Vishny, D., Morzfeld, M., Gwirtz, K., Bach, E., Dunbar, O. R. A., & Hodyss, D. (2024). High‐Dimensional Covariance Estimation From a Small Number of Samples. Journal of Advances in Modeling Earth Systems, 16(9), e2024MS004417. https://doi.org/10.1029/2024MS004417

Tong, X. T., & Morzfeld, M. (2023). Localized ensemble Kalman inversion. Inverse Problems, 39(6), 064002. https://doi.org/10.1088/1361-6420/accb08

Vavra, E. J., Qiu, H., Chi, B., Share, P., Allam, A., Morzfeld, M., Vernon, F., Ben‐Zion, Y., & Fialko, Y. (2023). Active Dipping Interface of the Southern San Andreas Fault Revealed by Space Geodetic and Seismic Imaging. Journal of Geophysical Research: Solid Earth, 128(11), e2023JB026811. https://doi.org/10.1029/2023JB026811

Hodyss, D., & Morzfeld, M. (2023). How Sampling Errors in Covariance Estimates Cause Bias in the Kalman Gain and Impact Ensemble Data Assimilation. Monthly Weather Review, 151(9), 2413–2426. https://doi.org/10.1175/MWR-D-23-0029.1

Cych, B., Morzfeld, M., Heslop, D., Maher, S., Gee, J., & Tauxe, L. (2023). Thermal Resolution of Unblocking Temperatures (TROUT): A Method for “Unmixing” Multi‐Component Magnetizations. Geochemistry, Geophysics, Geosystems, 24(6), e2023GC010920. https://doi.org/10.1029/2023GC010920

Blatter, D., Morzfeld, M., Key, K., & Constable, S. (2022). Uncertainty quantification for regularized inversion of electromagnetic geophysical data—Part I: motivation and theory. Geophysical Journal International, 231(2), 1057–1074. https://doi.org/10.1093/gji/ggac241

Blatter, D., Morzfeld, M., Key, K., & Constable, S. (2022). Uncertainty quantification for regularized inversion of electromagnetic geophysical data – Part II: application in 1-D and 2-D problems. Geophysical Journal International, 231(2), 1075–1095. https://doi.org/10.1093/gji/ggac242

Gwirtz, K., Davis, T., Morzfeld, M., Constable, C., Fournier, A., & Hulot, G. (2022). Can machine learning reveal precursors of reversals of the geomagnetic axial dipole field? Geophysical Journal International, 231(1), 520–535. https://doi.org/10.1093/gji/ggac195

Gwirtz, K., Morzfeld, M., Kuang, W., & Tangborn, A. (2021). A testbed for geomagnetic data assimilation. Geophysical Journal International, 227(3), 2180–2203. https://doi.org/10.1093/gji/ggab327

Swierczek, S., Mazloff, M. R., Morzfeld, M., & Russell, J. L. (2021). The effect of resolution on vertical heat and carbon transports in a regional ocean circulation model of the Argentine Basin. Journal of Geophysical Research-Oceans, 126(7), 19. https://doi.org/10.1029/2021jc017235

Gwirtz, K., Morzfeld, M., Fournier, A., & Hulot, G. (2021). Can one use Earth’s magnetic axial dipole field intensity to predict reversals? Geophysical Journal International, 225(1), 277–297. https://doi.org/10.1093/gji/ggaa542

Harty, T., Morzfeld, M., & Snyder, C. (2021). Eigenvector-spatial localisation. Tellus Series A-Dynamic Meteorology and Oceanography, 73(1), 1–18. https://doi.org/10.1080/16000870.2021.1903692

Lunderman, S., Morzfeld, M., Glassmeier, F., & Feingold, G. (2020). Estimating parameters of the nonlinear cloud and rain equation from a large-eddy simulation. Physica D-Nonlinear Phenomena, 410. https://doi.org/10.1016/j.physd.2020.132500

Tong, X. T., Morzfeld, M., & Marzouk, Y. M. (2020). MALA-within-Gibbs samplers for high-dimensional distributions with sparse conditional structure. Siam Journal on Scientific Computing, 42(3), A1765–A1788. https://doi.org/10.1137/19m1284014

Marcus van Lier-Walqui, Hugh Morrison, Matthew R Kumjian, Karly J. Reimel, Olivier P. Prat, Spencer Lunderman, & Matthias Morzfeld. (2019). A Bayesian approach for statistical-physical bulk parameterization of rain microphysics, Part II: Idealized Markov chain Monte Carlo experiments. Journal of the Atmospheric Sciences, null. https://doi.org/10.1175/jas-d-19-0071.1

Morzfeld, M., & Buffett, B. A. (2019). A comprehensive model for the kyr and Myr timescales of Earth’s axial magnetic dipole field. Nonlinear Processes in Geophysics, 26(3), 123–142. https://doi.org/10.5194/npg-26-123-2019

Bell, J., Day, M., Goodman, J., Grout, R., & Morzfeld, M. (2019). A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters. Combustion and Flame, 205, 305–315. https://doi.org/10.1016/j.combustflame.2019.04.023

Harty, T. M., Holmgren, W. F., Lorenzo, A. T., & Morzfeld, M. (2019). Intra-hour cloud index forecasting with data assimilation. Solar Energy, 185, 270–282. https://doi.org/10.1016/j.solener.2019.03.065

Morzfeld, M., & Hodyss, D. (2019). Gaussian approximations in filters and smoothers for data assimilation. Tellus Series A-Dynamic Meteorology and Oceanography, 71(1). https://doi.org/Artn 1600344 10.1080/16000870.2019.1600344

Morzfeld, M., Tong, X. T., & Marzouk, Y. M. (2019). Localization for MCMC: sampling high-dimensional posterior distributions with local structure. Journal of Computational Physics, 380, 1–28. https://doi.org/10.1016/j.jcp.2018.12.008

Morzfeld, M., Adams, J., Lunderman, S., & Orozco, R. (2018). Feature-based data assimilation in geophysics. Nonlinear Processes in Geophysics, 25(2), 355–374. https://doi.org/10.5194/npg-25-355-2018

Morzfeld, M., Hodyss, D., & Poterjoy, J. (2018). Variational particle smoothers and their localization. Quarterly Journal of the Royal Meteorological Society, 144(712), 806–825. https://doi.org/10.1002/qj.3256

Leach, A., Lin, K. K., & Morzfeld, M. (2018). Symmetrized Importance Samplers for Stochastic Differential Equations. Communications in Applied Mathematics and Computational Science, 13(2), 215–241. https://doi.org/10.2140/camcos.2018.13.215

Morzfeld, M., Day, M. S., Grout, R. W., Pao, G. S. H., Finsterle, S. A., & Bell, J. B. (2018). Iterative Importance Sampling Algorithms for Parameter Estimation. Siam Journal on Scientific Computing, 40(2), B329–B352. https://doi.org/10.1137/16m1088417

Lorenzo, A. T., Morzfeld, M., Holmgren, W. F., & Cronin, A. D. (2017). Optimal interpolation of satellite and ground data for irradiance nowcasting at city scales. Solar Energy, 144, 466–474. https://doi.org/10.1016/j.solener.2017.01.038

Morzfeld, M., Fournier, A., & Hulot, G. (2017). Coarse predictions of dipole reversals by low-dimensional modeling and data assimilation. Physics of the Earth and Planetary Interiors, 262, 8–27. https://doi.org/10.1016/j.pepi.2016.10.007

Morzfeld, M., Hodyss, D., & Snyder, C. (2017). What the collapse of the ensemble Kalman filter tells us about particle filters. Tellus Series A-Dynamic Meteorology and Oceanography, 69. https://doi.org/10.1080/16000870.2017.1283809

Goodman, J., Lin, K. K., & Morzfeld, M. (2016). Small-Noise Analysis and Symmetrization of Implicit Monte Carlo Samplers. Communications on Pure and Applied Mathematics, 69(10), 1924–1951. https://doi.org/10.1002/cpa.21592

Chorin, A. J., Lu, F., Miller, R. N., Morzfeld, M., & Tu, X. M. (2016). Sampling, Feasibility, and Priors in Bayesian Estimation. Discrete and Continuous Dynamical Systems, 36(8), 4227–4246. https://doi.org/10.3934/dcds.2016.8.4227

Hodyss, D., Bishop, C. H., & Morzfeld, M. (2016). To what extent is your data assimilation scheme designed to find the posterior mean, the posterior mode or something else? Tellus Series A-Dynamic Meteorology and Oceanography, 68. https://doi.org/ARTN 30625 10.3402/tellusa.v68.30625

Snyder, C., Bengtsson, T., & Morzfeld, M. (2015). Performance Bounds for Particle Filters Using the Optimal Proposal. Monthly Weather Review, 143(11), 4750–4761. https://doi.org/10.1175/Mwr-D-15-0144.1

Morzfeld, M. (2015). Implicit Sampling for Path Integral Control, Monte Carlo Localization, and SLAM. Journal of Dynamic Systems Measurement and Control-Transactions of the Asme, 137(5). https://doi.org/Artn 051016 10.1115/1.4029064

Lu, F., Morzfeld, M., Tu, X. M., & Chorin, A. J. (2015). Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems. Journal of Computational Physics, 282, 138–147. https://doi.org/10.1016/j.jcp.2014.11.010

Morzfeld, M., Tu, X. M., Wilkening, J., & Chorin, A. J. (2015). Parameter Estimation by Implicit Sampling. Communications in Applied Mathematics and Computational Science, 10(2), 205–225. https://doi.org/10.2140/camcos.2015.10.205

Kawano, D. T., Morzfeld, M., & Ma, F. (2013). The decoupling of second-order linear systems with a singular mass matrix. Journal of Sound and Vibration, 332(25), 6829–6846. https://doi.org/10.1016/j.jsv.2013.08.005

Chorin, A. J., & Morzfeld, M. (2013). Conditions for successful data assimilation. Journal of Geophysical Research-Atmospheres, 118(20), 11522–11533. https://doi.org/10.1002/2013jd019838

Atkins, E., Morzfeld, M., & Chorin, A. J. (2013). Implicit Particle Methods and Their Connection with Variational Data Assimilation. Monthly Weather Review, 141(6), 1786–1803. https://doi.org/10.1175/Mwr-D-12-00145.1

Morzfeld, M., Kawano, D. T., & Ma, F. (2013). Characterization of Damped Linear Dynamical Systems in Free Motion. Numerical Algebra Control and Optimization, 3(1), 49–62. https://doi.org/10.3934/naco.2013.3.49

Chorin, A. J., Morzfeld, M., & Tu, X. M. (2013). Implicit Sampling, with Application to Data Assimilation. Chinese Annals of Mathematics Series B, 34(1), 89–98. https://doi.org/10.1007/s11401-012-0757-5

Morzfeld, M., Tu, X. M., Atkins, E., & Chorin, A. J. (2012). A random map implementation of implicit filters. Journal of Computational Physics, 231(4), 2049–2066. https://doi.org/10.1016/j.jcp.2011.11.022

Morzfeld, M., & Chorin, A. J. (2012). Implicit particle filtering for models with partial noise, and an application to geomagnetic data assimilation. Nonlinear Processes in Geophysics, 19(3), 365–382. https://doi.org/10.5194/npg-19-365-2012

Kawano, D. T., Morzfeld, M., & Ma, F. (2011). The decoupling of defective linear dynamical systems in free motion. Journal of Sound and Vibration, 330(21), 5165–5183. https://doi.org/10.1016/j.jsv.2011.05.013

Morzfeld, M., & Ma, F. (2011). The decoupling of damped linear systems in configuration and state spaces. Journal of Sound and Vibration, 330(2), 155–161. https://doi.org/10.1016/j.jsv.2010.09.005

Morzfeld, M., Ma, F., & Parlett, B. N. (2011). The Transformation of Second-Order Linear Systems into Independent Equations. Siam Journal on Applied Mathematics, 71(4), 1026–1043. https://doi.org/10.1137/100818637

Ma, F., & Morzfeld, M. (2011). A General Methodology for Decoupling Damped Linear Systems. Proceedings of the Twelfth East Asia-Pacific Conference on Structural Engineering and Construction (Easec12), 14. https://doi.org/10.1016/j.proeng.2011.07.314

Ma, F., Morzfeld, M., & Imam, A. (2010). The decoupling of damped linear systems in free or forced vibration. Journal of Sound and Vibration, 329(15), 3182–3202. https://doi.org/10.1016/j.jsv.2010.02.017

Chorin, A., Morzfeld, M., & Tu, X. M. (2010). Implicit Particle Filters for Data Assimilation. Communications in Applied Mathematics and Computational Science, 5(2), 221–240. https://doi.org/DOI 10.2140/camcos.2010.5.221

Ma, F., Imam, A., & Morzfeld, M. (2009). The decoupling of damped linear systems in oscillatory free vibration. Journal of Sound and Vibration, 324(1–2), 408–428. https://doi.org/10.1016/j.jsv.2009.02.005

Morzfeld, M., Ajavakom, N., & Ma, F. (2009). Diagonal dominance of damping and the decoupling approximation in linear vibratory systems. Journal of Sound and Vibration, 320(1–2), 406–420. https://doi.org/10.1016/j.jsv.2008.07.025

Morzfeld, M., Ma, F., & Ajavakom, N. (2008). On The Decoupling Approximation in Damped Linear Systems. Journal of Vibration and Control, 14(12), 1869–1884. https://doi.org/10.1177/1077546308091212