Weather prediction systems
Poterjoy, J. 2022: Implications of multivariate non-Gaussian data assimilation for multi-scale weather prediction. Mon. Wea. Rev., In press.
Schwartz, C.S., J. Poterjoy, G. S. Romine, D. C. Dowell, and J. R. Carley, 2022: Short-term convection-allowing ensemble forecast sensitivity to resolution of initial condition perturbations and central initial states. Wea. Forecasting, In press.
Schwartz, C. S., J. Poterjoy, J. R. Carley, D. C. Dowell, G. S. Romine, and K. Ide, 2021: Comparing partial and continuously cycling ensemble Kalman filter data assimilation systems for convection-allowing ensemble forecast initialization. Wea. Forecasting, Published online 22 Sept. 2021.
Poterjoy, J., G. J. Alaka, Jr., and H. R. Winterbottom, 2021: The irreplaceable utility of sequential data assimilation for numerical weather prediction system development: Lessons learned from an experimental HWRF system. Wea. Forecasting, 36, 661 – 677.
Poterjoy, J., 2022: Regularization and tempering for a moment-matching localized particle filter. Quart. J. Roy. Meteor. Soc., Under revision.
Feng, J., X. Wang., and J. Poterjoy, 2020: A Comparison of Two Local Moment-Matching Nonlinear Filters: Local Particle Filter (LPF) and Local Nonlinear Ensemble Transform Filter (LNETF)., Mon. Wea. Rev., 148, 4377 – 4395.
Poterjoy, J., L. J. Wicker, and M. Buehner, 2019: Progress in the development of a localized particle filter for data assimilation in high-dimensional geophysical systems., Mon. Wea. Rev. 147, 1107 – 1126.
Morzfeld, M., D. Hodyss, J. Poterjoy, 2018: Variational particle smoothers and their localization., Q. J. R. Meteorol. Soc. 2018, 144:806 – 825.
Poterjoy, J., R. A. Sobash, and J. L. Anderson, 2017: Convective-scale data assimilation for the Weather Research and Forecasting model using the local particle filter., Mon. Wea. Rev. 145, 1897 – 1918.
Poterjoy, J., and J. L. Anderson, 2016: Efficient assimilation of simulated observations in a high-dimensional geophysical system using a localized particle filter. Mon. Wea. Rev., 144, 2007 – 2020.
Poterjoy, J., 2016: A localized particle filter for high-dimensional nonlinear systems. Mon. Wea. Rev., 144, 59 – 76.
Four-dimensional data assimilation
Kurosawa, K., and Poterjoy, J., 2021: Data assimilation challenges posed by nonlinear operators: A comparative study of ensemble and variational filters and smoothers, Mon. Wea. Rev. In press.
Poterjoy, J. and F. Zhang, 2016: Comparison of hybrid four-dimensional data assimilation methods with and without the tangent linear and adjoint models for predicting the life cycle of Hurricane Karl (2010). Mon. Wea. Rev. 144, 1449 – 1468.
Poterjoy, J. and F. Zhang, 2015: Systematic comparison of four-dimensional data assimilation methods with and without a tangent linear model using hybrid background error covariance: E4DVar versus 4DEnVar. Mon. Wea. Rev., 143, 1601 – 1621.
Poterjoy, J. and F. Zhang, 2014: Inter-comparison and coupling of ensemble and four-dimensional variational data assimilation methods for the analysis and forecasting of Hurricane Karl (2010). Mon. Wea. Rev., 142, 3347 – 3364.
Zhang, X., X.-Y. Huang, L. Yianyu,J. Poterjoy, Y. Weng, F. Zhang, and H. Wang, 2014: Development of an efficient regional four-dimensional variational data assimilation system for WRF. J. Atmos. Oceanic Technol., 31, 2777 – 2794.
Zhang, F., M. Zhang, and J. Poterjoy, 2013: E3DVar: Coupling an ensemble Kalman filter with three-dimensional variational data assimilation in a limited-area weather prediction model and comparison to E4DVar. Mon. Wea. Rev., 140, 900 – 917.
Tropical cyclone dynamics explored via ensemble methods
Poterjoy, J. and F. Zhang, 2014: Predictability and genesis of Hurricane Karl (2010) examined through the EnKF assimilation of field observations collected during PREDICT. J. Atmos. Sci., 71, 1260 – 1275.
Poterjoy, J., F. Zhang, and Y. Weng, 2014: The effects of sampling errors on the EnKF assimilation of inner-core hurricane observations. Mon. Wea. Rev., 142, 1609 – 1630.
Xie, B., F. Zhang, Q. Zhang, J. Poterjoy, and Y. Weng, 2013: Observing strategy and observation targeting for tropical cyclones using ensemble-based sensitivity analysis and data assimilation. Mon. Wea. Rev., 141, 1437 – 1453.
Poterjoy, J. and F. Zhang, 2011: Dynamics and structure of forecast error covariance in the core of a developing hurricane. J. Atmos. Sci., 68, 1586 – 1606.