1 / 40

Space weather

Space weather. Henrik Lundstedt Swedish Institute of Space Physics, Lund, Sweden www.lund.irf.se. Outline. Solar activity - the driver of space weather Forecast methods Applications Implementations for users Forecast centers (ISES/RWCs). We started early in Lund.

bryony
Télécharger la présentation

Space weather

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Space weather Henrik Lundstedt Swedish Institute of Space Physics, Lund, Sweden www.lund.irf.se

  2. Outline • Solar activity - the driver of space weather • Forecast methods • Applications • Implementations for users • Forecast centers (ISES/RWCs)

  3. We started early in Lund Space weather was mentioned for the first time in Swedish media 1991 HD 1981 (cycle 21) SDS 1991 (cycle 22) Arbetet 1981 (cycle 21) SDS 1991 (cycle 22) The US National Space Weather Program 1995: Space weather refers to conditions on the sun, and in the solar wind, magnetosphere, ionosphere and thermosphere that can influence the performance and reliability of space-borne and ground-based technological systems and Endanger human life or health. ESA Space Weather Programme started in April 1999.

  4. Why are space weather programs (ILWS/ESASWP) important? • They raise fundamental questions within space physics (about e.g. solar activity within solar physics) • They require a new scientific approach: an interdisciplinary approach (Knowledge from many disciplines must be used: solar physics, interplanetary, magnetospheric, ionospheric, atmospheric physics, physics about dynamic nonlinear systems, IHS and so on) • They show how fundamental forecasting is within science and again that a new approach is needed (Knowled-based neural models) • Forecasts of real-world events are also the real test of a model

  5. Solar activity • Solar activity is the driver of space weather • Better understanding and improved forecasts of solar activity are therefore a prime goal within space weather programs and a real challenge • Let me therefore now discuss new observation facilities, some new research results and attempts to forecast solar activity

  6. Solar observations with the new Swedish solar telescope on La Palma Anacapri, Capri, Italy 1951-1980 1980-2002 2002

  7. Solar Orbiter The orbit at heliocentric distance of 45 Rs and out-of ecliptic at heliographic latitudes of up to 38 degrees gives a 0.”05 resolution and a possibility to study the polar field that determines the 11 years solar cycle. Launch 2009.

  8. SDO

  9. SOHO has given us a totally new picture of the Sun- always active • Solar Heliospheric Observatory was launched on December 2, 1995 • SOHO carries three instruments observing the solar interior, six the solar corona and three the solar wind

  10. The oscillations reveal solar interior

  11. MDI/SOHO reveals the interiorand explains surface activity MDI shows how the dynamo changes (1.3y) Sunspots are footpoints of emerging magnetic flux tubes MDI shows how magnetic elements form sunspots

  12. Change of the nature of solar activity 1850 - 2000 High frequency content (2-4 days period) decreases with time, while the low frequency content (20-128 days) increases with time during the 150 years period. Daily sunspot numbers were used.

  13. Wavelet power spectra reveals solar activity periodicities WSO solar mean field May 16, 1975 - March 13, 2001 Wavelet power spectra shows 13,5, days 27 days, 154 days, 1.3 years periodicities

  14. Sunspot solar cycles Schwabe found the 11- year sunspot solar cycle. R = k(10g + f). Gleissberg found the 80-90 years cycle. Maunder-Spörer 207 years cycle, Houtermans cycle 2272 years and Sharma 100 000 years cycle. The two peaks of solar activity, 1.3 years separated!

  15. Solar activity and North Atlantic Oscillation Index

  16. Solar Polar Field

  17. The solar magnetic field further expand and CMEs occur

  18. Daily solar activity and NAO Proton events give positive NAO within days! Fast halo coronal mass ejection

  19. Solar mean field and wavelet power spectra March 16 - April 10, 1999 (1 min time resolution)

  20. Wavelet power spectra of MDI magnetic mean field Upper panel shows for 53 CME events. Lower panel shows for times without CMEs.

  21. Forecast Methods • First principles (MHD models) (MHD models of the whole Sun-Earth Connection are good at explaining and good for education, but not so good at forecasting.) • Linear and nonlinear filters (MA, ARMA, NARMA) MA filter applied as linear filter of AL.The impulse response Dst is predicted with an ARMA filter. function H of the magnetospheric system is convolved with a sequence of solar wind inputs (Problems: Linearity, nonstationary systems, high dimensions) • Knowledge-Based Neural Models (KBNM) i.e. Knowledge (Diff eqs of physics, dynamical system analysis, filters, information theory, expert, fuzzy rules) based neural networks

  22. Neural network prediction of Dst, 1990

  23. Download Lund Dst model in Java and Matlab (www.lund.irf.se/dst/models)

  24. Workshops arranged by us Workshops on ”Artificial Intelligence Applications in Solar-Terrestrial Physics” were held in Lund 1993 and 1997.

  25. Applications

  26. Applications

  27. Applications

  28. Real-time forecasts and warnings based on KBN Solar input data Solar observations with SOHO make warnings 1-3 days ahead possible. Solar wind observations with ACE make accurate forecasts 1-3 hours ahead possible.

  29. North Atlantic Oscillation and solar wind activity The NAO response on increased solar wind E, one month later! That makes forecasts one month ahead possible. 11 års, 1.3 variations are seen both in solar wind and NAO.

  30. ESA/Lund Space Weather Forecast Service

  31. Near and farside solar activity from MDI/SOHO observations

  32. Latest information on arrival of halo CME at L1

  33. Latest info on forecasts of satellite anomalies (SAAPS)

  34. Latest information on forecasts of Kp, Dst, AE and GIC

  35. Forecast Centers (ISES/RWC) David Boteler, Director (Canada) Henrik Lundstedt, Deputy Director

  36. Today’s space weather

  37. Forecasts of aurora as SMS, voice messages or WAP service

  38. Knowledge-Based Neural Models The basis of using neural networks as mathematical models is ”mapping”. Given a dynamic system, a neural network can model it on the basis of a set of examples encoding the input/output behavior of the system. It can learn the mathematical function underlying the system operation (i.e. generalize not just fit a curve), if the network is designed (architechure, weights) and trained properly (learning algorithm). Both architechure and weights can be determined from differential equations which describe the causal relations between the physical variables (solution of diff eq is approximized by a RBF). The network (KBN) is then trained with observations. The architechure (number of input and hidden nodes) can also be determined from dynamic system analysis (reconstruction of state space from time series gives dimension). Neural networks can discover laws from regularities in data (Newton’s law e.g.). If one construct a hierachy of neural networks where networks at each level can learn knowledge at some level of abstraction, even more advanced laws can be dicovered.

  39. Solar-weather relations 1981 Cosmic ray variation at time of solar wind IR and VAI (storminess)

  40. Medelvärdesbildade longitudinella fotosfärsmagnetfältet 1975-2000

More Related