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Space weatherSpace weather
Henrik Lundstedt
Swedish Institute of Space Physics, Lund, Sweden
www.lund.irf.se
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OutlineOutline
• Solar activity - the driver of space weather
• Forecast methods
• Applications
• Implementations for users
• Forecast centers (ISES/RWCs)
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Space weather was mentioned for the first time in Swedish media 1991
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.
We started early in LundWe started early in Lund
HD 1981 (cycle 21)
SDS 1991 (cycle 22)SDS 1991 (cycle 22) Arbetet 1981 (cycle 21)
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Why are space weather programs (ILWS/ESASWP) important?
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
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Solar activitySolar 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
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Solar observations with the new Swedish solar telescope on La Palma
Solar observations with the new Swedish solar telescope on La Palma
2002
1980-2002
1951-1980
Anacapri, Capri, Italy
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Solar OrbiterSolar Orbiter
The orbit at heliocentric distanceof 45 Rs and out-of ecliptic atheliographic latitudes of up to38 degrees gives a 0.”05 resolutionand a possibility to study thepolar field that determines the11 years solar cycle.
Launch 2009.
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SDOSDO
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SOHO has given us a totally new picture of the Sun- always activeSOHO 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
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QuickTime och enCinepak-dekomprimerare
krävs för att kunna se bilden.
The oscillations reveal solar interior
The oscillations reveal solar interior
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MDI/SOHO reveals the interiorand explains surface activity
MDI/SOHO reveals the interiorand explains surface activity
MDI shows how magnetic elements form sunspots
MDI shows how the dynamo changes (1.3y)
Sunspots are footpointsof emerging magnetic flux tubes
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Change of the nature of solar activity 1850 - 2000
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.
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Wavelet power spectra reveals solar activity periodicities
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
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Sunspot solar cycles 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!
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Solar activity and North Atlantic Oscillation Index
Solar activity and North Atlantic Oscillation Index
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Solar Polar FieldSolar Polar Field
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The solar magnetic field further expand and CMEs occur
The solar magnetic field further expand and CMEs occur
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Proton events give positiveNAO within days!
Fast halo coronal mass ejection
Daily solar activity and NAODaily solar activity and NAO
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March 16 - April 10, 1999 (1 min time resolution)
Solar mean field and wavelet power spectra
Solar mean field and wavelet power spectra
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Wavelet power spectra of MDI magnetic mean field
Wavelet power spectra of MDI magnetic mean field
Upper panel shows for 53 CME events.Lower panel shows for times without CMEs.
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Forecast MethodsForecast 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
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Neural network prediction of Dst, 1990
Neural network prediction of Dst, 1990
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Download Lund Dst model in Java and Matlab (www.lund.irf.se/dst/models)
Download Lund Dst model in Java and Matlab (www.lund.irf.se/dst/models)
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Workshops arranged by usWorkshops arranged by us
Workshops on ”Artificial Intelligence Applications in Solar-Terrestrial Physics” were held in Lund 1993 and 1997.
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ApplicationsApplicationsInput parameters Output KBNM
methodReference
Daily sunspot number Daily sunspot number SOM and MLP
Liszka 93;97
Monthly sunspot number Date of solar cycle max and amplitude
MLP and Elman
Macpherson et al., 95, Conway et al, 98
Monthly sunspot number and aa
Date of solar cycle max and amplitude
Elman Ashmall and Moore, 98
Yearly sunspot number Date of solar cycle max and amplitude
MLP Calvo et al., 95
McIntosh sunspot class & MW magn complex.
X class solar flare MLP expert system
Bradshaw et al., 89
Flare location, duration
X-ray and radio flux
Proton events MLP Xue et al., 97
X-ray flux Proton events Neuro- fuzzy system
Gabriel et al., 00
Photospheric magnetic field expansion factor
Solar wind velocity 1-3 days ahead
RBF & PF MHD
Wintoft and Lundstedt 97;99
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ApplicationsApplications
Input parameters Output KBNM method Reference
Solar wind n, V, Bz
Relativistic electrons in Earth magnetosphere hour ahead
MLP Wintoft and Lundstedt, 00
Solar wind n,V, Bz, Dst
Relativistic electrons hour ahead
MLP, MHD, MSFM
Freeman et al., 93
Kp Relativistic electrons day ahead
MLP Stringer and McPherron, 93
Solar wind V from photospheric B
Daily geomagnetic Ap index
MLP Detman et al., 00
Ap index Ap index MLP Thompson, 93
Solar wind n, V, Bz
Kp index 3 hours ahead MLP Boberg et al., 00
Solar wind n, V, B,Bz
Dst 1-8 hours ahead MLP, Elman Lundstedt, 91; Wu and Lundstedt, 97
Solar wind n, V, B,Bz
AE 1 hour ahead Elman Gleisner and Lundstedt, 00
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ApplicationsApplications
Input parametrs Output KBNM method References
Solar wind V2Bs, (nV2)1/2, LT, local geomag xe, Yw
Local geomagnetic field X,Y
MLP and RBF Gleisner and Lundstedt 00
Solar wind n,V, Bz None, weak or strong aurora
MLP Lundstedt et al., 00
foF2 foF2 1 hour ahead MLP Wintoft and Lundstedt, 99
AE, local time, seasonal information
foF2 1-24 hours ahead
MLP Wintoft and Cander, 00
foF2, Ap, F10.7 cm 24 hours ahead MLP Wintoft and Cander, 99
Kp Satellite anomalies MLP Wintoft and Lundstedt 00
Solar wind n, V, Bz GIC Elman, MLP Kronfeldt et al., 01
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Real-time forecasts and warnings based on KBN Real-time forecasts and warnings based on KBN
Solar wind observations with ACE make accurate forecasts 1-3 hours ahead possible.
Solar observations with SOHO make warnings 1-3days ahead possible.
Solar input data
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The NAO response on increased solar wind E, one month later! That makes forecasts one month ahead possible.
North Atlantic Oscillation and solar wind activity
North Atlantic Oscillation and solar wind activity
11 års, 1.3 variations are seen both insolar wind and NAO.
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ESA/Lund Space Weather Forecast Service
ESA/Lund Space Weather Forecast Service
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Near and farside solar activity from MDI/SOHO observationsNear and farside solar activity from MDI/SOHO observations
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Latest information on arrival of halo CME at L1
Latest information on arrival of halo CME at L1
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Latest info on forecasts of satellite anomalies (SAAPS)Latest info on forecasts of
satellite anomalies (SAAPS)
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Latest information on forecasts of Kp, Dst, AE and GIC
Latest information on forecasts of Kp, Dst, AE and GIC
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Forecast Centers (ISES/RWC)
Forecast Centers (ISES/RWC)
David Boteler, Director (Canada)Henrik Lundstedt, Deputy Director
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Today’s space weatherToday’s space weather
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Forecasts of aurora as SMS, voice messages or WAP service
Forecasts of aurora as SMS, voice messages or WAP service
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Knowledge-Based Neural Models
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 fita 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 ofdiff 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 bedicovered.
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Cosmic ray variation at time ofsolar wind IR and VAI (storminess)
Solar-weather relations 1981Solar-weather relations 1981
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Medelvärdesbildade longitudinella fotosfärsmagnetfältet
1975-2000