Statistical modeling of plasmaspheric hiss amplitude using solar wind measurements and geomagnetic indices

Golden, D. I.; Spasojević, M.; Li, W.; Nishimura, Y.

doi:10.1029/2012gl051185

Cited by 28 publications

(55 citation statements)

References 29 publications

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“…In contrast, our solar wind parameters model even without inclusion of the geomagnetic indices has a high performance. We stress that the Golden et al 's [] model is based on a multiple linear regression method while our model is based on an artificial neutral network that is driven by a set of parameters showing best correlation with hiss occurrence. Even though a quantitative comparison between the two models is difficult to make due to the different methods used for and inputs to the hiss models, both models suggest that solar wind parameter‐based hiss model is more likely appropriate to understanding of the hiss waves than using geomagnetic index only.…”

Section: Discussionmentioning

confidence: 99%

Dependence of plasmaspheric hiss on solar wind parameters and geomagnetic activity and modeling of its global distribution

2015

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Accurate knowledge of the global distribution of plasmaspheric hiss is essential for the radiation belt modeling because it provides a direct link to understanding the radiation belt loss in the slot region. In this paper, we study the dependence of hiss activity on solar wind parameters and geomagnetic activity indices using Time History of Events and Macroscale Interactions during Substorms hiss measurements made from 1 July 2008 to 30 June 2012 based on a correlation analysis. We find that hiss amplitudes are well correlated with the preceding solar wind speed V SW , interplanetary magnetic field (IMF) B Z , and interplanetary electric field (IEF) E Y with delay times of 5-6 h for V SW and 3-4 h for IMF B Z and IEF E Y , while the best correlation with the geomagnetic indices, AE, Kp, and SYM-H, occurs at a delay time of 2-3 h for AE and SYM-H and 3-4 h for Kp. Of the solar wind parameters, the dawn-to-dusk component of IEF E Y yields the best correlation with the variation of hiss wave. More interestingly, the global distribution of hiss waves shows a significant dependence on the V SW and IMF B Z : the most intense hiss region tends to occur at prenoon sector for a more southward IMF B Z , while the tendency is opposite with increasing V SW . This implies different origins of hiss activity. Also, we employ an artificial neural network technique to develop models of the global distribution of hiss amplitudes based on the solar wind parameters and geomagnetic indices. The solely solar wind parameter-based model generally results in a higher correlation between the measured and modeled hiss amplitudes than any other models based on the geomagnetic indices. Finally, we use the solar wind parameter-based model to investigate hiss activity during storm events by distinguishing between coronal mass ejection-driven storms and corotating interaction region-driven storms. The result shows that in spite of the differences in the behavior of solar wind parameters between the two storm groups, the different types of storms lead to the similar evolution of hiss waves in overall appearance even though the detailed behavior of hiss activations are different.

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Section: Discussionmentioning

confidence: 99%

Dependence of plasmaspheric hiss on solar wind parameters and geomagnetic activity and modeling of its global distribution

2015

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“…Any of three FBK channels with an intensity below the instrument noise floor are discarded. The noise floors of SCM FBK levels 80–227 Hz, 316–904 Hz, and 1390–4000 Hz are determined empirically to be slightly below 0.96, 1.1, and 4.4 pT, respectively [ Golden et al ., ]. The specific way that we used this data follows Li et al .…”

Section: Global Modeling Of Magnetospheric Chorus Amplitudementioning

confidence: 99%

Empirically modeled global distribution of magnetospheric chorus amplitude using an artificial neural network

et al. 2013

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Accurate knowledge of the global distribution of magnetospheric chorus waves is essential for radiation belt modeling because it provides a direct link to understanding radiation belt losses and acceleration processes. In this paper, we report on newly developed models of the global distribution of chorus amplitudes based on in situ measurements of interplanetary magnetic field (IMF) and solar wind parameters as well as geomagnetic indices using an artificial neural network technique. We find that solar wind speed and IMF BZ are the most influential parameters that affect the evolution of the magnetospheric chorus. The variations of chorus amplitudes in the outer (L ≥ 7) and in the inner (5 ≤ L < 7) regions, respectively, are well correlated with the variations of solar wind speed and IMF BZ. In addition, the solar wind parameter‐based chorus model generally results in a slightly higher correlation between measured and modeled chorus amplitudes than any other models including geomagnetic indices AE, Kp, and Dst. The developed model shows that the chorus is amplified near the prenoon sector during the geomagnetically disturbed conditions. With increasing southward IMF BZ the location of peak chorus amplitude moves from the prenoon sector to the midnight sector, which is due to the enhanced electron injection near midnight. We also present a comparison of diffusive transport simulations for radiation belt electrons interacting with two newly developed chorus models, solar wind parameter‐based and geomagnetic index‐based chorus models. The comparison between two models shows that the modeling outside the plasmapause can affect the dynamic even inside the plasmasphere because the populations outside the plasmapause can act as seed population to radiation belt particles inside the plasmapause. One weakness of our chorus modeling is that it is trained during the early phase of solar cycle 24 where very few strong storms occurred. Therefore, our model might not be valid in reproducing the chorus activity under extremely disturbed conditions, which should be updated in the future once chorus measurements for such conditions become available.

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“…Agapitov et al [] recently used data from the Akebono spacecraft to parametrize hiss at lower L ( L < 2) than was available from CRRES. Data from the Time History of Events and Macroscale Interactions during Substorms spacecraft have been used to create global models of hiss with both Golden et al [] and Kim et al [] examining the role of the time history of the solar wind on hiss wave amplitudes. Analysis of Cluster data has provided new insights on the wave normal distribution of hiss [ Agapitov et al , ], and measurements by both Cluster [ Agapitov et al , ] and Polar [ Tsurutani et al , ] show that hiss is widely distributed in magnetic latitude extending to λ > 45°.…”

Section: Introductionmentioning

confidence: 99%

Global empirical models of plasmaspheric hiss using Van Allen Probes

2015

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Plasmaspheric hiss is a whistler‐mode emission that permeates the Earth's plasmasphere and is a significant driver of energetic electron losses through cyclotron resonant pitch angle scattering. The Electric and Magnetic Field Instrument Suite and Integrated Science instrument on the Van Allen Probes mission provides vastly improved measurements of the hiss wave environment including continuous measurements of the wave magnetic field cross‐spectral matrix and enhanced low‐frequency coverage. Here, we develop empirical models of hiss wave intensity using two years of Van Allen Probes data. First, we describe the construction of the hiss database. Then, we compare the hiss spectral distribution and integrated wave amplitude obtained from Van Allen Probes to those previously extracted from the Combined Release and Radiation Effects Satellite mission. Next, we develop a cubic regression model of the average hiss magnetic field intensity as a function of Kp, L, magnetic latitude, and magnetic local time. We use the full regression model to explore general trends in the data and use insights from the model to develop a simplified model of wave intensity for straightforward inclusion in quasi‐linear diffusion calculations of electron scattering rates.

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Statistical modeling of plasmaspheric hiss amplitude using solar wind measurements and geomagnetic indices

Cited by 28 publications

References 29 publications

Dependence of plasmaspheric hiss on solar wind parameters and geomagnetic activity and modeling of its global distribution

Dependence of plasmaspheric hiss on solar wind parameters and geomagnetic activity and modeling of its global distribution

Empirically modeled global distribution of magnetospheric chorus amplitude using an artificial neural network

Global empirical models of plasmaspheric hiss using Van Allen Probes

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