Report: Physics Constrained Stochastic Statistical Models for Extended Range Environmental Prediction

The timing of the receipt of the MURI funds in August 2012 hampered the assembly of the full MURI team in this initial reporting period since typically post docs in applied math only became available for hiring after June, July, August, 2013. Despite this difficulty there are exciting results on eig...

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Bibliographic Details
Main Author: Majda, Andrew J
Other Authors: NEW YORK UNIV NY COURANT INST OF MATHEMATICAL SCIENCES
Format: Text
Language:English
Published: 2013
Subjects:
Atmospheric Physics
Statistics and Probability
*CLIMATE
*MATHEMATICAL PREDICTION
*STATISTICAL ANALYSIS
*STOCHASTIC PROCESSES
CONVECTION(HEAT TRANSFER)
ENVIRONMENTS
FORECASTING
NORTH PACIFIC OCEAN
OSCILLATION
REGRESSION ANALYSIS
SEA ICE
TURBULENCE
UNCERTAINTY
*STOCHASTIC STATISTICAL MODELS
ENVIRONMENTAL PREDICTION
NONLINEAR LAPLACIAN SPECTRAL ANALYSIS
MJO(MADDEN-JULIAN OSCILLATION)
Pacific
Sea ice
Online Access:http://www.dtic.mil/docs/citations/ADA601833
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA601833
Description
Summary:The timing of the receipt of the MURI funds in August 2012 hampered the assembly of the full MURI team in this initial reporting period since typically post docs in applied math only became available for hiring after June, July, August, 2013. Despite this difficulty there are exciting results on eight major topics in the MURI during the past year by MURI-PI, Andrew Majda, Co-PI s , Sam Stechmann (U. Wisconsin), John Harlim (Penn State), Duane Waliser (JPL-UCLA), and Dimitri Giannakis (Courant Institute) with their post docs and Ph.D. students: A. Reemergence Mechanisms for North Pacific Sea Ice Revealed through Nonlinear Laplacian Spectral Analysis B. Symmetric and Antisymmetric Madden-Julian oscillation signals in tropical deep convective systems C. Limits of Predictability in the North Pacific Sector of a Comprehensive Climate Model D. Stochastic Skeleton Model for the MJO E. Observations and the Stochastic Skeleton Model F. Physics Constrained Nonlinear Regression Models for Time Series G. Statistically Accurate Low Order Models for Uncertainty Quantification in Turbulent Dynamical Systems H. Mathematical Techniques for Quantifying Uncertainty in Complex Systems with Model Error with Prototype Applications.

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