OM21A:
Advances in Data Assimilation and Uncertainty Quantification for Ocean Forecasting and Analysis II


Session ID#: 37779

Session Description:
Data assimilation and uncertainty quantification are vital for ocean forecasting and reanalysis. They are also widely used for model calibration (including parameter inference) and observation systems design. The challenges in this area are numerous due to the paucity of observations, nonlinear dynamics and interactions at multiple spatio-temporal scales, involved numerical dimensions, and also uncertainties due to the resolution of physical processes, parameterizations, and inputs. The goal of this session is to bring together researchers working on the development and applications of ocean data assimilation and uncertainty quantification to discuss recent advances in the field. Contributions concerning the following issues are of particular interest:

- New technical developments and original applications of ocean data assimilation and uncertainty quantification

- Pushing the limits of predictability, through stochastic parameterization and in term of targeting submesoscales and extended forecasting windows

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

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

- Estimating and accounting for ocean models errors

- Assimilation of new datasets and design of observation systems

Primary Chair:  Ibrahim Hoteit, King Abdullah University of Science and Technology, Physical Sciences and Engineering, Thuwal, Saudi Arabia
Co-chairs:  Mohamed Iskandarani, University of Miami - RSMAS, Miami, FL, United States, Bruce D Cornuelle, University of California San Diego, La Jolla, CA, United States and Matthew Carrier, Naval Research Laboratory, Stennis Space Center, MS, United States
Moderators:  Matthew Carrier, Naval Research Laboratory, Stennis Space Center, MS, United States, Mohamed Iskandarani, University of Miami, RSMAS, Department of Ocean Sciences, Miami, FL, United States and Bruce D Cornuelle, Scripps Institution of Oceanography, CA, United States
Student Paper Review Liaison:  Mohamed Iskandarani, University of Miami, RSMAS, Department of Ocean Sciences, Miami, FL, United States
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]

Abstracts Submitted to this Session:

Fault-tolerant Ensemble Data Assimilation in the Red Sea: Analysis of a 5000-member run with a 4 km OGCM (313994)
Ibrahim Hoteit, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, Habib Toye Mahamadou Kele, KAUST, Thuwal, Saudi Arabia, Peng Zhan, Earth Sciences and Engineering Program, King Abdullah University of Science and Technology (KAUST), Jeddah, Saudi Arabia and Samuel Kortas, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
Error covariance tuning for data assimilation in biogeochemical ocean models (313202)
Jann Paul Mattern, Christopher A Edwards and Andrew M Moore, University of California Santa Cruz, Santa Cruz, CA, United States
Traceable observing system experiment in NCEP Global Ocean Data Assimilation System(GODAS) (306371)
Hyun-Chul Lee, IMSG AND EMC/NCEP/NOAA, College Park, MD, United States, David Behringer, Environmental Modeling Center, College Park, MD, United States and Suranjana Saha, National Centers For Environmental Prediction-Environmental Modeling Center, College Park, MD, United States
Assimilation of ocean-induced magnetic signals into an ocean general circulation model (304773)
Christopher Irrgang1, Jan Saynisch1 and Maik Thomas1,2, (1)Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany, (2)Institute of Meteorology, Freie Universität Berlin, Berlin, Germany, Berlin, Germany
A Multi-Scale Approach to High Resolution Observations within a 4DVAR Analysis System (305103)
Matthew Carrier1, John Osborne2, Hans Ngodock3, Scott R Smith3, Innocent Souopgui4 and Joseph Matthew D'Addezio5, (1)Naval Research Laboratory, Stennis Space Center, MS, United States, (2)American Society for Engineering Education (ASEE), Washington, DC, DC, United States, (3)Naval Research Lab Stennis Space Center, Stennis Space Center, MS, United States, (4)The University of New Orleans, New Orleans, LA, United States, (5)University of South Carolina Columbia, Columbia, SC, United States
An observation operator for assimilating skin and sub-skin sea surface temperature (323745)
Sam Pimentel1, Danitra Danaxa2, Eric Jansen3, Gerasimos Korres2, Isabelle Mirouze3, Andrea Storto4 and Simon Tse5, (1)Trinity Western University, Langley, BC, Canada, (2)Hellenic Centre for Marine Research, Greece, (3)Euro Mediterranean Centre on Climate Change, Italy, (4)Fondazione CMCC, Bolognia, Italy, (5)Trinity Western University, BC, Canada
Interdisciplinary Bayesian Data Assimilation (326840)
Pierre F J Lermusiaux1, Abhinav Gupta1 and Wael Hajj Ali2, (1)Massachusetts Institute of Technology, Cambridge, MA, United States, (2)Massachusetts Institute of Technology, MA, United States

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