A New JPL Interplanetary Solar High-Energy Particle Environment Model

1. A New JPL Interplanetary Solar High-Energy Particle Environment Model Insoo Jun (JPL), Randall Swimm (JPL), Joan Feynman (JPL), Alexander Ruzmaikin (JPL), Allan Tylka (NRL), and William Dietrich (NRL/Consultant) Presented at 4th Geant4 Space User’s Workshop and 3rd Spenvis Users Workshop November 8, 2006 Pasadena, CA

2. The Space Radiation Environment • Interplanetary Space: Galactic Cosmic Rays • Solar Wind • Sun • Solar Protons and Heavier ions • Trapped Particles

3. Solar Energetic Particle (SEP) Events • Increased levels of protons and heavier ions • Energies: • Protons: >10 MeV • Heavier ions: >1 GeV • Abundance dependent on radial distance from Sun • Partially ionized: Greater ability to penetrate magnetosphere • Number and intensity of events increases dramatically during solar maximum

4. SEP Events (cont.) • Gradual (Proton rich): ~ 10 per year during solar maximum at 1 AU • Strongly associated with CMEs • Same elemental abundances and ionization states as coronal and solar wind plasma • CME’s tend to be the events with the largest proton fluences • Impulsive (He3 rich): ~ 100 per year during solar maximum at 1 AU • Characterized by marked enhancements of heavy ions and electrons • Particles are directly accelerated by flares • Abundances characteristics of interactions in the flare plasma • Low energy electrons dominate and have smaller protonfluxes than the gradual events

5. Active period with numerous CMEs Series of CMEs and proton showers

6. 2003 Halloween SEP Event

7. Background • Particles from solar energetic particle (SEP) events are a critical consideration for future NASA manned and robotic missions. • Damage to science instruments or electronics • Damage to astronauts • At present, our ability to reliably predict SEP environments for missions is surprisingly poor. • SEP events are infrequent and sporadic • Statistically valid data for 1AU only • Radial dependence to be determined

8. Objective • To develop a “modular” code that estimates the mission-integrated fluences and peak fluxes for high energy protons and heavier ions with data set that covers the past 40 years of observation. • Arbitrary trajectory • Launch on an arbitrary future day • Statistics of SEP event fluences, durations, and intervals • Improved radial dependence • To extend the “Solar Probe” Approach to long missions

9. Existing SEP Models • King Model • Solar cycle 20 (from 1966 to 1972) • “ordinary” and “anomalously large” events • JPL91 (or simply JPL) Model • From day 331 of 1963 to day 126 of 1991 for >10, >30, and >60 MeV • From day 270 of 1972 (hence do not include the famous August 1972 event) to day 126 of 1992 for >1 and >4 MeV • Log-normal distribution • ESP (Xapsos) Model • Cover the solar cycle 20, 21 and 22 • Truncated power-law distribution

10. Problems with existing SEP Models • The current models were developed for missions at 1 AU for durations longer than or equal to 1 year. • Missions not at 1 AU??? • Missions with less than 1 year duration??? • Simple, energy-independent radial dependences for flux and fluence are used.

11. Example: Solar Probe Trajectory Solar Probe trajectory and activities near perihelion (view from Earth) (figure supplied by B. T. Tsurutani)

12. “Solar Probe” Approach to Estimate Mission Fluences • A code was written to estimate the mission fluences based on a method suggested for the Solar Probe mission: • As a test, we used the IMP-8/GSFC and IMP-8/UChicago data set collected over the last three solar cycles (from the day 305, 1973 to the day 319, 1997). • Fly a spacecraft through the database with an appropriate radial dependence law being applied at each time step at the beginning of a particular day. • Obtain the total fluence accumulated over the mission duration. • Repeat this process for a launch at the beginning of “each” day. • Calculate the probability of obtaining a fluence greater than F with a random launch date (given by the percentage of missions in which the fluence we calculated exceeded F).

13. Fraction of missions with proton fluences > F. This particular example was obtained for a 60-day solar probe mission trajectory with a 1/r2 scaling factor.

14. Fraction of missions with alpha particle fluences > F. This particular example was obtained for a 60-day solar probe mission trajectory with a 1/r2 scaling factor.

15. Fraction of missions with heavy ion fluences > F. This particular example was obtained for a 60-day solar probe mission trajectory with a 1/r2 scaling factor.

16. 2-Year Mission Fluences at 1 AU

17. Issues with the Solar Probe Approach • However, we found out during our study that this new approach needs to be improved for longer missions, since: • The historical data set does not cover long enough period for sampling very large SEP events. • Repeated launches should occur not at the beginning of each day, but at the next available day not already used to obtain statistically independent mission fluences. • For this approach to work properly, we need to have a data set covering much longer period. • Since available data are limited, we developed a new idea of generating a pseudo-data from the historical data. • To achieve this, we will have to understand the statistical distributions of the following three quantities: • Event fluences • Event durations • Intervals between events

18. Hypothetical N-day Mission Flux . . . . . . . . . . . . . . . Day 1 Day N Time

19. Event Definition • We defined an event when the daily-averaged flux of >10 MeV protons (in our data base, we used >11.1 MeV) exceeds 1 (cm2-s-sr)-1 (Feynman, et al., 1993). • We defined event fluence as the sum of the daily proton fluence from the first day on which the daily average flux exceeded the threshold to the last day on which the average daily flux exceeded the threshold, inclusive. • Under these criteria, 135 solar proton events were identified in 14 solar active years, resulting in ~10 events per solar active year. • This compares to 6-7 events per solar active year identified in previous studies (Feynman et al., 1993; Tylka et al., 1997).

21. Statistics: Event Fluences Log-normal distribution

22. Statistics: Event Fluences Log-normal distribution

23. Statistics: Event Fluences Log-normal distribution

24. Statistics: Event Fluences Log-normal distribution

25. Statistics: Event Durations Poisson distribution.

26. Statistics: Time Intervals between Events Poisson distribution.

27. 2-Year Mission Fluences at 1 AU with Virtual Data Set

28. Radial Dependence • Current recommendations if mission does not remain at 1 AU are (Feynman and Gabriel, 1988): • Fluences: Multiply by radial dependence of the fluence integrated over trajectory  Use 1/r2 • Peak Fluxes: Multiply by factor due to diffusive transport  Use 1/r3 • However, this simple radial dependences are not good approximations and no single radial dependence will suffice to model all energies and particle populations. The form of the radial dependence is expected to be highly energy dependent. (Zank, Rice, Wu, 2000). • There are three populations of SEP particles for which we are investigating the radial dependences: • Population One – Particles escaped from the shock (streaming limit) • Population Two – Intense spike of particles propagating with shocks • Population Three – Particles populating the region behind the shock

29. Summary • Continue to finalize the code. • Test and validate the model. • Comparison with the existing models. • Further progress on understanding of radial and longitudinal dependence.