Abstract Long‐term variations of South Atlantic anomaly (SAA) are generally derived by fitting a Gaussian‐like function to an averaged distribution of the proton flux at a certain altitude accumulated over time periods for a month or longer. These data do not show the short‐term variation of SAA arising from geomagnetic storm effects whose time scale is less than a month. To investigate the short‐term variations, the features of SAA for the high‐energy protons detected by NOAA Polar Orbiting Environmental Satellites during 1998–2008 have been investigated with a 5 day running average method. It is found that the two SAA parameters for three proton channels reflect the maximal proton flux in SAA and the extension of SAA decreases several percent during geomagnetic storms. Possible reasons for the decreases of the two SAA parameters for high‐energy protons are discussed. Proton losses at the outer boundary of the inner radiation belt can be explained by the field line curvature scattering mechanism, while the decrease of the proton flux near the center of SAA is probably caused by the enhanced neutral atmospheric density during geomagnetic storms. The study of the behavior of high‐energy protons in SAA is useful for understanding of storm time and long‐term variations of the radiation environment near Earth and for constructing dynamic radiation belt models.
Abstract Using the electron flux measurements obtained from five satellites (GOES 15 and POES 15, 16, 18, and 19), we investigate the flux variations of radiation belt electrons during forty solar wind dynamic pressure pulses identified between September 2012 and December 2014. By utilizing the mean duration of the pressure pulses as the epoch timeline and stretching or compressing the time phases of individual events to normalize the duration by means of linear interpolation, we have performed normalized superposed epoch analysis to evaluate the dynamic responses of radiation belt energetic electrons corresponding to various groups of solar wind and magnetospheric conditions in association with solar wind dynamic pressure pulses. Our results indicate that by adopting the timeline normalization we can reproduce the typical response of the electron radiation belts to pressure pulses. Radiation belt electron fluxes exhibit large depletions right after the P dyn peak during the periods of northward interplanetary magnetic field (IMF) B z and are more likely to occur during the P dyn pulse under southward IMF B z conditions. For the pulse events with large negative values of ( Dst ) min , radiation belt electrons respond in a manner similar to those with southward IMF B z , and the corresponding postpulse recovery can extend to L ~ 3 and exceed the prepulse flux levels. Triggered by the solar wind pressure enhancements, deeper earthward magnetopause erosion provides favorable conditions for the prompt electron flux dropouts that extend down to L ~ 5, and the pressure pulses with longer duration tend to produce quicker and stronger electron flux decay. In addition, the events with high electron fluxes before the P dyn pulse tend to experience more severe electron flux dropouts during the course of the pulse, while the largest rate of electron flux increase before and after the pulse occurs under the preconditioned low electron fluxes. These new results help us understand how electron fluxes respond to solar wind dynamic pressure pulses and how these responses depend on the solar wind and geomagnetic conditions and on the preconditions in the electron radiation belts.
Meandering river reservoirs are essential targets for hydrocarbon exploration, although their characterization can be complex due to their multiscale heterogeneity. Multipoint geostatistics (MPS) has advantages in establishing reservoir architectural models. Training image (TI) stationarity is the main factor limiting the uptake of MPS modeling algorithms in subsurface modeling. A modeling workflow was designed to reproduce the distribution of heterogeneities at different scales in the Miocene Minghuazhen Formation of the Yangerzhuang Oilfield in the Bohai Bay Basin. Two TIs are established for different scales of architecture. An initial unconditional model generated with a process-based simulation method is used as the megascale TI. The mesoscale TI of the lateral accretion layers is characterized by an uneven spatial distribution of mudstone in length, thickness, frequency, and spacing. Models of different scales are combined by the probability cube obtained by lateral accretion azimuthal data as an auxiliary variable. Moreover, the permeability function sets are more suitable than the porosity model for collaboratively simulating the permeability model. Model verification suggests this workflow can accurately realize the multiscale stochastic simulation of channels, point bars, and lateral accretion layers of meandering fluvial reservoirs. The produced model conforms geologically realistically and enables the prediction of interwell permeability variation to enhance oil recovery.
The plasma in situ detector is a multi-sensor package designed to in situ measure the bulk parameters of the local ionospheric plasma. The plasma in situ detector is comprised of three sensors: Langmuir probe (LP), retarding potential analyzer (RPA) and ion drift meter (IDM). LP measures electron density and temperature. RPA measures ion density, temperature and ion horizontal velocity. IDM measures the transverse horizontal component of the ram velocity. The plasma in situ detector has been installed outside the wentian module cabin, and the boom has been successfully deployed which extends the spherical sensor of LP beyond the sheath of the cabin. RPA and IDM were installed at the front of the experiment package, with the horizontal axis direction along the forward flight direction of the space station. This paper discusses the general performance characteristics of the in situ detector, the functional performance of each sensor, and initial results of some classical ionospheric features being observed.
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