Influence of solar wind density on ring current response R.S. Weigel George Mason University.

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Presentation transcript:

Influence of solar wind density on ring current response R.S. Weigel George Mason University

Geoeffectiveness – magnitude of a solar wind driver of geomagnetic activity Geoefficiency – amount of geomagnetic activity for a fixed magnitude of a solar wind driver

2x Input Output Efficiency=1 (unit change in input results in unit change output)

2x Input Output Efficiency=0 (unit change in input results in zero change output)

More clarification Polar cap saturation is a classic example of geoefficiency. For low levels of interplanetary electric field vBs, the polar cap potential linearly increases with vBs. For high values it saturates. The geoeffective parameter is vBs. For high values, the geoeffective parameter is less geoeffective. Another way of thinking about geoeffective versus geoefficient is to consider an instrument with a temperature sensitivity. The output of the instrument depends on the ambient magnetic field. But for high temps, the output is less for a given input magnetic field. Temperature affects the geoefficiency. Temperature is not a driver in the traditional sense, but it does affect the output. (Technically, if you held the magnetic field constant and changed temperature, you would see a change in output, but physically, it is not usually cast in the system of equations as a driver, but rather a constant parameter that is slowly changing.

Mechanisms Chen et al. [1994], Jordanova et al., [1998] and others – Simulations show ring current / N ps connection Borovsky [1998] – N sw pulses lead to response at geosynchronous; Thomson [1998] – N ps, D st * correlation; Smith et al., [1999] – D st has N sw dependence that is independent of vB s at 3 hour time lag; O’Brien et al., [2000] – With more storms, no independent D st dependence on N sw Lopez et al., [2004] – High compression ratio leads to higher reconnection rate Boudouridis et al., [2005] – Dynamic pressure and geoefficiency of cross-polar-cap potential in event study Lavraud et al. [2006] – CME and CIR storms had different epoch averages when CME or CIR was preceded by B z >0

Approaches for computing geoefficiency 1.Linear filter model – Compute a linear filter (impulse response) model under different N sw conditions. Efficiency is area under impulse response curve. 2.Integral ratios – Compare integrated input to integrated output for many events. Efficiency is slope computed using values of integrated output to integrated input for many events. 3.Epoch average ratio – Compute epoch averages first and then perform integral analysis on these curves. Efficiency is ratio of integrated epoch average of output to integrated epoch average input.

1. Linear Filter Approach

Impulse response function (IRF)

Pressure correction

Modeled -D st for htht t = High N sw Low N sw vB s

Result 1: Similar result if sorted by 4-hour running average of N sw htht t = High N sw Low N sw Modeled -D st for

Result 2: Similar result if sorted by P dyn htht t = High N sw Low N sw Modeled -D st for

Result 3: N sw belongs in transfer function, not driver htht t = High N sw Low N sw Modeled -D st for

    is geoefficiency at lowest N sw value Average N sw [#/cc]

2. Integral ratio approach

N sw [#/cc]

3. Epoch average approach

High N sw events (189) Low N sw events (207) 5N sw vB s /100 -D st vB s /100 5N sw -D st

High N sw events (189) Low N sw events (207) 5N sw vB s /100 -D st vB s /100 5N sw -D st

  is geoefficiency at lowest N sw value Average N sw [#/cc]  

Summary Multiple approaches show geoefficiency depends on N sw N sw should appear in transfer function, not coupling function Geoefficiency differences most simply explained by N sw rather than P dyn No significant difference (< 3% in RMS error) if more complex drivers are used Epoch average method is least reliable