NG31A:
Advances in Data Assimilation, Predictability, and Uncertainty Quantification III Posters

Submit an Abstract to this Session



Session ID#: 31478

Session Description:
Geophysical processes are typically sparsely observed, and their dynamics are nonlinear, so that the statistics are non-Gaussian. Successful and efficient data assimilation (DA), uncertainty quantification (UQ) and prediction require that these characteristics be directly addressed. This session focuses on ideas and advanced techniques for DA, UQ and predictability, for example: variational methods, Kalman filters, adjoint and ensemble sensitivity, hybrid techniques, Monte Carlo sampling, particle filters, as well as linear approximations to non-Gaussian/nonlinear applications. Contributions are welcome from all of the geosciences, as well as the mathematical and statistical communities, to share ideas that can be applied across the disciplines of the AGU and the larger scientific community.
Primary Convener:  Steven J Fletcher, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Conveners:  Carmen Blackwood, Jet Propulsion Laboratory, Pasadena, CA, United States, Brian C Ancell, Texas Tech University, Lubbock, TX, United States and Matthias Morzfeld, University of Arizona, Department of Mathematics, Tucson, AZ, United States
Chairs:  Matthias Morzfeld, University of Arizona, Department of Mathematics, Tucson, AZ, United States, Steven J Fletcher, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, Carmen Blackwood, Jet Propulsion Laboratory, Pasadena, CA, United States and Brian C Ancell, Texas Tech Univ-Geosciences, Lubbock, TX, United States
OSPA Liaison:  Matthias Morzfeld, University of Arizona, Department of Mathematics, Tucson, AZ, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • H - Hydrology
  • IN - Earth and Space Science Informatics
  • OS - Ocean Sciences
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
1990 Uncertainty [INFORMATICS]
3260 Inverse theory [MATHEMATICAL GEOPHYSICS]
3315 Data assimilation [ATMOSPHERIC PROCESSES]

Abstracts Submitted to this Session:

Filtering observations without the initial guess (214776)
Toshio Michael Chin1, Claudio Abbondanza1, Richard S Gross2, Michael B Heflin2, Jay W Parker1, Benedikt Soja1 and Xiaoping Wu2, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
The Nature and Variability of Ensemble Sensitivity Fields that Diagnose Severe Convection (220701)
Brian C Ancell, Texas Tech University, Lubbock, TX, United States
Using the Local Ensemble Transform Kalman Filter (LETKF) For Upper Atmospheric Modelling (221800)
Sean Elvidge, University of Birmingham, SERENE, Birmingham, B15, United Kingdom and Matthew James Angling, University of Birmingham, Birmingham, United Kingdom
On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models (222047)
Elizabeth Satterfield, US Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States, Daniel Hodyss, Naval Research Lab Monterey, Marine Meterology, Monterey, CA, United States, David Kuhl, Naval Research Laboratory, Remote Sensing Division, Washington, D.C., United States and Craig H Bishop, Naval Research Lab, Monterey, United States
More data is not always better: why and how feature-based data assimilation can be useful. (222093)
Spence Lunderman, University of Arizona, Tucson, AZ, United States and Matthias Morzfeld, Scripps Institution of Oceanography, University of California, San Diego, Institute of Geophysics and Planetary Physics, La Jolla, United States
Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors (226762)
Travis M Harty1, Antonio Lorenzo2, William Holmgren2 and Matthias Morzfeld3, (1)University of Arizona, Program in Applied Mathematics, Tucson, AZ, United States, (2)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (3)University of Arizona, Department of Mathematics, Tucson, AZ, United States
Localization of a variational particle smoother (225698)
Matthias Morzfeld, University of Arizona, Department of Mathematics, Tucson, AZ, United States, Daniel Hodyss, Naval Research Lab Monterey, Marine Meterology, Monterey, CA, United States and Jonathan Poterjoy, University of Maryland, Atmospheric and Oceanic Science, College Park, United States
Implementing of lognormal humidity and cloud-related control variables for the NCEP GSI hybrid EnVAR Assimilation scheme. (224904)
Steven J Fletcher, Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, Daryl Kleist, NOAA/NWS/NCEP/EMC, College Park, United States and Kayo Ide, University of Maryland, College Park, MD, United States
Detecting Non-Gaussian and Lognormal Characteristics of Temperature and Water Vapor Mixing Ratio (231947)
Anton Kliewer1, Steven J Fletcher2, Andrew S Jones2 and John Michael Forsythe3, (1)Colorado State University, Cooperative Institute for Research in the Atmosphere @NOAA/OAR/ESRL Global Systems Lab, Boulder, CO, United States, (2)Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, (3)Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, United States
Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data (232866)
John Michael Forsythe1, Anton Kliewer2, Steven J Fletcher3 and Andrew S Jones3, (1)Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, United States, (2)Colorado State University, Cooperative Institute for Research in the Atmosphere @NOAA/OAR/ESRL Global Systems Lab, Boulder, CO, United States, (3)Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Transient Calibration of a Variably-Saturated Groundwater Flow Model By Iterative Ensemble Smoothering: Synthetic Case and Application to the Flow Induced During Shaft Excavation and Operation of the Bure Underground Research Laboratory (233758)
Dan-Thuy Lam1, Jaouher Kerrou1, Hakim Benabderrahmane2 and Pierre Perrochet1, (1)University of Neuchâtel, Centre for Hydrogeology and Geothermics (CHYN), Neuchâtel, Switzerland, (2)ANDRA National Radioactive Waste Management Agency, Chatenay-Malabri Cedex, France
Bayesian Approaches for Model and Multi-mission Satellites Data Fusion (234457)
Mehdi Khaki Dr, Curtin University, Western Australian Centre for Geodesy and The Institute for Geoscience Research, Perth, WA, Australia, Ehsan Forootan, Cardiff University, School of Earth & Ocean Sciences, Cardiff, United Kingdom, Joseph Awange, Western Australian Centre for Geodesy and The Institute for Geoscience Research, Curtin University, Perth, Australia, Perth, Australia and Michael Kuhn, Curtin University, Perth, WA, Australia
Model Uncertainty Quantification Methods For Data Assimilation In Partially Observed Multi-Scale Systems (237108)
Sahani Darshika Pathiraja, University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia and Peter Jan van Leeuwen, University of Reading, Meteorology, Reading, United Kingdom
Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF) (240392)
Mozheng Wei1, Patrick J Hogan1, Clark David Rowley2, Ole Martin Smedstad1, Alan J Wallcraft3 and Stephen Gregory Penny4, (1)John C. Stennis Space Center, Stennis Space Center, MS, United States, (2)John C. Stennis Space Center, Oceanography Division, Stennis Space Center, MS, United States, (3)Naval Research Laboratory, Stennis Space Center, MS, United States, (4)NOAA Boulder, Boulder, MD, United States
Quadratic Polynomial Regression using Serial Observation Processing:Implementation within DART (242321)
Daniel Hodyss, Naval Research Lab Monterey, Marine Meteorology, Monterey, CA, United States, Jeffrey L Anderson, NCAR, Boulder, United States, Nancy Collins, NCAR, Boulder, CO, United States, William F Campbell, Organization Not Listed, Washington, DC, United States and Patrick Alexander Reinecke, Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States
Ensemble-sensitivity Analysis Based Observation Targeting for Mesoscale Convection Forecasts and Factors Influencing Observation-Impact Prediction (244064)
Aaron Hill, Texas Tech University, Lubbock, United States, Christopher Weiss, Texas Tech University, Lubbock, TX, United States and Brian C Ancell, Texas Tech Univ-Geosciences, Lubbock, TX, United States
Designing the Social Context for Easier Verification, Validation, and Uncertainty Quantification of Earth Science Data (246670)
Bruce R Barkstrom1, Norman G Loeb2 and Bruce A Wielicki2, (1)Self Employed, Washington, DC, United States, (2)NASA Langley Research Center, Hampton, VA, United States
Efficient Approaches for Propagating Hydrologic Forcing Uncertainty: High-Resolution Applications Over the Western United States (268703)
Jonathan Hobbs1, Michael Turmon2, Cedric H David1, John T Reager II3 and James S. Famiglietti3, (1)Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (3)NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration. (277550)
Bahri Uzunoglu, Uppsala University, Divison of Electricity, Uppsala, Sweden and Yousuff Hussaini, Florida State University, Department of Mathematics, Tallahassee, FL, United States
Multi-Scale 4DVAR Assimilation of Glider Teams on the North Carolina Shelf (277807)
John Joseph Osborne V1, Matthew Carrier2, Jeffrey W Book3, Charlie N. Barron4, Ana E Rice5, Clark David Rowley6, Lucy F Smedstad7, Innocent Souopgui8 and William J Teague7, (1)Organization Not Listed, Washington, DC, United States, (2)U.S. Naval Research Laboratory, Ocean Dynamics and Prediction, Stennis Space Center, United States, (3)U.S. Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, United States, (4)Naval Research Laboratory SSC, Stennis Space Center, United States, (5)U.S. Naval Research Laboratory, Stennis Space Center, MS, United States, (6)John C. Stennis Space Center, Oceanography Division, Stennis Space Center, MS, United States, (7)John C. Stennis Space Center, Stennis Space Center, MS, United States, (8)The University of New Orleans, New Orleans, United States
Efficient data assimilation algorithm for bathymetry application (290732)
Hojat Ghorbanidehno1, Jonghyun Harry Lee2, Matthew Farthing3, Tyler Hesser3, Peter K Kitanidis2 and Eric F Darve1, (1)Stanford University, Mechanical Engineering, Stanford, CA, United States, (2)Engineering Research Center for Re-Inventing the Nation's Urban Water Infrastructure (ReNUWIt), National Science Foundation, Stanford, CA, United States, (3)U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, United States
Reservoir Identification: Parameter Characterization or Feature Classification (297694)
Junxing Cao, Chengdu University of Technology, State Key Laboratory of Oil and Gas Reservoir Geology and Exploration; College of Geophysics, Chengdu, China

See more of: Nonlinear Geophysics