John Harlim

Brown, K. A., & Harlim, J. (2013). Assimilating irregularly spaced sparsely observed turbulent signals with hierarchical Bayesian reduced stochastic filters. JOURNAL OF COMPUTATIONAL PHYSICS, 235, 143–160. https://doi.org/10.1016/j.jcp.2012.11.006

Bakunova, E. S., & Harlim, J. (2013). Optimal filtering of complex turbulent systems with memory depth through consistency constraints. JOURNAL OF COMPUTATIONAL PHYSICS, 237, 320–343. https://doi.org/10.1016/j.jcp.2012.11.028

Majda, A. J., & Harlim, J. (2013). Physics constrained nonlinear regression models for time series. NONLINEARITY, 26(1), 201–217. https://doi.org/10.1088/0951-7715/26/1/201

Kang, E. L., Harlim, J., & Majda, A. J. (2013). Regression models with memory for the linear response of turbulent dynamical systems. Communications in Mathematical Sciences, 11(2), 481–498. https://doi.org/10.4310/cms.2013.v11.n2.a8

Harlim, J., & Majda, A. J. (2013). TEST MODELS FOR FILTERING WITH SUPERPARAMETERIZATION. MULTISCALE MODELING & SIMULATION, 11(1), 282–308. https://doi.org/10.1137/120890594

Harlim, J., & Majda, A. J. (2013). Test models for filtering and prediction of moisture-coupled tropical waves. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 139(670), 119–136. https://doi.org/10.1002/qj.1956

Gottwald, G. A., & Harlim, J. (2013). The role of additive and multiplicative noise in filtering complex dynamical systems. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 469(2155). https://doi.org/10.1098/rspa.2013.0096

Majda, A. J., & Harlim, J. (2012). Filtering Complex Turbulent Systems. In FILTERING COMPLEX TURBULENT SYSTEMS (pp. 1–357). https://doi.org/10.1017/cbo9781139061308

Kang, E. L., & Harlim, J. (2012). Filtering Partially Observed Multiscale Systems with Heterogeneous Multiscale Methods-Based Reduced Climate Models. MONTHLY WEATHER REVIEW, 140(3), 860–873. https://doi.org/10.1175/mwr-d-10-05067.1

Kang, E. L., & Harlim, J. (2012). Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models. PHYSICA D-NONLINEAR PHENOMENA, 241(12), 1099–1113. https://doi.org/10.1016/j.physd.2012.03.003

Harlim, J. (2011). INTERPOLATING IRREGULARLY SPACED OBSERVATIONS FOR FILTERING TURBULENT COMPLEX SYSTEMS. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 33(5), 2620–2640. https://doi.org/10.1137/100800427

Harlim, J. (2011). Numerical strategies for filtering partially observed stiff stochastic differential equations. JOURNAL OF COMPUTATIONAL PHYSICS, 230(3), 744–762. https://doi.org/10.1016/j.jcp.2010.10.016

Harlim, J., & Majda, A. J. (2010). Filtering Turbulent Sparsely Observed Geophysical Flows. MONTHLY WEATHER REVIEW, 138(4), 1050–1083. https://doi.org/10.1175/2009mwr3113.1

Gershgorin, B., Harlim, J., & Majda, A. J. (2010). Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation. JOURNAL OF COMPUTATIONAL PHYSICS, 229(1), 32–57. https://doi.org/10.1016/j.jcp.2009.09.022

Majda, A. J., Harlim, J., & Gershgorin, B. (2010). MATHEMATICAL STRATEGIES FOR FILTERING TURBULENT DYNAMICAL SYSTEMS. DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS, 27(2), 441–486. https://doi.org/10.3934/dcds.2010.27.441

Gershgorin, B., Harlim, J., & Majda, A. J. (2010). Test models for improving filtering with model errors through stochastic parameter estimation. JOURNAL OF COMPUTATIONAL PHYSICS, 229(1), 1–31. https://doi.org/10.1016/j.jcp.2009.08.019