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Response of the magnetosphereand ionosphere
to solar wind drivers (including complexity)
Mervyn FreemanBritish Antarctic Survey
The importance of Bz
• IMF Bz is a strong influence on many properties of the magnetosphere and ionosphere
• (and their space weather impacts)– electrical currents (GIC)– and electric field -> Joule heating (satellite drag)– particle precipitation (GNSS)– auroral oval location– geosynchronous magnetic field and energetic particles
(satellite anomalies)– etc
The importance of Bz - currents
• IMF Bz is a strong influence on auroral electrojet index, AE– peak magnitude of large-scale currents– hourly averages [Newell et al., J. Geophys. Res., 2007]
The importance of Bz - location
• IMF Bz is a strong influence on the latitude of auroral currents– cusp = poleward edge of auroral oval at noon (instantaneous)– Bs = Bz when Bz < 0, Bs = 0 otherwise (hourly average)
[Newell et al., J. Geophys. Res., 2007]
Bz – not even half the answer
• IMF Bz explains only 37% of variance of the auroral electrojet index, AE– hourly averages– similarly for other quantities
[Newell et al., J. Geophys. Res., 2007]
Not only Bz
• IMF By, B, and solar wind v (and n) also important• still explains only 69% of variance of the auroral electrojet index, AE
– hourly averages
)2/(sin 3/83/23/4 TBvdtd
[Newell et al., J. Geophys. Res., 2007]
Not just about the solar wind
• magnetosphere and ionosphere produce the impact on satellites, power grids, etc, from the solar wind input
Add some physics – models
• Prediction is no better than assuming the average value of the observations over the event, PE = 0 (- - -)
2
2mod
1obs
obs xxPE
• PE = 1 is perfect prediction
[Pulkkinen et al., J. Geophys. Res., 2010]
[Pulkkinen et al., J. Geophys. Res., 2010]
3 challenges
• Non-linearity – chaos
• Memory – substorms
• Turbulence – intermittency
Non-linearity – chaos
• What is the sensitivity of the M-I response to uncertainties in the solar wind driver?
• How big and how quickly do errors grow?
[Merkin et al., J. Geophys. Res., 2013]
[Merkin et al., J. Geophys. Res., 2013]
[Merkin et al., J. Geophys. Res., 2013]
LFM/Wind
[Merkin et al., J. Geophys. Res., 2013]
LFM/THC
[Merkin et al., J. Geophys. Res., 2013]
Ampere
[Merkin et al., J. Geophys. Res., 2013]
Memory – substorms
• Auroral electrojet index, AE, is influenced by past history of the IMF– 3-hour timescale, comparable to that of the substorm cycle
)2/(sin 3/83/23/4 TBvdtd
1
0
1 n
ii
i dtdwn
dtd
[Newell et al., J. Geophys. Res., 2007]
Memory – substorms
• Simple integrate-and-fire model explains substorm timing statistically
• But not so well individually due to non-linearity
fff
E
Time
Onsets
[Freeman and Morley, Geophys. Res. Lett., 2004]
Minimal substorm model
1. Solar wind power input at magnetopause P accumulates energy in magnetotail E.
2. Unique minimum energy state for magnetosphere F exists for given solar wind state P.
3. Magnetotail can only move to lower energy state F when energy threshold C is exceeded.
),( BvPdt
dE
)(PgCF
CEFE when
P
E
F
Time
[Freeman and Morley, Geophys. Res. Lett., 2004]
Turbulence – intermittency
• Wilder fluctuations on short timescales
• Dependent on large-scale state[Consolini and de Michelis, Geophys. Res. Lett., 1998]
Turbulence – intermittency
• Similar properties in space as well as time
• Wild fluctuations vary with spatial scale (and time scale)
[Consolini and de Michelis, Geophys. Res. Lett., 1998]
3 solutions?
• Non-linearity, Memory, Turbulence challenges need:
• Models and Ensemble forecasting– represent evolving uncertainties from Sun to Earth
• Observations and Data assimilation– update prediction with latest information
• Scaling schemes– to handle unresolved scales and extremes
Summary
• Bz is important• but ...
• it’s not even half the answer• magnetosphere and ionosphere produce the impact
from the solar wind input
• M-I observations, models, and research are just as vital