NMDB Kiel Meeting, 3-5/12/2008

On the possibility to use on-line one-minute NM data of NMDB network and available from

Internet satellite CR data for forecasting of great radiation hazard

L.I. Dorman (a, b)

(a) Israel Cosmic Ray & Space Weather Center and Emilio Segre’ Observatory, affiliated to Tel Aviv University, Technion and Israel Space Agency, P. O. Box 2217, Qazrin 12900, Israel(b) Cosmic Ray Department of IZMIRAN, Russian Academy of Science, Troitsk 142092, Moscow Region, Russia

Proton events and anomalies

Mean satellite anomaly frequencies in 0- and 1-days of proton enhancements

in dependence on the maximal > 10 MeV flux

Proton events and anomalies

Probability of any anomaly (high altitude – high inclination group) in dependence on the maximal proton > 10 and >60 MeV flux

FORECAST STEPS1. AUTOMATICALLY DETERMINATION OF THE FEP 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 FEP FLUXES AND COMPARISON WITH OBSERVATIONS

5. COMBINED FORECASTING ON THE BASIS OF NM DATA AND BEGINNING OF SATELLITE DATA IN THE FRAME OF ISOTROPIC MODE

6. USING TWO OR THREE NMDB STATIONS IN THE FRAME OF ISOTROPIC MODE

7. BASING ON ANISOTROPIC AND KINETIC MODE OF PROPAGATION: USING DATA OF ABOUT ALL NMDB STATIONS

1.1. AUTOMATICALLY DETERMINATION OF THE FEP EVENT START BY NEUTRON

MONITOR DATA

160

1201 60lnln

Zk

ZkAkAZZA IID

160

1201 60lnln

Zk

ZkBkBZZB IID

DZA1 2.5, DZB1 2.5,

1.2. SCHEME OF ALHORITHMS FOR “FEP ON-LINE SEARCH”

1.3. THE PROBABILITY OF FALSE ALARMS

9876.05.2 1min0062.025.21

152 min10845.325.21

194 min10478.125.21

1146 min10685.525.21

yearsinone 71034.3

1.4. THE PROBABILITY OF MISSED TRIGGERS

10% ~7, - 4.5, The probability of this negative fluctuation in one channel in one minute is equal

The probability of missed trigger for two successive minutes of observation simultaneously in two channels is 4 times larger: . It means that missed trigger is expected one per about 70000 events.

16 min1039.325.41

51036.1

1.6. EXAMPLE OF INTERNET PRESENTATION OF REAL TIME DATA FROM ESO (ISRAEL)

2.1. DETERMINATION OF ENERGY SPECTRUM OUT OF MAGNETOSPHERE BY THE METHOD OF

COUPLING FUNCTIONS

mmm km

kcm

kmmcm RaRaRkaRRW exp1,

11 , if cRR,

and 0,RRWcm , if cRR

bRRDRD o

dRRaRRakaRFc

mmm

R

km

kkcmmmcm

expexp1, 11

,,,,

,,,,,

cmccncnccm

clccmcmcclclmn RFRRWRFRRW

RFRRWRFRRWR

cmocmcm RIRIRI

,, ckcckcck RbFRRWRRI

2.2. DETERMINATION OF ENERGY SPECTRUM OUT OF MAGNETOSPHERE BY THE METHOD OF

COUPLING FUNCTIONS

cmcncncm

clcmcmclc RIRFRIRF

RIRFRIRFR

,,

,,

,,,,

,,

clccmcmccl

clccmcmccl

RFRRWRFRRW

RIRRWRIRRWb

cmccncnccm

clccmcmcclclmn RIRRWRIRRW

RIRRWRIRRWR

,,

,,,

The Case of Magnetically Quiet Period 0 cR .

Ii this case the expected variation in total counting rate or in multiplicity m will be ,cmcmocm RbFRIRI 4

where m = tot, 1, 2, 3,...., and

dRRaRRakaRF

c

mmm

R

km

kkcmmmcm

expexp1, 11 . 5

Let us compare data for multiplicities m and n. According to Eq. 4 we obtain ,cmncnocncmocm RRIRIRIRI , 6

where ,,, cncmcmn RFRFR 7

is the known function calculated according Eq. 5. Comparison of experimental results (left side of Eq. 6 with function ,cmn R gives immediately value of , and then by Eq. 4 value of parameter b. That

the data of observed FEP increase in different multiplicities gives important possibility to determine parameters b and in Eq. 3 for the primary variation of FEP event out of the Earth's magnetosphere.

3.1. DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION (1-st CASE:

K(R) DOES NOT DEPEND FROM DISTANCE TO THE SUN)

xTTtxTTtxTTt e 13312211 ,,

R TTxTTxTb

Tb

r

RK

xTTx

TT2123

122

12

112

12 ln4

R TTxTTxTb

Tb

r

RK

xTTx

TT3123

133

12

113

13 ln4

11312 TTTTx

R TTxTTxTb

Tb

R TTxTTxTb

Tb

TT

TT

132313

3

1

122312

2

1

12

13

ln

ln

3.2 DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION (1-st CASE:

K(R) DOES NOT DEPEND FROM DISTANCE TO SUN)

R TTxTTxTb

Tb

xTTxTTr

R TTxTTxTb

Tb

xTTxTTrRK

132313

3

1

13132

1

122312

2

1

12122

1

ln

4

ln

4

3

213332

212

2212

1111

4/exp2/32/124/exp2/3

2/124/exp2/32/12

tRKrtRKRDR ttbtRKrtRK

RDR ttbtRKrtRKRDR ttbRN

o

ooo

eeo TTRK

rTTRKRNTrRn4

2exp232

1,, 21

3.3 DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION (1-st

CASE: K(R) DOES NOT DEPEND FROM DISTANCE TO SUN)

The behavior of RK for R 10 GV with time

3.4 DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

(2-nd CASE: K(R, r) DEPENDS FROM DISTANCE TO THE SUN)

tRK

rrtRKrRNtrRn o

12

21

24

231

231

2exp

232,,

11, rrRKrRK 321 ,, nnn 321 ,, ttt

1

31132

1232113

132

12312 lnlnlnln32

nnttt

tttnntt

ttt

ttttt

31

213

13

11

21

212

12

12

11

21

1ln2ln23ln2ln23 nntt

ttr

nntt

ttrRK

kko

tRK

rtRKrnRN

12

2123

123

124

12

exp232

3.5 DETERMINATION OF TIME OF EJECTION, SOURCE FUNCTION AND PARAMETERS OF PROPAGATION

(2-nd CASE: K(R, r) DEPENDS FROM DISTANCE TO THE SUN)

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

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

SATELLITE DATA

11, rrRKrRK

111 RRcvKRK

dRdR

RKTT

rRKTTrRNdTTRF

e

e

TRo

Tcs

ce

1

21

2

24

231

231 2

exp232

RKTT

rrRKTTrRNTrRn

e

eo

12

21

24

231

231

2exp

232,,

maxln, kko EEaeoo RTTRNTRN

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

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

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

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

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

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

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

Forecasting of expected FEP fluency for . GeVEE ok 1.0

USING ONE-LINE COSMIC RAY DATA FROM TWO OBSERVATORIES In this case we will have ,, 11111 ckcckcck RbFRRWRRI , 13a

,, 11111 clcclccl RbFRRWRRI , 13a

,, 22222 cmccmccm RbFRRWRRI , 13b

,, 22222 cnccnccn RbFRRWRRI , 13b

where 1cR and 2cR are cut-off rigidities for these two observatories. In this case we will have 4 unknown

variables: , b, 21, cc RR . Unknown variables b, 21, cc RR entrance in Eq. 13a,b,c,d by linear

manner. It give possibility step by step to exclude them from the system of equations and finally to obtain non-linear equation for determining parameter :

,cR,cRklmncRmInWcRnImW

cRkIlWcRlIkW21

22

11

, 14

where

,RFW,RFW

,RFW,RFW,R,R

cmncnm

cklclkccklmn

22

1121

15

is a special function what can be calculated for any pair of two stations with cut-off rigidities 1cR and

2cR , by using known functions ,RF,,RF,,RF,,RF cncmclck 2211 (what can be calculated

according to Eq. 5), and known values ,R,RWW,R,RWW ccllcckk 1111 ,R,RWW ccmm 22

and 22 ccnn R,RWW (what can be calculated according to Eq. 2).

After determining we determine immediately for any moment of time three other unknown variables:

,RFW,RFW

RIWRIWb

cklclk

cklclk

11

11

,

,RFW,RFW

RI,RFRI,RFR

cknclm

ckclclckc

11

11111

,

,RFW,RFW

RI,RFRI,RFR

cmncnm

cmcncncmc

22

22222

.

CONCLUSIONS1. BY ONE-MINUTE NEUTRON MONITOR DATA WE DETERMINE AUTOMATICALLY THE BEGINNING OF BIG SOLAR CR INCREASINGS AND GIVE IN INTERNET THE ALARM IN REAL TIME.2. WE SHOW THAT THE PROBABILITY OF FALSE AND MISSED ALERTS ARE NEGLIGIBLE.3. BY THE METHOD OF COUPLING FUNCTIONS FOR EACH MINUTE OF DATA WE DETERMINE ENERGY SPECTRUM OF SOLAR CR IN THE SPACE AND THE CHANGE OF CUT-OFF RIGIDITY (CHARACTERIZED THE CHANGE OF RING CURRENT IN MAGNETOSPHERE).4. WE DETERMINE THE TIME OF EJECTION, DIFFUSION COEFFICIENT AND SOURCE FUNCTION BY NM DATA IN HIGH ENERGY REGION.

CONCLUSIONS

• 5. BY ONE-MINUTE NM AND AVAILABLE FROM NTERNET COSMIC RAY SATELLITE DATA WE DETERMINE ALL ABOVE MENTIONED PARAMETERS FOR BROAD CR SPECTRUM FROM HIGH TO VERY LOW ENERGIES.

• 6. BY COMBINING OF NM AND SATELLITE DATA FOR 30-40 MIN OBSERVATIONS IS POSSIBLE TO DETERMINE THE TIME OF EJECTION, SOURCE FUNCTION, AND DIFFUSION COEFFICIENT IN DEPENDENCE FROM ENERGY AND DISTANCE FROM THE SUN.

• 7. IT IS SHOWN THAT BY THIS METHOD IS POSSIBLE TO FORECAST OF SOLAR CR FLUXES AND FLUENCY IN HIGH AND LOW ENERGY RANGES UP TO ABOUT TWO DAYS.

• 8. SEPTEMBER 1989 EVENT IS USED AS A TEST CASE.

CONCLUSIONS

• 9. REALLY OFTEN THE BEGINNINGG OF GLE IS VERY ANISOTROPIC AND FOR THIS STAGE IS NECESSARY TO USE MODE OF PROPAGATION BASED ON ANISOTROPIC DIFFUSION AND KINETIC APPROACH, BUT AFTER 20-25 MIN DISTRIBUTION BECAME ISOTROPIC (SECOND STAGE)

• 10. BECOUSE MAIN PART OF RADIATION HAZARD IS FORMATTED MOSTLY DURING DIFFUSION STAGE, IT IS NOT CLEAR WHAT WILL GIVE THE FIRST STAGE FOR FORECASTING OF EXPECTED SOLAR CR FLUXES AND ESTIMATION EXPECTED RADIATION HAZARD

• 11. I THINK THAT THE FIRST STAGE IS NOT SO IMPORTANT FOR DETERMINING DIFFUSION COEFFICIENT, BUT IT IS VERY IMPORTANT FOR DETERMINING ACCELERATION MODE, ENERGY SPECTRUM IN SOURCE, AND THERFORE FOR ESTIMATION OF TOTAL RADIATION HAZARD

• 12. THE OTHER POSSIBILITY TO INCREASE EFFECTIVITY OF FORECASTING: IT WILL BE IMPORTANT TO SEPARATE STATIONS WHICH MEASURE DIRECT FLUX (ABOUT WITHOUT SCATTERING) AND OTHER STATIONS WHICH MEASURE ONLY DIFFUSION STAGE. THEY WILL GIVE VERY IMPRTANT DIFFERENT INFORMATION ON SOURCS FUNCTION AND PROPAGATION MODE, RESPECTIVELY

CONCLUSIONS

• 13. AS THE FIRST STEP WE MUST USE IN EACH NMDB STATION THE AUTOMATICAL PROGRAE FOR DETERMINING OF BEGINNING GLE

• 14. WE WILL TRAINING TO MADE FORECAST BY USING TWO OR THREE NMDB STATIONS WHICH HAVE DIFFERENT MULTIPLICITIES

AND/OR DIFFERENT CUTOFF RIGIDITIES