1 / 7

Three results

Model constraints and identifying nonlinear SW/M-I coupling effects Bob Weigel George Mason University. Three results. Conclusion: Detecting nonlinearities and coupling response effects is often complicated by model limitations. Estimation of solar wind/magnetosphere coupling function

arden-young
Download Presentation

Three results

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. Model constraintsand identifying nonlinear SW/M-I coupling effectsBob WeigelGeorge Mason University

  2. Three results Conclusion: Detecting nonlinearities and coupling response effects is often complicated by model limitations. • Estimation of solar wind/magnetosphere coupling function • Seasonal dependence on responsiveness • Solar wind density and magnetosphere responsiveness

  3. Result 1 G(t) is an averaged geomagnetic measurement centered on time t and S(t) is an average solar wind measurement centered on time t. • G(t) ~ S(t) • G(t) ~ S(t)*A(t) • G(t) = h0S(t)+h1S(t-1)+…+hTS(t-T) • If A(t) is correlated with S(t-1), S(t-2), … model (b) improvement over model (a) may be due to fact that (a) and (b) are poor approximations. • Boring result: as T is increased, “best-fit” S looks more like vBs

  4. Result 2 Linear regression of 1-hour averages predicts only about 33% of actual semiannual variation. Model of M-I coupling is 3-hour average of geomagnetic index = 3-hour average of Bs. Is remainder explained by conductance effects? Change in reconnection efficiency?

  5. Result 2 33% ~66% of variation explained when time history of Bs is included. ~75% when solar wind velocity is included In auroral zone, result is 50% of semiannual variation is explained by solar wind (up from 0%) [Weigel, 2007]

  6. Result 3 • Many studies have looked at modifying input, S(t), in Burton equation dDst*/dt = -Dst*/t+ S(t) • Most recent finding is that modifying S(t) by Pdyn1/2 gives improvement • Others have looked at modifying t. • What if you don’t constrain to 1-D ODE?

  7. Burton model is constrained to this response function Normalized Dst response Weigel 2010 vBs One finding is that Nsw modifies response efficiency, not Pdyn.

More Related