HR job title
- Professor
- Contact Info
Szunyogh, Istvan Professor
Positions
- Professor, Atmospheric Sciences, College of Arts and Sciences
- Overview
- Publications
- Research
- Teaching
- Works By Students
- Background
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Overview
Publications
selected publications
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academic article
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Arcomano, T., Szunyogh, I., Wikner, A., Hunt, B. R., & Ott, E.
(2023).
A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics-Based Component. Geophysical Research Letters.
50(8),
-
Brotzge, J. A., Berchoff, D., Carlis, D. L., Carr, F. H., Carr, R. H., Gerth, J. J., ... Wang, X.
(2023).
Challenges and Opportunities in Numerical Weather Prediction. Bulletin of the American Meteorological Society.
104(3), E698-E705.
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Arcomano, T., Szunyogh, I., Wikner, A., Pathak, J., Hunt, B. R., & Ott, E.
(2022).
A Hybrid Approach to Atmospheric Modeling That Combines Machine Learning With a Physics-Based Numerical Model. 14(3),
-
Szunyogh, I., Forinash, E., Gyarmati, G., Jia, Y., Chang, P., & Saravanan, R.
(2021).
Evaluation of a Coupled Modeling Approach for the Investigation of the Effects of SST Mesoscale Variability on the Atmosphere. Journal of Advances in Modeling Earth Systems.
13(9),
-
Wikner, A., Pathak, J., Hunt, B. R., Szunyogh, I., Girvan, M., & Ott, E.
(2021).
Using data assimilation to train a hybrid forecast system that combines machine-learning and knowledge-based components. Chaos: an interdisciplinary journal of nonlinear science.
31(5), 053114-053114.
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Szunyogh, I., Arcomano, T., Pathak, J., Wikner, A., Hunt, B., & Ott, E.
(2020).
A Machine Learning-Based Global Atmospheric Forecast Model. Geophysical Research Letters.
47(9),
-
Wikner, A., Pathak, J., Hunt, B., Girvan, M., Arcomano, T., Szunyogh, I., Pomerance, A., & Ott, E.
(2020).
Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems. Chaos: an interdisciplinary journal of nonlinear science.
30(5), 053111-053111.
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Zagar, N., & Szunyogh, I.
(2020).
Comments on "What Is the Predictability Limit of Midlatitude Weather?". Journal of the Atmospheric Sciences.
77(2), 781-785.
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Jia, Y., Chang, P., Szunyogh, I., Saravanan, R., & Bacmeister, J. T.
(2019).
A Modeling Strategy for the Investigation of the Effect of Mesoscale SST Variability on Atmospheric Dynamics. Geophysical Research Letters.
46(7), 3982-3989.
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Herrera, M. A., Szunyogh, I., Brainard, A., Kuhl, D. D., Hoppel, K., Bishop, C. H., ... Rainwater, S.
(2018).
Regionally Enhanced Global (REG) 4D-Var. MONTHLY WEATHER REVIEW.
146(12), 4015-4038.
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Battalio, M., Szunyogh, I., & Lemmon, M.
(2018).
Wave energetics of the southern hemisphere of Mars. Icarus.
309, 220-240.
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Han, F., & Szunyogh, I.
(2018).
A Technique for the Verification of Precipitation Forecasts and Its Application to a Problem of Predictability. MONTHLY WEATHER REVIEW.
146(5), 1303-1318.
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Battalio, M., Szunyogh, I., & Lemmon, M.
(2018).
Energetics of the Martian Atmosphere Using the Mars Analysis Correction Data Assimilation (MACDA) Dataset (vol 276, pg 1, 2016). Icarus.
302, 565-567.
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Han, F., & Szunyogh, I.
(2018).
How well can an ensemble predict the uncertainty in the location of winter storm precipitation?. 70(1), 1440870-1440870.
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Parsons, D. B., Beland, M., Burridge, D., Bougeault, P., Brunet, G., Caughey, J., ... Toth, Z.
(2017).
THORPEX RESEARCH AND THE SCIENCE OF PREDICTION. Bulletin of the American Meteorological Society.
98(4), 807-830.
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Loeser, C. F., Herrera, M. A., & Szunyogh, I.
(2017).
An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty. Weather and Forecasting.
32(1), 149-164.
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Khade, V., Kurian, J., Changa, P., Szunyogh, I., Thyng, K., & Montuoro, R.
(2017).
Oceanic ensemble forecasting in the Gulf of Mexico: An application to the case of the Deep Water Horizon oil spill. Ocean Modelling.
113, 171-184.
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Battalio, M., Szunyogh, I., & Lemmon, M.
(2016).
Energetics of the martian atmosphere using the Mars Analysis Correction Data Assimilation (MACDA) dataset. Icarus.
276, 1-20.
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Herrera, M. A., Szunyogh, I., & Tribbia, J.
(2016).
Forecast Uncertainty Dynamics in the THORPEX Interactive Grand Global Ensemble (TIGGE). MONTHLY WEATHER REVIEW.
144(7), 2739-2766.
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Han, F., & Szunyogh, I.
(2016).
A Morphing-Based Technique for the Verification of Precipitation Forecasts. MONTHLY WEATHER REVIEW.
144(1), 295-313.
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Roh, S., Jun, M., Szunyogh, I., & Genton, M. G.
(2015).
Multivariate localization methods for ensemble Kalman filtering. Nonlinear Processes in Geophysics.
22(6), 723-735.
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Holt, C., Szunyogh, I., Gyarmati, G., Leidner, S. M., & Hoffman, R. N.
(2015).
Assimilation of Tropical Cyclone Observations: Improving the Assimilation of TCVitals, Scatterometer Winds, and Dropwindsonde Observations. MONTHLY WEATHER REVIEW.
143(10), 3956-3980.
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Roh, S., Jun, M., Szunyogh, I., & Genton, M. G.
(2015).
Multivariate localization methods for ensemble Kalman filtering. 2(3), 833-863.
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Kretschmer, M., Hunt, B. R., Ott, E., Bishop, C. H., Rainwater, S., & Szunyogh, I.
(2015).
A composite state method for ensemble data assimilation with multiple limited-area models. 67(0), 26495-26495.
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Roh, S., Genton, M. G., Jun, M., Szunyogh, I., & Hoteit, I.
(2013).
Observation Quality Control with a Robust Ensemble Kalman Filter. MONTHLY WEATHER REVIEW.
141(12), 4414-4428.
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Kavulich, M., Szunyogh, I., Gyarmati, G., & Wilson, R. J.
(2013).
Local Dynamics of Baroclinic Waves in the Martian Atmosphere. Journal of the Atmospheric Sciences.
70(11), 3415-3447.
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Szunyogh, I.
(2013).
Coupled Global-Regional Data Assimilation Using Joint States
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Holt, C. R., Szunyogh, I., & Gyarmati, G.
(2013).
Can a Moderate-Resolution Limited-Area Data Assimilation System Add Value to the Global Analysis of Tropical Cyclones?. MONTHLY WEATHER REVIEW.
141(6), 1866-1883.
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Yoon, Y., Hunt, B. R., Ott, E., & Szunyogh, I.
(2012).
Simultaneous global and limited-area ensemble data assimilation using joint states. Tellus Series A: Dynamic Meteorology and Oceanography.
64(0), 18407-18407.
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Szunyogh, I.
(2012).
Coupled Global-Regional Data Assimilation Using Joint States
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Szunyogh, I.
(2012).
Tropical Cyclone Ensemble Data Assimilation
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Jun, M., Szunyogh, I., Genton, M. G., Zhang, F., & Bishop, C. H.
(2011).
A Statistical Investigation of the Sensitivity of Ensemble-Based Kalman Filters to Covariance Filtering. MONTHLY WEATHER REVIEW.
139(9), 3036-3051.
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Szunyogh, I.
(2011).
Tropical Cyclone Ensemble Data Assimilation
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Merkova, D., Szunyogh, I., & Ott, E.
(2011).
Strategies for coupling global and limited-area ensemble Kalman filter assimilation. Nonlinear Processes in Geophysics.
18(3), 415-430.
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Aravequia, J. A., Szunyogh, I., Fertig, E. J., Kalnay, E., Kuhl, D., & Kostelich, E. J.
(2011).
Evaluation of a Strategy for the Assimilation of Satellite Radiance Observations with the Local Ensemble Transform Kalman Filter. MONTHLY WEATHER REVIEW.
139(6), 1932-1951.
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Satterfield, E., & Szunyogh, I.
(2011).
Assessing the Performance of an Ensemble Forecast System in Predicting the Magnitude and the Spectrum of Analysis and Forecast Uncertainties. MONTHLY WEATHER REVIEW.
139(4), 1207-1223.
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Li, H., Liu, J., Fertig, E., Kalnay, E., Kostelich, E., & Szunyogh, I.
(2011).
IMPROVED ANALYSES AND FORECASTS WITH AIRS TEMPERATURE RETRIEVALS USING THE LOCAL ENSEMBLE TRANSFORM KALMAN FILTER. Journal of Tropical Meteorology.
17(1), 43-49.
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Yoon, Y., Ott, E., & Szunyogh, I.
(2010).
On the Propagation of Information and the Use of Localization in Ensemble Kalman Filtering. Journal of the Atmospheric Sciences.
67(12), 3823-3834.
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Hoffman, M. J., Greybush, S. J., Wilson, R. J., Gyarmati, G., Hoffman, R. N., Kalnay, E., ... Szunyogh, I.
(2010).
An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments. Icarus.
209(2), 470-481.
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Szunyogh, I.
(2010).
Tropical Cyclone Ensemble Data Assimilation
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Satterfield, E., & Szunyogh, I.
(2010).
Predictability of the Performance of an Ensemble Forecast System: Predictability of the Space of Uncertainties. MONTHLY WEATHER REVIEW.
138(3), 962-981.
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Liu, J., Li, H., Kalnay, E., Kostelich, E. J., & Szunyogh, I.
(2009).
Univariate and Multivariate Assimilation of AIRS Humidity Retrievals with the Local Ensemble Transform Kalman Filter. MONTHLY WEATHER REVIEW.
137(11), 3918-3932.
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Baek, S., Szunyogh, I., Hunt, B. R., & Ott, E.
(2009).
Correcting for Surface Pressure Background Bias in Ensemble-Based Analyses. MONTHLY WEATHER REVIEW.
137(7), 2349-2364.
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Fertig, E. J., Baek, S., Hunt, B. R., Ott, E., Szunyogh, I., Aravequia, J. A., ... Liu, J.
(2009).
Observation bias correction with an ensemble Kalman filter. Tellus Series A: Dynamic Meteorology and Oceanography.
61(2), 210-226.
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Fertig, E. J., Baek, S., Hunt, B. R., Ott, E., Szunyogh, I., Aravquia, J. A., ... Liu, J.
(2009).
Observation bias correction with an ensemble Kalman filter. Tellus Series A: Dynamic Meteorology and Oceanography.
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Sellwood, K. J., Majumdar, S. J., Mapes, B. E., & Szunyogh, I.
(2008).
Predicting the influence of observations on medium-range forecasts of atmospheric flow. Quarterly Journal of the Royal Meteorological Society.
134(637), 2011-2027.
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Hoffman, R. N., Ponte, R. M., Kostelich, E. J., Blumberg, A., Szunyogh, I., Vinogradov, S. V., & Henderson, J. M.
(2008).
A simulation study using a local ensemble transform Kalman filter for data assimilation in New York Harbor. Journal of Atmospheric and Oceanic Technology.
25(9), 1638-1656.
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Liu, J., Fertig, E. J., Li, H., Kalnay, E., Hunt, B. R., Kostelich, E. J., Szunyogh, I., & Todling, R.
(2008).
Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM - perfect model experiments. Nonlinear Processes in Geophysics.
15(4), 645-659.
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Szunyogh, I., Kostelich, E. J., Gyarmati, G., Kalnay, E., Hunt, B. R., Ott, E., Satterfield, E., & Yorke, J. A.
(2008).
A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus Series A: Dynamic Meteorology and Oceanography.
60(1), 113-130.
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Szunyogh, I., Kostelich, E. J., Gyarmati, G., Kalnay, E., Hunt, B. R., Ott, E., Satterfield, E., & Yorke, J. A.
(2008).
A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus Series A: Dynamic Meteorology and Oceanography.
-
Fertig, E. J., Hunt, B. R., Ott, E., & Szunyogh, I.
(2007).
Assimilating non-local observations with a local ensemble Kalman filter. Tellus Series A: Dynamic Meteorology and Oceanography.
59(5), 719-730.
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Hunt, B. R., Kostelich, E. J., & Szunyogh, I.
(2007).
Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D: Nonlinear Phenomena.
230(1-2), 112-126.
-
Kuhl, D., Szunyogh, I., Kostelich, E. J., Gyarmati, G., Patil, D. J., Oczkowski, M., ... Yorke, J. A.
(2007).
Assessing predictability with a local ensemble Kalman filter. Journal of the Atmospheric Sciences.
64(4), 1116-1140.
-
Baek, S. J., Hunt, B. R., Kalnay, E., Ott, E., & Szunyogh, I.
(2006).
Local ensemble Kalman filtering in the presence of model bias. Tellus Series A: Dynamic Meteorology and Oceanography.
58(3), 293-306.
-
Baek, S., Hunt, B. R., Kalnay, E., Ott, E., & Szunyogh, I.
(2006).
Local ensemble Kalman filtering in the presence of model bias. Tellus Series A: Dynamic Meteorology and Oceanography.
-
Zimin, A. V., Szunyogh, I., Hunt, B. R., & Ott, E.
(2006).
Extracting envelopes of nonzonally propagating Rossby wave packets. MONTHLY WEATHER REVIEW.
134(4), 1329-1333.
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Szunyogh, I., Kostelich, E. J., Gyarmati, G., Patil, D. J., Hunt, B. R., Kalnay, E., Ott, E., & Yorke, J. A.
(2005).
Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model. Tellus Series A: Dynamic Meteorology and Oceanography.
57(4), 528-545.
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Oczkowski, M., Szunyogh, I., & Patil, D. J.
(2005).
Mechanisms for the development of locally low-dimensional atmospheric dynamics. Journal of the Atmospheric Sciences.
62(4), 1135-1156.
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Szunyogh, I., Kostelich, E. J., Gyarmati, G., Patil, D. J., Hunt, B. R., Kalnay, E., Ott, E., & Yorke, J. A.
(2005).
Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model. Tellus Series A: Dynamic Meteorology and Oceanography.
57(4), 528-528.
-
Baek, S., Hunt, B. R., Szunyogh, I., Zimin, A., & Ott, E.
(2004).
Localized error bursts in estimating the state of spatiotemporal chaos. Chaos: an interdisciplinary journal of nonlinear science.
14(4), 1042-1049.
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Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E. J., Corazza, M., ... Yorke, J. A.
(2004).
A local ensemble Kalman filter for atmospheric data assimilation. Tellus Series A: Dynamic Meteorology and Oceanography.
56(5), 415-428.
-
Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E. J., Corazza, M., ... Yorke, J. A.
(2004).
Estimating the state of large spatio-temporally chaotic systems. Physics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics.
330(5), 365-370.
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Hunt, B. R., Kalnay, E., Kostelich, E. J., Ott, E., Patil, D. J., Sauer, T., ... Zimin, A. V.
(2004).
Four-dimensional ensemble Kalman filtering. Tellus Series A: Dynamic Meteorology and Oceanography.
56(4), 273-277.
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Hunt, B. R., Kalnay, E., Kostelich, E. J., Ott, E., Patil, D. J., Sauer, T., ... Zimin, A. V.
(2004).
Four-dimensional ensemble Kalman filtering. Tellus Series A: Dynamic Meteorology and Oceanography.
56(4), 273-273.
-
Zimin, A. V., Szunyogh, I., Patil, D. J., Hunt, B. R., & Ott, E.
(2003).
Extracting envelopes of Rossby wave packets. MONTHLY WEATHER REVIEW.
131(5), 1011-1017.
-
Zimin, A. V., Szunyogh, I., Patil, D. J., Hunt, B. R., & Ott, E.
(2003).
Extracting envelopes of Rossby wave packets. MONTHLY WEATHER REVIEW.
131(5), 1011-1017.
-
Gyarmati, G., Szunyogh, I., & Patil, D. J.
(2003).
Local predictability in a simple model of atmospheric balance. Nonlinear Processes in Geophysics.
10(3), 183-196.
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Corazza, M., Kalnay, E., Patil, D. J., Yang, S. C., Morss, R., Cai, M., ... Yorke, J. A.
(2003).
Use of the breeding technique to estimate the structure of the analysis "errors of the day". Nonlinear Processes in Geophysics.
10(3), 233-243.
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Szunyogh, I., Toth, Z., Zimin, A. V., Majumdar, S. J., & Persson, A.
(2002).
Propagation of the effect of targeted observations: The 2000 Winter Storm Reconnaissance program. MONTHLY WEATHER REVIEW.
130(5), 1144-1165.
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Szunyogh, I., & Toth, Z.
(2002).
The effect of increased horizontal resolution on the NCEP global ensemble mean forecasts. MONTHLY WEATHER REVIEW.
130(5), 1125-1143.
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Majumdar, S. J., Bishop, C. H., Etherton, B. J., Szunyogh, I., & Toth, Z.
(2001).
Can an ensemble transform Kalman filter predict the reduction in forecast-error variance produced by targeted observations?. Quarterly Journal of the Royal Meteorological Society.
127(578), 2803-2820.
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Szunyogh, I., Toth, Z., Morss, R. E., Majumdar, S. J., Etherton, B. J., & Bishop, C. H.
(2000).
The effect of targeted dropsonde observations during the 1999 winter storm reconnaissance program. MONTHLY WEATHER REVIEW.
128(10), 3520-3537.
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Szunyogh, I., Toth, Z., Emanuel, K. A., Bishop, C. H., Snyder, C., Morss, R. E., Woolen, J., & Marchok, T.
(1999).
Ensemble-based targeting experiments during FASTEX: The effect of dropsonde data from the Lear jet. 125(561), 3189-3217.
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Langland, R. H., Toth, Z., Gelaro, R., Szunyogh, I., Shapiro, M. A., Majumdar, S. J., ... Bishop, C. H.
(1999).
The North Pacific Experiment (NORPEX-98): Targeted observations for improved North American weather forecasts. Bulletin of the American Meteorological Society.
80(7), 1363-1384.
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Toth, Z., Szunyogh, I., Kalnay, E., & Iyengar, G.
(1999).
Comments on: "Notes on the appropriateness of 'bred modes' for generating initial perturbations". Tellus Series A: Dynamic Meteorology and Oceanography.
51(3), 442-449.
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Pu, Z. X., Kalnay, E., Sela, J., & Szunyogh, I.
(1997).
Sensitivity of forecast errors to initial conditions with a quasi-inverse linear method. MONTHLY WEATHER REVIEW.
125(10), 2479-2503.
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McLachlan, R. I., Szunyogh, I., & Zeitlin, V.
(1997).
Hamiltonian finite-dimensional models of baroclinic instability. Physics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics.
229(5), 299-305.
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Szunyogh, I., Kalnay, E., & Toth, Z.
(1997).
A comparison of Lyapunov and optimal vectors in a low-resolution GCM. Tellus Series A: Dynamic Meteorology and Oceanography.
49(2), 200-227.
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SZUNYOGH, I.
(1993).
FINITE-DIMENSIONAL QUASI-HAMILTONIAN STRUCTURE IN SIMPLE-MODEL EQUATIONS. Meteorology and Atmospheric Physics.
52(1-2), 49-57.
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Arcomano, T., Szunyogh, I., Wikner, A., Hunt, B. R., & Ott, E.
(2023).
A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics-Based Component. Geophysical Research Letters.
50(8),
-
book
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Szunyogh, I.
(2014).
Applicable Atmospheric Dynamics, Techniques for the Exploration of Atmospheric Dynamics. World Scientific Publishing.
-
Szunyogh, I.
(2014).
Applicable atmospheric dynamics: Techniques for the exploration of atmospheric dynamics. WORLD SCIENTIFIC.
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Szunyogh, I.
(2014).
Applicable Atmospheric Dynamics, Techniques for the Exploration of Atmospheric Dynamics. World Scientific Publishing.
-
chapter
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Kalnay, E., Hunt, B., Ott, E., & Szunyogh, I.
(2006).
Ensemble forecasting and data assimilation: two problems with the same solution?. PREDICTABILITY OF WEATHER AND CLIMATE.
(pp. 157-180).
Cambridge University Press (CUP).
-
Kalnay, E., Hunt, B., Ott, E., & Szunyogh, I.
(2006).
Ensemble forecasting and data assimilation: two problems with the same solution?. PREDICTABILITY OF WEATHER AND CLIMATE.
(pp. 157-180).
Cambridge University Press (CUP).
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conference paper
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Hoffman, R., Ponte, R. M., Kostelich, E., Blumberg, A., Szunyogh, I., & Vinogradov, S. V.
(2008).
ENSEMBLE DATA ASSIMILATION SIMULATION EXPERIMENTS FOR THE COASTAL OCEAN: IMPACT OF DIFFERENT OBSERVED VARIABLES. v-441-v-444-444.
-
Li, H., Liu, J., Fertig, E., Kalnay, E., Aravquia, J. A., Szunyogh, I., Kostelich, E. J., & Todling, R.
(2007).
Improved analyses and forecasts with airs retrievals using the local ensemble transform Kalman filter
-
Liu, J., Fertig, E., Li, H., Szunyogh, I., Hunt, B., Kalnay, E., Kostelich, E. J., & Todling, R.
(2006).
Application of local ensemble transform Kalman filter: Perfect model experiments with NASA FVGCM model
-
Sauer, T., Hunt, B. R., Yorke, J. A., Zimin, A. V., Ott, E., Kostelich, E. J., ... Patil, D. J.
(2004).
4D ensemble Kalman filtering for assimilation of asynchronous observations. Bulletin of the American Meteorological Society.
3075-3079.
-
Sauer, T., Hunt, B. R., Yorke, J. A., Zimin, A. V., Ott, E., Kostelichf, E. J., ... Patil, D. J.
(2004).
4D ensemble Kalman filtering for assimilation of asynchronous observations. Bulletin of the American Meteorological Society.
141-145.
-
Szunyogh, I., Kostelich, E. J., Gyarmati, G., Hunt, B. R., Ott, E., Zimin, A. V., ... Yorke, J. A.
(2004).
A local ensemble Kalman filter for the NCEP GFS model. Bulletin of the American Meteorological Society.
3001-3011.
-
Szunyogh, I., Kostelich, E. J., Gyarmati, G., Hunt, B. R., Ott, E., Zimin, A. V., ... Yorke, J. A.
(2004).
A local ensemble kalman filter for the NCEP GFS model. Bulletin of the American Meteorological Society.
67-77.
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Patil, D. J., Szunyogh, I., Zimin, A. V., Hunt, B. R., Ott, E., Kalnay, E., & Yorke, J. A.
(2003).
Local low dimensionality and relation to effects of targeted weather observations. AIP Conference Proceedings.
139-153.
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Toth, Z., Szunyogh, I., Bishop, C., Majumdar, S., Morss, R., Moskaitis, J., ... Lord, S.
(2002).
Adaptive observations at NCEP: Past, present, and future. 185-190.
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Szunyogh, I., Zimin, A. V., Patil, D. J., Hunt, B. R., Kalnay, E., Ott, E., & Yorke, J. A.
(2002).
On the dynamical basis of targeting weather observations. 197-202.
-
Corazza, M., Kalnay, E., Patil, D. J., Ott, E., Yorke, J. A., Hunt, B. R., Szunyogh, I., & Cai, M.
(2002).
Use of the breeding technique in the estimation of the background covariance matrix for a quasi-geostrophic model. 154-157.
-
Patil, D. J., Szunyogh, I., Hunt, B. R., Kalnay, E., Ott, E., & Yorke, J. A.
(2002).
Using large member ensembles to isolate local low dimensionality of atmospheric dynamics. 191-196.
-
Toth, Z., & Szunyogh, I.
(2001).
The use of targeted observations in operational numerical weather forecasting. 72-79.
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Toth, Z., Szunyogh, I., Majumdar, S., Morss, R., Etherton, B., Bishop, C., ... Pu, Z. X.
(2000).
Targeted observations at NCEP: Toward an operational implementation. 186-193.
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Bishop, C. H., Toth, Z., Szunyogh, I., & Majumdar, S.
(1998).
Ensemble transformation and adaptive observations. 517-519.
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Toth, Z., Szunyogh, I., Emanuel, K., Snyder, C., Woollen, J., Wu, W. S., ... Bishop, C.
(1998).
Ensemble-based targeted observations during FASTEX. 24-27.
-
Hoffman, R., Ponte, R. M., Kostelich, E., Blumberg, A., Szunyogh, I., & Vinogradov, S. V.
(2008).
ENSEMBLE DATA ASSIMILATION SIMULATION EXPERIMENTS FOR THE COASTAL OCEAN: IMPACT OF DIFFERENT OBSERVED VARIABLES. v-441-v-444-444.
-
institutional repository document
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Arcomano, T., Szunyogh, I., Wikner, A., Hunt, B. R., & Ott, E.
(2022).
A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics-Based Component
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Arcomano, T., Szunyogh, I., Wikner, A., Pathak, J., Hunt, B. R., & Ott, E.
(2021).
Hybrid Approach to Atmospheric Modeling that Combines Machine Learning with a Physics-Based Numerical Model
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Arcomano, T., Szunyogh, I., Wikner, A., Pathak, J., Hunt, B. R., & Edward, O.
(2021).
Hybrid Approach to Atmospheric Modeling that Combines Machine Learning with a Physics-Based Numerical Model
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Arcomano, T., Szunyogh, I., Wikner, A., Pathak, J., Hunt, B. R., & Edward, O.
(2021).
Hybrid Approach to Atmospheric Modeling that Combines Machine Learning with a Physics-Based Numerical Model
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Wikner, A., Pathak, J., Hunt, B. R., Szunyogh, I., Girvan, M., & Ott, E.
(2021).
Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components
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Szunyogh, I., Forinash, E., Gyarmati, G., Jia, Y., Chang, P., & Saravanan, R.
(2020).
Evaluation of a Coupled Modeling Approach for the Investigation of the Effects of SST Mesoscale Variability on the Atmosphere
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Szunyogh, I., Arcomano, T., Pathak, J., Wikner, A., Hunt, B., & Ott, E.
(2020).
A Machine-Learning-Based Global Atmospheric Forecast Model
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Szunyogh, I., Arcomano, T., Pathak, J., Wikner, A., Hunt, B., & Ott, E.
(2020).
A Machine-Learning-Based Global Atmospheric Forecast Model
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Wikner, A., Pathak, J., Hunt, B., Girvan, M., Arcomano, T., Szunyogh, I., Pomerance, A., & Ott, E.
(2020).
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems
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Yoon, Y., Hunt, B. R., Ott, E., & Szunyogh, I.
(2011).
Ensemble regional data assimilation using joint states
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Yoon, Y., Ott, E., & Szunyogh, I.
(2011).
On the propagation of information and the use of localization in ensemble Kalman filtering
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Liu, J., Fertig, E. J., Li, H., Kalnay, E., Hunt, B. R., Kostelich, E. J., Szunyogh, I., & Todling, R.
(2007).
Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM: perfect model experiments
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Hunt, B. R., Kostelich, E. J., & Szunyogh, I.
(2005).
Efficient Data Assimilation for Spatiotemporal Chaos: a Local Ensemble Transform Kalman Filter
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Ott, E., Hunt, B. R., Szunyogh, I., Zimin, A. V., Kostelich, E. J., Corazza, M., ... Yorke, J. A.
(2002).
A Local Ensemble Kalman Filter for Atmospheric Data Assimilation
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Arcomano, T., Szunyogh, I., Wikner, A., Hunt, B. R., & Ott, E.
(2022).
A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics-Based Component
Research
principal investigator on
- Regionally Enhanced Global (REG) Local Ensemble Transform Kalman Filter (LETKF) awarded by United States Department of the Navy - (Arlington, Virginia, United States) 2018 - 2021
- Investigation of the Effects of Oceanic Mesoscale Eddies on the Midlatitude Storm Tracks and Their Predictability awarded by National Oceanic and Atmospheric Administration - (Washington D.C., District of Columbia, United States) 2016 - 2020
- Coupled Global-Regional Data Assimilation with NAVDAS-AR awarded by United States Department of the Navy - (Arlington, Virginia, United States) 2016 - 2017
- Regionally Enhanced Global (REG) 4D-Var awarded by United States Department of the Navy - (Arlington, Virginia, United States) 2016 - 2017
- NSF: the Effect of Model Uncertainty and Erro On the Forecast Uncertainty awarded by National Science Foundation - (Arlington, Virginia, United States) 2012 - 2016
- Coupled Global-Regional Data Assimilation Using Joint States awarded by United States Department of the Navy - (Arlington, Virginia, United States) 2012 - 2015
Teaching
teaching activities
- ATMO201 Weather & Climate Instructor
- ATMO321 Comp App Atmos Science Instructor
- ATMO335 Atmospher Thermodynamics Instructor
- ATMO455 Numerical Wea Prediction Instructor
- ATMO484 Internship Instructor
- ATMO484 Internship Instructor
- ATMO491 Research Instructor
- ATMO602 Atmos Physics I Instructor
- ATMO681 Seminar Instructor
- ATMO685 Directed Studies Instructor
- ATMO689 Sptp: Numerical Weather Pred Instructor
- ATMO691 Research Instructor
- ATMO691 Research Instructor
Works By Students
chaired theses and dissertations
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Han, Fan (2014-11). A Morphing-based Approach for the Verification of Precipitation Forecasts.
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Herrera, Michael Aaron (2014-12). An Investigation of the Dynamics of Forecast Errors and Its Representation in the THORPEX Interactive Grand Global Ensemble (TIGGE).
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Holt, Christina (2012-10). Testing a Coupled Global-limited-area Data Assimilation System Using Observations from the 2004 Pacific Typhoon Season.
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Holt, Christina (2014-04). Tropical Cyclone Data Assimilation: Experiments with a Coupled Global-Limited-Area Analysis System.
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Kavulich, Michael J., Jr. (2011-10). Local Dynamics of Synoptic Waves in the Martian Atmosphere.
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Loeser, Carlee Frances (2016-07). An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty.
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Satterfield, Elizabeth A. (2011-10). Linear Diagnostics to Assess the Performance of an Ensemble Forecast System.
Background
education and training
- Ph.D. in Earth Sciences, Hungarian Academy of Sciences - (Budapest, Hungary) 1994
Contact
first name
- Istvan
has last name
- Szunyogh
mailing address
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Texas A&M University
Meteorology
3150 TAMU
College Station, TX 77843-3150
USA
Other
- szunyogh@tamu.edu