Istvan Szunyogh
Affiliations: | Atmospheric and Oceanic Sciences | University of Maryland, College Park, College Park, MD |
Area:
Atmospheric Sciences, Atmospheric Chemistry, Remote SensingGoogle:
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Publications
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| Wikner A, Pathak J, Hunt B, et al. (2020) Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems. Chaos (Woodbury, N.Y.). 30: 053111 |
| Žagar N, Szunyogh I. (2020) Comments on “What Is the Predictability Limit of Midlatitude Weather?” Journal of the Atmospheric Sciences. 77: 781-785 |
| Arcomano T, Szunyogh I, Pathak J, et al. (2020) A Machine Learning‐Based Global Atmospheric Forecast Model Geophysical Research Letters. 47 |
| Jia Y, Chang P, Szunyogh I, et al. (2019) A Modeling Strategy for the Investigation of the Effect of Mesoscale SST Variability on Atmospheric Dynamics Geophysical Research Letters. 46: 3982-3989 |
| Herrera MA, Szunyogh I, Brainard A, et al. (2018) Regionally Enhanced Global (REG) 4D-Var Monthly Weather Review. 146: 4015-4038 |
| 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: 1303-1318 |
| Battalio M, Szunyogh I, Lemmon M. (2018) Wave energetics of the southern hemisphere of Mars Icarus. 309: 220-240 |
| Battalio M, Szunyogh I, Lemmon M. (2018) Corrigendum to “Energetics of the Martian Atmosphere Using the Mars Analysis Correction Data Assimilation (MACDA) Dataset” [Icarus 276 (2016) 1--20] Icarus. 302: 565-567 |
| Loeser CF, Herrera MA, Szunyogh I. (2017) An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty Weather and Forecasting. 32: 149-164 |
| Parsons DB, Beland M, Burridge D, et al. (2017) THORPEX Research and the Science of Prediction Bulletin of the American Meteorological Society. 98: 807-830 |