Electron radiation belt safety indices based on the SafeSpace modelling pipeline and dedicated to the internal charging risk
Abstract. In this paper, we present the SafeSpace prototype for a safety warning system, dedicated to the electron-radiation-belt induced internal charging hazard, aboard spacecraft. The space weather tool relies on a synergy of physical models associated in a chain that covers the whole Sun-interplanetary space-Earth's inner magnetosphere medium. With the propagation of uncertainties along the modelling pipeline, the safety prototype provides a global nowcast and forecast (within a 4-day lead time) of the electron radiation belt dynamic as well as tailored indicators for space industry operators. They are meant to inform the users about the severity of the electron space environment via a three colored alarm system, which sorts the indices intensity according to a representative historical distribution of in-situ data. The system was challenged over the St-Patrick 2015 storm in order to assess its performance. It showed overall good nowcasting and forecasting capabilities, due to its broad physics-driven pipeline.
Nour Dahmen et al.
Status: final response (author comments only)
CC1: 'Comment on egusphere-2022-1509', Yann Pfau-Kempf, 10 Feb 2023
- AC1: 'Reply on CC1', Nour Dahmen, 26 Apr 2023
RC1: 'Comment on egusphere-2022-1509', Yihua Zheng, 17 Mar 2023
- AC2: 'Reply on RC1', Nour Dahmen, 26 Apr 2023
RC2: 'Comment on egusphere-2022-1509', Anonymous Referee #2, 01 Apr 2023
- AC3: 'Reply on RC2', Nour Dahmen, 26 Apr 2023
Nour Dahmen et al.
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The manuscript "Electron radiation belt safety indices based on the SafeSpace modelling pipeline and dedicated to the internal charging risk" was presented by Yann Pfau-Kempf and discussed by the members of the Journal club of the Space physics group at the University of Helsinki. This interactive comment presents the main points raised in our discussion, especially by Emilia Kilpua and Adnane Osmane in addition to Yann Pfau-Kempf.
This manuscript presents the complex modelling pipeline developed and used by the SafeSpace project to obtain indices for the internal spacecraft charging risk incurred by spacecraft at LEO, MEO and GEO orbits. A succinct overview of all the components of the pipeline is given, as well as the requirements and definitions used to develop the indices yielding three alert levels for the three orbital regions considered. Finally, the pipeline is validated by comparing its output with measured electron fluxes for the period of the St Patrick storm in March 2015. The effort that must have gone into chaining this large number of components into one modelling pipeline is deserving praises, and the challenge is indeed very significant, yet we would like to present a number of comments and suggestions that could hopefully help in bolstering the authors' conclusions regarding the quality of the results.
l. 75 and following: We are surprised by the use of By, isn't Bz a better first indicator of geoeffectiveness?
l. 111: Can the authors explain why they chose to use daily averages? Are these not underestimating strong events and wouldn't e.g. 12 or 24 hour fluences be more adapted to the purpose? Large flux events can be localized on timescales much less than a day and certainly do not obey Gaussian statistics, so the average will most certainly underestimate spacecraft exposure.
Section 4: We would like to suggest an additional validation step: could the authors compare the ensemble output of the solar wind propagation to observations at L1? A good match would indeed narrow down the sources of mismatch of the alert indices to observation to the latter part of the pipeline, but possibly the heliospheric part of the pipeline already introduces discrepancies with respect to observations?
l. 185–186: We would suggest a discussion of the computational cost of the pipeline in general and the Salammbô step in particular.
Firstly, we feel that the present study would be a lot more convincing if the indices matched better, we are reluctant to call the results "fine" as presented. If indeed the critical factor is the low resolution of the Salammbô grid, we would suggest to show the same analysis run with a good grid and accordingly better matches between forecast/nowcast and observed indices.
Secondly, how quickly can the code be run on what kind of architecture? What elements can be e.g. parallelised to obtain a better performance? What would it cost in terms of required computing to run the Salammbô step with a better grid operationally? As this manuscript presents a tool with expected operational applicability, we would appreciate seeing some quantitative estimations of the requirements for operational deployment, in particular regarding the grid resolution of Salammbô pointed out by the authors.
l. 71–74: What CME model is used in the propagation modelling?
l. 73: What is the source of the magnetograms used?
l. 114–116: Can the authors develop a little this point (here or elsewhere in the text): what distinguishes the proposed indices from already-existing three-colour warning levels or other such indices?
l. 85: Could the authors introduce the variables used as they may not be familiar to all readers?
Figure 4 has poor resolution, and the third panel's horizontal axis line is missing. It would be more useful to have integer tick marks and values for the last panel with the Kp index.
l. 187: as regards the forecast results
l. 190: beforehand -> before
Table 2 and throughout: certainly the authors mean 10th-90th percentile, not decile.
Figure 5: median
l. 210: no "of"
l. 218: sensibility -> sensitivity