scholarly journals Analyzing electric field morphology through data-model comparisons of the Geospace Environment Modeling Inner Magnetosphere/Storm Assessment Challenge events

2006 ◽  
Vol 111 (A11) ◽  
Author(s):  
Michael W. Liemohn ◽  
Aaron J. Ridley ◽  
Janet U. Kozyra ◽  
Dennis L. Gallagher ◽  
Michelle F. Thomsen ◽  
...  
Keyword(s):  
Electric Field ◽  
Data Model ◽  
Environment Modeling ◽  
Inner Magnetosphere ◽  
Model Comparisons

scholarly journals Paleovariability: Data Model Comparisons

2014 ◽  
Vol 22 (2) ◽  
pp. 102-102 ◽  
Author(s):  
Chris Brierley ◽  
Kira Rehfeld
Keyword(s):  
Data Model ◽  
Model Comparisons

scholarly journals Global estimates of plasmaspheric losses during moderate disturbance intervals

2010 ◽  
Vol 28 (1) ◽  
pp. 27-36 ◽  
Author(s):  
M. Spasojevic ◽  
B. R. Sandel
Keyword(s):  
Solar Wind ◽  
Electric Field ◽  
Boundary Layers ◽  
Total Mass ◽  
Density Ratio ◽  
Individual Case ◽  
Number Density ◽  
Inner Magnetosphere ◽  
Moderate Disturbance ◽  
Global Estimates

Abstract. For a set of five moderate disturbance events, we calculate the total number of He+ ions removed the plasmasphere using calibrated global EUV images. In each of the events, between ~0.6 and 2.2×1030 He+ ions are removed from a region of the inner magnetosphere from L=1.5 to 5.5. This loss constitutes between 20% and 42% of the initial He+ distribution. The lost percentage is correlated with the number of hours of strongly positive solar wind electric field (Ey>2.5 mV/m). Also, the total amount of material removed from the plasmasphere is estimated by using several values of the He+ to H+ number density ratio. The total mass lost is found to be in the range of 20 to 80 metric tons although for each individual case the estimate can vary by over 50% depending on assumed density ratio. We also attempt to distinguish between losses to the ionosphere and losses to the dayside boundary layers by estimating losses interior and exterior to the newly formed plasmapause boundary. For the events studied, losses inside the new plasmapause constitute between 24% to 54% of the total number of He+ ions lost.

Temporal and spatial considerations in data-model comparisons involving transient paleoclimatic simulations

2021 ◽  
Author(s):  
Patrick Bartlein ◽  
Sandy Harrison
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Data Model ◽  
Environmental Data ◽  
Climatic Effects ◽  
Data Archiving ◽  
Model Comparisons ◽  
Climate Reconstructions ◽  
Temporal And Spatial ◽  
Further Development

<p>The increasing availability of time-evolving or transient palaeoclimatic simulations makes it imperative to develop “best-practices” for comparing simulations with palaeoclimatic observations including both climate reconstructions and environmental data.  There are two sets of considerations, temporal and spatial, that should guide those comparisons.  The chronology of simulations can in some ways be viewed as exact, as determined by the insolation forcing, but data archiving and reporting conventions, such as reporting summaries that use the modern calendar (that leads to the long-recognized palaeo-calendar effect) can, if ignored, lead to “built-in” temporal offsets of thousands of years in such features as temperature or precipitation maxima or minima.  Likewise, there are age uncertainties in time series of palaeoclimatic data that are often ignored, despite the fact that these are large during “climatically interesting times” such as the Younger Dryas chronozone.  Similarly, although model resolution is increasing, there is still a mismatch in topography (and its climatic effects) between a model and the “real world” sensed by the palaeoclimatic data sources. </p><p>There are existing approaches for dealing with some of these issues, such as calendar-adjustment programs, Monte-Carlo approaches for describing age uncertainties in palaeoclimate time series, or clustering approaches for objectively defining appropriate regions for the calculation of area averages, but there is certainly room for further development.  This abstract is intended to serve as platform for discussion of some of best practices for data-model comparisons in transient mode.</p>

scholarly journals Magnetospheric convection electric field dynamics andstormtime particle energization: case study of the magneticstorm of 4 May 1998

2004 ◽  
Vol 22 (2) ◽  
pp. 497-510 ◽  
Author(s):  
G. V. Khazanov ◽  
M. W. Liemohn ◽  
T. S. Newman ◽  
M.-C. Fok ◽  
A. J. Ridley
Keyword(s):  
Electric Field ◽  
Electric Fields ◽  
Transport Model ◽  
Storm Event ◽  
Inner Magnetosphere ◽  
Narrow Channels ◽  
Near Earth Space ◽  
Magnetospheric Convection ◽  
Convection Electric Field ◽  
Seed Population

Abstract. It is shown that narrow channels of high electric field are an effective mechanism for injecting plasma into the inner magnetosphere. Analytical expressions for the electric field cannot produce these channels of intense plasma flow, and thus, result in less entry and adiabatic energization of the plasma sheet into near-Earth space. For the ions, omission of these channels leads to an underprediction of the strength of the stormtime ring current and therefore, an underestimation of the geoeffectiveness of the storm event. For the electrons, omission of these channels leads to the inability to create a seed population of 10-100 keV electrons deep in the inner magnetosphere. These electrons can eventually be accelerated into MeV radiation belt particles. To examine this, the 1-7 May 1998 magnetic storm is studied with a plasma transport model by using three different convection electric field models: Volland-Stern, Weimer, and AMIE. It is found that the AMIE model can produce particle fluxes that are several orders of magnitude higher in the L = 2 – 4 range of the inner magnetosphere, even for a similar total cross-tail potential difference. Key words. Space plasma physics (charged particle motion and acceleration) – Magnetospheric physics (electric fields, storms and substorms)

Data‐model comparisons for scattering by a bubbly sediment

2003 ◽  
Vol 114 (4) ◽  
pp. 2317-2317
Author(s):  
Darrell R. Jackson ◽  
Dajun Tang
Keyword(s):  
Data Model ◽  
Model Comparisons
Sign in / Sign up

Export Citation Format

Share Document