NG24A:
Stochastic Modeling in Atmosphere, Ocean, and Climate Dynamics I

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Session ID#: 15969

Session Description:
Stochastic approaches are increasingly important in atmosphere, ocean, and climate models and can be applied across all levels of complexity of such models. In these approaches, critical but unresolved or poorly understood physical processes are modeled stochastically. Recent progress has been made in stochastic modeling of precipitation-, cloud- and ice-processes, as well as in hydromechanics and sub-surface hydrology. However, applications of increasing complexity require new and sophisticated numerical and computational tools and data assimilation techniques. This session aims at bringing together the mathematical, statistical, and geophysical communities. It welcomes submissions related to stochastic processes in meteorology, oceanography, and climate science, including discussion of new modeling techniques; stochastic parameterization schemes; and data-driven stochastic modeling.
Primary Convener:  Cecile Penland, Physical Sciences Division, Boulder, CO, United States
Conveners:  Paul Williams, University of Reading, Reading, United Kingdom, Juan M. Restrepo, Oregon State University, Corvallis, OR, United States and Fei Lu, University of California Berkeley, Mathematics, Berkeley, CA, United States
Chairs:  Cecile Penland, Physical Sciences Division, Boulder, CO, United States and Juan M. Restrepo, Oregon State University, Corvallis, OR, United States
OSPA Liaison:  Paul Williams, University of Reading, Reading, United Kingdom

Cross-Listed:
  • A - Atmospheric Sciences
  • GC - Global Environmental Change
  • H - Hydrology
  • OS - Ocean Sciences
Index Terms:

3265 Stochastic processes [MATHEMATICAL GEOPHYSICS]
3275 Uncertainty quantification [MATHEMATICAL GEOPHYSICS]
3325 Monte Carlo technique [ATMOSPHERIC PROCESSES]
4468 Probability distributions, heavy and fat-tailed [NONLINEAR GEOPHYSICS]

Abstracts Submitted to this Session:

Dynamically Consistent Parameterization of Mesoscale Eddies This work aims at parameterization of eddy effects for use in non-eddy-resolving ocean models and focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones. (Invited) (121261)
Pavel S Berloff, Imperial College London, London, SW7, United Kingdom
Data-Informed Stochastic Model and Parametrization of Wave Breaking (129461)
Juan M. Restrepo, Oregon State University, Corvallis, OR, United States and Jorge M Ramirez, Universidad Nacional de Colombia, Escuela de Matemáticas, Bogota, Colombia
Leading Nonlinear Mode of Inter-Annual and Decadal Climate Behavior (173899)
Dmitry Mukhin1, Andrey Gavrilov1, Evgeny Loskutov2, Alexander Feigin2 and Juergen Kurths3, (1)Institute of Applied Physics of RAS, Nizhny Novgorod, Russia, (2)Institute of Applied Physics RAS, Nizhny Novgorod, Russia, (3)Potsdam Institute for Climate Impact Research, Potsdam, Germany
Climatology of the Arctic Sea Ice Thickness Distribution as a Stochastic Process (159896)
Srikanth Toppaladoddi1 and John S. Wettlaufer1,2, (1)Yale University, New Haven, CT, United States, (2)University of Oxford, Oxford, United Kingdom
Sampling extreme heat waves using a large deviation algorithm (Invited) (133506)
Freddy Bouchet, Francesco Ragone and Jeroen Wouters, Ecole Normale Supérieure de Lyon and CNRS, Lyon, France
Stochastic Switching and Optimal Vehicle Navigation in Geophysical Flows (187684)
Mong-ying Ani Hsieh, University of Pennsylvania, Mechanical Engineering and Applied Mechanics, Philadelphia, PA, United States, Dhanushka Kularatne, Drexel University, Philadelphia, PA, United States, Eric Forgoston, Montclair State University, Mathematical Sciences, Montclair, NJ, United States and Philip A. Yecko, The Cooper Union, Physics, New York, NY, United States
Stochastic Lagrangian Coherent Structures (198211)
Pierre F J Lermusiaux, Florian Feppon and Chinmay Kulkarni, Massachusetts Institute of Technology, Cambridge, MA, United States
Roll Instability in Neutral Boundary Layers Induced by Free-stream Turbulence (126883)
Brian Farrell, Harvard University, Cambridge, MA, United States

See more of: Nonlinear Geophysics