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Abstract Maintaining accurate real‐time hindcast and forecast specification of the radiation environment is essential for operators to monitor and mitigate the effects of hazardous radiation on satellite components. The Radiation Belt Forecasting Model and Framework (RBFMF) provides real‐time forecasts and hindcasts of the electron radiation belt environment, which are used as inputs for the Satellite Charging Assessment Tool. We evaluated the long‐term statistical error and bias of the RBFMF by comparing the 10‐hr hindcast of electron phase space densities (PSD) to a multi‐mission data set of PSD observations. We found that, between the years 2016–2018, the RBFMF reproduced the radiation belt environment to within a factor of 1.5. While the error and bias of assimilated observations were found to influence the error and bias of the hindcast, data assimilation resulted in more accurate specification of the radiation belt state than real‐time Van Allen Probe observations alone. Furthermore, when real‐time Van Allen Probe observations were no longer available, the hindcast errors increased by an order of magnitude. This highlights two needs; (a) the development of physics‐based modeling incorporated into this framework, and (b) the need for real‐time observations which span the entire outer radiation belt. 

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts.In-situmulti-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations. 

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. In-situ multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations. 

Archived data for the manuscript “Differentiating Between Simultaneous Loss Drivers in Earth’s Outer Radiation Belt: Multi-Dimensional Phase Space Density Analysis”  Staples et al., submitted to Geophysical Research Letters 2022.</p> These files contain multi-mission phase space density measurements including, Van Allen Probes, GOES 13, 14, 15, GPS, MMS, and THEMIS, computed in adiabatic coordinates. All data is from September 2017. For detailed description of the method used in the computation of this data, see section 2.1 of the submitted manuscript. The THEMIS, Van Allen Probe, MMS, and GOES data used in computations is publicly available via http://cdaweb.gsfc.nasa.gov  The GPS data is available via https://www.ngdc.noaa.gov/stp/space-weather/satellite-data/satellite-systems/gps/</p> FILES:</p> 'psd_intp_T89_20170901-20170930_allsc.cdf'</p> 'psd_intp_T89_20170901-20170930_rbsp-b.cdf'</p> DATA OWNER: Adam Kellerman DATA PREPERATION: Frances Staples</p> CONTACT: Adam Kellerman: akellerman@epss.ucla.edu Frances Staples: frances.staples@ucl.ac.uk</p> FS was supported by NASA grants 80NSSC20K1402 and NSF grant 2149782. ACK acknowledges support from NASA grants 80NSSC20K1402 and 80NSSC20K1281, and NSF grant 2149782.