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1 Simulating a Solar Cycle My impetus (in addition to this GEM-FG):My impetus (in addition to this GEM-FG): –Attended 2 CDAWs (2005, 2007) on large geomagnetic.

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Presentation on theme: "1 Simulating a Solar Cycle My impetus (in addition to this GEM-FG):My impetus (in addition to this GEM-FG): –Attended 2 CDAWs (2005, 2007) on large geomagnetic."— Presentation transcript:

1 1 Simulating a Solar Cycle My impetus (in addition to this GEM-FG):My impetus (in addition to this GEM-FG): –Attended 2 CDAWs (2005, 2007) on large geomagnetic storms –Examined all intense storms (Dst min ≤ -100 nT) for solar cycle 23 (1996-2005) –Considered solar sources and geospace consequences Getting diverse communities to talk to each otherGetting diverse communities to talk to each other Challenge issued to modelers:Challenge issued to modelers: –Simulate all of these events

2 2 Methodology Run HEIDI for all 90 eventsRun HEIDI for all 90 events –HEIDI: Hot Electron and Ion Drift Integrator –Formerly known as the Michigan version of RAM (Fok et al., 1993; Jordanova et al., 1996) Choose a very simplistic set-upChoose a very simplistic set-up –Dipole magnetic field –Volland-Stern electric field (shielded, Kp driven) –LANL moments for outer boundary condition –Just the major species: H + and O +

3 3 Data-Model Comparisons Limit it to only Dst* for this initial studyLimit it to only Dst* for this initial study Definition of "observed Dst*":Definition of "observed Dst*": Definition of "simulated Dst*":Definition of "simulated Dst*":

4 4 Intense Storms of Solar Cycle 23 The numbers:The numbers: –90 storms in all (1996-2005) –79 storms with "good" main phase LANL data –Zhang et al. [JGR, 2007] published solar sources of all 90 events Jie Zhang of GMU, not Jichun Zhang my PhD studentJie Zhang of GMU, not Jichun Zhang my PhD student

5 5 Data-Model Statistics Remember, the only data is Dst*Remember, the only data is Dst*

6 6 More on Data-Model Statistics Let's look at some of the numbersLet's look at some of the numbers

7 7 V-S E-field and the ring current V-S driving systematically underestimates the observed Dst*V-S driving systematically underestimates the observed Dst* –Note: Dst* includes C IC –Sheath storms are better than other driver categories Esp. for large eventsEsp. for large events

8 8 DPS/Dst* vs Dst* Here is a better plotHere is a better plot –Underestimation is clearly seen Not the same as previous plot:Not the same as previous plot: –This is for a 12-h average (pre-peak) for each storm

9 9 DPS and Input Input function:Input function: –A(kp) * Ncorr –Good measure of the resulting ring current intensity in the code –Esp. for CIR-driven and MC-driven events

10 10 Some Explanation Young et al. [1982] composition formula:Young et al. [1982] composition formula: N corr : N MPA corrected for compositionN corr : N MPA corrected for composition Input function: estimate of ring current source termInput function: estimate of ring current source term

11 11 Maynard and Chen Convection Kp-driven shielded Volland-Stern 2-cell convection from Maynard and Chen [1975]Kp-driven shielded Volland-Stern 2-cell convection from Maynard and Chen [1975]

12 12 DPS and either input by itself Not nearly as good as the combined input functionNot nearly as good as the combined input function –Esp. for sheath- driven storms –Kp: plots have a kink near -70 nT –Above this, Kp is uncorrelated

13 13 DPS and Composition Two trends in all plots:Two trends in all plots: –Smaller than -170 nT: UncorrelatedUncorrelated Most values < unityMost values < unity –Larger than -200 nT: Still uncorrelatedStill uncorrelated Most values > unityMost values > unity –Is O + dominance necessary for large Dst events? Plots imply this to be the case...Plots imply this to be the case...

14 14 Conclusions on VS-driven HEIDI Works well for sheath-driven stormsWorks well for sheath-driven storms –Inner magnetosphere simple for these storms? Not so good for CIR- or MC-driven stormsNot so good for CIR- or MC-driven storms –Longer events...internal feedback important? Kp-DPS correlations have a kinkKp-DPS correlations have a kink –Driving saturates and other terms control Dst? O + /H + -DPS correlations are bimodalO + /H + -DPS correlations are bimodal –H + dominates for DPS min > -170 nT, O + for bigger storms –O+ necessary for large events? Local time asymmetry not dependent on driverLocal time asymmetry not dependent on driver –Probably due to constancy of the VS potential pattern

15 15 Extra Slides

16 16 Data Analysis Results even before we run the codeResults even before we run the code

17 17 More on Data Analysis Let's look at some interesting numbersLet's look at some interesting numbers

18 18 Dst and Input Some correlation, but not perfectSome correlation, but not perfect –Less good relative to DPS-to-Input Final Dst depends on both in a complicated wayFinal Dst depends on both in a complicated way –Time history –Double rings occur

19 19 Ring Current Simulations of the Storms of Solar Cycle 23 Mike Liemohn University of Michigan to GEM Space Radiation Climatology Focus Group June 26, 2008


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