PO53C:
Developments and Ocean Applications of Data Assimilation, Uncertainty, and Sensitivity Analyses III


Session ID#: 11486

Session Description:
Data assimilation and uncertainty and sensitivity analyses are vital components in the production of ocean science reanalyses for the study of various ocean processes. They are also used in model calibration (including parameter estimation), design of observation systems, and for operational forecasts and analyses. The challenges in this area are numerous due to the non-linear interaction of multiple spatio-temporal scales as well as uncertainties due to the resolution of physical processes, parameterizations, and uncertain inputs. The goal of this session is to bring together researchers working in the areas of ocean data assimilation, model sensitivity analysis, and uncertainty quantification, with the goal of discussing new technical developments and recent applications. Contributions concerning the following issues are particularly of interest:

-       New developments and original applications of data assimilation, uncertainty and sensitivity analyses methods

-       Coupled data assimilation, including ocean-atmosphere and ocean-biogeochemical systems

-       Estimation and uncertainty quantification of ocean models parameters, inputs, and outputs

-       Developments of advanced ocean operational and reanalysis systems

-       Assimilation of new data sets and design of observation systems

Primary Chair:  Ibrahim Hoteit, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Chairs:  Bruce D Cornuelle, University of California San Diego, La Jolla, CA, United States, Mohamed Iskandarani, University of Miami - RSMAS, Miami, FL, United States and Hans E Ngodock, Naval Research Lab Stennis Space Center, Stennis Space Center, MS, United States
Moderators:  Ibrahim Hoteit, King Abdullah University of Science and Technology, Physical Sciences and Engineering, Thuwal, Saudi Arabia and Mohamed Iskandarani, University of Miami - RSMAS, Miami, FL, United States
Student Paper Review Liaison:  Ibrahim Hoteit, King Abdullah University of Science and Technology, Physical Sciences and Engineering, Thuwal, Saudi Arabia
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
1990 Uncertainty [INFORMATICS]
4260 Ocean data assimilation and reanalysis [OCEANOGRAPHY: GENERAL]
4263 Ocean predictability and prediction [OCEANOGRAPHY: GENERAL]
Co-Sponsor(s):
  • OD - Ocean Observing and Data Management
  • PC - Past, Present and Future Climate
  • O - Other

Abstracts Submitted to this Session:

PO53C-01
Observation impact studies with the Mercator Ocean analysis and forecasting systems (91089)
Elisabeth D Remy1, Pierre-Yves Le Traon1, Jean-Michel Lellouche2, Marie Drevillon1, Victor Turpin1 and Mounir Benkiran3, (1)Mercator Océan, Ramonville St Agne, France, (2)Mercator Océan, Ramonville Saint Agne, France, (3)Mercator Ocean, D&D, Ramonvile St-Agne, France
PO53C-02
Inverse Regional Modeling with Adjoint-Free Technique (87290)
Max Yaremchuk, Naval Research Lab, Stennis Space Center, MS, United States, Paul Martin, Naval Research Laboratory, Oceanography Division, Stennis Space Center, MS, United States, Gleb Panteleev, University of Alaska Fairbanks, Fairbanks, AK, United States and Chris Beattie, Virginia Tech
PO53C-03
Quantifying the Impacts of Initial and Wind Forcing Uncertainties on Oceanic ForecastUncertainties in the Gulf of Mexico. (91868)
Mohamed Iskandarani, University of Miami - RSMAS, Miami, FL, United States, Guotu Li, Duke, Mechanical Engineering and Material Science, Durham, NC, United States, Matthieu Le Henaff, CIMAS/University of Miami, Miami, FL, United States, Justin Winokur, Sandia National Laboratories, Albuquerque, NM, United States, Olivier P. Le Maitre, Laboratoire d'Informatique pour la Mécanique et les Science de l'Ingénieur, Orsay, France and Omar M Knio, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
PO53C-04
Comparison of Data Assimilation for Biogeochemical Ocean Models of Different Complexities -- an Example Using Joint Physical-Biological Assimilation for a 3D Regional Model (92427)
Jann Paul Mattern1, Hajoon Song2, Christopher A Edwards3, Andrew M Moore3 and Jerome Fiechter4, (1)University of California Santa Cruz, Ocean Sciences Department, Santa Cruz, CA, United States, (2)Massachusetts Institute of Technology, Cambridge, MA, United States, (3)University of California Santa Cruz, Santa Cruz, CA, United States, (4)University of California Santa Cruz, Ocean Sciences, Santa Cruz, CA, United States
PO53C-05
Multiscale Data Assimilation for Very High Resolution Models (92106)
Zhijin Li, NASA Jet Propulsion Laboratory, Pasadena, CA, United States, James C McWilliams, University of California Los Angeles, Atmospheric and Oceanic Sciences, Los Angeles, CA, United States and Kayo Ide, University of Maryland, College Park, MD, United States
PO53C-06
Assimilation of High-Density Low-Precision GNSS-R Altimetry Observations to Constrain Simulations of the Ocean Circulation - Impact on SSH and Subsurface Processes (90951)
Jan Saynisch1, Maximilian Semmling1, Jens Wickert1 and Maik Thomas2, (1)Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany, (2)Free University of Berlin, Berlin, Germany
PO53C-07
Bayesian estimation of observation error covariance matrix in the equatorial Pacific (93303)
Genta Ueno, The Inst of Statistical Math, Tokyo, Japan
PO53C-08
A Comparison of Linear and Non-linear Data Assimilation Methods Using the NEMO Ocean Model (91291)
Lars Nerger1, Paul Kirchgessner1, Julian Toedter2 and Bodo Ahrens2, (1)Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research Bremerhaven, Bremerhaven, Germany, (2)University of Frankfurt, Institute for Atmospheric and Environmental Sciences, Frankfurt, Germany
See more of: Physical Oceanography/Ocean Circulation