Interpretation of geomagnetic Pc3, 4 pulsations

Interpretation of geomagnetic Pc4 and Pc3 pulsation

Nanosecond molecular relaxations in lipid bilayers studied by high energy resolution neutron scattering and in-situ diffraction

We report a high energy-resolution neutron backscattering study to investigate slow motions on nanosecond time scales in highly oriented solid supported phospholipid bilayers of the model system DMPC -d54 (deuterated 1,2-dimyristoyl-sn-glycero-3-phoshatidylcholine), hydrated with heavy water. Wave vector resolved quasi-elastic neutron scattering (QENS) is used to determine relaxation times $\tau$, which can be associated with different molecular components, i.e., the lipid acyl chains and the interstitial water molecules in the different phases of the model membrane system. The inelastic data are complemented both by energy resolved and energy integrated in-situ diffraction. From a combined analysis of the inelastic data in the energy and time domain, the respective character of the relaxation, i.e., the exponent of the exponential decay is also determined. From this analysis we quantify two relaxation processes. We associate the fast relaxation with translational diffusion of lipid and water molecules while the slow process likely stems from collective dynamics

Chemically Controlled Bending of Compositionally Anisotropic Microcylinders

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90375/1/anie_201105387_sm_miscellaneous_information.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/90375/2/660_ftp.pd

Comparison of predictive estimates of high‐latitude electrodynamics with observations of global‐scale Birkeland currents

Two of the geomagnetic storms for the Space Weather Prediction Center Geospace Environment Modeling challenge occurred after data were first acquired by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). We compare Birkeland currents from AMPERE with predictions from four models for the 4–5 April 2010 and 5–6 August 2011 storms. The four models are the Weimer (2005b) field‐aligned current statistical model, the Lyon‐Fedder‐Mobarry magnetohydrodynamic (MHD) simulation, the Open Global Geospace Circulation Model MHD simulation, and the Space Weather Modeling Framework MHD simulation. The MHD simulations were run as described in Pulkkinen et al. (2013) and the results obtained from the Community Coordinated Modeling Center. The total radial Birkeland current, ITotal, and the distribution of radial current density, Jr, for all models are compared with AMPERE results. While the total currents are well correlated, the quantitative agreement varies considerably. The Jr distributions reveal discrepancies between the models and observations related to the latitude distribution, morphologies, and lack of nightside current systems in the models. The results motivate enhancing the simulations first by increasing the simulation resolution and then by examining the relative merits of implementing more sophisticated ionospheric conductance models, including ionospheric outflows or other omitted physical processes. Some aspects of the system, including substorm timing and location, may remain challenging to simulate, implying a continuing need for real‐time specification.Key PointsPresents the first comparison between observed field‐aligned currents and models previously evaluated for space weather operational useThe model and observed integrated currents are well correlated, but the ratio between them ranges from 1/3 to 3The 2‐D current densities are weakly correlated with observations implying significant areas for improvements in the modelsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136469/1/swe20415_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136469/2/swe20415.pd

Using a Magnetic Flux Transport Model to Predict the Solar Cycle

We present the results of an investigation into the use of a magnetic flux transport model to predict the amplitude of future solar cycles. Recently Dikpati, de Toma, & Gilman (2006) showed how their dynamo model could be used to accurately predict the amplitudes of the last eight solar cycles and offered a prediction for the next solar cycle - a large amplitude cycle. Cameron & Schussler (2007) found that they could reproduce this predictive skill with a simple 1-dimensional surface flux transport model - provided they used the same parameters and data as Dikpati, de Toma, & Gilman. However, when they tried incorporating the data in what they argued was a more realistic manner, they found that the predictive skill dropped dramatically. We have written our own code for examining this problem and have incorporated updated and corrected data for the source terms - the emergence of magnetic flux in active regions. We present both the model itself and our results from it - in particular our tests of its effectiveness at predicting solar cycles