Publications

This list gets updated as frequently as possible, however some more recent publications may also be available on the UCAR/NCAR online database Opensky. Simply use it and search for “ensemble data assimilation” (for example). Many, if not most, are related to DART. The following list also contains some publications from our collaborators. If you would like to list your publication that uses DART, please let us know! (dart@ucar.edu)

Please use the folowing to cite DART:

The Data Assimilation Research Testbed (Version X.Y.Z) [Software]. (2019). Boulder, Colorado: UCAR/NCAR/CISL/DAReS. http://doi.org/10.5065/D6WQ0202

Update the DART version and year as appropriate.

The seminal reference is:

Anderson, J. L., T. Hoar, K. Raeder, H. Liu, N. Collins, R. Torn and A. Arellano, 2009
The Data Assimilation Research Testbed: A Community Facility.
Bulletin of the American Meteorological Society, 90, 1283-1296, doi:10.1175/2009BAMS2618.1

2023

Chen, Y., Z. Shen, Y. Tang, and X. Song, 2023: Ocean data assimilation for the initialization of seasonal prediction with the Community Earth System Model. Ocean Modelling, 183, 102194, doi.org/10.1016/j.ocemod.2023.102194

Kurosawa, K., and J. Poterjoy, 2023: A Statistical Hypothesis Testing Strategy for Adaptively Blending Particle Filters and Ensemble Kalman Filters for Data Assimilation. Monthly Weather Review, 151, 105–125, doi.org/10.1175/MWR-D-22-0108.1

2022

Fox, A. M., X. Huo, T.J. Hoar, H. Dashti, W.K. Smith, N. MacBean, J.L. Anderson, M. Roby, and D.J.P. Moore, 2022
Assimilation of Global Satellite Leaf Area Estimates Reduces Modeled Global Carbon Uptake and Energy Loss by Terrestrial Ecosystems. Journal of Geophysical Research: Biogeosciences, 127, e2022JG006830, doi.org/10.1029/2022JG006830

Jiang, F., W. Ju, W. He, M. Wu, H. Wang, J. Wang, M. Jia, S. Feng, L. Zhang, and J.M. Chen, 2022
A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO2 retrievals (GCAS2021).
Earth System Science Data, 14, 3013–3037, doi.org/10.5194/essd-14-3013-2022

Sun, J., Y. Jiang, S. Zhang, W. Zhang, L. Lu, G. Liu, Y. Chen, X. Xing, X. Lin, and L. Wu, 2022
An online ensemble coupled data assimilation capability for the Community Earth System Model: system design and evaluation.
Geoscientific Model Development, 15, 4805–4830, doi.org/10.5194/gmd-15-4805-2022

Zhang, Y.-F., M. Bushuk, M. Winton, B. Hurlin, T. Delworth, M. Harrison, L. Jia, F. Lu, A. Rosati, and X. Yang, 2022
Subseasonal-to-Seasonal Arctic Sea Ice Forecast Skill Improvement from Sea Ice Concentration Assimilation.
Journal of Climate, 35, 4233–4252, doi.org/10.1175/JCLI-D-21-0548.1

Anderson, J. L., 2022
A Quantile-Conserving Ensemble Filter Framework. Part I: Updating an Observed Variable.
Monthly Weather Review, 150, 1061–1074, doi.org/10.1175/MWR-D-21-0229.1

Deng, S., Z. Shen, S. Chen, and R. Wang, 2022 Comparison of Perturbation Strategies for the Initial Ensemble in Ocean Data Assimilation with a Fully Coupled Earth System Model.
Journal of Marine Science and Engineering, 10, 412, doi.org/10.3390/jmse10030412

Dietrich, N., T. Matsuo, and C.-T. Hsu, 2022
Specifying Satellite Drag Through Coupled Thermosphere-Ionosphere Data Assimilation of Radio Occultation Electron Density Profiles.
Space Weather, 20, e2022SW003147, doi.org/10.1029/2022SW003147

George, B., and G. Kutty, 2022
Multivariate ensemble sensitivity analysis applied for an extreme rainfall over Indian subcontinent.
Atmospheric Research, 277, 106324, doi.org/10.1016/j.atmosres.2022.106324

Huang, Y., J. Wei, J. Jin, Z. Zhou, and Q. Gu, 2022
CO Fluxes in Western Europe during 2017–2020 Winter Seasons Inverted by WRF-Chem/Data Assimilation Research Testbed with MOPITT Observations.
Remote Sensing, 14, 1133, doi.org/10.3390/rs14051133

Pedatella, N. M., and J. L. Anderson, 2022
The Impact of Assimilating COSMIC-2 Observations of Electron Density in WACCMX.
Journal of Geophysical Research: Space Physics, 127, e2021JA029906, doi.org/10.1029/2021JA029906

2021

Xing, X., B. Liu, W. Zhang, J. Wu, X. Cao, and Q. Huang, 2021 An Investigation of Adaptive Radius for the Covariance Localization in Ensemble Data Assimilation.
Journal of Marine Science and Engineering, 9, 1156, doi.org/10.3390/jmse9111156

Risanto, C. B., C. L. Castro, A. F. Arellano, J. M. Moker, and D. K. Adams, 2021
The Impact of Assimilating GPS Precipitable Water Vapor in Convective-Permitting WRF-ARW on North American Monsoon Precipitation Forecasts over Northwest Mexico.
Monthly Weather Review, 149(9), 3013-3035, doi.org/10.1175/MWR-D-20-0394.1

Liu, G., R. S. Lieberman, V. L. Harvey, N. M. Pedatella, J. Oberheide, R. E. Hibbins, P. J. Espy, and D. Janches, 2021
Tidal Variations in the Mesosphere and Lower Thermosphere Before, During, and After the 2009 Sudden Stratospheric Warming.
Journal of Geophysical Research: Space Physics, 126, e2020JA028827, doi.org/10.1029/2020JA028827

Jiang, P., X., Chen, K. Chen, J. L. Anderson, N.Collins, N., & M. E. Gharamti, 2021
DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters.
Environmental Modelling & Software, 142, 105074, doi.org/10.1016/j.envsoft.2021.105074

Rakesh, S., & G, Kutty, 2021
Intercomparison of the Performance of Four Data Assimilation Schemes in a Limited‐Area Model on Forecasts of an Extreme Rainfall Event Over the Uttarakhand in Himalayas.
Earth and Space Science, 8(7), doi.org/10.1029/2020EA001461

Riedel, C. P., S. M. Cavallo, & D. B. Parsons, 2021
Mesoscale Prediction in the Antarctic Using Cycled Ensemble Data Assimilation.
Monthly Weather Review, 149(2), 443-462, doi.org/10.1175/MWR-D-20-0009.1

Raczka, B., Hoar T.J., Duarte H.F., Fox A.M., Anderson J.L., Bowling D.R., & Lin J.C., 2021
Improving CLM5.0 Biomass and Carbon Exchange across the Western US Using a Data Assimilation System.
Journal of Advances in Modeling Earth Systems, doi.org/10.1029/2020MS002421

Raeder, K., T. J. Hoar, M. El Gharamti, B. K. Johnson, N. Collins, J. L. Anderson, J. Steward, and M. Coady, 2021
A new CAM6 + DART reanalysis with surface forcing from CAM6 to other CESM models.
Scientific Reports, 11, 16384, doi.org/10.1038/s41598-021-92927-0

Kodikara, T., Zhang, K., Pedatella, N. M., & Borries, C., 2021
The impact of solar activity on forecasting the upper atmosphere via assimilation of electron density data.
Space Weather, 19, e2020SW002660, doi.org/10.1029/2020SW002660

Zhang, Q., Li, M., Wei, C., Mizzi, A. P., Huang, Y., & Gu, Q., 2021
Assimilation of OCO-2 retrievals with WRF-Chem/DART: A case study for the Midwestern United States.
Atmospheric Environment, 246, 118106, doi.org/10.1016/j.atmosenv.2020.118106

Hsu, C. T., Matsuo, T., Maute, A., Stoneback, R., & Lien, C. P.. 2021
Data‐Driven Ensemble Modeling of Equatorial Ionospheric Electrodynamics: A Case Study During a Minor Storm Period Under Solar Minimum Conditions.
Journal of Geophysical Research: Space Physics, 126(2), e2020JA028539. doi.org/10.1029/2020JA028539

George, B., & Kutty, G., 2021
Ensemble sensitivity analysis of an extreme rainfall event over the Himalayas in June 2013.
Dynamics of Atmospheres and Oceans, 93, 101202, doi.org/10.1016/j.dynatmoce.2021.101202

Toye, H., Zhan, P., Sana, F., Sanikommu, S., Raboudi, N., & Hoteit, I., 2021
Adaptive ensemble optimal interpolation for efficient data assimilation in the red sea.
Journal of Computational Science, 51, 101317, doi.org/10.1016/j.jocs.2021.101317

El Gharamti, M., McCreight, J. L., Noh, S. J., Hoar, T. J., RafieeiNasab, A., & Johnson, B. K., 2021
Ensemble Streamflow Data Assimilation using WRF-Hydro and DART: Hurricane Florence Flooding.
Hydrology and Earth System Sciences Discussions, 1-31. doi.org/10.5194/hess-2020-642

Laskar, F. I., Pedatella, N. M., Codrescu, M. V., Eastes, R. W., Evans, J. S., Burns, A. G., & McClintock, W., 2021
Impact of GOLD retrieved thermospheric temperatures on a whole atmosphere data assimilation model.
Journal of Geophysical Research: Space Physics, 126, e2020JA028646. doi.org/10.1029/2020JA028646

Zhang, Y.-F., Bitz, C. M., Anderson, J. L., Collins, N. S., Hoar, T. J., Raeder, K. D., and Blanchard-Wrigglesworth, E., 2021
Estimating parameters in a sea ice model using an ensemble Kalman filter.
The Cryosphere, 15, 1277–1284, doi.org/10.5194/tc-15-1277-2021.

Gaubert, B., Emmons, L. K., Raeder, K., Tilmes, S., Miyazaki, K., Arellano Jr., A. F., Elguindi, N., Granier, C., Tang, W., Barré, J., Worden, H. M., Buchholz, R. R., Edwards, D. P., Franke, P., Anderson, J. L., Saunois, M., Schroeder, J., Woo, J.-H., Simpson, I. J., Blake, D. R., Meinardi, S., Wennberg, P. O., Crounse, J., Teng, A., Kim, M., Dickerson, R. R., He, H., Ren, X., Pusede, S. E., and Diskin, G. S., 2020:
Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ.
Atmos. Chem. Phys., 20, 14617–14647, doi.org/10.5194/acp-20-14617-2020.

2020

Castruccio, F. S., A. Karspeck, G. Danabasoglu, J. Hendricks, T. J. Hoar, N. S. Collins, J. L. Anderson, 2020
An EnOI‐based Data Assimilation System with DART for a High‐Resolution Version of the CESM2 Ocean Component.
Journal of Advances in Modeling Earth Systems, 12, doi:10.1029/2020MS002176

Moore, A., J. Zavala-Garay, H. G. Arango, C. A. Edwards, J. L. Anderson, T. J. Hoar, 2020
Regional and basin scale applications of ensemble adjustment Kalman filter and 4D-Var ocean data assimilation systems.
Progress in Oceanography, 189, 102450, doi:0.1016/j.pocean.2020.102450

Li, C. H., Berner, J., Hong, J. S., Fong, C. T., & Kuo, Y. H., 2020
The Taiwan WRF Ensemble Prediction System: Scientific description, model-error representation and performance results.
Asia-Pacific Journal of Atmospheric Sciences, 56(1), 1-15. doi.org/10.1007/s13143-019-00127-8

Smith, W. K., Fox, A. M., MacBean, N., Moore, D. J., & Parazoo, N. C., 2020
Constraining estimates of terrestrial carbon uptake: New opportunities using long‐term satellite observations and data assimilation.
New Phytologist, 225(1), 105-112. doi.org/10.1111/nph.16055

Wong, M., Romine, G., & Snyder, C., 2020
Model improvement via systematic investigation of physics tendencies.
Monthly Weather Review, 148(2), 671-688, doi.org/10.1175/MWR-D-19-0255.1

Siongco, A. C., Ma, H. Y., Klein, S. A., Xie, S., Karspeck, A. R., Raeder, K., & Anderson, J. L., 2020
A hindcast approach to diagnosing the equatorial Pacific cold tongue SST bias in CESM1.
Journal of Climate, 33(4), 1437-1453, doi.org/10.1175/JCLI-D-19-0513.1

Eliashiv, J., Subramanian, A. C., & Miller, A. J., 2020
Tropical climate variability in the Community Earth System Model: Data Assimilation Research Testbed.
Climate Dynamics, 54(1), 793-806, doi.org/10.1007/s00382-019-05030-6

Ma, C., Wang, T., Jiang, Z., Wu, H., Zhao, M., Zhuang, B., … & Wu, R., 2020
Importance of bias correction in data assimilation of multiple observations over eastern China using WRF‐Chem/DART.
Journal of Geophysical Research: Atmospheres, 125(1), e2019JD031465, doi.org/10.1029/2019JD031465

Singh, T., 2020
Development of an ensemble data assimilation system with LMDZ5 AGCM for regional reanalysis.
Climate Dynamics, 54(5), 2847-2868, doi.org/10.1007/s00382-020-05147-z

Anderson, J. L., 2020
A Marginal Adjustment Rank Histogram Filter for Non-Gaussian Ensemble Data Assimilation.
Monthly Weather Review, 148(8), 3361-3378, doi.org/10.1175/MWR-D-19-0307.1

Liu, H., Kuo, Y. H., Sokolovskiy, S., Zou, X., & Zeng, Z., 2020
Analysis bias induced in assimilation of the radio occultation bending angle with complex structures in the tropical troposphere.
Quarterly Journal of the Royal Meteorological Society, 146(733), 4030-4037, doi.org/10.1002/qj.3887

Pedatella, N. M., Anderson, J. L., Chen, C. H., Raeder, K., Liu, J., Liu, H. L., & Lin, C. H., 2020
Assimilation of Ionosphere Observations in the Whole Atmosphere Community Climate Model with Thermosphere‐Ionosphere EXtension (WACCMX).
Journal of Geophysical Research: Space Physics, 125(9), e2020JA028251, doi.org/10.1029/2020JA028251

Toye, H., Sanikommu, S., Raboudi, N. F., & Hoteit, I., 2020
A hybrid ensemble adjustment Kalman filter based high‐resolution data assimilation system for the Red Sea: Implementation and evaluation.
Quarterly Journal of the Royal Meteorological Society, 146(733), 4108-4130, doi.org/10.1002/qj.3894

Ma, H., Siongco, A. C., Klein, S. A., Xie, S., Karspeck, A. R., Raeder, K., Anderson, J. L., Lee, J., Kirtman, B. P., Merryfield, W. J., Murakami, H., & Tribbia, J. J., 2020
On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature.
Journal of Climate, 34(1), 427-446, doi.org/10.1175/JCLI-D-20-0338.1

Brown, M., Smith, B., Capon, C., Abay, R., Polo, M. C., Gehly, S., … & Boyce, R., 2020
SSA Experiments for the Australian M2 Formation Flying CubeSat Mission.
Advanced Maui Optical and Space Surveillance Technologies pdf

El Gharamti, M., 2020
Hybrid Ensemble–Variational Filter: A Spatially and Temporally Varying Adaptive Algorithm to Estimate Relative Weighting.
Monthly Weather Review, 149(1), 65-76. doi.org/10.1175/MWR-D-20-0101.1

Toye, H., 2020
Efficient Ensemble Data Assimilation and Forecasting of the Red Sea Circulation
Doctoral dissertation

Qiao, X., S. Wang, C. S. Schwartz, Z. Liu, and J. Min, 2020
A Method for Probability Matching Based on the Ensemble Maximum for Quantitative Precipitation Forecasts.
Monthly Weather Review, 148, 3379-3396, doi.org/10.1175/MWR-D-20-0003.1

Schwartz, C. S., M. Wong, G. S. Romine, R. A. Sobash, and K. R. Fossell, 2020
Initial Conditions for Convection-Allowing Ensembles over the Conterminous United States.
Monthly Weather Review, 148, 2645-2669, doi.org/10.1175/MWR-D-19-0401.1

2019

Coniglio, M. C., G. S. Romine, D. D. Turner, and R. D. Torn, 2019
Impacts of targeted AERI and Doppler lidar wind retrievals on short-term forecasts of the initiation and early evolution of thunderstorms.
Monthly Weather Review, 147, 1149-1170, doi.org/10.1175/MWR-D-18-0351.1

Gopalakrishnan, G., I. Hoteit, B. Cornuelle, and D. Rudnick, 2019
Comparison of 4DVAR and EnKF states estimates and forecasts in the Gulf of Mexico.
Quarterly Journal of the Royal Meteorological Society, 145, 1354-1376, doi:10.1002/qj.3493

Kerr, C. A., Stensrud, D. J., & Wang, X., 2019
Diagnosing convective dependencies on near-storm environments using ensemble sensitivity analyses.
Monthly Weather Review, 147(2), 495-517. doi.org/10.1175/MWR-D-18-0140.1

Ling, X. L., Fu, C. B., Yang, Z. L., & Guo, W. D., 2019
Comparison of different sequential assimilation algorithms for satellite-derived leaf area index using the Data Assimilation Research Testbed (version Lanai). Geoscientific Model Development, 12(7), 3119-3133. doi.org/10.5194/gmd-12-3119-2019

Tang, W., Emmons, L. K., Arellano Jr, A. F., Gaubert, B., Knote, C., Tilmes, S., … & Kim, D., 2019
Source contributions to carbon monoxide concentrations during KORUS‐AQ based on CAM‐chem model applications.
Journal of Geophysical Research: Atmospheres, 124(5), 2796-2822. doi.org/10.1029/2018JD029151

Laskar, F. I., Stober, G., Fiedler, J., Oppenheim, M. M., Chau, J. L., Pallamraju, D., … & Renkwitz, T., 2019
Mesospheric anomalous diffusion during noctilucent cloud scenarios.
Atmospheric Chemistry and Physics, 19(7), 5259-5267. doi.org/10.5194/acp-19-5259-2019

El Gharamti, M., Raeder, K., Anderson, J., & Wang, X., 2019
Comparing adaptive prior and posterior inflation for ensemble filters using an atmospheric general circulation model.
Monthly Weather Review, 147(7), 2535-2553. doi.org/10.1175/MWR-D-18-0389.1

Anderson, J. L., 2019
A nonlinear rank regression method for ensemble Kalman filter data assimilation.
Monthly Weather Review, 147(8), 2847-2860. doi.org/10.1175/MWR-D-18-0448.1

Moker Jr, J. M., 2019
Investigating the Performance of Convection-allowing Hindcast Simulations During the North American Monsoon with and Without GPS-PWV Data Assimilation.
Doctoral Dissertaion

Kurzrock, F., Nguyen, H., Sauer, J., Chane Ming, F., Cros, S., Smith Jr, W. L., … & Lajoie, G., 2019
Evaluation of WRF-DART (ARW v3. 9.1. 1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment.
Geoscientific Model Development, 12(9), 3939-3954. doi.org/10.5194/gmd-12-3939-2019

Ma, C., Wang, T., Mizzi, A. P., Anderson, J. L., Zhuang, B., Xie, M., & Wu, R., 2019
Multiconstituent data assimilation with WRF‐Chem/DART: Potential for adjusting anthropogenic emissions and improving air quality forecasts over eastern China.
Journal of Geophysical Research: Atmospheres, 124(13), 7393-7412. doi.org/10.1029/2019JD030421

Potvin, C. K., Carley, J. R., Clark, A. J., Wicker, L. J., Skinner, P. S., Reinhart, A. E., … & Xue, M., 2019
Systematic comparison of convection-allowing models during the 2017 NOAA HWT Spring Forecasting Experiment.
Weather and Forecasting, 34(5), 1395-1416. doi.org/10.1175/WAF-D-19-0056.1

Yang, J., Astitha, M., & Schwartz, C. S., 2019
Assessment of storm wind speed prediction using gridded Bayesian regression applied to historical events with NCAR’s real‐time ensemble forecast system.
Journal of Geophysical Research: Atmospheres, 124(16), 9241-9261. doi.org/10.1029/2018JD029590

Bian, Q., Xu, Z., Zhao, L., Zhang, Y. F., Zheng, H., Shi, C., … & Yang, Z. L., 2019
Evaluation and intercomparison of multiple snow water equivalent products over the Tibetan Plateau.
Journal of Hydrometeorology, 20(10), 2043-2055. doi.org/10.1175/JHM-D-19-0011.1

Flora, M. L., Skinner, P. S., Potvin, C. K., Reinhart, A. E., Jones, T. A., Yussouf, N., & Knopfmeier, K. H., 2019
Object-based verification of short-term, storm-scale probabilistic mesocyclone guidance from an experimental warn-on-forecast system.
Weather and Forecasting, 34(6), 1721-1739. doi.org/10.1175/WAF-D-19-0094.1

Smith, N. H., & Ancell, B. C., 2019
Variations in parametric sensitivity for wind ramp events in the Columbia river basin.
Monthly Weather Review, 147(12), 4633-4651. doi.org/10.1175/MWR-D-19-0019.1

Pedatella, N. M., Liu, H. L., Marsh, D. R., Raeder, K., & Anderson, J. L., 2019
Error growth in the Mesosphere and Lower Thermosphere Based on Hindcast Experiments in a Whole Atmosphere Model.
Space Weather, 17(10), 1442-1460. doi.org/10.1029/2019SW002221

Elmer, N. J., 2019
Using satellite observations of river height and vegetation to improve National Water Model initialization and streamflow prediction.
Doctoral Dissertation University of Alabama.

Kodikara, T., 2019
Physical Understanding and Forecasting of the Thermospheric Structure and Dynamics
Doctoral Dissertation RMIT University, Melbourne, Australia.

Trier, S. B., G. S. Romine, D. A. Ahijevych, and R. A. Sobash, 2019
Lower-Tropospheric Influences on the Timing and Intensity of Afternoon Severe Convection over Modest Terrain in a Convection-Allowing Ensemble.
Weather and Forecasting, 34, 1633-1656, doi.org/10.1175/WAF-D-19-0087.1

Schwartz, C. S., G. S. Romine, R. A. Sobash, K. R. Fossell, and M. L. Weisman, 2019
NCAR’s Real-Time Convection-Allowing Ensemble Project.
Bulletin of the American Meteorological Society, 100, 321-343, doi.org/10.1175/BAMS-D-17-0297.1

2018

Aydoğdu, A., Hoar, T. J., Vukicevic, T., Anderson, J. L., Pinardi, N., Karspeck, A., Hendricks, J., Collins, N., Macchia, F., and Özsoy, E., 2018
OSSE for a sustainable marine observing network in the Sea of Marmara.
Nonlinear Processes in Geophysics, 25, 537-551, doi.org/10.5194/npg-25-537-2018

El Gharamti M., 2018
Enhanced Adaptive Inflation Algorithm for Ensemble Filters.
Monthly Weather Review, 2, 623-640, doi:10.1175/MWR-D-17-0187.1

Fox, A. M., Hoar, T. J., Anderson, J. L., Arellano, A. F., Smith, W. K., Litvak, M. E., et al., 2018
Evaluation of a data assimilation system for land surface models using CLM4.5.
Journal of Advances in Modeling Earth Systems, 10, 2471–2494, doi.org/10.1029/2018MS001362

Karspeck, A. R., G. Danabasoglu, J. L. Anderson, S. Karol, N. Collins, M. Vertenstein, K. Raeder, T. Hoar, R. Neale, J. Edwards and A. Craig, 2018
A global coupled ensemble data assimilation system using the Community Earth System Model and the Data Assimilation Research Testbed.
Quarterly Journal of the Royal Meteorological Society, doi:10.1002/qj.3308

Toye, H., S. Kortas, P. Zhan and I. Hoteit, 2018
A fault-tolerant HPC scheduler extension for large and operational ensemble data assimilation: Application to the Red Sea.
Journal of Computational Science, 27, 46-56, doi:10.1016/j.jocs.2018.04.018

Zhang, Y. -F., C. M. Bitz, J. L. Anderson, N. Collins, J. Hendricks, T. Hoar, K. Raeder and F. Massonnet, 2018
Insights on Sea Ice Data Assimilation from Perfect Model Observing System Simulation Experiments.
Journal of Climate, doi:10.1175/JCLI-D-17-0904.1

Pedatella, N. M., H.‐L. Liu, D. R. Marsh, K. Raeder, J. L. Anderson, J. L. Chau, L. P. Goncharenko and T. A. Siddiqui, 2018
Analysis and Hindcast Experiments of the 2009 Sudden Stratospheric Warming in WACCMX+ DART.
Journal of Geophysical Research: Space Physics, 123, 3131-3153, doi:10.1002/2017JA025107

Clark, A. J., I. L. Jirak, S. R. Dembek, G. J. Creager, F. Kong, K. W. Thomas, K. H. Knopfmeier, B. T. Gallo, C. J. Melick, M. Xue, and K. A. Brewster, 2018
The Community Leveraged Unified Ensemble (CLUE) in the 2016 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment.
Bulletin of the American Meteorological Society, doi:10.1175/WAF-D-16-0178.1

Pan, S., J. Gao, D. J. Stensrud, X. Wang and T. A. Jones, 2018
Assimilation of Radar Radial Velocity and Reflectivity, Satellite Cloud Water Path, and Total Precipitable Water for Convective-Scale NWP in OSSEs.
Journal of Atmospheric and Oceanic Technology, 35, 67-89, doi:10.1175/JTECH-D-17-0081.1

Matus, S. A., 2018
Using ensemble precipitation forecasts to improve hydrologic risk assessment at river crossings
M.S. Thesis

2017

Gaubert, B., H. M. Worden, A. F. J. Arellano, L. K. Emmons, S. Tilmes, J. Barré, S. Martinez Alonso, F. Vitt, J. L. Anderson, F. Alkemade, S. Houweling, D. P. Edwards, 2017
Chemical feedback from decreasing carbon monoxide emissions.
Geophysical Research Letters, 44, 9985-9995, doi:10.1002/2017GL074987

Lee, J. A., J. P. Hacker, L. Delle Monache, B. Kosović, A. Clifton, F. Vandenberghe and J. S. Rodrigo, 2017
Improving wind predictions in the marine atmospheric boundary layer through parameter estimation in a single-column model.
Monthly Weather Review, 145, 5-24, doi:10.1175/MWR-D-16-0063.1

Gu, S. -Y., H. Liu, N. M. Pedatella, X. Dou, and Y. Liu, 2017
On the wave number 2 eastward propagating quasi 2 day wave at middle and high latitudes.
Journal of Geophysical Research: Space Physics, 122, 4489-4499, doi:10.1002/2016JA023353

Hodyss, D., J. L. Anderson, N. Collins, W. F. Campbell and P. A. Reinecke, 2017
Quadratic polynomial regression using serial observation processing: Implementation within DART.
Monthly Weather Review, 145, 4467-4479, doi:10.1175/MWR-D-17-0089.1

Kwon, Y., Z. -L. Yang, T. J. Hoar and A. M. Toure, 2017
Improving the radiance assimilation performance in estimating snow water storage across snow and land-cover types in North America.
Journal of Hydrometeorology, 18, 651-668, doi:10.1175/JHM-D-16-0102.1

Keclik, A. M., C. Evans, P. J. Roebber and G. S. Romine, 2017
The influence of assimilated upstream, preconvective dropsonde observations on ensemble forecasts of convection initiation during the Mesoscale Predictability Experiment.
Monthly Weather Review, 145, 4747-4770, doi:10.1175/MWR-D-17-0159.1

Liu, X., A. P. Mizzi, J. L. Anderson, I. Y. Fung and R. C. Cohen, 2017
Assimilation of satellite NO2 observations at high spatial resolution using OSSEs.
Atmospheric Chemistry and Physics, 17, 7067-7081, doi:10.5194/acp-17-7067-2017

Ha, S., C. Snyder, W. C. Skamarock, J. Anderson and N. Collins, 2017
Ensemble Kalman filter data assimilation for the Model for Prediction Across Scales (MPAS).
Monthly Weather Review, 145, 4673-4692, doi:10.1175/MWR-D-17-0145.1

Rubin, J. I., J. S. Reid, J. A. Hansen, J. L. Anderson, B. N. Holben, P. Xian, D. L. Westphal and J. Zhang, 2017
Assimilation of AERONET and MODIS AOT observations using variational and ensemble data assimilation methods and its impact on aerosol forecasting skill.
Journal of Geophysical Research: Atmospheres, 122, 4967-4992, doi:10.1002/2016JD026067

Chen, C. ‐H., C. Lin, Wei. ‐H. Chen, and T. Matsuo, 2017
Modeling the ionospheric prereversal enhancement by using coupled thermosphere‐ionosphere data assimilation.
Geophysical Research Letters, 44, 1652-1659, doi:10.1002/2016GL071812

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.
Monthly Weather Review, 145, 1897-1918, doi:10.1175/MWR-D-16-0298.1

Chen, C. ‐H., C. Lin, Wei. ‐H. Chen, T. Matsuo and W. H. Chen, 2017
The impact of FORMOSAT-5/AIP observations on the ionospheric space weather.
Terrestrial, Atmospheric and Oceanic Sciences, 28, 129-137, doi:10.3319/TAO.2016.09.30.01(EOF5)

Velden, C., W. E. Lewis, W. Bresky, D. Stettner, J. Daniels and S. Wanzong, 2017
Assimilation of high-resolution satellite-derived atmospheric motion vectors: Impact on HWRF forecasts of tropical cyclone track and intensity.
Monthly Weather Review, 145, 1107-1125, doi:10.1175/MWR-D-16-0229.1

Kerr, C. A., D. J. Stensrud and X. Wang, 2017
Verification of convection-allowing model ensemble analyses of near-storm environments using MPEX upsonde observations.
Monthly Weather Review, 145, 857-875, doi:10.1175/MWR-D-16-0287.1

Madaus, L. E. and C. F. Mass, 2017
Evaluating Smartphone Pressure Observations for Mesoscale Analyses and Forecasts.
Monthly Weather Review, 32, 511-531, doi:10.1175/WAF-D-16-0135.1

Berman, J. D., R. D. Torn, G. S. Romine, and M. L. Weisman, 2017
Sensitivity of Northern Great Plains Convection Forecasts to Upstream and Downstream Forecast Errors.
Monthly Weather Review, 145, 2141-2163, doi.org/10.1175/MWR-D-16-0353.1

Schwartz, C. S., 2017
A Comparison of Methods Used to Populate Neighborhood-Based Contingency Tables for High-Resolution Forecast Verification.
Weather and Forecasting, 32, 733-741, doi.org/10.1175/WAF-D-16-0187.1

Dawson, L. C., G. S. Romine, R. J. Trapp, and M. E. Baldwin, 2017
Verifying Supercellular Rotation in a Convection-Permitting Ensemble Forecasting System with Radar-Derived Rotation Track Data.
Weather and Forecasting, 32, 781-795, doi.org/10.1175/WAF-D-16-0121.1

Schwartz, C. S., G. S. Romine, K. R. Fossell, R. A. Sobash, and M. L. Weisman, 2017
Toward 1-km Ensemble Forecasts over Large Domains.
Monthly Weather Review, 145, 2943-2969, doi.org/10.1175/MWR-D-16-0410.1

Torn, R. D., G. S. Romine, and T. J. Galarneau, 2017
Sensitivity of Dryline Convection Forecasts to Upstream Forecast Errors for Two Weakly Forced MPEX Cases.
Monthly Weather Review, 145, 1831-1852, doi.org/10.1175/MWR-D-16-0457.1

2016

Hill, A. J., C. C. Weiss, and B. C. Ancell, 2016
Ensemble sensitivity analysis for mesoscale forecasts of dryline convection initiation. Monthly Weather Review, 144(11) 4161-4182 doi.org/10.1175/MWR-D-15-0338.1

Gaubert, B., A. F. Arellano Jr., J. Barré, H. M. Worden, L. K. Emmons, S. Tilmes, R. R. Buchholz, F. Vitt, K. Raeder, N. Collins, J. L. Anderson, C. Wiedinmyer, S. Martinez Alonso, D. P. Edwards, M. O. Andreae, J. W. Hannigan, C. Petri, K. Strong, N. Jones , 2016
Toward a chemical reanalysis in a coupled chemistry-climate model: An evaluation of MOPITT CO assimilation and its impact on tropospheric composition.
Journal of Geophysical Research: Atmospheres, 121, 7310-7343, doi:10.1002/2016JD024863

Jewtoukoff, V., R. Plougonven, A. Hertzog, C. Snyder and G. Romine, 2016
On the prediction of stratospheric balloon trajectories: Improving winds with mesoscale simulations.
Journal of Atmospheric and Oceanic Technology, 33, 1629-1647, doi:10.1175/JTECH-D-15-0110.1

Gu, S. -Y., H. -L. Liu, N. M. Pedatella, X. Dou and Z. Shu, 2016
The quasi-2 day wave activities during 2007 boreal summer period as revealed by Whole Atmosphere Community Climate Model.
Journal of Geophysical Research: Space Physics, 121, 2743-2754, doi:10.1002/2015JA022225

Pedatella, N., J. Oberheide, E. K. Sutton, H. Liu, J. L. Anderson and K. D. Raeder, 2016
Short-term nonmigrating tide variability in the mesosphere, thermosphere, and ionosphere.
Journal of Geophysical Research: Space Physics, 121, 3621-3633, doi:10.1002/2016JA022528

Zhao, L., Z. -L. Yang and T. J. Hoar, 2016
Global soil moisture estimation by assimilating AMSR-E brightness temperatures in a coupled CLM4-RTM-DART system.
Journal of Hydrometeorology, 17, 2431-2454, doi:10.1175/JHM-D-15-0218.1

Dikpati, M., D. Mitra and J. L. Anderson, 2016
Role of response time of a Babcock-Leighton solar dynamo model in meridional flow-speed reconstruction by EnKF data assimilation.
Advances in Space Research, 58, 1589-1595, doi:10.1016/j.asr.2016.08.004

Mizzi, A. P., A. F. Arellano, D. P. Edwards, J. L. Anderson and G. Pfister, 2016
Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system.
Geoscientific Model Development, 9, 965-978, doi:10.5194/gmd-9-965-2016

Dikpati M., J. L. Anderson and D. Mitra, 2016
Data assimilation in a solar dynamo model using ensemble Kalman filters: Sensitivity and robustness in reconstruction of meridional flow speed.
The Astrophysical Journal, 828, 91, doi:10.3847/0004-637X/828/2/91

Penny, A. B., J. P. Hacker, P. A. Harr, 2016
Analysis of tropical storm formation based on ensemble data assimilation and high-resolution numerical simulations of a nondeveloping disturbance.
Monthly Weather Review, 144, 3631-3649, doi:10.1175/MWR-D-16-0100.1

Garcia, M., T. Hoar, M. Thomas, B. Bailey and J. Castillo, 2016
Interfacing an ensemble Data Assimilation system with a 3D nonhydrostatic Coastal Ocean Model, an OSSE experiment.
OCEANS MTS/IEEE Monterey, pp. 1-11, doi:10.1109/OCEANS.2016.7760992

Chartier, A. T., T. Matsuo, J. L. Anderson, N. S. Collins, T. J. Hoar, G. Lu, C. N. Mitchell, A. J. Coster, L. J. Paxton, G. S. Bust, 2016
Ionospheric data assimilation and forecasting during storms.
Journal of Geophysical Research: Space Physics, 121, 764-778, doi:10.1002/2014JA020799

Rubin, J. I., J. S. Reid, J. A. Hansen, J. L. Anderson, N. S. Collins, T. J. Hoar, T. Hogan, P. Lynch, J. McLay, Carolyn A. Reynolds, W. R. Sessions, D. L. Westphal and J. Zhang, 2016
Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting.
Atmospheric Chemistry and Physics, 15, 28069-28132, doi:10.5194/acpd-15-28069-2015

Marquis, J., Y. Richardson, P. Markowski, J. Wurman, K. Kosiba, and P. Robinson, 2016
An Investigation of the Goshen County, Wyoming, Tornadic Supercell of 5 June 2009 Using EnKF Assimilation of Mobile Mesonet and Radar Observations Collected during VORTEX2. Part II: Mesocyclone-Scale Processes Affecting Tornado Formation, Maintenance, and Decay.
Monthly Weather Review, 144, 3441-3463, doi.org/10.1175/MWR-D-15-0411.1

Sobash, R. A., G. S. Romine, C. S. Schwartz, D. J. Gagne, and M. L. Weisman, 2016
Explicit Forecasts of Low-Level Rotation from Convection-Allowing Models for Next-Day Tornado Prediction.
Weather and Forecasting, 31, 1591-1614, doi.org/10.1175/WAF-D-16-0073.1

Sobash, R. A., C. S. Schwartz, G. S. Romine, K. R. Fossell, and M. L. Weisman, 2016
Severe Weather Prediction Using Storm Surrogates from an Ensemble Forecasting System.
Weather and Forecasting, 31, 255-271, doi.org/10.1175/WAF-D-15-0138.1

2015

Barré, J., B. Gaubert, A. F. J. Arellano, H. M. Worden, D. P. Edwards, M. Deeter, J. L. Anderson, K. D. Raeder, N. S. Collins, S. Tilmes, G. Francis, C. Clerbaux, L. Emmons, G. Pfister, P.-F. Coheur and D. Hurtmans, 2015
Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM-CAM-chem and DART.
Journal of Geophysical Research: Atmospheres, 120, no. 19, doi:10.1002/2015JD023467

Bernardet, L., V. Tallapragada, S. Bao, S. Trahan, Y. Kwon, Q. Liu, M. Tong, M. Biswas, T. Brown, D. Stark, L. Carson, R. Yablonsky, E. Uhlhorn, S. Gopalakrishnan, X. Zhang, T. Marchok, Y. H. Kuo and R. Gall, 2015
Community support and transition of research to operations for the Hurricane Weather Research and Forecasting Model.
Bulletin of the American Meteorological Society, 96, 953-960, doi:10.1175/BAMS-D-13-00093.1

Ha, S.-Y., J. Berner and C. M. Snyder, 2015
A comparison of model error representations in mesoscale ensemble data assimilation.
Monthly Weather Review, 143, 3893-3911, doi:10.1175/MWR-D-14-00395.1

Singh, T., R. Mitta, H.C. Upadhyaya, 2015
Ensemble Adjustment Kalman Filter Data Assimilation for a Global Atmospheric Model.
International Conference on Dynamic Data-Driven Environmental Systems Science, 284-298, doi:10.1007/978-3-319-25138-7_26

Newman, K. M., C. S. Schwartz, Z. Liu, H. Shao, and X.-Y. Huang, 2015
Evaluating Forecast Impact of Assimilating Microwave Humidity Sounder (MHS) Radiances with a Regional Ensemble Kalman Filter Data Assimilation System.
Weather and Forecasting, 30, 964-983, doi.org/10.1175/WAF-D-14-00091.1

Trier, S. B., G. S. Romine, D. A. Ahijevych, R. J. Trapp, R. S. Schumacher, M. C. Coniglio, and D. J. Stensrud, 2015
Mesoscale Thermodynamic Influences on Convection Initiation near a Surface Dryline in a Convection-Permitting Ensemble.
Monthly Weather Review, 143, 3726-3753, doi.org/10.1175/MWR-D-15-0133.1

Weisman, M. L., and Coauthors, 2015
The Mesoscale Predictability Experiment (MPEX).
Bulletin of the American Meteorological Society, 96, 2127-2149, doi.org/10.1175/BAMS-D-13-00281.1

Lei, L., J. L. Anderson, and G. S. Romine, 2015
Empirical Localization Functions for Ensemble Kalman Filter Data Assimilation in Regions with and without Precipitation.
Monthly Weather Review, 143, 3664-3679, doi.org/10.1175/MWR-D-14-00415.1

Schwartz, C. S., Z. Liu, and X.-Y. Huang, 2015
Sensitivity of Limited-Area Hybrid Variational-Ensemble Analyses and Forecasts to Ensemble Perturbation Resolution.
Monthly Weather Review, 143, 3454-3477, doi.org/10.1175/MWR-D-14-00259.1

Schwartz, C. S., G. S. Romine, R. A. Sobash, K. R. Fossell, and M. L. Weisman, 2015
NCAR’s Experimental Real-Time Convection-Allowing Ensemble Prediction System.
Weather and Forecasting, 30, 1645-1654, doi.org/10.1175/WAF-D-15-0103.1

Schwartz, C. S., G. S. Romine, M. L. Weisman, R. A. Sobash, K. R. Fossell, K. W. Manning, and S. B. Trier, 2015
A Real-Time Convection-Allowing Ensemble Prediction System Initialized by Mesoscale Ensemble Kalman Filter Analyses.
Weather and Forecasting, 30, 1158-1181, doi.org/10.1175/WAF-D-15-0013.1

Torn, R. D., and G. S. Romine, 2015
Sensitivity of Central Oklahoma Convection Forecasts to Upstream Potential Vorticity Anomalies during Two Strongly Forced Cases during MPEX.
Monthly Weather Review, 143, 4064-4087, doi.org/10.1175/MWR-D-15-0085.1

2014

Wu, T.-C., H. Liu, S. J. Majumdar, C. S. Velden, J. L. Anderson, 2014
Influence of assimilating satellite-derived atmospheric motion vector observations on numerical analyses and forecasts of tropical cyclone track and intensity.
Monthly Weather Review, 142, 49-71, doi:10.1175/MWR-D-13-00023.1

Lei, L. and J. L. Anderson, 2014
Impacts of frequent assimilation of surface pressure observations on atmospheric analyses.
Monthly Weather Review, 142 4477-4483, doi:10.1175/MWR-D-14-00097.1

Dikpati, M., J. L. Anderson and D. Mitra, 2014
Ensemble Kalman filter data assimilation in a Babcock-Leighton solar dynamo model: An observation system simulation experiment for reconstructing meridional flow speed.
Geophysical Research Letters, 41 5361-5369, doi:10.3847/0004-637X/828/2/91

Ha, S.-Y. and C. Snyder, 2014
Influence of surface observations in mesoscale data assimilation using an ensemble Kalman filter.
Monthly Weather Review, 142 1489-1508, doi:10.1175/MWR-D-13-00108.1

Pedatella, N., K. D. Raeder, J. L. Anderson and H. Liu, 2014
Ensemble data assimilation in the Whole Atmosphere Community Climate Model.
Journal of Geophysical Research: Atmospheres, 119 9793-9809, doi:10.1002/2014JD021776

Zhang, Y.-F., T. J. Hoar, Z.-L. Yang, J. L. Anderson, A. M. Toure and M. Rodell, 2014
Assimilation of MODIS snow cover through the Data Assimilation Research Testbed and the Community Land Model version 4.
Journal of Geophysical Research: Atmospheres, 142 1489-1508, doi:10.1002/2013JD021329

Romine, G. S., C. S. Schwartz, J. Berner, K. R. Fossell, C. Snyder, J. L. Anderson, and M. L. Weisman, 2014
Representing Forecast Error in a Convection-Permitting Ensemble System.
Monthly Weather Review, 142, 4519-4541, doi.org/10.1175/MWR-D-14-00100.1

Schwartz, C. S., G. S. Romine, K. R. Smith, and M. L. Weisman, 2014
Characterizing and Optimizing Precipitation Forecasts from a Convection-Permitting Ensemble Initialized by a Mesoscale Ensemble Kalman Filter.
Weather and Forecasting, 29, 1295-1318, doi.org/10.1175/WAF-D-13-00145.1

2013

Hoteit, I., T. J. Hoar, G. Gopalakrishnan, N. Collins, J. L. Anderson, B. Cornuelle, A. Kohl and P. Heimbach, 2013
A MITgcm/DART ensemble analysis and prediction system with application to the Gulf of Mexico.
Dynamics of Atmospheres and Oceans, 63, 1-23, doi:10.1016/j.dynatmoce.2013.03.002

Hacker, J. and W. Angevine, 2013
Ensemble data assimilation to characterize surface-layer errors in numerical weather prediction models.
Monthly Weather Review, 141, 1804-1821, doi:10.1175/MWR-D-12-00280.1

Rostkier-Edelstein, D. and J. Hacker, 2013
Impact of flow-dependence, column covariance, and forecast-model type on surface-observations assimilation for probabilistic PBL-profiles nowcasts.
Weather Forecasting, 28, 29-54, doi:10.1175/WAF-D-12-00043.1

Morozov, A. V., A. J. Ridley, D. S. Bernstein, N. Collins, T. J. Hoar and J. L. Anderson, 2013
Data assimilation and driver estimation for the Global Ionosphere-Thermosphere Model using the Ensemble Adjustment Kalman Filter.
Journal of Atmospheric and Solar-Terrestrial Physics, 104, 126-136, doi:10.1016/j.jastp.2013.08.016

Morozov, A. V., A. J. Ridley, D. S. Bernstein, N. Collins, T. J. Hoar and J. L. Anderson, 2013
Development and verification of a new wind speed forecasting system using an ensemble Kalman filter data assimilation technique in a fully coupled hydrologic and atmospheric model.
Journal of Advances in Modeling Earth Systems, 5, 785-800, doi:10.1002/jame.20051

Romine, G. S., C. S. Schwartz, C. Snyder, J. L. Anderson and M. L. Weisman, 2013
Model bias in a continuously cycled assimilation system and its influence on convection-permitting forecasts.
Monthly Weather Review, 141, 1263-1284, doi:10.1175/MWR-D-12-00112.1

Schwartz, C. S., Z. Liu, X.-Y. Huang, Y.-H. Kuo, and C.-T. Fong, 2013
Comparing Limited-Area 3DVAR and Hybrid Variational-Ensemble Data Assimilation Methods for Typhoon Track Forecasts: Sensitivity to Outer Loops and Vortex Relocation.
Monthly Weather Review, 141, 4350-4372, doi.org/10.1175/MWR-D-13-00028.1

2012

Anderson, J. L., 2012
Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation.
Monthly Weather Review, 140, 2359–2371, doi.org/10.1175/MWR-D-11-00013.1

Raeder, K, J. L., Anderson, N. Collins, T. J. Hoar, J. E. Kay, P. H., Lauritzen and R. Pincus, 2012
DART/CAM: An Ensemble Data Assimilation for CESM Atmospheric Models.
Journal of Climate, 25, 6304-6317, doi:10.1175/JCLI-D-11-00395.1

Dikpati, M. and J. L. Anderson, 2012
Evaluating potential for data assimilation in a flux-transport dynamo model by assessing sensitivity and response to meridional flow variation.
The Astrophysical Journal, 756 20 pp. 20 pp., doi:10.1088/0004-637X/756/1/20

Lee, I-Te, T. Matsuo, A. D. Richmond, J. Y. Liu, Wenbin Wang, C. H. Lin, J. L. Anderson and M. Q. Chen, 2012
Assimilation of FORMOSAT‐3/COSMIC electron density profiles into a coupled thermosphere/ionosphere model using ensemble Kalman filtering.
Journal of Geophysical Research: Space Physics, 117 A10, doi:10.1029/2012JA017700

Lauritzen, P. H., A. A. Mirin, J. Truesdale, K. Raeder, J. L. Anderson, J. Bacmeister and R. B. Neale, 2012
Implementation of new diffusion/filtering operators in the CAM-FV dynamical core.
The International Journal of High Performance Computing Applications, 26 63-73, doi:10.1177/1094342011410088

Lei, L., D. R. Stauffer, and A. Deng, 2012
A hybrid nudging-ensemble Kalman filter approach to data assimilation in WRF/DART.
Quarterly Journal of the Royal Meteorological Society, 138, 2066–2078, doi.org/10.1002/qj.1939

Liu, Z., C. S. Schwartz, C. Snyder, and S.-Y. Ha, 2012
Impact of Assimilating AMSU-A Radiances on Forecasts of 2008 Atlantic Tropical Cyclones Initialized with a Limited-Area Ensemble Kalman Filter.
Monthly Weather Review, 140, 4017-4034, doi.org/10.1175/MWR-D-12-00083.1

Schwartz, C. S., Z. Liu, Y. Chen, and X.-Y. Huang, 2012
Impact of Assimilating Microwave Radiances with a Limited-Area Ensemble Data Assimilation System on Forecasts of Typhoon Morakot.
Weather and Forecasting, 27, 424-437, doi.org/10.1175/WAF-D-11-00033.1

2011

Pendergrass, A. G., G. J. Hakim, D. S. Battisti and G. Roe, 2011
Coupled air-mixed-layer temperature predictability for climate reconstruction.
Journal of Climate, 25, 459-472, doi:10.1175/2011JCLI4094.1

Matsuo, T. and E. A. Araujo-Pradere, 2011
Role of thermosphere-ionosphere coupling in a global ionospheric specification.
Radio Science, 46, RS0D23, 7pp., doi:10.1029/2010RS004576

Zagar, N., J. Tribbia, J. L. Anderson and K. Raeder, 2011
Balance of the Background-Error Variances in the Ensemble Assimilation System DART/CAM.
Monthly Weather Review, 139, 2061-2079, doi:10.1175/2011MWR3477.1

C. Lee, W. G. Lawson, M. I. Richardson, J. L. Anderson, N. Collins, T. Hoar and M. Mischna, 2011
Demonstration of ensemble data assimilation for Mars using DART, MarsWRF, and radiance observations from MGS TES.
Journal of Geophysical Research, 116, E11011, 17 pp., doi:10.1029/2011JE003815

Otkin, J. A., 2011
Assessing the impact of the covariance localization radius when assimilating infrared brightness temperature observations using an ensemble Kalman filter.
Monthly Weather Review, 140, 543-561, doi:10.1175/MWR-D-11-00084.1

Otkin, J. A., D. C. Hartung, D. D. Turner, R. Peterson, W. F. Feltz and E. Janzon, 2011
Assimilation of surface-based boundary layer profiler observations during a cool season weather event using an Observation System Simulation Experiment. Part 1: Analysis impact.
Monthly Weather Review, 139, 2309-2326, doi:10.1175/2011MWR3622.1

Otkin, J. A., D. C. Hartung, D. D. Turner, R. Peterson, W. F. Feltz and Erik Janzon, 2011
Assimilation of surface-based boundary layer profiler observations during a cool season weather event using an Observation System Simulation Experiment. Part 2: Forecast assessment.
Monthly Weather Review, 139, 2327-2346, doi:10.1175/2011MWR3623.1

Kay, J., K. Raeder, A. Gettelman and J. L. Anderson, 2011
The boundary layer response to recent Arctic sea ice loss and implications for high-latitude climate feedbacks.
Journal of Climate, 24, 428-447, doi:10.1175/2010JCLI3651.1

Lauritzen, P.H., A. Mirin, J. E. Truesdale, K. Raeder, J. L. Anderson, J. Bacmeister and R. B. Neale, 2011
Implementation of new diffusion/filtering operators in the CAM-FV dynamical core.
International Journal of High Performance Computing Applications, 26, 63-73, doi:10.1177/1094342011410088

Pincus, R., P. Hofmann, J. Robert, J. L. Anderson, K. Raeder, N. Collins and J. S. Whitaker, 2011
Can Fully Accounting for Clouds in Data Assimilation Improve Short-Term Forecasts by Global Models?
Monthly Weather Review, 139, 3, pp. 946-957, doi:10.1175/2010MWR3412.1

Dorita Rostkier-Edelstein and Joshua P. Hacker, 2011
Experience and Conclusions from the Factor Separation Method: Ensemble Data Assimilation and Forecasting Applications
The Factor Separation Method in the Atmosphere- Applications and Future Prospects,
Pinhas Alpert and Tatiana Sholokhman, Cambridge University Press, ISBN: 9780521191739

2010

Anderson, J. L., 2010
A Non-Gaussian Ensemble Filter Update for Data Assimilation.
Monthly Weather Review, 138 pp. 4186-4198, doi:10.1175/2010MWR3253.1

Arellano, A. F., P. G. Hess, D. P. Edwards and D. Baumgardner, 2010
Constraints on black carbon aerosol distribution from Measurement Of Pollution In The Troposphere (MOPITT) CO
Geophysical Research Letters, 37 L17801, doi:10.1029/2010GL044416

Aksoy, A., D. C. Dowell and C. Snyder, 2010 A multicase comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part II: Short-range ensemble forecasts.
Monthly Weather Review, 138, pp 1273-1292, doi:10.1175/2009MWR3086.1

C. Lee, M. I. Richardson, W. G. Lawson and J. L. Anderson, 2010
Ensemble Data Assimilation of the Martian Atmosphere Using Temperature and Radiance Data from the Thermal Emission Spectrometer
American Astronomical Society DPS meeting #42, #30.09
Bulletin of the American Astronomical Society, Vol. 42, p.1029

C. Lee, M. I. Richardson, W. G. Lawson, J. L. Anderson, N. Collins, T. Hoar, M. Mischna and A. D. Toigo, 2010 Initial Results from Ensemble Data Assimilation of Radiances and Retrieved Temperatures from TES and MCS in a Martian GCM.
2010 AGU Fall Meeting, San Francisco, Abstract P53E-1563.

Davis, C., W. Wang, J. Dudhia and R. Torn, 2010
Does increased horizontal resolution improve hurricane wind forecasts?
Weather and Forecasting, 25, 1826-1841, doi:10.1175/2010WAF2222423.1

Davis, C., W. Wang, S. Cavallo, J. Done, J. Dudhia, S. Fredrick, J. Michalakes, G. Caldwell, T. Engel and R. Torn, 2010
High-resolution hurricane forecasts.
Computing in Science and Engineering, 13, 22-30, doi:10.1109/MCSE.2010.74

Dowell, D., G. Romine and C. Snyder, 2010
Ensemble storm-scale data assimilation and prediction for severe convective storms.
25th Severe Local Storms Conference  Denver, Colorado, Amer. Meteor. Soc., paper 9.5.

Otkin, J.A., 2010
Clear and cloudy-sky infrared brightness temperature assimilation using an ensemble Kalman filter.
Journal of Geophysical Research, 115,D19207, 14pp, doi:10.1029/2009JD013759

Torn, R. D., 2010
Ensemble-based Sensitivity Analysis applied to African Easterly Waves.
Weather and Forecasting, 25, 61-78, doi:10.1029/2008JD011375

Torn, R. D., 2010
Performance of a Mesoscale Ensemble Kalman Filter (EnKF) During the NOAA High-Resolution Hurricane Test.
Monthly Weather Review, 138, 4375-4392, doi:10.1175/2010MWR3361.1

Rostkier-Edelstein, D. and J. Hacker, 2010
The roles of surface-observation ensemble assimilation and model complexity for nowcasting of PBL profiles: A factor separation analysis.
Weather and Forecasting, 25, 1670-1690, doi:10.1175/2010WAF2222435.1

Zagar, N., J. Tribbia, J. L. Anderson, K. Raeder and D. T. Kleist, 2010
Diagnosis of systematic analysis increments by using normal modes.
Quarterly Journal of the Royal Meteorological Society, 136, 61-76, doi:10.1002/qj.533

2009

Anderson, J. L., T. Hoar, K. Raeder, H. Liu, N. Collins, R. Torn and A. Arellano, 2009
The Data Assimilation Research Testbed: A Community Facility.
Bulletin of the American Meteorological Society, 90, 1283-1296, doi:10.1175/2009BAMS2618.1

Anderson, J. L., 2009
Spatially and temporally varying adaptive covariance inflation for ensemble filters.
Tellus A, 61, 72-83, doi:10.1111/j.1600-0870.2008.00361.x

Anderson, J. L., 2009
Ensemble Kalman filters for large geophysical applications.
IEEE Control Systems Magazine, 29, 66-82, doi:10.1109/MCS.2009.932222

Aksoy, A., D. C. Dowell and C. Snyder, 2009
A Multicase Comparative Assessment of the Ensemble Kalman Filter for Assimilation of Radar Observations. Part I: Storm-Scale Analyses.
Monthly Weather Review, 137, 1805-1824, doi:10.1175/2008MWR2691.1

Edwards, D. P., A. F. Arellano and M. N. Deeter, 2009
A satellite observation system simulation experiment for carbon monoxide in the lowermost troposphere,
J. Geophys. Res. 114, D14304, doi:10.1029/2008JD011375

Hamill, T. M., J. S. Whitaker, J. L. Anderson and C. M. Snyder, 2009
Comments on “Sigma-Point Kalman filter data assimilation methods for strongly nonlinear systems”.
Journal of the Atmospheric Sciences, 66, 3498-3500, doi:10.1175/2009JAS3245.1

Rostkier-Edelstein, D. and J. P. Hacker, 2009
Probabilistic nowcasting of PBL profiles with surface observations and an ensemble filter.
The 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction , Omaha, NE, USA 
extended abstract

Thomas, S. J., J. P. Hacker, and J. L. Anderson, 2011
A robust formulation of the ensemble Kalman filter.
Quarterly Journal of the Royal Meteorological Society, 135, 507-521, doi:10.1002/qj.372

Zagar, N., J. Tribbia, J. L. Anderson, K. Raeder, 2009
Uncertainties of estimates of inertia-gravity energy in the atmosphere. Part I: Intercomparison of four analysis systems
Monthly Weather Review, 137, 3837-3857, doi:10.1175/2009MWR2815.1

Zagar, N., J. Tribbia, J. L. Anderson and K. Raeder, 2009
Uncertainties of estimates of inertia-gravity energy in the atmosphere. Part II: Large-scale equatorial waves.
Monthly Weather Review, 137, 3858-3873, doi:10.1175/2009MWR2816.1

2008

Anthes, R. A., P. A. Bernhardt, Y. Chen, L. Cucurull, K. F. Dymond, D. Ector, S. Healy, S.-P. Ho, D. C. Hunt, Y.-H. Kuo, H. Liu, K. Manning, C. McCormick, T. K. Meehan, W. J. Randel, C. Rocken, W. Schreiner, S. V. Sokolovskiy, S. Syndergaard, D. C. Thompson, K. E. Trenberth, T.-K. Wee, N. L. Yen and Z. Zeng,
The COSMIC/FORMOSAT-3 Mission: Early Results,
Bulletin of the American Meteorological Society, 89 No. 3, 313-333, doi:10.1175/BAMS-89-3-313

Snyder, C., T. Bengtsson, P. Bickel and J. L. Anderson, 2008 Obstacles to high-dimensional particle filtering. Monthly Weather Review, 136, 4629-4640, doi:10.1175/2008MWR2529.1

Zubrow, A., L. Chen and V. R. Kotamarthi, 2008
EAKF-CMAQ: Introduction and evaluation of a data assimilation for CMAQ based on the ensemble adjustment Kalman filter,
J. Geophys. Res., 113, D09302, doi:10.1029/2007JD009267

Liu H., J. L. Anderson, Y.-H. Kuo, C. Snyder and A. Caya, 2008
Evaluation of a non-local observation operator in assimilation of CHAMP radio occultation refractivity with WRF.
Monthly Weather Review, 136 No.1, 242-256, doi:10.1175/2007MWR2042.1

Khare, S. P., J. L. Anderson, T. J. Hoar and D. W. Nychka, 2008
An investigation into the application of an ensemble Kalman smoother to high-dimensional geophysical systems.
Tellus Series A-dynamic Meteorology and Oceanography, 60, 97-112, doi:10.1111/j.1600-0870.2007.00281.x

Torn, R. D. and G. J. Hakim, 2008
Ensemble-based sensitivity analysis.
Monthly Weather Review, 136, 663-677, doi:10.1175/2007MWR2132.1

2007

Anderson, J. L., 2007
An adaptive covariance inflation error correction algorithm for ensemble filters.
Tellus A, 59, 210-224, doi:10.1111/j.1600-0870.2006.00216.x

Anderson, J. L., 2007
Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter.
Physica D, 230, 99-111, doi:10.1016/j.physd.2006.02.011

Anderson, J. and N. Collins, 2007
Scalable Implementations of Ensemble Filter Algorithms for Data Assimilation.
Journal of Atmospheric and Oceanic Technology, 24, 1452-1463, doi:10.1175/JTECH2049.1

Arellano, A. F., K. Raeder, J. L. Anderson, P. Hess, L. K. Emmons, D. P. Edwards, G. G. Pfister, T. L. Campos and G. W. Sachse: 2007
Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission,
Atmos. Chem. Phys., 7, 5695-5710, doi:10.5194/acp-7-5695-2007

Arellano, A. F., P. Hess, D. Edwards, J. L. Anderson, K. Raeder, L. K. Emmons, G. G. Pfister, T. L. Campos, G. Diskin, J. Jimenez and R. Subramanian, 2007
Chemical Data Assimilation of MOPITT CO and MODIS AOD Retrievals in the Community Atmosphere Model.
Eos. Trans. AGU, 88(52), Fall Meet. Suppl., Abstract A14D-03.

Edwards, D., A. Arellano and M. Deeter, 2007
Defining Requirements for Future Satellite Air Quality Chemistry Observations.
Eos. Trans. AGU, 88(52), Fall Meet. Suppl., Abstract A54C-01.

Lawson, W. G., M. I. Richardson, D. J. McCleese, J. T. Schofield, O. Aharonson, S. B. Calcutt, P. G. J. Irwin, D. M. Kass, C. B. Leovy, S.R. Lewis, D. A. Paige, P. L. Read, F. W. Taylor and R. W. Zurek, 2007
Adapting State of the Art Data Assimilation Approaches for Use with the Mars Climate Sounder and the PlanetWRF Martian GCM.
Seventh International Conference on Mars, Pasadena, Californa,
LPI Contribution No. 1353, p 3321.

Lawson, W. G., M. I. Richardson, D. J. McCleese, J. L. Anderson, Y. Chen and C. Snyder, 2007
Ensemble-Based Data Assimilation with a Martian GCM
Eos Trans. AGU, 88(52), Fall Meeting Suppl., Abstract P11A-0251.

Hacker, J. P., J. L. Anderson and M. Pagowski, 2007
Improved vertical covariance estimates for ensemble filter assimilation of near-surface observations.
Monthly Weather Review, 135, 1021-1036, doi:10.1175/MWR3333.1

Hacker, J. P. and D. Rostkier-Edelstein, 2007
PBL state estimation with surface observations, a column model, and an ensemble filter.
Monthly Weather Review, 135, Issue 8, 2958-2972, doi:10.1175/MWR3443.1

Karspeck, A. and J. L. Anderson, 2007
Experimental implementation of an ensemble adjustment filter for an intermediate ENSO model. Journal of Climate, 20 4638-4658, doi:10.1175/JCLI4245.1

2006

Aksoy, A., F. Zhang and J. W. Nielsen-Gammon, 2006
Ensemble-based simultaneous state and parameter estimation with MM5.
Geophysical Research Letters, 33, L12801

Aksoy, A., F. Zhang and J. W. Nielsen-Gammon, 2006
Ensemble-based simultaneous state and parameter estimation in a two-dimensional sea breeze model.
Monthly Weather Review, 134, 2951-2970, doi:10.1175/MWR3224.1

Chen, Y. and C. Snyder, 2006
Assimilation of hurricane position with an ensemble Kalman Filter.
Geophysical Research Abstracts, 8, 09910

D. Rostkier-Edelstein, J. Hacker and M. Pagowski, 2006
Estimates of boundary layer profiles by means of ensemble-filter assimilation of near surface observations in a parameterized PBL.
Proceedings of the 17th Symposium on Boundary Layers and Turbulence AMS, San Diego, 16-22 May 2006.

W. G. Lawson, M. I. Richardson, D. J. McCleese, J. T. Schofield, O. Aharonson, S. B. Calcutt, P. G. J. Irwin, D. M. Kass, C. B. Leovy, S.R. Lewis, D. A. Paige, P. L. Read, F. W. Taylor and R. W. Zurek 2006
Data Assimilation With the Mars Climate Sounder
2006 Fall AGU Meeting, abstract P23B-0061

J. Hacker, M. Pagowski and D. Rostkier-Edelstein, 2006
Parameter estimation in land-surface model using atmospheric data assimilation: finding distributions for use in an ensemble prediction system.
Proceedings of the 17th Symposium on Boundary Layers and Turbulence, AMS, San Diego, 16-22 May 2006.

2005

Anderson, J. L., B. Wyman, S. Zhang and T. Hoar, 2005
Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system.
Journal of the Atmospheric Sciences, 62, 2925-2938, doi:10.1175/JAS3510.1

BD … Before DART

Zhang, F., C. Snyder and J. Sun, 2004
Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter.
Monthly Weather Review, 132, 1238-1253.

Bengtsson, T., C. Snyder and D. Nychka, 2003
A nonlinear filter that extends to high dimensional systems.
Journal of Geophysical Research-Atmosphere, 108, 1-10

Tribbia, J. J. and D. P. Baumhefner, 2004
Scale interactions and atmospheric predictablility: An updated perspective.
Monthly Weather Review, 132, 703-713.

Anderson, J. L., 2003
A local least squares framework for ensemble filtering.
Monthly Weather Review, 131, 634-642, doi:10.1175/1520-0493(2003)131<0634:ALLSFF>2.0.CO;2

Tippett, M. K., J. L. Anderson,
C. H. Bishop, T. M. Hamill and J. S. Whitaker, 2003
Ensemble square root filters.
Monthly Weather Review, 131, 1485-1490.

Zhang, S. and J. L. Anderson, 2003
Impact of spatially and temporally varying estimates of error
covariance on assimilation in a simple atmospheric model.
Tellus, 55A, 126-147.

Snyder, C. and F. Zhang, 2003
Assimilation of simulated Doppler radar observations with an ensemble Kalman filter
Monthly Weather Review, 131, 1663-16776.

Anderson, J. L., 2001
An Ensemble Adjustment Kalman Filter for Data Assimilation.
Monthly Weather Review, 129, 2884-2903, doi:10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2