Tatiana Podladchikova

Tatiana Podladchikova

Assistant Professor
Space Center

Space weather, Transitioning Research to Operations
Research in solar-terrestrial physics, development of space weather services and mitigation of space weather hazards:

  • Detection of eruptive events on Sun (coronal mass ejections and accompanying solar events)
  • Forecasting of solar wind speed at Earth
  • Forecasting of geomagnetic storms and polar aurora
  • Solar activity forecasting
  • Scientific and service products

“Space weather refers to conditions on the Sun, in the solar wind, and within Earth’s magnetosphere,
ionosphere and thermosphere that can influence the performance and reliability of space-borne
and ground-based technological systems and can endanger human life or health”.

The main users of space weather services are:

  • Satellite designers and operators;
  • Human space flight;
  • Space insurance companies;
  • Airlines;
  • Space tourism;
  • Power systems and pipeline operators;
  • Scientists and engineers.

Interdisciplinary applications
Development of advanced data analysis techniques for the extraction of useful knowledge, control and forecasting
in interdisciplinary applications (biomedicine, navigation, self-driving car).
Co-founder of start-up company Sense2Bit, AFib Management System.

 

Operating Space Weather Services:

–  Geomagnetic Storm Forecasting Service StormFocus
StormFocus service provides advance warnings about the future geomagnetic storm magnitude on an hourly basis.
The forecast is based on real-time solar wind and interplanetary magnetic field data, provided by the DSCOVR spacecraft,
which is located at the L1 Sun-Earth liberation point 1 500 000 km upstream of Earth.  Forecasts are updated every hour
and published on SpaceWeather.Ru.

Updated medium-term sunspot number prediction service
A universal technique that improves medium-term prediction methods as they are monthly updated using the latest available
observations of smoothed sunspot numbers using an adaptive Kalman filter. Forecasts are updated every month and published
on the World Data Center for the production, preservation and dissemination of the international sunspot number (SILSO).

Forecast of the auroral oval boundaries and aurora borealis on Yamal island
Forecast based on real-time DSCOVR solar wind and interplanetary magnetic field data. The forecast provides estimates
of geomagnetic latitudes of poleward and equatorward boundaries of the auroral oval, and equatorward boundary
of the diffusive aurora for the next hour. Forecasts are updated every hour and published on SpaceWeather.Ru.

Recent publications

1. Dissauer K, A. M. Veronig, M.Temmer, T. Podladchikova, K. Vanninathan (2018), Statistics of coronal dimmings associated with
coronal mass ejections. I. Characteristic dimming properties and flare association, The Astrophysical Journal, accepted, arxiv.org/abs/1807.05056.

2. Shadrin D., A. Somov, T. Podladchikova, and R. Gerzer (2018), Pervasive agriculture: Measuring and predicting plant growth
using statistics and 2D/3D imaging, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC),
Houston, TX, USA, pp. 1-6.,  ieeexplore.ieee.org/document/8409700.

3. Podladchikova T.V., A.A. Petrukovich, and Y. Yermolaev (2018),  Geomagnetic storm forecasting service StormFocus: 5 years online,
Journal of Space Weather and Space Climate, 8, A22Special issue “Developing New Space Weather Tools: Transitioning fundamental
science to operational prediction systems,”  doi.org/10.1051/swsc/2018017.

4. Dissauer K., A.M. Veronig, M. Temmer,  Podladchikova T., and K. Vanninathan (2018), On the detection of coronal
dimmings and the extraction of their characteristic properties, The Astrophysical Journal, 855,2, doi.org/10.3847/1538-4357/aaadb5.

5. Podladchikova T., , R.A.M. Van der Linden,  and A.M. Veronig (2017),  Sunspot number second differences as precursor
of the following 11-year sunspot cycle,  The Astrophysical Journal,  850, 81, doi:10.3847/1538-4357/aa93ef.

Short description:  Forecasting the strength of the sunspot cycle is highly important for many space weather applications.
We introduce a method to reliably calculate sunspot number second differences (SNSD) in order to quantify the short-term
variations of sunspot activity. We demonstrate a steady relationship between the SNSD dynamics in the early stage of the
declining phase of a given cycle and the strength of the following sunspot cycle. This fi nding may bear physical implications
on the underlying dynamo at work. On the basis of the developed predictive indicator, at the early stage of declining phase
of cycle 24, we predict that the sunspot cycle 25 will be weaker.

6. Podladchikova, T. V., Y. Y. Shprits, and A. C. Kellerman, (2016), Customizations of the Kalman Filter to Reconstruct
the Dynamics of Earth’s Radiation Belts using Satellite Measurements, Special issue of Space Research Institute
Russian Academy of Science  “Practical aspects of Heliogeophysics”, series  “Applied aspects of space weather”.

Short description: Adaptive Kalman filter on the basis of noise statistics identification using electron flux measurements
of Van Allen Probes is developed to reconstruct globally the state and evolution of Earth’s radiation belts.
A technique to determine the rate of radial diffusion and the direction of its propagation is proposed.

7.    Podladchikova, T. V., Y. Y. Shprits, D. Kondrashov, and A. C. Kellerman (2014), Noise statistics identification for Kalman filtering
of the electron radiation belt observations I: Model errors, Journal of Geophysical  Research: Space Physics, 119, doi:10.1002/2014JA019897.

Short description: The development of innovation tools to identify the errors in theoretical models of radiation belts.
This tool is used to improve our confidence in the results of radiation belt electron phase space density reconstruction
by an adaptive Kalman filter.

8.    Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2014), Noise statistics identification for Kalman filtering
of the electron radiation belt observations: 2. Filtration and smoothing, Journal of Geophysical  Research: Space Physics, 119, doi:10.1002/2014JA019898.

Short description: The development of identification technique of measurement errors to optimize the data assimilation
of sparse satellite data. This provides the accurate and reliable global reconstruction of radiation belt dynamics.
Further improvement of radiation belt reconstruction is achieved by the backward smoothing procedure applied
to the forward Kalman filter.

9.    Podladchikova,T. V., and A. A. Petrukovich (2012), Extended geomagnetic storm forecast ahead of available solar wind
measurements, Space Weather, 10, S07001, doi:10.1029/2012SW000786.

Short description:  Real-time space weather service that provides the forecast of the geomagnetic storm magnitude
for the next several hours based on real-time solar wind and interplanetary magnetic field data.

10.    Podladchikova T., and R.A.M. Van der Linden (2012), Kalman Filter Technique for Improving Prediction of Smoothed
Monthly Sunspot Numbers. Solar Physics, 277 (2), 397-416 , doi:10.1007/s11207-011-9899-y.

Short description:  Real-time space weather service that provides the medium-term forecasting of the sunspot number
for the next 12 months using adaptive Kalman filter

11.    Podladchikova T., and R.A.M. Van der Linden (2011), An upper limit prediction of the peak sunspot number for solar cycle 24.
Space Weather and Space Climate, 1, A01, doi:10.1051/swsc/2011110013.

Short description: The prediction of the maximum sunspot number in solar cycle 24 once the epoch of the minimum of cycle 23
has passed (2008 January). According to the prediction the peak value of cycle 24 will not exceed 72.

Recent conferences

  1. Podladchikova T., A.M. Veronig, K. Dissauer, Temmer, D.B. Seaton, J. Guo, and B. Vršnak (2018), CME acceleration
    and EUV wave kinematics for September 10th 2017 event, The 42th COSPAR Scientific Assembly (July 14-22, Pasadena, USA).
  2. Podladchikova T., A.M. Veronig, M. Temmer, and S. Hofmeister (2018), Development of Adaptive Kalman Filter for solar wind forecast,
    The 42th COSPAR Scientific Assembly (July 14-22, Pasadena, USA).
  3. Podladchikova T., Petrukovich A.A, and Y. Yermolaev (2018), Performance Analysis of Geomagnetic Storm Forecasting Service StormFocus,
    The 42th COSPAR Scientific Assembly (July 14-22, Pasadena, USA)
  4. Dissauer K., A.M. Veronig, M. Temmer, Podladchikova T., and K. Vanninathan, What can we learn from coronal dimmings about
    the early evolution of Earth-directed CMEs? The 42th COSPAR Scientific Assembly (July 14-22, Pasadena, USA).
  5. Petrukovich A.A, Uvarov I, Nikiforov O., and T. Podladchikova (2018), Integrated system to handle and visualize auroral oval data,
    The 42th COSPAR Scientific Assembly (July 14-22, Pasadena, USA).
  6. Podladchikova T., A.M. Veronig, K. Dissauer, Temmer, D.B. Seaton, J. Guo, and B. Vršnak (2018), CME acceleration
    and EUV wave kinematics for September 10th 2017 event, 14th Quadrennial Solar-Terrestrial Physics Symposium (July 9-13, Toronto, Canada).
  7. Podladchikova T., A.M. Veronig, M. Temmer, and S. Hofmeister (2018), Development of Adaptive Kalman Filter for solar wind forecast,
    14th Quadrennial Solar-Terrestrial Physics Symposium (July 9-13, Toronto, Canada).
  8. Dissauer K., A.M. Veronig, M. Temmer, Podladchikova T., and K. Vanninathan, Studying the early evolution of Earth-directed CMEs
    by analyzing coronal dimmings, 14th Quadrennial Solar-Terrestrial Physics Symposium (July 9-13, Toronto, Canada).
  9. Podladchikova T., A.M. Veronig, M.Temmer, and S. Hofmeister (2018), Solar Wind Forecast based on Data Assimilation
    with an Adaptive Kalman Filter, European Geosciences Union General Assembly 2018 (April 8 -13, Vienna, Austria).
  10. Podladchikova T.V., A.M. Veronig, and K. Dissauer (2017), 3D structure and kinematics characteristics
    of EUV wave front, American Geophysical Union (December 11-15, New Orleans, USA).
  11. Podladchikova T.V., A.M. Veronig, and K. Dissauer (2017) 3D reconstructions of EUV wave fronts using multi-point
    STEREO observations, 14th European Space Weather Weak (November 27 – December 1, Ostende, Belgium).
  12. K. Dissauer, A.M. Veronig, M. Temmer, K. Vanninathan, Podladchikova T.V., and J.M. Riedl (2017,  Can coronal dimmings serve as proxy for characteristic CME parameters? 14th European Space Weather Weak (November 27 – December 1, Ostende, Belgium).
  13. Petrukovich A.A., Nikiforov O.V., Uvarov I.A., Podladchikova T.V., Information system of monitoring and forecasting of auroral oval,
    15th Opened All-russia Conference “Current Aspects of Remote Sensing of Earth from Space (November 13-17, Moscow, Russia).
  14. Podladchikova T.V., A.M. Veronig, and K. Dissauer (2017), 3D reconstructions of EUV wave front heights and their influence
    on wave kinematics, 15th European Solar Physics Meeting (September 4-8, Budapest, Hungary).
  15. Dissauer K., A.M. Veronig, M. Temmer, K. Vanninathan, Podladchikova T.V., and J.M. Riedl (2017),
    Are coronal dimmings statistically related to solar flares and CMEs? 15th European Solar Physics Meeting
    (September 4-8, Budapest, Hungary).
  16. Glazkova N., T. Podladchikova., and R. Gerzer R (2017). Non-Invasive Wearable ECG-Patch for the Assessment
    of Cardiac Arrhythmias, Generation-Y conference (September 27 – October 1, Sochi, Russia).
  17. Shadrin D., T. Podladchikova., Hauslage J., and R. Gerzer R (2017). Development of methodology for prediction dynamics
    of plant growth, Generation-Y conference (September 27 – October 1, Sochi, Russia).
  18. Podladchikova T.V., and A.A. Petrukovich (2017), Forecast of future geomagnetic storm strength: 5 years online,
    European Geosciences Union General Assembly 2017 (April 23 – 28, Vienna, Austria).
  19. Podladchikova T.V., and A R. Van der Linden (2016), Short-term variations of the sunspot number second differences
    as a predictor of the next cycle strength, (November 14 – 18, Ostende, Belgium).
  20. Podladchikova T.V., and A.A. Petrukovich (2016), Forecast of future geomagnetic storm strength: 5 years online,
    13th European Space Weather Weak (November 14 -18, Ostend, Belgium).
  21. Podladchikova T.V., and R. Van der Linden, (2016), Predictive potential of short-term variations of sunspot number
    second derivative, Conference “Plasma Phenomena in the Solar System”, (February 15 -19, Moscow, Russia)
  22. Podladchikova, T. V., Y. Y. Shprits, and A. C. Kellerman, (2016), Customizations of the Kalman Filter to Reconstruct
    the Dynamics of Earth’s Radiation Belts using Satellite Measurements, Conference “Plasma Phenomena in the Solar System”,
    (February 15 -19, Moscow, Russia)
  23. Podladchikova, T. V., Y. Y. Shprits, and A. C. Kellerman (2015), Kalman filtering and smoothing of the Van Allen Probes
    observations to estimate the radial, energy and pitch angle diffusion rates, AGU Fall Meeting, (December  14-18, San Francisco, USA).
  24. Podladchikova, T. V., Y. Y. Shprits, and A. C. Kellerman (2015), Estimation of radial, energy and pitch angle diffusion rates of radiation
    belt electrons using Van Allen Probes observations (2015), GEM Summer Workshop (June 14-19, Snowmass, CO, USA)
  25. Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2015), Customizations of the Kalman Filter for the
    Three-Dimensional Data Assimilation to Reconstruct the Dynamics of the Radiation Belts,  Inner Magnetosphere Coupling III,
    (March 23-27, Los Angeles, USA).
  26. Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2014), Customizations of the Kalman Filter for the
    Three-Dimensional Data Assimilation to Reconstruct the Dynamics of the Radiation Belts,  AGU Fall Meeting,
    (December  15-19, San Francisco, USA).
  27. Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2014), Model error identification for the radiation belt
    data assimilation, The 40th COSPAR Scientific Assembly (August 2 – 10, Moscow, Russia).
  28. Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2014), Optimal smoothing of the electron radiation belts
    observations using the observation errors identification, The 40th COSPAR Scientific Assembly (August 2 – 10, Moscow, Russia).
  29. Podladchikova, T. V., and A.A. Petrukovich (2014), Geomagnetic storm forecasts several hours ahead,
    The 40th COSPAR Scientific Assembly (2 – 10 August, Moscow, Russia).
  30. Podladchikova, T. V., and R. Van der Linden (2014), Short-term variations of the 11-year sunspot cycle as a predictor
    of the next cycle strength, The 40th COSPAR Scientific Assembly (August 2 – 10, Moscow, Russia).
  31. Podladchikova, T. V., Y. Y. Shprits, A. C. Kellerman, and D. Kondrashov (2014), Identification of model and measurement
    noise statistics for Kalman filtering and smoothing of the electron radiation belt PSD (2014), GEM Summer Workshop
    (June 15-20, Portsmouth, VA, USA).
  32. Podladchikova T.V., and R. Van der Linden. (2011), Updated Medium‐Term Sunspot Number Prediction Service using
    Kalman Filter, Eight European Space Weather Weak (November 28 – December 2, Namur, Belgium).
  33. Podladchikova T.V., and A.A. Petrukovich (2011), Geomagnetic Storm Forecasting Service, Eight European Space Weather Weak
    (November 28 – December 2, Namur, Belgium).
  34. Podladchikova T.V. and A.A. Petrukovich (2011), Joint research of geomagnetic storm forecasting, International Conference
    “Space research in the states – participants of CIS: integration, capacity development and legal aspects”
    (October 3-5, Moscow, Russia).
  35. Podladchikova T.V., and R. Van der Linden, (2011), Adaptive Kalman filter for the medium-term sunspot number prediction,
    Conference “Plasma Phenomena in the Solar System”, (February 14-18, Moscow, Russia).

 

2018 Award the “Best Professor of the Year 2018” in the nomination “Mentoring”.

The award is  granted to a faculty member who is approachable and accessible, and who listens to
and cares about students needs, while challenging and encouraging students to grow.

2015 The International Alexander Chizhevsky medal for Space Weather and Space
Climate for major contributions to space weather research and/or services.

2015  Excellence in Service Award, Skolkovo Institute of Science and Technology,
in recognition of outstanding performance and contribution to Skoltech mission and values.

2015 Certificate of Appreciation, Skolkovo Institute of Science and Technology,
for the notable contribution and service on the Organizing Committee at Skoltech Poster Competition in 2014 and 2015.

2011 Bottle of French Champagne for the paper to be first published in Journal of Space
Weather and Space Climate, a link between all the communities involved in Space Weather and in Space Climate.

2009 Best poster at European Space Weather Week 6, Belgium.

August 2018 “The star called Sun”, Radio program “Data transmission”, Komsomol Truth.

June 2018 Skoltech scientists use computer vision and machine learning to predict plant growth (English, Russian).

June 2018 Award the “Best Professor of the Year 2018” in the nomination “Mentoring”.
The award is  granted to a faculty member who is approachable and accessible, and who listens to
and cares about students needs, while challenging and encouraging students to grow.

February 2018 The Earth in the embraces of Sun, Live scientific-popular journal “Kot Shrodingera” (Russian).

February 2018 3D reconstructions of EUV wave fronts using multi-point STEREO observations,
Webinar for the project “Solar Flares and Active Regions Reconstructing the 3D Reality“.

February 2018  “We have to take space weather forecasts into account in our daily plans”,
Almanac “Skoltech, 5 steps into the future” (English, Russian).

December 2017 Skoltech-led team proposes new space-weather forecasting method (English, Russian).

September 2017  Public lecture  “In arms of the star called Sun”,   Skolkovo International Gymnasium.

May 2017 Kultura TV, show “Nablyudatel”, “How the Sun changes the Earth: climate turns” .

March 2017 Public lecture “Sun and Space Weather”,  Experimentanium Science Museum,  educational program “Scientists for kids”, Moscow.

February 2017 Space sector course. Aerospace business: The Devil is in the Details  (English, Russian).

September 2016 Public lecture “Where Does the Solar Wind Blow”,  educational program for exhibition “Cosmos: birth of new age”,  Moscow.

May 2016 Public lecture  “In arms of the star called Sun”,  The Spring School 2016 for the Oxford Russia Fund fellows.

March 2016 Prime Minister of Russia Dmitry Medvedev meets with representatives of science and business (Russian).
First channel and Mir 24 also covered the news, Russia.

February 2016 Public lecture  “Space Weather Forecast: Yesterday, Today, Tomorrow”, Russian State Library for Young Adults, Moscow.

December 2015 “How Space Weather affects the inhabitants of Earth?” Radio program “Science in Focus”, Echo of Moscow radio station, Russia.

November 2015 Tatiana Podladchikova, applied mathematician from Skoltech, was awarded with the prestigious
International Alexander Chizhevsky medal (English, Russian). Sk.ru and the electronic journal
RF Science and Technology‘ also covered the news.

April 2015 Public lecture  “Hot Breath of the Sun” Polytechnic Museum, Moscow (in Russian).

August 2014  Sharing impressions of participating in the COSPAR 2014 conference to the Skoltech Newsletter (Russian, English).

July 2014 Skoltech Researchers Achieve Unprecedented Accuracy in “Space Forecast” and Magnetospheric Reconstruction –
New Method Might Save Satellites and Predict Extreme Weather (English, Russian).

 


Course “Experimental data processing”
The course introduces students to practically useful approaches of data processing for control and forecasting.
The focus is on identifying the hidden and implicit features and regularities of dynamical processes using experimental data.
The course exposes data processing methods from multiple vantage points: standard data processing methods and their hidden
capacity to solve difficult problems; statistical methods based on state-space models; methods of extracting the regularities
of a process on the basis of identifying key parameters. The course addresses the problems in navigation, solar physics,
geomagnetism, space weather and biomedical research.
Course content and main topics:  Experimental data processing

Course “Data analysis for Space Weather”
The course introduces students to Solar-Terrestrial physics, Space Weather and practically useful approaches of data analysis for study, forecasting, and mitigation of space weather effects. The course provides an overview of Sun-Earth connections, starting from the interior of the Sun and ending in the Earth’s magnetosphere. To gain insight into this field, we focus on such topics as: solar interior and solar structure, solar atmosphere, solar wind, solar flares and coronal mass ejections, as well as associated geomagnetic storms and polar auroras. These phenomena drive Space Weather with the implications for space-borne and ground-based technological systems (satellites, human spaceflight, airlines, power systems and pipelines). We also examine the space weather effects on technology and human health, hazard assessment, mitigation and forecasting, space environment data, scientific and service products.
Course content and main topics: Data analysis for Space Weather

Course “Space Sector Course”
This course examines the domain of space from multiple vantage points — space as a business, a way of life, as industry,
and as a fulfillment of human dreams. In addition, it examines space-related issues that drive key international regulatory,
economic, and global policy. To gain insight into these different dimensions, we examine space through three different lenses:
sub-sectors, technologies, and organizations.
Course content and main topics:  Space Sector

 

ФИО: Подладчикова Татьяна Владимировна

Занимаемая должность (должности): Старший преподаватель

Преподаваемые дисциплины:
1. Анализ экспериментальных данных.
2. Анализ данных для космической погоды.
3. Космический сектор.

Ученая степень: кандидат технических наук 2009

Ученое звание: нет

Наименование направления подготовки и/или специальности:  прикладная математика

Данные о повышении квалификации и/или профессиональной переподготовке: нет

Общий стаж работы: Более 8 лет

Стаж работы по специальности: 8 лет