NG23C:
Non-Gaussian and Nonlinear Techniques for Data Assimilation/Fusion, Predictability, and Uncertainty Quantification and Neural Networks I

Session ID#: 1829

Tuesday, 16 December 2014: 1:40 PM-3:40 PM
Salon 7 (Marriott Marquis)
Chairs:  Ute C Herzfeld, University Colorado Boulder, Geomathematics, Remote Sensing and Cryospheric Sciences Laboratory; Electrical, Computer and Energy Engineering, Boulder, United States, Steven J Fletcher, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, Brian C Ancell, Texas Tech University, Lubbock, TX, United States and Anton Kliewer, Colorado State University, Cooperative Institute for Research in the Atmosphere @NOAA/OAR/ESRL Global Systems Lab, Boulder, CO, United States
Primary Convener:  Steven J Fletcher, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Co-conveners:  Brian C Ancell, Texas Tech Univ-Geosciences, Lubbock, TX, United States, Matthias Morzfeld, Scripps Institution of Oceanography, University of California, San Diego, Institute of Geophysics and Planetary Physics, La Jolla, United States and Anton Kliewer, Colorado State University, Cooperative Institute for Research in the Atmosphere @NOAA/OAR/ESRL Global Systems Lab, Boulder, CO, United States
OSPA Liaison:  Steven J Fletcher, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Co-Sponsor(s):
  • A - Atmospheric Sciences
  • GC - Global Environmental Change
  • H - Hydrology
  • OS - Ocean Sciences
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
3315 Data assimilation [ATMOSPHERIC PROCESSES]
3325 Monte Carlo technique [ATMOSPHERIC PROCESSES]
4468 Probability distributions, heavy and fat-tailed [NONLINEAR GEOPHYSICS]
Virtual Option?: Yes
Swirl Theme: Characterizing Uncertainty

Abstracts Submitted to this Session:

NG23C-01
Particle Filters for Very High-Dimensional Systems (Invited) (3633)
Peter Jan van Leeuwen, University of Reading, Meteorology, Reading, United Kingdom
NG23C-02
4D Hybrid Ensemble-Variational Data Assimilation for the NCEP GFS: Outer Loops and Variable Transforms (Invited) (3636)
Daryl T Kleist1, Kayo Ide1, Rahul Mahajan2 and Catherine Thomas3, (1)University of Maryland, College Park, MD, United States, (2)Environmental Modeling Center, College Park, MD, United States, (3)IMSG at NOAA NWS NCEP EMC, College Park, United States
NG23C-03
A Global Approach to the Identification of Model Noise (13575)
Alexandre J Chorin1, Kevin K Lin2 and Matthias Morzfeld1, (1)University of California Berkeley, Berkeley, CA, United States, (2)University of Arizona, Mathematics, Tucson, AZ, United States
NG23C-04
A Local Approach to Hybrid Data Assimilation (28764)
Kayo Ide, University of Maryland, College Park, MD, United States and Daryl T Kleist, NOAA NCEP/EMC, College Park, United States
NG23C-05
Bounds on the performance of particle filters (31040)
Chris Snyder, National Center for Atmospheric Research, Boulder, CO, United States and Thomas Bengtsson, Genentech, South San Francisco, CA, United States
NG23C-06
Transport map-accelerated Markov chain Monte Carlo for Bayesian parameter inference (25093)
Youssef Marzouk, Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, Cambridge, United States and Matthew Parno, Cold Regions Research and Engineering Laboratory, Hanover, NH, United States
NG23C-07
Using Self-Organizing Maps in Creation of an Ocean Forecasting System (11028)
Ivica Vilibic1, Nedjeljka Zagar2, Simone Cosoli3, Vlado Dadic1, Damir Ivankovic1, Blaz Jesenko2, Hrvoje Kalinic1, Hrvoje Mihanovic1, Jadranka Sepic1 and Martina Tudor4, (1)Institute of Oceanography and Fisheries, Split, Croatia, (2)University of Ljubljana, Ljubljana, Slovenia, (3)National Institute of Oceanography and Experimental Geophysics - OGS, Trieste, Italy, (4)Croatian Meteorological and Hydrological Service, Zagreb, Croatia
NG23C-08
A connectionist-geostatistical approach for classification of deformation types in ice surfaces (18794)
Lukas R Goetz-Weiss1, Ute C Herzfeld2,3, Robert Griffin Hale4, Elizabeth Clare Hunke5 and Jessica Bobeck1, (1)University of Colorado at Boulder, Boulder, CO, United States, (2)Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, United States, (3)University Colorado Boulder, Geomathematics, Remote Sensing and Cryospheric Sciences Laboratory; Electrical, Computer and Energy Engineering, Boulder, United States, (4)Sierra Nevada Corporation, Broomfield, CO, United States, (5)Los Alamos National Laboratory, Los Alamos, United States
See more of: Nonlinear Geophysics