrafts, which in turn change the winds and affect the fire spread. Fire emissions, estimated from the burning organic matter, are inserted in every time step into WRF-Chem tracers at the lowest atmospheric layer. The buoyancy caused by the fire then naturally simulates plume dynamics, and the chemical transport in WRF-Chem provides a forecast of the pollution spread. We discuss the choice of wood burning models and compatible chemical transport models in WRF-Chem, and demonstrate the results on case studies., Comment: Proceedings of 4th Fire Behavior and Fuels Conference, February 18-22, 2013, Raleigh, North Carolina, USA

We describe two recent additions to WRF coupled with a fire spread model. Fire propagation is strongly dependent on fuel moisture, which in turn depends on the history of the atmosphere. We have implemented a equilibrium time-lag model of fuel moisture driven by WRF variables. The code allows the user to specify fuel parameters, with the defaults calibrated to the Canadian fire danger rating system for 10-hour fuel. The moisture model can run coupled with the atmosphere-fire model, or offline from WRF output to equilibrate the moisture over a period of time and to provide initial moisture conditions for a coupled atmosphere-fire-moisture simulation. The fire model also inserts smoke tracers into WRF-Chem to model the transport of fire emissions. The coupled model is available from OpenWFM.org. An earlier version of the fire model coupled with atmosphere is a part of WRF release., Comment: 2012 WRF Users Workshop, Boulder, CO, 25-29 June 2012, paper P51, 5 pages. Corrected a typo

We introduce several useful utilities in development for the creation and analysis of real wildland fire simulations using WRF and SFIRE. These utilities exist as standalone programs and scripts as well as extensions to other well known software. Python web scrapers automate the process of downloading and preprocessing atmospheric and surface data from common sources. Other scripts simplify the domain setup by creating parameter files automatically. Integration with Google Earth allows users to explore the simulation in a 3D environment along with real surface imagery. Postprocessing scripts provide the user with a number of output data formats compatible with many commonly used visualization suites allowing for the creation of high quality 3D renderings. As a whole, these improvements build toward a unified web application that brings a sophisticated wildland fire modeling environment to scientists and users alike., Comment: Submitted to proceedings of IGARSS 2012, 4 papers, 1 figure

This study uses in-situ measurements collected during the FireFlux field experiment to evaluate and improve the performance of coupled atmosphere-fire model WRF-Sfire. The simulation by WRF-Sfire of the experimental burn shows that WRF-Sfire is capable of providing realistic head fire rate-of-spread and the vertical temperature structure of the fire plume, and, up to 10 m above ground level, fire-induced surface flow and vertical velocities within the plume. The model captured the changes in wind speed and direction before, during, and after fire front passage, along with arrival times of wind speed, temperature, and updraft maximae, at the two instrumented flux towers used in FireFlux. The model overestimated vertical velocities and underestimated horizontal wind speeds measured at tower heights above the 10 m, and it is hypothesized that the limited model resolution over estimated the fire front depth, leading to too high a heat release and, subsequently, too strong an updraft. However, on the whole, WRF-Sfire fire plume behavior is consistent with the interpretation of FireFlux observations. The study suggests optimal experimental pre-planning, design, and execution of future field campaigns that are needed for further coupled atmosphere-fire model development and evaluation.

Phonology typically describes speech in terms of discrete signs like features. The field of intonational phonology uses discrete accents to describe intonation and prosody. But, are such representations useful? The results of mimicry experiments indicate that discrete signs are not a useful representation of the shape of intonation contours. Human behaviour seems to be better represented by a attractors where memory retains substantial fine detail about an utterance. There is no evidence that discrete abstract representations that might be formed that have an effect on the speech that is subsequently produced. This paper also discusses conditions under which a discrete phonology can arise from an attractor model and why - for intonation - attractors can be inferred without the implying a discrete phonology., Comment: 36 pages, plus extra figures

We present a methodology to change the state of the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE, based on Rothermel's formula and the level set method, and with a fuel moisture model. The fire perimeter in the model changes in response to data while the model is running. However, the atmosphere state takes time to develop in response to the forcing by the heat flux from the fire. Therefore, an artificial fire history is created from an earlier fire perimeter to the new perimeter, and replayed with the proper heat fluxes to allow the atmosphere state to adjust. The method is an extension of an earlier method to start the coupled fire model from a developed fire perimeter rather than an ignition point. The level set method is also used to identify parameters of the simulation, such as the spread rate and the fuel moisture. The coupled model is available from openwfm.org, and it extends the WRF-Fire code in WRF release., Comment: ICCS 2012, 10 pages; corrected some DOI typesetting in the references

There are many wildfire behaviors of increasing relevance that are outside the forecast capabilities of even the most sophisticated operational fire spread and fire behavior model. The limitations of the operational models are due primarily to their inability to represent coupled fire-atmosphere interactions. Coupled wildfire-atmosphere models are physics-based fluid-dynamical prognostic models of wildfire spread and behavior that attempt an almost complete representation of fire-atmosphere interactions. This level of fidelity however means that these models cannot be used operationally. The reason is that, despite ever increasing computational resources, the complexity and range of processes and scales (1 mm to 100 km) involved in this modeling approach make computational costs prohibitively expensive. In this study we propose an intermediate approach. A physics-based coupled atmosphere-fire model is used to resolve the large-scale and local weather as well as the atmosphere-fire interactions, while combustion is represented simply using an existing operational surface fire behavior model. This model combination strikes a balance between fidelity and speed of execution. The feasibility of this approach is examined based on an analysis of a numerical simulation of two very large Santa Ana fires using WRF-Sfire, a coupled atmosphere-fire model available at the Open Wildland Fire Modeling Community (OpenWFM.org); an earlier version is available as WRF-Fire in WRF release. The study demonstrates that a wind and fire spread forecast of reasonable accuracy was obtained at an execution speed that would have made real-time wildfire forecasting of this event possible., Comment: Exploring the Mega-fire Reality 2011, November 14-17, 2011, Florida State University Conference Center, Tallahassee, Florida. Added full author names

The ability to forecast grass fire spread could be of a great importance for agencies making decisions about prescribed burns. However, the usefulness of the models used for fire-spread predictions is limited by the time required for completing the coupled atmosphere-fire simulations. In this study we analyze the sensitivity of a coupled model with respect to the vertical resolution of the atmospheric grid and the resolution of fire mesh that both affect computational performance of the model. Based on the observations of the plume properties recorded during the FireFlux experiment (Clements et al., 2007), we try to establish the optimal model configuration that provides realistic results for the least computational expense., Comment: AMS, Ninth Symposium on Fire and Forest Meteorology, Palm Springs 2011

We present an overview of a modeling environment, consisting of a coupled atmosphere-wildfire model, utilities for visualization, data processing, and diagnostics, open source software repositories, and a community wiki. The fire model, called SFIRE, is based on a fire-spread model, implemented by the level-set method, and it is coupled with the Weather Research Forecasting (WRF) model. A version with a subset of the features is distributed with WRF 3.3 as WRF-Fire. In each time step, the fire module takes the wind as input and returns the latent and sensible heat fluxes. The software architecture uses WRF parallel infrastructure for massively parallel computing. Recent features of the code include interpolation from an ideal logarithmic wind profile for nonhomogeneous fuels and ignition from a fire perimeter with an atmosphere and fire spin-up. Real runs use online sources for fuel maps, fine-scale topography, and meteorological data, and can run faster than real time. Visualization pathways allow generating images and animations in many packages, including VisTrails, VAPOR, MayaVi, and Paraview, as well as output to Google Earth. The environment is available from openwfm.org. New diagnostic variables were added to the code recently, including a new kind of fireline intensity, which takes into account also the speed of burning, unlike Byram's fireline intensity., Comment: 12 pages; Ninth Symposium on Fire and Forest Meteorology, Palm Springs, CA, October 2011

The current WRF-Fire model starts the fire from a given ignition point at a given time. We want to start the model from a given fire perimeter at a given time instead. However, the fuel balance and the state of the atmosphere depend on the history of the fire. The purpose of this work is to create an approximate artificial history of the fire based on the given fire perimeter and time and an approximate ignition point and time. Replaying the fire history then establishes a reasonable fuel balance and outputs heat fluxes into the atmospheric model, which allow the atmospheric circulation to develop. Then the coupled atmosphere-fire model takes over. In this preliminary investigation, the ignition times in the fire area are calculated based on the distance from the ignition point to the perimeter, assuming that the perimeter is convex or star-shaped. Simulation results for an ideal example show that the fire can continue in a natural way from the perimeter. Possible extensions include algorithms for more general perimeters and running the fire model backwards in time from the perimeter to create a more realistic history. The model used extends WRF-Fire and it is available from openwfm.org., Comment: 12th Annual WRF Users' Workshop, Boulder, CO, June 2011

We use a coupled atmosphere-fire model to simulate a fire that occurred on August 14--17, 2009, in the Harmanli region, Bulgaria. Data was obtained from GIS and satellites imagery, and from standard atmospheric data sources. Fuel data was classified in the 13 Anderson categories. For correct fire behavior, the spatial resolution of the models needed to be fine enough to resolve the essential micrometeorological effects. The simulation results are compared to available incident data. The code runs faster than real time on a cluster. The model is available from openwfm.org and it extends WRF-Fire from WRF 3.3 release., Comment: 8 pages, 2 tables, 5 figures. 8th International Conference on Large-Scale Scientific Computations, June 6-10, 2011, Sozopol, Bulgaria

We describe the physical model, numerical algorithms, and software structure of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the level-set method, coupled with the Weather Research and Forecasting model. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. The level-set method allows submesh representation of the burning region and flexible implementation of various ignition modes. WRF-Fire is distributed as a part of WRF and it uses the WRF parallel infrastructure for parallel computing., Comment: Version 3.3, 41 pages, 2 tables, 12 figures. As published in Discussions, under review for Geoscientific Model Development

We describe the coupled atmosphere-wildfire model WRF-Fire, which is distributed as a part of WRF. The fire module is based on a fire-spread model, implemented by the level-set method. In each time step, the fire module takes the wind as input and returns the latent and sensible heat fluxes. We report on the software architecture and features of the software., Comment: 91st American Meteorological Society Annual Meeting, Seattle, WA, January 2011

The paper presents methods for evaluating the accuracy of alignments between transcriptions and audio recordings. The methods have been applied to the Spoken British National Corpus, which is an extensive and varied corpus of natural unscripted speech. Early results show good agreement with human ratings of alignment accuracy. The methods also provide an indication of the location of likely alignment problems; this should allow efficient manual examination of large corpora. Automatic checking of such alignments is crucial when analysing any very large corpus, since even the best current speech alignment systems will occasionally make serious errors. The methods described here use a hybrid approach based on statistics of the speech signal itself, statistics of the labels being evaluated, and statistics linking the two., Comment: Four pages, 3 figures. Presented at "New Tools and Methods for Very-Large-Scale Phonetics Research", University of Pennsylvania, January 28-31, 2011

In this paper, we ask what properties makes a large corpus more or less useful. We suggest that size, by itself, should not be the ultimate goal of building a corpus. Large-scale corpora are considered desirable because they offer statistical stability and rich variation. But this rich variation means more factors to control and evaluate, which can limit the advantages of size. We discuss the use of multi-channel data to complement large-scale speech corpora. Even though multi-channel data may limit the scale of a corpus (due to the complex and labor-intensive nature of data collection) they can offer information that allows us to tease apart various factors related to speech production.

A novel procedure is described for accelerating the convergence of Markov chain Monte Carlo computations. The algorithm uses an adaptive bootstrap technique to generate candidate steps in the Markov Chain. It is efficient for symmetric, convex probability distributions, similar to multivariate Gaussians, and it can be used for Bayesian estimation or for obtaining maximum likelihood solutions with confidence limits. As a test case, the Law of Categorical Judgment (Corrected) was fitted with the algorithm to data sets from simulated rating scale experiments. The correct parameters were recovered from practical-sized data sets simulated for Full Signal Detection Theory and its special cases of standard Signal Detection Theory and Complementary Signal Detection Theory.

The notion of the Trojan state of a Rydberg electron, introduced by I.Bialynicki-Birula, M.Kali\'nski, and J.H.Eberly (Phys. Rev. Lett. 73, 1777 (1994)) is extended to the case of the electromagnetic field quantized in acavity. The shape of the electronic wave packet describing the Trojan state is practically the same as in the previously studied externally driven system. The fluctuations of the quantized electromagnetic field around its classical value exhibit strong squeezing. The emergence of Trojan states in the cylindrically symmetrical system is attributed to spontaneous symmetry braking., Comment: 9 pages, 8 figures

An operational time of arrival is introduced using a realistic position and momentum measurement scheme. The phase space measurement involves the dynamics of a quantum particle probed by a measuring device. For such a measurement an operational positive operator valued measure in phase space is introduced and investigated. In such an operational formalism a quantum mechanical time operator is constructed and analyzed. A phase space time and energy uncertainty relation is derived., Comment: 23 pages, 5 figures, to appear in Phys. Rev. A