The implications of temporal variability in wave‐particle interactions in Earth's Radiation Belts

Watt, C.E.J.; Allison, H.J.; Thompson, R.L.; Bentley, S.N.; Meredith, N.P. ORCID: https://orcid.org/0000-0001-5032-3463; Glauert, S.A. ORCID: https://orcid.org/0000-0003-0149-8608; Horne, R.B. ORCID: https://orcid.org/0000-0002-0412-6407; Rae, I.J.. 2021 The implications of temporal variability in wave‐particle interactions in Earth's Radiation Belts. Geophysical Research Letters, 48 (1), e2020GL089962. 10, pp. https://doi.org/10.1029/2020GL089962

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Official URL: https://agupubs.onlinelibrary.wiley.com/doi/10.102...

Abstract/Summary

Changes in electron flux in Earth's outer radiation belt can be modeled using a diffusion‐based framework. Diffusion coefficients D for such models are often constructed from statistical averages of observed inputs. Here, we use stochastic parameterization to investigate the consequences of temporal variability in D. Variability time scales are constrained using Van Allen Probe observations. Results from stochastic parameterization experiments are compared with experiments using D constructed from averaged inputs and an average of observation‐specific D. We find that the evolution and final state of the numerical experiment depends upon the variability time scale of D; experiments with longer variability time scales differ from those with shorter time scales, even when the time‐integrated diffusion is the same. Short variability time scale experiments converge with solutions obtained using an averaged observation‐specific D, and both exhibit greater diffusion than experiments using the averaged‐input D. These experiments reveal the importance of temporal variability in radiation belt diffusion.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2020GL089962
ISSN:	0094-8276
Additional Keywords:	stochastic parameterization, probabilistic methods
Date made live:	14 Dec 2020 13:58 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/529155

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1029/2020GL089962

ISSN:

0094-8276

Additional Keywords:

stochastic parameterization, probabilistic methods

Date made live:

14 Dec 2020 13:58 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/529155