A001
Addressing Challenges for the Next Generation of Earth System Models
Session ID#: 80033
Session Description:
Advances in HPC resources have pushed the resolution of Earth System Models to length scales unattainable until now. However, obtaining physically accurate results in an efficient manner at these scales requires more than just increasing the number of grid cells. The formulation of the models themselves needs to be revisited, including hydrostatic assumptions, convection parametrization, meso-scale eddies in the ocean, and machine learning methods to improve/emulate parametrization schemes. Solving these new models requires new numerical approaches to address scalability issues and challenges from resolving new model features. Furthermore, many of the recent and planned HPC systems use a combination of CPU and GPU cores. To obtain the necessary throughput on these hybrid architectures, new computational strategies are needed to enhance conventional models optimized for CPU-only systems. This session will present progress on the new modeling approaches, numerical techniques, and computational strategies that will enable higher resolution for Earth System Models.
Index Terms:
3336 Numerical approximations and analyses [ATMOSPHERIC PROCESSES]
3337 Global climate models [ATMOSPHERIC PROCESSES]
Primary Convener: Christopher Vogl, Lawrence Livermore National Laboratory, Livermore, CA, United States
Conveners: Carol S Woodward, Lawrence Livermore National Laboratory, Livermore, CA, United States, Katherine J Evans, Oak Ridge National Laboratory, Oak Ridge, TN, United States and Peter D Dueben, European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Primary Liaison: Christopher Vogl, Lawrence Livermore National Laboratory, Center for Applied Scientific Computing, Livermore, CA, United States
Global Nonhydrostatic Atmospheric Modeling using a layer-averaged approach with a dry-mass hybrid vertical coordinate on an unstructured mesh (487902)
Yi Zhang1, Jian Li1, Rucong Yu1, Zhuang Liu2 and Yihui Zhou3, (1)Chinese Academy of Meteorological Sciences, Beijing, China, (2)National Supercomputing Center in Wuxi, Wuxi, China, (3)Lasg，IAP，CAS, Beijing, China
Preparing the Exascale Energy Earth System Model (E3SM) for Exascale Computing Platforms (490841)
Matthew R Norman1, Walter Hannah2, Benjamin R Hillman3, Christopher R Jones4, Sarat Sreepathi1 and Mark Taylor3, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)Lawrence Livermore National Laboratory, Livermore, CA, United States, (3)Sandia National Laboratories, Albuquerque, NM, United States, (4)University of Washington Seattle Campus, Seattle, WA, United States
HiPerSeis: Supercharging Seismic Workflows on High Performance Computing Platforms (504469)
Rakib Hassan1, Babak Hejrani2, Alexei Gorbatov1, Marcus Haynes1, Fei Zhang2, Jason Zhao Dr.2 and Andrew Medlin2, (1)Geoscience Australia, Canberra, ACT, Australia, (2)Geoscience Australia, Canberra, Australia
The development of the Terrestrial Dynamical core (TDycore) library and it’s coupling with E3SM (516011)
Gautam Bisht, Pacific Northwest National Laboratory, Richland, WA, United States, Jed Brown, Argonne National Laboratory, Argonne, IL, United States, Nathan Collier, Oak Ridge National Laboratory, Computational Earth Sciences, Oak Ridge, TN, United States, Jennifer Frederick, Sandia National Laboratories, Albuquerque, NM, United States, Glenn E Hammond, Sandia National Laboratories, Applied Systems Analysis & Research, Albuquerque, NM, United States, Satish Karra, Los Alamos National Laboratory, Los Alamos, NM, United States and Matthew Knepley, Univ of Chicago, Chicago, IL, United States
A semi-implicit barotropic mode solver for the MPAS-Ocean (516847)
Hyun-Gyu Kang1, Katherine J Evans1, Philip W Jones2, Mark R Petersen2, Andy Salinger3 and Raymond S Tuminaro4, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)Los Alamos National Laboratory, Los Alamos, NM, United States, (3)Sandia National Laboratory, Albuquerque, FL, United States, (4)Sandia National Laboratories, Livermore, CA, United States
Evaluation of Implicit-Explicit, Additive Runge-Kutta Method Efficiency in HOMME-NH (519496)
Carol S Woodward, Lawrence Livermore National Laboratory, Livermore, CA, United States, Christopher Vogl, Lawrence Livermore National Laboratory, Center for Applied Scientific Computing, Livermore, CA, United States, Andrew Steyer, Sandia National Laboratories, Albuquerque, NM, United States, Daniel R Reynolds, Southern Methodist University, Dallas, TX, United States and Paul Aaron Ullrich, Univ California Davis, Fremont, CA, United States
An Objective and Efficient Method for Assessing the Impact of Reduced-precision Calculations on Solution Correctness (520600)
Shixuan Zhang1, Hui Wan1, Philip J Rasch1, Balwinder Singh1, Vincent E Larson2 and Carol S. Woodward3, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Univ Wisconsin-Milwaukee, Milwaukee, WI, United States, (3)Lawrence Livermore National Laboratory, Livermore, CA, United States
Using Time-step Convergence to Improve the Numerical Robustness and Physical Consistency of Atmospheric Physics Parameterizations (523413)
Hui Wan1, Shixuan Zhang2, Christopher Vogl3, Carol S. Woodward4, Panos Stinis5, Vincent E Larson6 and Philip J Rasch1, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)University of Utah, Salt Lake City, UT, United States, (3)Lawrence Livermore National Laboratory, Center for Applied Scientific Computing, Livermore, CA, United States, (4)Lawrence Livermore National Laboratory, Livermore, CA, United States, (5)Pacific Northwest National Laboratory, Richland, United States, (6)Univ Wisconsin-Milwaukee, Milwaukee, WI, United States
Scenario and model uncertainty in ocean biogeochemical response: Isolating the role of ocean lateral mixing (536695)
Alexis Anne Bahl, Johns Hopkins University, Baltimore, MD, United States, Anand Gnanadesikan, Johns Hopkins Univ-EPS, Baltimore, MD, United States and Marie-Aude Sabine Pradal, Johns Hopkins Univ, Baltimore, MD, United States
Comparative study of GEOS-Chem and WRF-GC in the United States (553073)
Nan Lin1, Yuxuan Wang2, Haipeng Lin3, Tzung-May Fu3 and Xu Feng3, (1)Tsinghua University, Earth System Sciences, Beijing, China, (2)University of Houston, Department of Earth and Atmospheric Sciences, Houston, TX, United States, (3)Peking University, Beijing, China
A Sub-grid Reconstruction Approach for Improving Numerical Robustness and Physical Consistency of Atmospheric Physics Parameterizations (564145)
Christopher Vogl, Lawrence Livermore National Laboratory, Center for Applied Scientific Computing, Livermore, CA, United States, Shixuan Zhang, University of Utah, Salt Lake City, UT, United States, Carol S. Woodward, Lawrence Livermore National Laboratory, Livermore, CA, United States, Hui Wan, Pacific Northwest National Laboratory, Richland, WA, United States and Panos Stinis, Pacific Northwest National Laboratory, Richland, United States
Research on Model Uncertainty Representation for Convection-Allowing Ensemble Prediction System Based on CNOP-P (569394)
Xueshun Shen, National Meteorological Center, Beijing, China, Lu Wang, National Meteorological Center, Numerical Weather Prediction Center of CMA, Beijing, China, Bin Wang, TsingHua University, Department for Earth System Science, Beijing, China and Juanjuan Liu, Institute of Atmosphere Physics, State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics, Beijing, China
Accelerating cloud and radiation schemes within the Unified Model for CPU-GPU based high-performance computing systems (588468)
Min Xu1, Wei Zhang2, Mario Morales-Hernandez3, Matthew R Norman4, Salil Mahajan5 and Katherine J Evans3, (1)Oak Ridge National Laboratory, Computational Sciences and Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States, (2)Oak Ridge National Labortory, Oak Ridge, United States, (3)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (4)Oak Ridge National Lab, Oak Ridge, TN, United States, (5)Oak Ridge Nat'l Lab, Oak Ridge, TN, United States
Comparing Numerical Accuracy of Icosahedral A-grid and C-grid Schemes for the Shallow-Water Model (592739)
Yonggang G Yu, Cooperative Institute for Research in Environmental Sciences, Boulder, United States, Ning Wang, CIRA; NOAA/ESRL/GSD, Boulder, United States and Mark Govett, NOAA Earth System Research Laboratory, Boulder, CO, United States
The Impact of Stochastic Forcing in a Global Coupled Ocean-Ice-Atmosphere Forecast System (606567)
Patrick J Hogan1, Carolyn A. Reynolds2, Richard Allard3, Neil P Barton4, Prasad G Thoppil5, Ole Martin Smedstad6, Justin McLay7, James A Ridout7 and Will Crawford8, (1)Naval Research Laboratory, Stennis Space Center, MS, United States, (2)US Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States, (3)Naval Research Lab, Stennis Space Center, MS, United States, (4)Naval Research Lab, Monterey, CA, United States, (5)Naval Research Laboratory, Oceanography Division, Stennis Space Center, MS, United States, (6)QinetiQ North America, Stennis Space Center, MS, United States, (7)Naval Research Laboratory, Monterey, CA, United States, (8)Naval Research Laboratory, Monterey, United States
Accelerating MPAS-A model radiation schemes on GPUs using OpenACC (612236)
Zhifeng Yang1, Milton Halem2, Richard Loft3 and Supreeth Suresh3, (1)University of Maryland Baltimore County, Department of Physics, Baltimore, MD, United States, (2)University of Maryland Baltimore County, Computer Science, Baltimore, MD, United States, (3)National Center for Atmospheric Research, Boulder, CO, United States
Improving the software architecture for a continental scale integrated modeling framework for better software productivity: Boundary Conditions, Programming Abstractions, and Developments in the ParFlow modeling platform (618224)
Michael Burke, Boise, ID, United States, Catherine Olschanowsky, Boise State University, Boise, ID, United States, Laura E Condon, University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States and Reed M Maxwell, Colorado School of Mines, Golden, CO, United States
End-to-End Workflow-Driven Hydrologic Analysis for Different User Groups in HydroFrame (624155)
Shweta Purawat1, Cathie Olschanowsky2, Laura E Condon3, Reed M Maxwell4, Ilkay Altintas1 and the HydroFrame team (www.hydroframe.org), (1)University of California San Diego, La Jolla, CA, United States, (2)Boise State University, Boise, United States, (3)University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (4)Colorado School of Mines, Golden, CO, United States
Hydroframe: A Software Framework to enable Continental Scale Hydrologic Simulation (631272)
Reed M Maxwell1, Catherine Olschanowsky2, Laura E Condon3, Michelle Strout4, Ilkay Altintas5, Shweta Purawat5, Lisa Gallagher6, Hoang Tran7, Jun Zhang3 and The HydroFrame Team (www.hydroframe.org), (1)Colorado School of Mines, Hydrologic Science and Engineering Program and Department of Geology and Geological Engineering, Golden, CO, United States, (2)Boise State University, Computer Science, Boise, ID, United States, (3)University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (4)University of Arizona, Computer Science, Tucson, AZ, United States, (5)University of California San Diego, La Jolla, CA, United States, (6)Colorado School of Mines, Integrated GroundWater Modeling Center, Golden, CO, United States, (7)Colorado School of Mines, Department of Geology and Geological Engineering, Golden, CO, United States
