Jan Mandel
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View article: Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts
Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts Open
Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in using satellites to detect fire locations further provides t…
View article: Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model
Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model Open
Correctly initializing the fire within coupled fire-atmosphere models is critical for producing accurate forecasts of meteorology near the fire, as well as the fire growth, and plume evolution. Improperly initializing the fire in a coupled…
View article: Introduction to Infinite Dimensional Statistics and Applications
Introduction to Infinite Dimensional Statistics and Applications Open
These notes started to educate ourselves and to collect some background for our future work, with the hope that perhaps they will be useful to others also. Many if not all results are more or less elementary or available in the literature,…
View article: Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts
Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts Open
Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in using satellites to detect fire locations further provides t…
View article: Integration of a Coupled Fire-Atmosphere Model Into a Regional Air Quality Forecasting System for Wildfire Events
Integration of a Coupled Fire-Atmosphere Model Into a Regional Air Quality Forecasting System for Wildfire Events Open
The objective of this study was to assess feasibility of integrating a coupled fire-atmosphere model within an air-quality forecast system to create a multiscale air-quality modeling framework designed to simulate wildfire smoke. For this …
View article: Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data
Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data Open
Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progressi…
View article: Score matching filters
Score matching filters Open
<p>A widely popular group of data assimilation methods in meteorological and geophysical sciences is formed by filters based on Monte-Carlo approximation of the traditional Kalman filter, e.g. <span>E</span><span>ns…
View article: Simple finite elements and multigrid for efficient mass-consistent wind downscaling in a coupled fire-atmosphere model
Simple finite elements and multigrid for efficient mass-consistent wind downscaling in a coupled fire-atmosphere model Open
We present a simple finite element formulation of mass-consistent approximation, and a fast multigrid iterative method with adaptive semicoarsening, which maintains the convergence of the iterations over a range of grids and penalty coeffi…
View article: Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix
Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix Open
We present an ensemble filtering method based on a linear model for the precision matrix (the inverse of the covariance) with the parameters determined by Score Matching Estimation. The method provides a rigorous covariance regularization …
View article: Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn
Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn Open
Forecasting fire growth, plume rise and smoke impacts on air quality remains a challenging task. Wildland fires dynamically interact with the atmosphere, which can impact fire behavior, plume rises, and smoke dispersion. For understory fir…
View article: Modeling Wildfire Smoke Feedback Mechanisms Using a Coupled Fire‐Atmosphere Model With a Radiatively Active Aerosol Scheme
Modeling Wildfire Smoke Feedback Mechanisms Using a Coupled Fire‐Atmosphere Model With a Radiatively Active Aerosol Scheme Open
During the summer of 2015, a number of large wildfires burned across Northern California in areas of localized topographic relief. Persistent valley smoke hindered fire‐fighting efforts, delayed helicopter operations, and exposed communiti…
View article: Fire behaviour and smoke modelling: model improvement and measurement needs for next-generation smoke research and forecasting systems
Fire behaviour and smoke modelling: model improvement and measurement needs for next-generation smoke research and forecasting systems Open
There is an urgent need for next-generation smoke research and forecasting (SRF) systems to meet the challenges of the growing air quality, health and safety concerns associated with wildland fire emissions. This review paper presents simu…
View article: Retrieving Fire Perimeters and Ignition Points of Large Wildfires from Satellite Observations
Retrieving Fire Perimeters and Ignition Points of Large Wildfires from Satellite Observations Open
We present a new statistical interpolation method to estimate fire perimeters from Active Fires detection data from satellite-based sensors, such as MODIS, VIIRS, and GOES-16. Active Fires data is available at varying temporal and spatial …
View article: Data Likelihood of Active Fires Satellite Detection and Applications to Ignition Estimation and Data Assimilation
Data Likelihood of Active Fires Satellite Detection and Applications to Ignition Estimation and Data Assimilation Open
Data likelihood of fire detection is the probability of the observed detection outcome given the state of the fire spread model. We derive fire detection likelihood of satellite data as a function of the fire arrival time on the model grid…
View article: Quantifying the Impact of Biomass Burning Emissions on Major Inorganic Aerosols and Their Precursors in the U.S.
Quantifying the Impact of Biomass Burning Emissions on Major Inorganic Aerosols and Their Precursors in the U.S. Open
The primary sources for inorganic aerosols from biomass burning are rather negligible, but they are predominantly formed chemically following emission of their precursors (e.g., SO 2 , NH 3 , HO x , and NO x ). The biomass burning contribu…
View article: On well-posedness of Bayesian data assimilation and inverse problems in Hilbert space
On well-posedness of Bayesian data assimilation and inverse problems in Hilbert space Open
Bayesian inverse problem on an infinite dimensional separable Hilbert space with the whole state observed is well posed when the prior state distribution is a Gaussian probability measure and the data error covariance is a cylindric Gaussi…
View article: On well-posedness of Bayesian data assimilation and inverse problems in Hilbert space
On well-posedness of Bayesian data assimilation and inverse problems in Hilbert space Open
Bayesian inverse problem on an infinite dimensional separable Hilbert space with the whole state observed is well posed when the prior state distribution is a Gaussian probability measure and the data error covariance is a cylindric Gaussi…
View article: Data assimilation of dead fuel moisture observations from remote automated weather stations
Data assimilation of dead fuel moisture observations from remote automated weather stations Open
Fuel moisture has a major influence on the behaviour of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content (FMC) observations from remote automated wea…
View article: Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method
Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method Open
The ensemble Kalman smoother (EnKS) is used as a linear least-squares solver in the Gauss–Newton method for the large nonlinear least-squares system in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble member…
View article: Spectral diagonal ensemble Kalman filters
Spectral diagonal ensemble Kalman filters Open
A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis. It is proved that this technique improves the approximation of the covariance wh…
View article: Hybrid Levenberg–Marquardt and weak constraint ensemble Kalman smoother method
Hybrid Levenberg–Marquardt and weak constraint ensemble Kalman smoother method Open
We propose to use the ensemble Kalman smoother (EnKS) as the linear least squares solver in the Gauss–Newton method for the large nonlinear least squares in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble m…
View article: Spectral diagonal ensemble Kalman filters
Spectral diagonal ensemble Kalman filters Open
A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis. It is proved that this technique improves the aproximation of the covariance whe…
View article: Convergence of the Square Root Ensemble Kalman Filter in the Large Ensemble Limit
Convergence of the Square Root Ensemble Kalman Filter in the Large Ensemble Limit Open
Ensemble filters implement sequential Bayesian estimation by representing the probability distribution by an ensemble mean and covariance. Unbiased square root ensemble filters use deterministic algorithms to produce an analysis (posterior…
View article: Towards Data-Driven Operational Wildfire Spread Modeling: A Report of the NSF-Funded WIFIRE Workshop
Towards Data-Driven Operational Wildfire Spread Modeling: A Report of the NSF-Funded WIFIRE Workshop Open
This report presents a record of the discussions that took place during the workshop entitled “Towards Data-Driven Operational Wildfire Spread Modeling” held on January 12-13, 2015, at the University of California, San Diego. The workshop …