An improved forecast system for relativistic electrons at geosynchronous orbit

Turner, D. L.; Li, Xiaocan; Roziers, E. Burin des; Monk, S.

doi:10.1029/2010sw000647

Cited by 12 publications

(22 citation statements)

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“…The declining phase and minimum of solar cycle 23 provide an independent test of the model. This model has also been revised to make real‐time forecasts one and two days ahead of >2 MeV electron fluxes at GEO using real‐time solar wind data from ACE, normalized with real‐time GOES measurements at GEO [e.g., Li , 2004; Turner and Li , 2008; Turner et al , 2011].…”

Section: Introductionmentioning

confidence: 99%

Behavior of MeV electrons at geosynchronous orbit during last two solar cycles

Temerin

Baker

et al. 2011

J. Geophys. Res.

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[1] A comparison of MeV electron measurements at geosynchronous orbit, GEO, with solar wind shows that the MeV electron prediction model developed for GEO using data from the declining phase of solar cycle 22 (1995-1996) works well for the declining phase of solar cycle 23 (2006-2008), indicating that the MeV electron flux has a predictable and systematic response to the solar wind. The same comparison for solar maximum (2000)(2001)(2002)(2003) shows that the model works less well partly because it does not match the high flux cutoff seen in the data and partly because it does not reproduce the sudden drops in flux that occur when the magnetopause is close to GEO. The model also reproduces the nonlinear correlation of the solar wind speed with the log of the MeV electron flux seen at GEO. An examination of 15 yr of solar wind and the MeV electron data shows that geomagnetic activity driven by a southward orientation of the interplanetary magnetic field, IMF, is a necessary condition for MeV electron enhancements at GEO and that high-speed solar wind are not necessary. The reason that high-speed solar wind is almost always associated with the enhancement of MeV electrons is mainly because high-speed solar wind almost always has some southward components of the IMF.

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Section: Introductionmentioning

confidence: 99%

Behavior of MeV electrons at geosynchronous orbit during last two solar cycles

Temerin

Baker

et al. 2011

J. Geophys. Res.

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“…In the upper panel it can also be seen that the flux decay is reproduced by the model. (Turner et al 2011).…”

Section: Resultsmentioning

confidence: 99%

“…In addition, as these models are based on averages taken over large timescales, they fade away the characteristics of physical processes that drive the dynamic of particle flux variations. Recently, space weather preoccupations have therefore encouraged the development of dynamic models, either physics based (Beutier & Boscher 1995;Fung 1996;Glauert & Horne 2005;Koller et al 2007;Fok et al 2008;Albert et al 2009;Subbotin & Shprits 2009) or empirical (O'Brien & McPherron 2003;Ling et al 2010;Turner et al 2011). The physics-based models are mostly data-driven physical models that incorporate a radial diffusion code and where the measured data provide the boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

The transient observation-based particle (TOP) model and its potential application in radiation effects evaluation

Benck

Cyamukungu

Cabrera

et al. 2013

J. Space Weather Space Clim.

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The evaluation of the radiation hazards on components used in space environment is based on the knowledge of the radiation level encountered on orbit. The models that are widely used to assess the near-Earth environment for a given mission are empirical trapped radiation models derived from a compilation of spacecraft measurements. However, these models are static and hence are not suited for describing the short timescale variations of geomagnetic conditions. The transient observation-based particle (TOP)-model tends to break with this classical approach by introducing dynamic features based on the observation and characterization of transient particle flux events in addition to classical mapping of steady-state flux levels. In order to get a preliminary version of an operational model (actually only available for electrons at low Earth orbit, LEO), (i) the steady-state flux level, (ii) the flux enhancements probability distribution functions, and (iii) the flux decay-time constants (at given energy and positions in space) were determined, and an original dynamic model skeleton with these input parameters has been developed. The methodology is fully described and first flux predictions from the model are presented. In order to evaluate the net effects of radiation on a component, it is important to have an efficient tool that calculates the transfer of the outer radiation environment through the spacecraft material, toward the location of the component under investigation. Using the TOP-model space radiation fluxes and the transmitted radiation environment characteristics derived through GEANT4 calculations, a case study for electron flux/dose variations in a small silicon volume is performed. Potential cases are assessed where the dynamic of the spacecraft radiation environment may have an impact on the observed radiation effects.

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“…They note that the worst forecasts occurred during solar maximum (second half of 1999 through first half of 2002), better forecasts during the declining years of solar minimum (second half of 2002 through 2008), and their best forecasts during the inclining years of solar minimum (1996 through first half of 1999). Turner et al [] reviewed forecasting models for Earth's outer radiation belt electrons other than those considered by Perry et al [] but come to similar conclusions, namely that forecast accuracy is related to the solar cycle. Kellerman et al [] examined forecast accuracy for their geosynchronous radiation belt electron empirical prediction model between 1991 and 2009.…”

Section: Parameter Estimate Sensitivity To Training Datamentioning

confidence: 98%

“…By fitting Model separately for each year, we are able to detect that parameter estimates change over time. The time‐varying functional relationship between log electron flux and solar wind speed has been noted in the literature [e.g., Reeves et al , ; Perry et al , ; Turner et al , ; Kellerman et al , ]. Reeves et al [] graphically examined the long‐term variations between solar wind speed and log electron flux and concluded that the functional relationship between these two variables is not constant in time.…”

Section: Parameter Estimate Sensitivity To Training Datamentioning

confidence: 99%

Dynamic linear models for forecasting of radiation belt electrons and limitations on physical interpretation of predictive models

et al. 2014

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Key Points:• Static models are ill equipped to model dynamics in radiation belt • Models with many inputs are often nonuniquely interpretable • DLMs are attractive models for forecasting radiation belt dynamics Abstract Relationships exist between radiation belt electron flux intensities and solar drivers such as solar wind speed, ion density, and magnetic fields. The particulars of these relationships, however, are not well understood. Many forecasting models have been developed in the last 25 years, attempting to make sense of these relationships and produce accurate forecasts for electron flux intensities. We discuss some of the inherent limitations that many forecasting models (e.g., static models) possess when trying to untangle the intricate and dynamic relationships between electron flux levels and solar wind drivers. Dynamics related to the solar cycle limit physical interpretations for static forecasting models to customized and narrow time windows. Furthermore, the interrelatedness of solar drivers severely limit the ability to uniquely partition and describe the relationship between any one solar driver with electron flux levels. We suggest an alternate approach using dynamic linear models (DLMs). DLMs avoid some of the inherent limitations of physical understanding static models possess. We compare the 1 day ahead forecast accuracy of a relatively simple DLM to the current NOAA relativistic electron forecast model (REFM). The REFM does produce a more favorable prediction efficiency averaged across years when compared to the relatively simple DLM (0.749 to 0.721). However, the competitiveness of the DLM suggests that further development may lead to more accurate and interpretable models in the future.

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An improved forecast system for relativistic electrons at geosynchronous orbit

Cited by 12 publications

References 50 publications

Behavior of MeV electrons at geosynchronous orbit during last two solar cycles

Behavior of MeV electrons at geosynchronous orbit during last two solar cycles

The transient observation-based particle (TOP) model and its potential application in radiation effects evaluation

Dynamic linear models for forecasting of radiation belt electrons and limitations on physical interpretation of predictive models

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