OS41F:
Improvements in Synoptic, Subseasonal to Seasonal, and Decadal Projections Through Next-Generation Ocean Model Developments, Observations, and Coupled Data Assimilation Posters


Submit an Abstract to this Session


Session ID#: 54139

Session Description:
From weather to climate timescales, detailed atmospheric, oceanic, and land-surface predictions are critical to socioeconomic planning, mitigation, and emergency response. Earth System Models (ESMs) for synoptic, S2S, and decadal predictions depend on accurate ESM component initialization and accurate representations of critical ocean, sea ice, and wave processes. Higher resolutions and regional/component impacts on predictability complicate these dependencies; emerging high-performance computing (HPC) architectures require new algorithms for efficient system use. Implementing CDA in ESMs and improvements to component models, particularly at high resolution and in regionally refined configurations, represents a grand scientific, algorithmic, and computational challenge. Meeting these challenges efficiently within operational run-time constraints will require restructured ocean and atmosphere models that are performant on new HPC systems. This session seeks submissions discussing: novel theoretical and algorithmic techniques for CDA in ESMs, the use of CDA to understand ESMs biases, novel ocean model discretizations, and parameterizations of multiscale phenomena.
Primary Convener:  Jessie Carman, NOAA OAR Weather Program Office, Silver Spring, United States
Conveners:  Luke P Van Roekel, Los Alamos National Laboratory, Los Alamos, United States, Santha Akella, NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, United States and Bradford Johnson, Trivector Services/NOAA OAR, Office of Weather and Air Quality, Silver Spring, MD, United States
Primary Liaison:  Bradford Johnson, Trivector Services/NOAA OAR, Office of Weather and Air Quality, Silver Spring, MD, United States
Chairs:  Jessie Carman, NOAA OAR Weather Program Office, Silver Spring, United States and Luke P Van Roekel, Los Alamos National Laboratory, Los Alamos, United States
OSPA Liaison:  Bradford Johnson, Trivector Services/NOAA OAR, Office of Weather and Air Quality, Silver Spring, MD, United States

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

1622 Earth system modeling [GLOBAL CHANGE]
1627 Coupled models of the climate system [GLOBAL CHANGE]
3315 Data assimilation [ATMOSPHERIC PROCESSES]
4263 Ocean predictability and prediction [OCEANOGRAPHY: GENERAL]

Abstracts Submitted to this Session:

Reduced Order Modeling For Climate-Ocean Models: Feasibility and Applications (465128)
Kenneth Chadwick Sockwell, Florida State University, Scientific Computing, Tallahassee, FL, United States
The development of a coupled data assimilation system using only surface pressure observations: potential for decadal climate prediction initialization (425135)
Xiaosong Yang1, Thomas L Delworth2, Fanrong Jenny Zeng3, William Cooke2 and Liping Zhang4, (1)NOAA, GFDL, Princeton, United States, (2)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (3)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, United States, (4)Princeton University, Princeton, NJ, United States
Efficient Parallel Implementation of Off-line and On-line Ensemble Data Assimilation Interfaces for MOM6 (461232)
Matt Harrison1, Feiyu Lu2, Anthony John Rosati1, Alistair Adcroft3 and Travis Cole Sluka4, (1)Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (2)University Corporation for Atmospheric Research, Boulder, United States, (3)Program for Atmospheric and Oceanic Sciences, Princeton University, Princeton, United States, (4)JCSDA/UCAR, Boulder, United States
Update on the US Navy’s Earth System Prediction Capability Effort (344847)
Neil P Barton1, Carolyn A. Reynolds2, Craig H Bishop3, Daniel P Eleuterio4, Maria K. Flatau5, Sergey Frolov6, Patrick J Hogan7, Gregg A. Jacobs8, Matthew Janiga5, Justin McLay5, E. Joseph Metzger9, James G Richman10, James A Ridout5, Clark David Rowley9, Benjamin Ruston11 and Timothy Whitcomb5, (1)Naval Research Laboratory, Monterey, CA, United States, (2)U.S. Naval Research Laboratory, Monterey, United States, (3)Naval Research Lab, Monterey, United States, (4)Office Naval Research, Ocean, Atmosphere and Space Research Division (322), Arlington, VA, United States, (5)Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States, (6)US Naval Research Laboratory, Monterey, CA, United States, (7)Stennis Space Ctr, Stennis Space Center, MS, United States, (8)US Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States, (9)Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States, (10)Naval Research Lab Stennis Space Center, Stennis Space Center, MS, United States, (11)US Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States
Assessing the impact of assimilating atmospheric data on the ocean state estimation and climate forecast in an ensemble coupled data assimilation system (350275)
Shu WU, University of Wisconsin Madison, Nelson Institute Center for Climatic Research, Madison, WI, United States, Zhengyu Liu, The Ohio State University, Department of Geography, Columbus, United States, Shaoqing Zhang, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China, Robert L Jacob, Argonne National Laboratory, Argonne, IL, United States, Xinyao Rong, Chinese Academy of Meteorological Sciences, Beijing, China, Beijing, China, Yun Liu, Victoria, BC, Canada and Feiyu Lu, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, United States
The DOE E3SM coupled model version 1: Ocean Mean State biases and Historical Transient Variability. (367845)
Luke P Van Roekel1, Jean-Christophe Golaz2, Mathew E Maltrud1, Adrian Turner3, Jonathan D Wolfe1 and Steven R Brus1, (1)Los Alamos National Laboratory, Los Alamos, United States, (2)Lawrence Livermore National Laboratory, Livermore, United States, (3)Los Alamos National Laboratory, Los Alamos, NM, United States
Assimilation of satellite sea surface temperature data for a coupled ocean-atmosphere model (377622)
Qi Tang, Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research Bremerhaven, Bremerhaven, Germany, Dmitry Sidorenko, Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research, Bremerhaven, Germany and Lars Nerger, Alfred Wegener Institute (AWI), Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany
The Impact on Seasonal Forecasts of GMAO's Higher Resolution Seasonal Prediction and Data Assimilation System (380397)
Andrea Molod1, Eric C Hackert2, Lauren C Andrews3, Robin M Kovach4, Zhao Li5, Young-Kwon Lim3, Anna Borovikov6, Guillaume Vernieres7, Jelena Marshak8, Randal D Koster9, James Carton2, Richard I Cullather10, Siegfried D Schubert11, Deepthi Achuthavarier12, Yury V Vikhliaev13 and Bin Zhao14, (1)Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, United States, (2)University of Maryland College Park, College Park, MD, United States, (3)NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, MD, United States, (4)NASA, GSFC, Greenbelt, MD, United States, (5)Global Modeling and Assimilation Office, Greenbelt, MD, United States, (6)Sugar Land, TX, United States, (7)NASA GSFC, Greenbelt, United States, (8)NASA Goddard Space Flight Center, GMAO, Greenbelt, MD, United States, (9)NASA Goddard SFC, Global Modeling and Assimilation Office, Greenbelt, United States, (10)NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, United States, (11)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (12)Goddard Earth Sciences Technology and Research, Greenbelt, MD, United States, (13)Universities Space Research Association Greenbelt, Greenbelt, MD, United States, (14)Science Applications International Corporation Greenbelt, Greenbelt, MD, United States

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