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MCRN

An Introduction to Variational Data Assimilation

Naratip Santitissadeekorn gives an introductory survey of variational techniques in data assimilation including 3D-VAR and 4D-VAR. This talk was given on 10-2-14. Naratip Santitissadeekorn gives an introductory survey of variational techniques in data assimilation including 3D-VAR and 4D-VAR. This t…
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MCRN

Statistical Data Assimilation For Parameter Estimation In Costal Ocean Hydrodynamics Modeling

Coastal ocean models are used for a variety of applications, including modeling tides and hurricane storm surge. These models numerically solve the shallow water equations, which are derived by depth integrating the Navier-Stokes equations. The inherent uncertainties in coastal ocean models are a re…
  • Resource Presentations
MCRN

Complex Energy Systems

This is the opening guest lecture for the Electric Grid Focus Group. Dr. Michael Chertkov of Los Alamos National Lab describes the statistical and mathematical problems arising in complex energy systems, including the electric grid and gas networks. Systems with high penetration of renewable energy …
  • Resource Presentations
MCRN

IMA Hot Topics Workshop: Predictability in Earth System Processes

A major question facing climate modeling is how best to incorporate data into models. As climate models increase in complexity, their results become correspondingly intricate. Such models represent climate processes spanning multiple spatial and temporal scales and must relate disparate physical phe…
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MCRN

Midwest Mathematics and Climate Conference

The conference is sponsored by the National Science Foundation, Institute of Mathematics and Its Applications, the Office of Research,College of Liberal Arts and Sciences, and the Department of Mathematics, Department of Geography/Atmospheric Science Program, and The Commons at the University of Kan…
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MCRN

Hybrid EnKF and Particle Filter: Lagrangian DA and Parameter Estimation

Dealing with high dimensional systems is one of the central problems of data assimilation. A strategy is proposed here for systems that enjoys a skew-product structure. Christopher Jones, University of North Carolina at Chapel Hill, presents joint work with Naratip Santitssadeekorn to the Stochastic…
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MCRN

Extending the square root method to account for model noise in the ensemble Kalman filter

Presented by Patrick Raanes on 2-18-2015 Abstract:A novel approach to account for model noise in the forecast step of the Ensemble Kalman filter (EnKF) is proposed. The core method is based on the approach of the analysis step of ensemble square root filters (ETKF), and consists in right-multiplying…
  • Resource Presentations
MCRN

NSF's Science Nation Video on David Holland's field work in Greenland

http://www.nsf.gov/news/special_reports/science_nation/meltingglaciers.jsp?WT.mc_id=USNSF_51 MCRN member and founding principal investigator David Holland was featured in the NSF's Science Nation video, titled, "Mathematician uses skills to study Greenland's retreating glaciers," on Septembe…
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MCRN

Andy Reagan: Masters Thesis

Andy Reagan at UVM gives a talk about his masters work on uncertainty quantification and data assimilation to improve the numerical prediction of fluids in the thermosyphon. This talk will involve several data assimilation methods, including variational techniques, but will focus on LETKF. This talk…
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MCRN

Correlated Observation Errors in Data Assimilation

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information, and reduction in analysis accu…
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MCRN

Toward a hybrid particle-ensemble Kalman filter for assimilating data from Lagrangian instruments into high dimensional models

Presented by Elaine Spiller on 3-26-15Abstract:We discuss a recently proposed hybrid particle-ensemble Kalman filter for assimilating Lagrangian data, and apply it to a high-dimensional quasi-geostrophic ocean model. Effectively the hybrid filter applies a particle filter to the highly nonlinear, lo…
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MCRN

Particle filters for geophysical applications

Avoiding degeneracy is a crucial challenge for particle filters. Results have shown that the number of particles scales exponentially with respect to the number of independent observations. In this talk I will review attempts to counteract this phenomenon by exploiting proposal densities. I will put…
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MCRN

Complex Phytoplankton Dynamics: The Mathematical Perspective

Bibliography by Arjen Doelman and Antonios Zagaris to accompany tutorial lecture on Phytoplankton-Nutrient Modeling at the 2011 MBI Workshop on Ocean Ecologies and their Physical Habitats in a Changing Climate and the follow-on lectures on Phytoplankton growth in oligotrophic oceans: Linear theory b…
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MCRN

Realistic modeling and analysis of synchronization dynamics in power-grid networks

An imperative condition for the functioning of a power-grid network is that its power generators remain synchronized. Disturbances can prompt desynchronization, which is a process that has been involved in large power outages. In this talk I will first give a comparative review of three leading mode…
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MCRN

Midwest Mathematics and Climate Conference - Day 1 Afternoon Session

Graham Feingold, National Oceanic & Atmospheric AdministratonDynamical System Analogues to Cloud SystemsShallow convection exhibits fascinating cellular structures at scales of a few to several hundred kilometers. Configurations of relatively cloud free open cell states, or much cloudier closed cell…
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MCRN

Midwest Mathematics and Climate Conference - Day 2 Morning Session

Juan Restrepo, Oregon State UniversityData AssimilationAccounting for uncertainties has led us to alter our expectations of what is predictable and how such predictions compare to nature. A significant effort, in recent years, has been placed on creating new uncertainty quantification techniques, re…
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MCRN

The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

A comparison of parameter estimation techniques for a simplified ecosystem model. A follow-on to the OpTIC study with a more complex model (DALEC). A comparison of parameter estimation techniques for a simplified ecosystem model. A follow-on to the OpTIC study with a more complex model (DALEC). …
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MCRN

A Tutorial on Kalman Filters

This is an introduction to the Kalman filter, explaining some underlying assumptions, use and extensions of the method.This talk was given on 10-7-2015. This is an introduction to the Kalman filter, explaining some underlying assumptions, use and extensions of the method.This talk was given on 10-7-…
  • Resource Presentations
MCRN

Hybrid EnKF and Particle Filter: Langrangian DA and Parameter Estimation

This is a talk delivered at the Imperial College meeting on Stochastic Modeling in GFD, Data Assimilation and Non-equilibrium Phenomena on 11-4-2015. This talk presents joint research by Chris Jones at UNC-CH and Naratip Santitissandeekorn on hybrid data assimilation methods. This is a talk delivere…
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MCRN

An Introduction to Lagrangian Data Assimilation - Part I

Laura Slivinski at Woods Hole Oceanographic Institute gives an introduction to Lagrangian Data Assimlation on 10-30-2014. Laura Slivinski at Woods Hole Oceanographic Institute gives an introduction to Lagrangian Data Assimlation on 10-30-2014. …
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