1. Cosmic Rays and Space Weather
Lev I. Dorman (1, 2)
(1) Israel Cosmic Ray and Space Weather Center and Emilio Segre’ Observatory affiliated to Tel Aviv University, Technion and Israel Space Agency, Israel,
(2) Cosmic Ray Department of IZMIRAN, Russian Academy of Science, Russia
Contact: / Fax: /Tel: )

2. 1. Cosmic rays (CR) as element of space weather
1.1. Influence of CR on the Earth’s atmosphere and global climate change 1.2. Radiation hazard from galactic CR Radiation hazard from solar CR Radiation hazard from energetic particle precipitation from radiation belts

3. 2. CR as tool for space weather forecasting
2.1. Forecasting of the part of global climate change caused by CR intensity variations
2.2. Forecasting of radiation hazard for aircrafts and spacecrafts caused by variations of galactic CR intensity
2.3. Forecasting of the radiation hazard from solar CR events by using on-line one-min ground neutron monitors network and satellite data
2.4. Forecasting of great magnetic storms hazard by using on-line one hour CR intensity data from ground based world-wide network of neutron monitors and muon telescopes

4. 3. CR, space weather, and satellite anomalies
4. CR, space weather, and people health

5. ISRAEL CR & SPACE WEATHER CENTER Data Analysis
Search of flare beginning in cosmic rays (automatic SEP detection)
Restoration of particles impact (F(t,E))
Prediction of magnetic storms from CR-network data

7. Monitoring and Forecast of Solar Flare Particle Events Using Cosmic-Ray Neutron Monitor and Satellite 1-min Data

8. FORECAST STEPS
1. AUTOMATICALLY DETERMINATION OF THE SEP EVENT START BY NEUTRON MONITOR DATA
2. DETERMINATION OF ENERGY SPECTRUM OUT OF MAGNETOSPHERE BY THE METHOD OF COUPLING FUNCTIONS
3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION
4. FORECASTING OF EXPECTED SEP FLUXES AND COMPARISON WITH OBSERVATIONS
5. COMBINED FORECASTING ON THE BASIS OF NM DATA AND BEGINNING OF SATELLITE DATA

9. 1. AUTOMATICALLY DETERMINATION OF THE FEP EVENT START BY NEUTRON MONITOR DATA
THE PROBABILITY OF FALSE ALARMS
THE PROBABILITY OF MISSED TRIGGERS

10. 2. DETERMINATION OF ENERGY SPECTRUM OUT OF MAGNETOSPHERE BY THE METHOD OF COUPLING FUNCTIONS

11. 2. DETERMINATION OF ENERGY SPECTRUM OUT OF MAGNETOSPHERE BY THE METHOD OF COUPLING FUNCTIONS

12. 3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

13. 3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

14. 3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

15. 3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

16. 3. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

17. 4.1 FORECASTING OF EXPECTED FEP FLUXES AND COMPARISON WITH OBSERVATIONS (2-nd CASE: K(R, r) DEPENDS FROM DISTANCE TO THE SUN)

18. 5.1 COMBINED FORECASTING ON THE BASIS OF NM DATA AND BEGINNING OF SATELLITE DATA

19. 5B. COMBINED FORECASTING ON THE BASIS OF NM DATA AND BEGINNING OF SATELLITE DATA; COMPARISON WITH GOES OBSERVATIONS

20. CONCLUSION FOR SEP BY ONE-MINUTE NEUTRON MONITOR DATA AND
ONE-MINUTE AVAILABLE FROM INTERNET
COSMIC RAY SATELLITE DATA FOR MIN
DATA IT IS POSSIBLE TO DETERMINE THE TIME OF
EJECTION, SOURCE FUNCTION, AND DIFFUSION
COEFFICIENT IN DEPENDENCE FROM ENERGY AND
DISTANCE FROM THE SUN.
THEN IT IS POSSIBLE TO FORECAST OF SEP FLUXES
AND FLUENCY IN HIGH AND LOW ENERGY RANGES UP TO ABOUT TWO DAYS.
SEPTEMBER 1989 EVENT IS USED AS A TEST CASE.

21. The relation between malfunctions of satellites at different orbits and space weather factors,
Malfunction data on different satellites, including “Kosmos” series (circular orbit at 800 km altitude and 74º inclination) in the period were analyzed in the search of possible influence of different space environmental parameters. The special database was created, which combined, beyond the malfunction information, various characteristics of space weather: geomagnetic activity indices (Ap, AE and Dst), fluxes and fluences of electrons and protons at different energy, high energy cosmic ray variations, solar wind characteristics and other solar, interplanetary and geophysical data. All satellites were divided on several groups by their essential orbital characteristics (altitude, inclination). In the present study we consider an influence of a range of cosmic ray variations on the chosen groups of spacecraft. In particular, the following cosmic ray variations were involved to the analysis: 1) enhancements of the solar protons of different energy; 2) variations of high energy electrons in the Earth magnetosphere; 3) cosmic ray activity indices, obtained from neutron monitor measurements.
It was found, that relation of the satellite malfunctions to the cosmic ray variations is different for various orbital groups, and it should be taken into account when the forecasting models for the malfunction frequency are being elaborated.
This study was supported by the European Commission (INTAS project No 00810)

22. Red, Green and Blue Groups
Самая многочисленная группа – GEO (135 спутников).
На втором месте (68 спутников) группа (low altitude – high inclination). Это “Kosmos” like satellites и мы можем называть эту группу - “Kosmos” group. «Космосы» составляют здесь явное большинство и находятся в центре распределения этой группы.
В группе (high altitude – high inclination), в основном, MEO satellites. Главное отличие от GEO не высота, а наклон орбиты. К сожалению, в этой группе только 14 спутников, но они сообщили о > 1000 malfunctions. Так что возможности для статистического анализа есть. Чтобы понять особую важность и специфичность этой группы достаточно взглянуть на октябрьскую (1989 г.) картинку.
Группа (low altitude – low inclination) также важна. Здесь, в основном, пилотируемые аппараты с особой ценой сбоя. Но эта группа так мала (5 спутников), что мы вряд ли сможем получить здесь хорошо обоснованные результаты.

23. Period with big number of satellite malfunctions
Upper panel – cosmic ray activity near the Earth: variations of 10 GV cosmic ray density; solar proton (> 10 MeV and >60 MeV) fluxes.
Lower panel – geomagnetic activity: Kp- and Dst-indices.
Vertical arrows on the upper panel correspond to the malfunction moments.
Look on two examples. First one – the wellknown period – October 89. All our topic is originated from this period with exclusevily bad space weather. We see here 3 big proton events, very strong magnetic storm. In upper part the variations of groundlevel cosmic rays. These proton events were groundlevel enancements. And these arrows are momets of satellite malfunctions. We have 3 clusters of malfunctions and they coincide with maximal proton fluxes.

24. Period with big number of satellite malfunctions
Upper panel – cosmic ray activity near the Earth: variations of 10 GV cosmic ray density; electron (> 2 MeV) fluxes – hourly data.
Vertical arrows correspond to the malfunction moments. Lower row – all malfunctions.
Lower panel – geomagnetic activity: Kp- and Dst-indices.
Here the majority of the satellite malfunctions coincides with period of magnetic storm and enhancement of high-energy electron flux.
The malfunctions are absent entirely in the high altitude - high inclination group, which played the main role in preceding example. Only a few malfunctions were in GEO group and huge majority – in “blue” group (low altitude - high inclination). We see entirely other subset of satellites comparing with first example.

25. High- and low altitude anomalies
Actually in all mass we have no …. No at all
No correlation between high and low malfunction’s frequencies

26. Seasonal dependence
Anomaly’s frequency (all orbits) with statistical errors
27-day averaged frequencies and corresponding half year wave
Now some words about seasonal dependence.

27. Seasonal dependence
Satellite malfunction frequency and Ap-index averaged over the period The curve with points is the 27-day running mean values; the grey band corresponds to the 95 % confidence interval. The sinusoidal curve is a semidiurnal wave with maxima in equinoxes best fitting the frequency data.
Now some words about seasonal dependence.

28. Seasonal dependence (different orbits)
27-day averaged frequencies and corresponding half year wave for different satellite groups
The biggest season variation in GEO group. The red group is not demonstrated spring-autumn preference

29. Time distribution of anomalies

30. Space Weather Indices Solar activity Solar wind Geomagnetic activity
Solar protons
Electrons
Ground Level Cosmic Rays
~30 indices in total
We calculated mean daily frequencies for all groups and insert them in daily table. The main part of this table are

31. 27-day running averaged Sunspot Numbers and Solar Radio Flux
Solar activity
27-day running averaged Sunspot Numbers and Solar Radio Flux
We use SSN and F – daily Sunspot Numbers and radio fluxes;
SSN27, SSN365 – 1 year and 1 rotation running averaged SSN

32. Daily Ap-index and minimal (for this day) Dst-index
Geomagnetic activity
Daily Ap-index and minimal (for this day) Dst-index
Different geomagnetic indices
We use Apd, Apmax – daily and maximal Ap-index;
AEd, AEmax – daily and maximal AE-index;
DSTd, DSTmin – daily and minimal Dst-index;

33. Energetic protons and electrons
Daily proton and electron fluencies
p10, p100 – daily proton (>10, >100 MeV) fluencies (GOES);
p10d, p60d – daily proton (>10, >60 MeV) fluxes (IMP);
p10max, p60max – maximal hourly proton (>10, >60 MeV) fluxes (IMP);
e2 – daily electron (>2 MeV) fluence (GOES);
e2d, e2max – daily and maximal electron (>2 MeV) fluх (GOES);

34. Daily solar wind speed and intensity of interplanetary magnetic field
Vsw, Vmax – daily and maximal solar wind speed;
Bm – daily IMF intensity;
Bzd, Bzmin – daily and minimal z-component IMF (GSM);
Bznsum – sum of negative z-component values;

35. Cosmic Ray Activity Indices
Daily CRA-indices and sum of negative IMF z-component
da10, CRA – indices of cosmic ray activity, obtained from ground level CR observations (Belov et al., 1999);
Eakd, Eakmax – estimation of daily and maximal energy, transferred from solar wind to magnetosphere (Akasofu, 1987);

36. SSC and anomalies
Averaged behavior of satellite malfunction frequency near Sudden Storm Commencements
634 days with SSC in total
a – all storms
b – storms with Ap>50 nT
c – storms with Ap>80 nT
Sometimes we have the special crucial moments and periods in Space Weather, SSC for example. We see clear effect. The bigger storm – the bigger effect. Мы видим, что после прихода к Земле ударной волны частота спутниковых сбоев возрастает и остаётся повышенной около недели. Чем сильнее магнитная буря, тем больше это возрастание. Если для всех SSCs возрастание составляет ~20 %, то для магнитных бурь с максимальным Ap-индексом >80 нТл – оно уже близко к двухкратному. Казалось бы, это свидетельствует о связи сбоев с геомагнитными возмущениями.
Однако две особенности приведенных картинок говорят о том, что всё не так просто. 1) Средняя частота сбоев pa растёт после SSC, но не в тот же день. На самом деле, средняя величина pa в дни с SSC равна 0.009±0.001, а в дни без SSC 0.014±0.001, т. е. в 1.5 раза выше. 2) Большинство магнитных бурь не продолжаются так долго.

37. SSC and anomalies
Averaged behavior Ap, Dst – indices of geomagnetic activity and satellite malfunction frequency near Sudden Storm Commencements
Malfunctions start later and last longer than magnetic storms
But is not so simple. M

38. Proton events and anomalies
Averaged behavior of p>10, p>100 MeV and satellite malfunction frequency during proton event periods.
The enhancement with >300 pfu were used
Other kind of special period. Here 0-day is proton event onset day. 0-день – это день начала протонного возрастания у Земли. Здесь усреднялись только возрастания, в которых среднечасовой поток протонов с энергией >10 МэВ превышал 300 pfu
Мы видим возрастание частоты сбоев в нулевой и первый дни, которое на больших высотах больше, чем на малых. Правда, это не единственная особенность в поведении частоты. Сложность полученной картины может объясняться несколькими обстоятельствами: 1) недостаточной статистикой; 2) магнитными бурями, которые часто следуют за протонными возрастаниями; 3) тем, что протонные возрастания часто наблюдаются сериями.

39. Proton events and anomalies
Other kind of special period. Here 0-day is proton event onset day. The biggest effect is in 0- and 1-days and in red group. The smaller effect in green goup and nothing on low altitudes. Различия между группами очевидно. На малых высотах связь с протонными событиями почти незаметна, а самые большие возрастания частоты аномалий наблюдаются в группе high altitude – high inclination. К сожалению, в этой группе не так много спутников. Во время многих из выделенных протонных возрастаний в этой группе было только 3-6 спутников.
Mean satellite anomaly frequencies in 0- and 1-days of proton enhancements in dependence on the maximal > 10 MeV flux

40. Proton events and anomalies
Usually we have 10% probability of malfunction, in special proton days this probability rises to 100 %. Вероятность каких-либо аномалий для спутников high altitude – high inclination группы в зависимости от величины максимального потока протонов >10 and > 60 MeV (IMP-8).
В среднем спутники группы high altitude – high inclination сообщали о каких-либо сбоях 1 раз в 10 дней. В дни протонных возрастаний вероятность таких сообщений больше. При увеличении величины протонного возрастания опасность спутниковых сбоев быстро возрастает и для самых больших возрастаний становится почти неизбежной.
Если брать не все возрастания, а только те, при которых в группе high altitude – high inclination было >6 спутников, то все вероятности существенно увеличиваются – для > 10 MeV протонов практически вдвое. Для этих дней коэффициент корреляции между флюэнсом протонов >10 MeV и частотой (phih) возрастает до 0.83 (p10max>9 pfu, nhih>6).
Probability of any anomaly (high altitude – high inclination group) in dependence on the maximal proton > 10 and >60 MeV flux

41. Proton and electron hazards on the different orbits
Red group is obviously the proton group. Blue group is electron one and green is mixed.
Mean proton and electron fluencies on the anomaly day

42. Anomalies and different indices (precursors)
We found interesting feature in behavior of some parameters. Here is Ap-index. We see enhanced geomagnetic activity not only in zero-day but some days before
Mean behavior of Ap-index in anomaly periods (GEO satellites)

43. Anomalies and different indices (precursors)
We found interesting feature in behavior of some parameters. Here is Ap-index. We see enhanced geomagnetic activity not only in zero-day but some days before
Mean behavior of >2 MeV electron fluence in anomaly periods (GEO satellites)

44. Anomalies and different indices (precursors)
We found interesting feature in behavior of some parameters. Here is Ap-index. We see enhanced geomagnetic activity not only in zero-day but some days before
Mean behavior of solar wind speed in anomaly periods (GEO satellites)

45. Models of the anomaly frequency
high alt.- low incl.
e>2 MeV
Apd, AEd, sf
p60d, p100 Vsw
Bzd, da10
low alt.-high incl.
e>2 MeV
CRA
Apd, AEd, sf
Vsw, Bzd
The parameters used to simulate anomaly frequencies for different orbits are listed here. Green, blue and red group. Main role is for electrons in green and blue group, especially – green. In red group protons are much more important than other indices.
high alt.-high incl.
p>100 MeV, p60d
Eak, Bznsum, SSN365

46. Models of the anomaly frequency
We checked ~ 30 different Space Weather parameters and a lot of their combinations
We used the parameters for anomaly day and for several preceding days
Only simplest linear regression models were checked (exclusions for e and p indices)
Obtained models contain 3-8 different geo- heliophysical parameters
The models appear to be different for different satellite groups
We tried to build the models for anomaly frequencies.
Example of frequency model (GEO):

47. Summary on satellite anomalies
The models simulated anomaly frequency in different orbits are developed and could be adjusted for forecasting
The relation between Space Weather parameters and frequency of satellite malfunctions are different for different satellite groups (orbits)

48. THE END
Thank You