J
Jeffrey L. Anderson
Researcher at National Center for Atmospheric Research
Publications - 184
Citations - 12743
Jeffrey L. Anderson is an academic researcher from National Center for Atmospheric Research. The author has contributed to research in topics: Data assimilation & Ensemble Kalman filter. The author has an hindex of 41, co-authored 174 publications receiving 11289 citations. Previous affiliations of Jeffrey L. Anderson include University Corporation for Atmospheric Research & Geophysical Fluid Dynamics Laboratory.
Papers
More filters
Journal ArticleDOI
An Ensemble Adjustment Kalman Filter for Data Assimilation
TL;DR: In this paper, an ensemble adjustment Kalman filter is proposed to estimate the probability distribution of the state of a model given a set of observations using Monte Carlo approximations to the nonlinear filter.
Journal ArticleDOI
A Monte Carlo Implementation of the Nonlinear Filtering Problem to Produce Ensemble Assimilations and Forecasts
TL;DR: In this paper, a nonlinear filtering theory is applied to unify the data assimilation and ensemble generation problem and to produce superior estimates of the probability distribution of the initial state of the atmosphere (or ocean) on regional or global scales.
Journal ArticleDOI
Ensemble Square Root Filters
TL;DR: In this article, a deterministic analysis ensemble updates are implemented in Kalman square root filters, and the nonuniqueness of the deterministic transformation used in square root Kalman filters provides a framework to compare ensemble data assimilation methods.
Journal ArticleDOI
The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations
Jeffrey L. Anderson,V. B Alaji,Anthony J. Broccoli,Anthony J. Broccoli,William F. C Ooke,W. D Ixon,L Eo J. Donner,Krista A. Dunne,S. M. Freidenreich,T. G Arner,R Ichard G. Gudgel,Saac M. Held,Richard S. Hemler,L Arry W. H Orowitz,Stephen A. Klein,Stephen A. Klein,Thomas R. Knutson,Paul J. Kushner,Paul J. Kushner,Amy R. Langenhost,Ngar-Cheung Lau,Zhi Liang,Sergey Malyshev,Paul C.D. Milly,Mary Jo Nath,Jeffrey J. Ploshay,Elena Shevliakova,Joseph J. Sirutis,Rian J. Soden,W Illiam F. S Tern,Lori A. Thompson,R. John Wilson,Andrew T. W Ittenberg,Bruce Wyman +33 more
TL;DR: The configuration and performance of a new global atmosphere and land model for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented in this article, where the performance of the coupled model AM2•LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations.
Journal ArticleDOI
Obstacles to High-Dimensional Particle Filtering
TL;DR: In this article, Bengtsson et al. showed that the ensemble size required for a successful particle filter scales exponentially with the problem size and that the required ensemble size scales with the state dimension.