Publications

@article{10.1063/5.0295634,

title = {Accurate and robust real-time prediction of September Arctic sea ice},

author = {Dmitri Kondrashov and Ivan Sudakow and Valerie Livina and Qingping Yang},

url = {https://doi.org/10.1063/5.0295634},

doi = {10.1063/5.0295634},

issn = {1054-1500},

year  = {2026},

date = {2026-01-01},

journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},

volume = {36},

number = {2},

pages = {023110},

abstract = {We describe the real-time forecasting of September 2024 Arctic sea ice extent using a theory-guided machine learning method based on data-adaptive harmonic decomposition and frequency-based nonlinear stochastic modeling, as part of the Sea Ice Outlook. Compared to standard statistical and machine learning models, this method adeptly accounts for non-linear behavior, effectively incorporates memory effects, and handles a wide range of time scale variations, from synoptic (stochastic-like) weather effects to low-frequency (red-noise like) variability, significantly enhancing the accuracy and reliability of sea ice prediction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2026JA035068,

title = {Examining Chorus Wave Power and Electron Density During Multi-MeV Electron Flux Enhancement Events},

author = {A. A. Saikin and A. Y. Drozdov and A. N. Jaynes and Joshua Doucette and D. Kondrashov and A. Boyd and Y. Y. Shprits},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2026JA035068},

doi = {https://doi.org/10.1029/2026JA035068},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Geophysical Research: Space Physics},

volume = {131},

number = {6},

pages = {e2026JA035068},

abstract = {Abstract During the Van Allen Probes era, several multi-MeV electron flux enhancements were observed. The origin of those enhancements remains an active area of research. In this study, we examined the relationship between Phase Space Density (PSD) profiles—indicative of local acceleration or radial diffusion—chorus wave power, electron density, and the occurrence of electron enhancement events to determine the role each plays in electron acceleration. Growing peaks in PSD profiles were associated with local acceleration via wave–particle interactions, whereas monotonic profiles indicated radial diffusion; both mechanisms can accelerate electrons to such high energies. For each acceleration mechanism, we compared the estimated chorus wave power and the measured electron density. Chorus wave power was estimated as a proxy using POES (Polar Orbiting Environmental Satellites) observations of precipitating electron flux. The higher chorus wave power coincided with enhanced electron flux above 1 MeV, particularly for local acceleration events. On average, electron density during electron flux enhancement events decreased relative to that observed during non-acceleration events. Finally, using the VERB code, we tested how electron density influences electron flux acceleration, using chorus wave diffusion coefficients derived with modified electron density values.},

note = {e2026JA035068 2026JA035068},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2026SW005194,

title = {Recommendations for Advancing Heliophysics and Space Weather Modeling Through Open Science},

author = {M. A. Reiss and M. M. Kuznetsova and C. Corti and J. Yue and J. Karpen and C. N. Arge and F. Bacchini and C. Bard and S. Bruinsma and R. M. Caplan and L. K. S. Daldorff and P. J. Deka and C. R. DeVore and S. Elvidge and N. Ganushkina and J. D. Huba and B. V. Jackson and V. Jordanova and J. A. Linker and H. Liu and J. G. Luhmann and S. Markidis and P. Mayank and V. Merkin and N. Moens and D. Odstrcil and Y. A. Omelchenko and M. Palmroth and S. Poedts and A. J. Ridley and Y. Shou and V. Tenishev and D. R. Themens and G. Toth and W. Wang and R. -P. Wilhelm and M. A. Young and B. Cecconi and M. -Y. Chou and D. De Zeeuw and G. L. Delzanno and C. Didigu and M. El Alaoui and S. Fung and J. Green and Z. Huang and L. K. Jian and L. J. Landwer and M. Lesko and P. J. MacNeice and A. Masson and M. L. Mays and P. M. Mehta and M. S. Miesch and E. Palmerio and M. Petrenko and E. Provornikova and L. Rastätter and L. Rusaitis and N. Sachdeva and E. Samara and D. Sur and A. Taktakishvili and J. Topper and T. Tsui and C. Verbeke and J. Wang and C. Wiegand and M. Wiltberger and Y. Zheng and M. M. Bisi and M. K. Georgoulis and T. Kodikara and T. Pulkkinen and A. Chartier and D. Silva and A. Faturahman and K. Garcia-Sage and D. Kondrashov and V. E. Ledvina and W. Liu and C. Pandey and E. Resnick and C. Shi and R. S. Weigel and K. Whitman and I. Zakharenkova and K. Zhang},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2026SW005194},

doi = {https://doi.org/10.1029/2026SW005194},

year  = {2026},

date = {2026-01-01},

journal = {Space Weather},

volume = {24},

number = {6},

pages = {e2026SW005194},

abstract = {Abstract Numerical models are essential for advancing fundamental research in heliophysics and for operational forecasting of space weather events. Open science can accelerate progress, but applying an open science approach to numerical models requires careful consideration; models are not data analysis software and often demand substantial domain expertise, experience, and computational resources to be used correctly. This commentary distills the recommendations from Corti et al. (2026), https://doi.org/10.22541/essoar.176824639.92354528/v2 and proposes a pathway for advancing heliophysics and space weather modeling through open science. Rather than focusing on open science policies and practices, we recommend concrete actions to make models usable by the broader community (open use), increase confidence and transparency throughout the Research-to-Operations-to-Research (R2O2R) pipeline (open validation), enable collaborative model improvement (open development), and strengthen partnerships (open collaboration). Together, these recommendations address several of the open science challenges experienced by contributing authors in developing, validating, using, and hosting advanced models, as identified during the 2024 Open Science Workshop held at College Park, USA. The recommendations also highlight the importance of a culture of shared responsibility, adherence to best practices, and proper recognition of prior work. The Heliophysics Open Modeling Environment will serve as a platform for modelers and model users to work together, facilitate community modeling, and increase the scientific return on modeling investment.},

note = {e2026SW005194 2026SW005194},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2025SW004922,

title = {Advancing Heliophysics and Space Weather Modeling Through Open Science},

author = {C. Corti and M. M. Kuznetsova and M. A. Reiss and J. Yue and J. Karpen and C. N. Arge and F. Bacchini and C. Bard and S. Bruinsma and R. M. Caplan and L. K. S. Daldorff and P. J. Deka and C. R. DeVore and S. Elvidge and N. Ganushkina and J. D. Huba and B. V. Jackson and V. Jordanova and J. A. Linker and H. Liu and J. G. Luhmann and S. Markidis and P. Mayank and V. Merkin and N. Moens and D. Odstrcil and Y. A. Omelchenko and M. Palmroth and S. Poedts and A. J. Ridley and Y. Shou and V. Tenishev and D. R. Themens and G. Toth and W. Wang and R. -P. Wilhelm and M. A. Young and B. Cecconi and M. -Y. Chou and D. De Zeeuw and G. L. Delzanno and C. Didigu and M. El Alaoui and S. Fung and J. Green and Z. Huang and L. K. Jian and L. J. Landwer and M. Lesko and P. MacNeice and A. Masson and M. L. Mays and P. M. Mehta and M. S. Miesch and E. Palmerio and M. Petrenko and E. Provornikova and L. Rastätter and L. Rusaitis and N. Sachdeva and E. Samara and D. Sur and A. Taktakishvili and J. Topper and T. Tsui and C. Verbeke and J. Wang and C. Wiegand and M. Wiltberger and Y. Zheng and M. M. Bisi and M. K. Georgoulis and T. Kodikara and T. Pulkkinen and A. Chartier and D. Silva and A. Faturahman and K. Garcia-Sage and D. Kondrashov and V. E. Ledvina and W. Liu and C. Pandey and E. Resnick and C. Shi and R. S. Weigel and K. Whitman and I. Zakharenkova and K. Zhang},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025SW004922},

doi = {https://doi.org/10.1029/2025SW004922},

year  = {2026},

date = {2026-01-01},

journal = {Space Weather},

volume = {24},

number = {6},

pages = {e2025SW004922},

abstract = {Abstract We present a community-wide effort to develop a strategy and action plan to advance heliophysics and space weather modeling through open science. While open science has the potential to enhance the quality and pace of scientific discovery, its application to scientific modeling requires more careful consideration regarding open data and open software guidelines, as scientific models differ significantly from data analysis software. We gathered feedback from modeling teams worldwide through a living survey and discussion sessions at the 2024 Open Science Workshop in College Park, USA, and at the 2025 COSPAR ISWAT Working Meeting in Cape Canaveral, USA. We complement these findings with lessons learned from almost 25 years of experience at the Community Coordinated Modeling Center in enabling open use of models. We identify key roadblocks in current open science practices and guidelines and offer recommendations for future progress across four overlapping themes: open use of models and simulation results, open validation, open development, and open collaboration. An essential outcome of the discussion is the need for model developers and model users to speak with a united voice and promote the role of models in future open science efforts. We introduce a new cross-domain community initiative called the Heliophysics Open Modeling Environment (HOME), which will be integrated as an overarching activity within COSPAR ISWAT. HOME will serve as a platform for modelers and model users to work together, facilitate community modeling, improve the scientific return on modeling investment, and advance understanding, modeling, and forecasting in heliophysics and space weather.},

note = {e2025SW004922 2025SW004922},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2024SW004219,

title = {Observing System Simulation Experiments and Observing System Experiments for the Van Allen Radiation Belts},

author = {Yuri Y. Shprits and Quintin Schiller and Alexander Y. Drozdov and Dmitri Kondrashov and Terrance Onsager},

doi = {10.1029/2024SW004219},

year  = {2025},

date = {2025-01-01},

journal = {Space Weather},

volume = {23},

number = {7},

pages = {e2024SW004219},

abstract = {Abstract In this study, we introduce observing system simulation experiments (OSSE) and observing system experiments (OSE) to reconstruct the near-Earth radiation environment. This study investigates the impact of satellite measurements on different orbits and the number of spacecraft measuring the particle fluxes on the reconstruction of the radiation environment at Geostationary (GEO) orbit. We also test the sensitivity of the reconstruction of the environment to the assumed parameters of the model. The results indicate that blending the model with data, even from a single spacecraft at low Earth orbit (LEO), may significantly improve the outer belt reconstruction compared to a reconstruction without data. Additionally, the highest accuracy is achieved when multiple satellites at different orbits covering various radial distances are used. Future improvements to the model are identified. The discrepancies between the observed GEO environment and the environment reconstructed from LEO data may be stronger during storms and should be better understood. Results of the OSE may be included in synthetic data runs representing the “truth,” the so-called nature run, to provide a more realistic baseline for the OSSEs. When there is an abundance of observations at all radial distances, energies, and pitch angles, the assumptions of the code become less important as data provides enough information to constrain even an inaccurate model. This study gives an example of OSSEs and OSEs and paves the way for the routine application of the OSE and OSSE for mission planning.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LE2025,

title = {Correlation of Atmospheric CO2 Level Changes with Geophysical and Atmospheric Indices},

author = {Nhung Le and Luyen K. Bui and Dmitri Kondrashov and T. T. Thuy Pham and Harald Schuh},

doi = {10.1016/j.asr.2025.07.054},

issn = {0273-1177},

year  = {2025},

date = {2025-01-01},

journal = {Advances in Space Research},

abstract = {Parts of the Earth’s system interact with each other, causing effects that are attributed to the dynamic and complex features of the Earth’s climate system. Both solar and human activities are warned to have an impact on atmospheric Carbon Dioxide (CO2) concentration, contributing to global climate change. Thus, determining the relationship between changes in atmospheric CO2 levels and atmospheric and geophysical indices is crucial for a better understanding of the global carbon cycle and key climate drivers. However, the methods and physical parameters selected among studies are inconsistent, as different studies often use different parameters. Additionally, the relationship between CO2 and the indices of solar and geomagnetic activity has only been quantified by trends indicating increases or decreases, but not specific correlation coefficients. Therefore, through comprehensive assessments of 194 CO2 monitoring stations in the Fluxnet database, we examine thirteen atmospheric and geophysical indices, including surface atmospheric loading, four meteorological parameters, seven solar activity indices, and the Dst index of the geomagnetic activity, to determine their linear and nonlinear correlations with changes in atmospheric CO2 levels. The parameters investigated in this study, e.g., the Dst index, plasma speed, and F10.7, may be valuable for ionospheric modeling and communication and navigation applications. Significantly, the cross-correlation technique is employed to detect time lags, which indicate how quickly changes in CO2 levels are observed on the data pattern of the investigated indices for a better understanding of the carbon cycle. Our experimental results show that Spearman’s test and squared wavelet spectral coherence are recommended for measuring correlations between CO2 levels and atmospheric and geophysical indices. Moreover, this study identifies the typical thirteen physical parameters statistically relevant to changes in atmospheric CO2 levels, which might be considered as potential features for the prediction of atmospheric CO2 levels. Of those, three parameters, namely temperature, wind speed, and shortwave radiation, could be recommended for warnings of atmospheric CO2 anomalies. Six parameters, including precipitation, atmospheric surface loading, plasma speed, F10.7, R sunspot number, and sunlight magnitude, would be more suitable for (near) real-time tracking of CO2 level changes. Our findings could also contribute to ionospheric imaging by identifying key parameters for data assimilation or validating ionospheric models under varying solar and geomagnetic conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2024JA033180,

title = {The Role of Local Acceleration and Radial Diffusion in Multi-MeV Electron Flux Enhancements},

author = {A. A. Saikin and A. Y. Drozdov and A. N. Jaynes and D. Kondrashov and A. Boyd and Y. Y. Shprits},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JA033180},

doi = {https://doi.org/10.1029/2024JA033180},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Geophysical Research: Space Physics},

volume = {130},

number = {1},

pages = {e2024JA033180},

abstract = {Abstract During the Van Allen Probes era, several multi-MeV (>4~MeV) electron flux enhancements were observed. The cause of electron acceleration up to multi-MeV remains an ongoing science topic. In this study, we focus on examining the relationship between phase space density (PSD) radial profile shapes and the occurrence of multi-MeV electron flux enhancement events. This will determine which process (local acceleration or radial diffusion) is dominant in producing multi-MeV electron flux enhancements at a specific L*. Growing peaks in PSD radial profiles are associated with the local acceleration (i.e., a wave-particle interaction) of multi-MeV electrons. For each growing peak in PSD, we determined the L* where the local acceleration occurs for each respective electron energy. Similarly, we also identify which PSD profiles are related to acceleration via radial diffusion profiles. Both sets of profiles are compared with the Van Allen Probe-A observed multi-MeV electron flux enhancements. Results show that both mechanisms (local acceleration and radial diffusion) can facilitate multi-MeV electron acceleration, however each mechanism has a preferable L* region where it is the dominant acceleration process.},

note = {e2024JA033180 2024JA033180},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KDS2024,

title = {Nonlinear Wave-Particle Interaction Effects on Radiation Belt Electron Dynamics in 9 October 2012 Storm},

author = {D. Kondrashov and A. Y. Drozdov and Y. Shprits},

url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024JA032898},

doi = {10.1029/2024JA032898},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Geophysical Research: Space Physics},

volume = {129},

number = {9},

pages = {e2024JA032898},

abstract = {Abstract We study the geomagnetic storm of 9 October 2012, where it had been generally accepted that the resulting prominent outer radiation belt electron acceleration throughout the storm is due to whistler-mode chorus waves. This storm has been studied previously by two-dimensional Fokker–Planck numerical simulations with data-driven quasi-linear (QL) diffusion rates. However, possible nonlinear (NL) resonant interaction effects on electron flux dynamics haven’t been looked at yet. This study aims to fill this gap by demonstrating that theory-informed rescaling of QL diffusion rates accounting for contributions of NL resonant interactions helps to reproduce better observed increase of electron fluxes by diffusion simulations. We use machine learning, uncertainty quantification (UQ), physics-perturbed ensemble of VERB simulations and Van Allen Probes observations to identify optimal rescaling of quasi-linear diffusion rates.},

note = {e2024JA032898 2024JA032898},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SIOReview2024,

title = {Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison},

author = {Mitchell Bushuk and Sahara Ali and David A. Bailey and Qing Bao and Lauriane Batté and Uma S. Bhatt and Edward Blanchard-Wrigglesworth and Ed Blockley and Gavin Cawley and Junhwa Chi and François Counillon and Philippe Goulet Coulombe and Richard I. Cullather and Francis X. Diebold and Arlan Dirkson and Eleftheria Exarchou and Maximilian Göbel and William Gregory and Virginie Guemas and Lawrence Hamilton and Bian He and Sean Horvath and Monica Ionita and Jennifer E. Kay and Eliot Kim and Noriaki Kimura and Dmitri Kondrashov and Zachary M. Labe and WooSung Lee and Younjoo J. Lee and Cuihua Li and Xuewei Li and Yongcheng Lin and Yanyun Liu and Wieslaw Maslowski and François Massonnet and Walter N. Meier and William J. Merryfield and Hannah Myint and Juan C. Acosta Navarro and Alek Petty and Fangli Qiao and David Schröder and Axel Schweiger and Qi Shu and Michael Sigmond and Michael Steele and Julienne Stroeve and Nico Sun and Steffen Tietsche and Michel Tsamados and Keguang Wang and Jianwu Wang and Wanqiu Wang and Yiguo Wang and Yun Wang and James Williams and Qinghua Yang and Xiaojun Yuan and Jinlun Zhang and Yongfei Zhang},

url = {https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-23-0163.1/BAMS-D-23-0163.1.xml},

doi = {10.1175/BAMS-D-23-0163.1},

year  = {2024},

date = {2024-01-01},

journal = {Bulletin of the American Meteorological Society},

publisher = {American Meteorological Society},

address = {Boston MA, USA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Drozdov_2023,

title = {Reconstruction of electron radiation belts using data assimilation and machine learning},

author = {Alexander Y. Drozdov and Dmitri Kondrashov and Kirill Strounine and Yuri Y. Shprits},

url = {https://doi.org/10.3389/fspas.2023.1072795},

doi = {10.3389/fspas.2023.1072795},

year  = {2023},

date = {2023-05-01},

journal = {Frontiers in Astronomy and Space Sciences},

volume = {10},

publisher = {Frontiers Media SA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SUDAKOW2023114273,

title = {Diverse soil microbial communities may mitigate climate system bifurcation},

author = {Ivan Sudakow and Elena Savenkova and Dmitri Kondrashov and Sergey A. Vakulenko and Elena Sashina},

url = {https://www.sciencedirect.com/science/article/pii/S096007792301175X},

doi = {https://doi.org/10.1016/j.chaos.2023.114273},

issn = {0960-0779},

year  = {2023},

date = {2023-01-01},

journal = {Chaos, Solitons & Fractals},

volume = {177},

pages = {114273},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov_2022,

title = {Prediction of plasmaspheric hiss spectral classes},

author = {Dmitri Kondrashov and Alexander Y. Drozdov and Daniel Vech and David M. Malaspina},

url = {https://doi.org/10.3389/fspas.2022.977801},

doi = {10.3389/fspas.2022.977801},

year  = {2022},

date = {2022-08-01},

journal = {Frontiers in Astronomy and Space Sciences},

volume = {9},

publisher = {Frontiers Media SA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{agarwal_ryzhov_kondrashov_berloff_2021,

title = {Correlation-based flow decomposition and statistical analysis of the eddy forcing},

author = {N. Agarwal and E. A. Ryzhov and D. Kondrashov and P. Berloff},

url = {https://doi.org/10.1017/jfm.2021.604},

doi = {10.1017/jfm.2021.604},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Fluid Mechanics},

volume = {924},

pages = {A5},

publisher = {Cambridge University Press},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{https://doi.org/10.1029/2021MS002537,

title = {A Comparison of Data-Driven Approaches to Build Low-Dimensional Ocean Models},

author = {Niraj Agarwal and D. Kondrashov and P. Dueben and E. Ryzhov and P. Berloff},

url = {https://doi.org/10.1029/2021MS002537},

doi = {10.1029/2021MS002537},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Advances in Modeling Earth Systems},

volume = {13},

number = {9},

pages = {e2021MS002537},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov2020,

title = {On data-driven induction of the low-frequency variability in a coarse-resolution ocean model},

author = {E. A. Ryzhov and D. Kondrashov and N. Agarwal and J. C. McWilliams and P. Berloff},

url = {https://doi.org/10.1016/j.ocemod.2020.101664},

doi = {10.1016/j.ocemod.2020.101664},

year  = {2020},

date = {2020-01-01},

journal = {Ocean Modelling},

volume = {153},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov2020b,

title = {Data-adaptive harmonic analysis of oceanic waves and turbulent flows},

author = {D. Kondrashov and E. A. Ryzhov and P. Berloff},

url = {https://doi.org/10.1063/5.0012077},

doi = {10.1063/5.0012077},

year  = {2020},

date = {2020-01-01},

journal = {Chaos},

volume = {30},

number = {6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ryzhov_2019,

title = {On data-driven augmentation of low-resolution ocean model dynamics},

author = {E. A. Ryzhov and D. Kondrashov and N. Agarwal and P. S. Berloff},

url = {https://doi.org/10.1016/j.ocemod.2019.101464},

doi = {10.1016/j.ocemod.2019.101464},

year  = {2019},

date = {2019-10-01},

journal = {Ocean Modelling},

volume = {142},

pages = {101464},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov_2018b,

title = {Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres},

author = {Dmitri Kondrashov and Mickael Chekroun and Pavel Berloff},

url = {https://doi.org/10.3390/fluids3010021},

doi = {10.3390/fluids3010021},

year  = {2018},

date = {2018-03-01},

journal = {Fluids},

volume = {3},

number = {1},

pages = {21},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov2018,

title = {Extratropical sub-seasonal to seasonal oscillations and multiple regimes: The dynamical systems view},

author = {M. Ghil and A. Groth and D. Kondrashov and A. W. Robertson},

url = {https://shop.elsevier.com/books/sub-seasonal-to-seasonal-prediction/robertson/978-0-12-811714-9$#$},

year  = {2018},

date = {2018-01-01},

journal = {Sub-seasonal to Seasonal Prediction: The Gap Between Weather and Climate Forecasting},

pages = {119-142},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1024182154953-46,

title = {Data-adaptive harmonic analysis and modeling of solar wind-magnetosphere coupling},

author = {D. Kondrashov and M. D. Chekroun},

url = {https://doi.org/10.1016/j.jastp.2017.12.021},

doi = {10.1016/j.jastp.2017.12.021},

year  = {2018},

date = {2018-01-01},

journal = {Journal of Atmospheric and Solar-Terrestrial Physics},

volume = {177},

pages = {179-189},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kondrashov_2018,

title = {Data-adaptive harmonic decomposition and prediction of Arctic sea ice extent},

author = {Dmitri Kondrashov and Mickael D Chekroun and Michael Ghil},

url = {https://doi.org/10.1093/climsys/dzy001},

doi = {10.1093/climsys/dzy001},

year  = {2018},

date = {2018-01-01},

journal = {Dynamics and Statistics of the Climate System},

volume = {3},

number = {1},

publisher = {Oxford University Press (OUP)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1024182154953-44,

title = {Data-adaptive harmonic spectra and multilayer Stuart-Landau models},

author = {Mickael D. Chekroun and Dmitri Kondrashov},

url = {https://doi.org/10.1063/1.4989400},

doi = {10.1063/1.4989400},

year  = {2017},

date = {2017-01-01},

journal = {Chaos},

volume = {27},

number = {9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:0818171559688-39,

title = {Interannual Variability in the North Atlantic Ocean’s Temperature Field and Its Association with the Wind Stress Forcing},

author = {A. Groth and Y. Feliks and D. Kondrashov and M. Ghil},

url = {https://doi.org/10.1175/JCLI-D-16-0370.1},

doi = {10.1175/JCLI-D-16-0370.1},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Climate},

volume = {30},

number = {7},

pages = {2655-2678},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1024182154953-43,

title = {Inverse stochastic-dynamic models for high-resolution Greenland ice core records},

author = {Niklas Boers and Mickael D. Chekroun and Honghu Liu and Dmitri Kondrashov and Denis-Didier Rousseau and Anders Svensson and Matthias Bigler and Michael Ghil},

url = {https://doi.org/10.5194/esd-8-1171-2017},

doi = {10.5194/esd-8-1171-2017},

year  = {2017},

date = {2017-01-01},

journal = {Earth System Dynamics},

volume = {8},

number = {4},

pages = {1171-1190},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650604-1,

title = {Comment on "Nonparametric forecasting of low-dimensional dynamical systems"},

author = {Dmitri Kondrashov and Mickael D. Chekroun and Michael Ghil},

url = {https://doi.org/10.1103/PhysRevE.93.036201},

doi = {10.1103/PhysRevE.93.036201},

year  = {2016},

date = {2016-01-01},

journal = {Physical Review E},

volume = {93},

number = {3},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650604-3,

title = {Data assimilation of low-altitude magnetic perturbations into a global magnetosphere model},

author = {V. G. Merkin and D. Kondrashov and M. Ghil and B. J. Anderson},

url = {https://doi.org/10.1002/2015SW001330},

doi = {10.1002/2015SW001330},

year  = {2016},

date = {2016-01-01},

journal = {Space Weather-the International Journal of Research and Applications},

volume = {14},

number = {2},

pages = {165-184},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650605-2,

title = {Diversity, Nonlinearity, Seasonality, and Memory Effect in ENSO Simulation and Prediction Using Empirical Model Reduction},

author = {Chen Chen and Mark A. Cane and Naomi Henderson and Dong Eun Lee and David Chapman and Dmitri Kondrashov and Mickael D. Chekroun},

url = {https://doi.org/10.1175/JCLI-D-15-0372.1},

doi = {10.1175/JCLI-D-15-0372.1},

year  = {2016},

date = {2016-01-01},

journal = {Journal of Climate},

volume = {29},

number = {5},

pages = {1809-1830},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650605-5,

title = {Data-driven non-Markovian closure models},

author = {Dmitri Kondrashov and Mickael D. Chekroun and Michael Ghil},

url = {https://doi.org/10.1016/j.physd.2014.12.005},

doi = {10.1016/j.physd.2014.12.005},

year  = {2015},

date = {2015-01-01},

journal = {Physica D-Nonlinear Phenomena},

volume = {297},

pages = {33-55},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650605-6,

title = {Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models},

author = {Dmitry Mukhin and Dmitri Kondrashov and Evgeny Loskutov and Andy Gavrilov and Alexander Feigin and Michael Ghil},

url = {https://doi.org/10.1175/JCLI-D-14-00240.1},

doi = {10.1175/JCLI-D-14-00240.1},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Climate},

volume = {28},

number = {5},

pages = {1962-1976},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650606-4,

title = {Stochastic modeling of decadal variability in ocean gyres},

author = {D. Kondrashov and P. Berloff},

url = {https://doi.org/10.1002/2014GL062871},

doi = {10.1002/2014GL062871},

year  = {2015},

date = {2015-01-01},

journal = {Geophysical Research Letters},

volume = {42},

number = {5},

pages = {1543-1553},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650606-8,

title = {Noise statistics identification for Kalman filtering of the electron radiation belt observations: 2. Filtration and smoothing},

author = {T. V. Podladchikova and Y. Y. Shprits and A. C. Kellerman and D. Kondrashov},

url = {https://doi.org/10.1002/2014JA019898},

doi = {10.1002/2014JA019898},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Geophysical Research-Space Physics},

volume = {119},

number = {7},

pages = {5725-5743},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650606-9,

title = {Noise statistics identification for Kalman filtering of the electron radiation belt observations I: Model errors},

author = {T. V. Podladchikova and Y. Y. Shprits and D. Kondrashov and A. C. Kellerman},

url = {https://doi.org/10.1002/2014JA019897},

doi = {10.1002/2014JA019897},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Geophysical Research-Space Physics},

volume = {119},

number = {7},

pages = {5700-5724},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650607-10,

title = {Reconstruction of gaps in the past history of solar wind parameters},

author = {D. Kondrashov and R. Denton and Y. Y. Shprits and H. J. Singer},

url = {https://doi.org/10.1002/2014GL059741},

doi = {10.1002/2014GL059741},

year  = {2014},

date = {2014-01-01},

journal = {Geophysical Research Letters},

volume = {41},

number = {8},

pages = {2702-2707},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650607-11,

title = {Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances},

author = {Mickael David Chekroun and J. David Neelin and Dmitri Kondrashov and James C. McWilliams and Michael Ghil},

url = {https://doi.org/10.1073/pnas.1321816111},

doi = {10.1073/pnas.1321816111},

year  = {2014},

date = {2014-01-01},

journal = {Proceedings of the National Academy of Sciences of the United States of America},

volume = {111},

number = {5},

pages = {1684-1690},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650607-7,

title = {Three-dimensional data assimilation and reanalysis of radiation belt electrons: Observations of a four-zone structure using five spacecraft and the VERB code},

author = {A. C. Kellerman and Y. Y. Shprits and D. Kondrashov and D. Subbotin and R. A. Makarevich and E. Donovan and T. Nagai},

url = {https://doi.org/10.1002/2014JA020171},

doi = {10.1002/2014JA020171},

year  = {2014},

date = {2014-01-01},

journal = {Journal of Geophysical Research-Space Physics},

volume = {119},

number = {11},

pages = {8764-8783},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650608-12,

title = {Application of a new data operator-splitting data assimilation technique to the 3-D VERB diffusion code and CRRES measurements},

author = {Yuri Shprits and Adam Kellerman and Dmitri Kondrashov and Dmitriy Subbotin},

url = {https://doi.org/10.1002/grl.50969},

doi = {10.1002/grl.50969},

year  = {2013},

date = {2013-01-01},

journal = {Geophysical Research Letters},

volume = {40},

number = {19},

pages = {4998-5002},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650608-13,

title = {Low-order stochastic model and "past-noise forecasting" of the Madden-Julian Oscillation},

author = {D. Kondrashov and M. D. Chekroun and A. W. Robertson and M. Ghil},

url = {https://doi.org/10.1002/grl.50991},

doi = {10.1002/grl.50991},

year  = {2013},

date = {2013-01-01},

journal = {Geophysical Research Letters},

volume = {40},

number = {19},

pages = {5305-5310},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650608-19,

title = {An empirical stochastic model of sea-surface temperatures and surface winds over the Southern Ocean},

author = {S. Kravtsov and D. Kondrashov and I. Kamenkovich and M. Ghil},

url = {https://doi.org/10.5194/os-7-755-2011},

doi = {10.5194/os-7-755-2011},

year  = {2011},

date = {2011-01-01},

journal = {Ocean Science},

volume = {7},

number = {6},

pages = {755-770},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650609-17,

title = {Extreme events: dynamics, statistics and prediction},

author = {M. Ghil and P. Yiou and S. Hallegatte and B. D. Malamud and P. Naveau and A. Soloviev and P. Friederichs and V. Keilis-Borok and D. Kondrashov and V. Kossobokov and O. Mestre and C. Nicolis and H. W. Rust and P. Shebalin and M. Vrac and A. Witt and I. Zaliapin},

url = {https://doi.org/10.5194/npg-18-295-2011},

doi = {10.5194/npg-18-295-2011},

year  = {2011},

date = {2011-01-01},

journal = {Nonlinear Processes in Geophysics},

volume = {18},

number = {3},

pages = {295-350},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650609-14,

title = {Lognormal Kalman filter for assimilating phase space density data in the radiation belts},

author = {D. Kondrashov and M. Ghil and Y. Shprits},

url = {https://doi.org/10.1029/2011SW000726},

doi = {10.1029/2011SW000726},

year  = {2011},

date = {2011-01-01},

journal = {Space Weather-the International Journal of Research and Applications},

volume = {9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650609-16,

title = {Predicting stochastic systems by noise sampling, and application to the El Nino-Southern Oscillation},

author = {Mickael David Chekroun and Dmitri Kondrashov and Michael Ghil},

url = {https://doi.org/10.1073/pnas.101575},

doi = {10.1073/pnas.101575},

year  = {2011},

date = {2011-01-01},

journal = {Proceedings of the National Academy of Sciences of the United States of America},

volume = {108},

number = {29},

pages = {11766-11771},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650610-15,

title = {Reanalysis of radiation belt electron phase space density using various boundary conditions and loss models},

author = {M. Daae and Y. Y. Shprits and B. Ni and J. Koller and D. Kondrashov and Y. Chen},

url = {https://doi.org/10.1016/j.asr.2011.07.001},

doi = {10.1016/j.asr.2011.07.001},

year  = {2011},

date = {2011-01-01},

journal = {Advances in Space Research},

volume = {48},

number = {8},

pages = {1327-1334},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650610-18,

title = {Signatures of Nonlinear Dynamics in an Idealized Atmospheric Model},

author = {Dmitri Kondrashov and Sergey Kravtsov and Michael Ghil},

url = {https://doi.org/10.1175/2010JAS3524.1},

doi = {10.1175/2010JAS3524.1},

year  = {2011},

date = {2011-01-01},

journal = {Journal of the Atmospheric Sciences},

volume = {68},

number = {1},

pages = {3-12},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650610-20,

title = {Gap filling of solar wind data by singular spectrum analysis},

author = {D. Kondrashov and Y. Shprits and M. Ghil},

url = {https://doi.org/10.1029/2010GL044138},

doi = {10.1029/2010GL044138},

year  = {2010},

date = {2010-01-01},

journal = {Geophysical Research Letters},

volume = {37},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650611-21,

title = {Reduced models of atmospheric low-frequency variability: Parameter estimation and comparative performance},

author = {K. Strounine and S. Kravtsov and D. Kondrashov and M. Ghil},

url = {https://doi.org/10.1016/j.physd.2009.10.013},

doi = {10.1016/j.physd.2009.10.013},

year  = {2010},

date = {2010-01-01},

journal = {Physica D-Nonlinear Phenomena},

volume = {239},

number = {3-4},

pages = {145-166},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RID:1011161650611-22,

title = {Reanalyses of the radiation belt electron phase space density using nearly equatorial CRRES and polar-orbiting Akebono satellite observations},

author = {Binbin Ni and Yuri Shprits and Tsugunobu Nagai and Richard Thorne and Yue Chen and Dmitri Kondrashov and Hee-jeong Kim},

url = {https://doi.org/10.1029/2008JA013933},

doi = {10.1029/2008JA013933},

year  = {2009},

date = {2009-01-01},

journal = {Journal of Geophysical Research-Space Physics},

volume = {114},

keywords = {},

pubstate = {published},

tppubtype = {article}

}