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Results of the 2006 Ship-Borne Neutron Monitor Survey

Seminar V. Results of the 2006 Ship-Borne Neutron Monitor Survey. . PRESENTED BY WARAPORN NUNTIYAKUL 5238713 SCPY/D. OUTLINE. Page 2. The computed trajectories for Newark, De. OUTLINE. Introduction Methodology 3. Results and Discussion 4. Conclusion 5. Acknowledgments

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Results of the 2006 Ship-Borne Neutron Monitor Survey

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  1. Seminar V Results of the 2006 Ship-Borne Neutron Monitor Survey .. PRESENTED BY WARAPORN NUNTIYAKUL 5238713 SCPY/D

  2. OUTLINE Page 2 • The computed trajectories for Newark, De OUTLINE Introduction Methodology 3. Results and Discussion 4. Conclusion 5. Acknowledgments 6. References

  3. INTRODUCTION Page 3 INTRODUCTION WHAT IS A NEUTRON MONITOR? neutron monitor is a ground-based detector designed to measure the number of high-energy charged particles striking the Earth's atmosphere from outer space. Developed to Standard NM64 IGY monitor (International Geophysical Year) Counting Rate Vs Time Pressure Vs Time FIG. 1 NM model

  4. INTRODUCTION Page 4 NEUTRON MONITOR PRINCIPLE BARE NMs Fig. 2 Image Credit : Paul Evenson, January2009 Fig. 3 Image Credit :PSNM • - Detects secondary neutrons generated by collision of primary • cosmic rays with air molecules. • Detection Method: • Older type-proportional counter filled with BF3 • n + 10B  + 7Li • Modern type-proportional counter filled with 3He • n + 3He  p + 3H

  5. INTRODUCTION Page 5 • Rigidity is a concept used to determine the effect of particular magnetic fields on the motion of the charged particles.It is defined as • R = Bρ = p/q • WhereB is the magnetic field • ρ is the gyroradius of the particle due to this field • p is the particle momentum • and qis its charge. • Vertical Cutoff Rigidity is the cutoff for a vertically incident particle • Apparent Cutoff Rigidity is the cutoff depends upon the details of • cosmic ray penumbra in each possible direction of incidence. • Solar modulation is the flux (flow rate) of cosmic rays incident on the Earth’s upper atmosphere is modulated (varied) by two processes; the sun’s solar wind and the Earth's magnetic field. • Differential response is the differentiation the curve relating counting rate and • cutoff rigidity FIG. 4

  6. INTRODUCTION 9 SURVEY TECHNIQUE To improve NM response function Describes the input-output relationship of a signal transducer such as a neuron turning synaptic input into a response. • Dorman Function • Nagashima et al (1989) Page 6 Dorman Function: 1 FIG. 5-1 Spectral Crossover FIG. 5-2 Sample fit of a segment’s data to a Dorman function, along with the corresponding derivative.

  7. Page 7 SURVEY TECHNIQUE To improve Cutoff Sky Map 2 geomagnetic cutoff model • DGRF Magnetic Field Model : Definitive International Geomagnetic Reference FieldplusTsyganenko magnetosphere • Calculate “Efficient Apparent” • (sky average) Cutoffs “A sky map is calculated by tracing trajectories of charged particles through the geomagnetic field to determine allowed and forbidden rigidities” [Lin et al., 1995]. Fig 6 Example of an effective cutoff rigidity sky map for 43.92 OS, 76.64 OW at 2330 UT on day 75 of 1995. Here the effective vertical cutoff is 8.23 GV and the apparent cutoff is 8.65 GV. (Clem et al., 1997)

  8. INTRODUCTION Page 8 SCIENTIFIC BACKGROUND: Nagashima Response Function Transportable Monitor (not to scale) U.S. Coast Guard icebreakers, the Polar Seaor the Polar Star carry a Neutron monitor standard 3-NM64 geomagnetic Transmission Pc heliosphericModulation GCR spectrum Yield function Counting Rate STEP FUNCTION Assuming L is a limiting rigidity, Tis a step function T Differential Response fn. 1 P 0

  9. INTRODUCTION Page 9 DEVELOP OPTIMAL METHODS( ) FOR EXTRACTING COSMIC RAY SPECTRA FROM LATITUDE SURVEYS. [Calculate integrals of the Nagashima Response Function using Simpson’s rule] Nagashima method Set and manage the parameters of the response function calculations. There are a total of 14 adjustable parameters. In this routine they are numbered 1-14 and dealt with systematically. The defaults are the values in the paper. Galactic Cosmic Ray Spectrum GCR Spectrum The total energy per nucleon (assuming proton) in unit of Proton mass = 0.93827231 Best parameters from the paper --- > 1 = 1.2 ×108, 2 = 0.0, 3 = 2.585

  10. INTRODUCTION Page 10 Yield Function - The total energy per nucleon (assuming proton) in unit of Best parameters from the paper --- >  = 0.0, 1 = 2.2, 2 = 1.62, 3 = 12.7, 4 = 0.50, 5 = 0.42 Modulation Function Yield Function Modulation Function - This term is due to the energy dependence of the neutron production and expresses the h-dependence of Y in high-energy region - This term expresses the decrease of the production mainly due to the decrease of the number of effective nucleons in the atmosphere with the increase of h and with the decrease of u where 1(t) as a function of other parameters and variables so it must be recomputed from time to time by the functions that use the parameters Best parameters from the paper --- > 2 = 0.097, 3 = 1.02, 4 = 1.15, 5 = 14.9, 6 = 1.12

  11. INTRODUCTION Page 11 ANALYZE THE DATA FROM A SHIP-BORNE MONITOR WITH THREE COUNTER TUBES Made trips across the Pacific ocean from Seattle to Antarctica and back, over a wide range of cutoff rigidities, over 1994 to 2007. U.S. Coast Guard icebreakers Fig. 7Route of Latitude surveys

  12. INTRODUCTION Page 12 WHAT ARE “PITCH” AND “ROLL” MOTION? Ship Motions: Pitchis when the vessel rotates about the transverse (side-to-side axis) Row is when the vessel rotates about the longitudinal (front/back axis) Yaw is when the vessel rotates about the longitudinal (up/down axis) Fig. 8 Ship motions YAW The Clinometer Assembly ROLL Side View PITCH

  13. METHODOLOGY Page 13 Fig. 9 Planning for my work

  14. RESULTS & DISCUSSION Page 14 Result of Simulated Survey fitting Nagashima parameters Square of the accumulated counting rate difference Fig. 10 Data (box) and model fit (line) to the moderated neutron detector Latitude survey conducted under award OPP-0838838. Fit parameters were used follow Nagashima (1989) paper Best parameters from Nagashima et al., 1989 Definitions 1 = An overall normalization  and  = The parameters describe the yield function.

  15. RESULTS & DISCUSSION Page 15 Result of Simulated Survey fitting my parameters Quality = 1.8139E+01 Quality = 2.7561E+01 Best parameters in Nagashima et al., 1989 Fig. 11 Data (box) and model fit (line) to the moderated neutron detector Latitude survey.The parameters in the figure show the best fit in my research. Best parameters in my research Box symbol: we show the counting rate (counts/second) plotted against the apparent cutoff calculated at the center point of the averaging interval. Most of the systematic wandering results from variations in barometric-pressure. Line symbol: we show the model achieved after several iterations of my fitting routine.

  16. RESULTS & DISCUSSION Page 16 Comparing with Nagashima parameters ▫Start: 320.88680 (Acut =1.89 GV) End: 344.00625 (Acut = 15.78 GV) ▫ Start: 344.02742 (Acut=15.77 GV) End: 416.70694 (Acut = 0.10 GV) ▫ Start: 416.728111 (Acut=0.14 GV) End: 439.93090 (Acut= 15.85 GV) ▫ Start: 439.93090 (Acut=15.84 GV) End: 458.77152 (Acut = 1.83 GV) FORBUSH DECREASE Forbushdecreaseis a rapid decrease in the observed GCRs intensity following a CME. It occurs due to the magnetic field of the plasmasolar wind sweeping some of the GCRs away from Earth. Comparing with my parameters DOY 352 DOY 348 black bunches occurring due to the problem of barometric pressure. Fig. 12 Residuals (counts/second) from the fit shown in Fig. 11 as a function of geomagnetic cutoff.

  17. RESULTS & DISCUSSION Page 17 Result of residuals as a function of time Fig. 13 Residuals (counts/second) from the fit shown in Fig. 11 as a function of time.

  18. RESULTS & DISCUSSION Page 18 Result of residuals as a function of barometric-pressure Fig. 14 Residuals (counts/second) from the fit shown in Fig. 11 as a function of barometric-pressure (mmHg)

  19. RESULTS & DISCUSSION Page 19 Result of residuals as a function of modulation level Mt Washington max =2465 counts/hour McMurdo max =10600 counts/hour FORBUSH DECREASE Fig. 15 Residuals (counts/second) from the fit shown in Fig. 11 as a function of modulation level.

  20. RESULTS & DISCUSSION Page 20 Result of cosmic ray spectra As a function of rigidity, depth (pressure), n Atmospheric depth in atmospheres (1.000=1033 g/cm2 = 760 mmHg Differential Response Function Differential Response Function 300 (g/cm2) 300 (g/cm2) 500 (g/cm2) 500 (g/cm2) 700 (g/cm2) 700 (g/cm2) 1033 (g/cm2) 1033 (g/cm2) (a) (b) Fig. 16 Differential response function of neutron monitor for several atmospheric depths in the periods of the maximum and minimum solar activities as derived by Nagashima et al. : (a) analyze by using the best parameters from paper and (b) analyze by using the best parameters from my research. Figures attached to each curve express the atmospheric depth (h g/cm2). Figure (above dots) is the minimum solar activity (JMtW=2465), Figure(below dots) is the maximum solar activity (JMtW=1990).

  21. CONCLUSION Page 21 CONCLUSION The ultimate goal is to go beyond the Dorman functions to more physical response functions. At any rate in this work need to begin folding modulation levels into the analysis. In my research is successful in determining the value of 14 parameters which it provides the simulation model better than Nagashima. As we vary parameters by using Simpson’s rule until we got the best model. The number of Quality is even low, the fit is even better. When residuals are plotted as a function of apparent cutoff rigidity, barometric-pressure, modulation level or time there is no structure apart from statistical scatter, the deviation from the model is clearly visible; systematic analysis of the data from our thirteen surveys with the same instrument on sister ships (and therefore a truly constant yield function) should clearly define the spectral dependence. In this analysis particular attention will be paid to the implications of composition on the results by explicitly allowing for composition variation in the model. When combined with the results from other proposed tasks, this work will enable us to refine knowledge of the yield function.

  22. ACKNOWLEDGEMENT Page 22 ACKNOWLEDGEMENT The Royal Golden Jubilee Ph.D Program [โครงการปริญญาเอกกาญจนาภิเษก] Prof. Paul Evenson Prof. David Ruffolo Assoc.Prof. John Clem Dr. Alejandro Sáiz Dr. Andrew Snodin Dr. Takao Kuwabara

  23. REFERENCES Page 23 REFERENCES 1. Moraal, H., Potgieter, M.S., Stoker, P.H., and van derWalt, A.J., “NM Latitude Survey of the Cosmic Ray Intensity During the 1986/87 Solar Minimum”, J. Geophys. Res. 94, 1,459–1,464, 1989. 2. Bieber, J.W., Evenson, P.E., Humble J.E., and Duldig, M.., 1997, “Cosmic Ray Spectra Deduced from Neutron Monitor Surveys”, Proc. 25th Intl. Cosmic Ray Conf. (Durban) 2, 45– 48, 1997. 3. Lockwood, J.A. and Webber, W.R., “Comparison of the rigidity dependence of the 11-year cosmic ray variation at the Earth in two solar cycles of opposite magnetic polarity”, J. Geophys. Res., 101, 21573-21580, 1996. 4. Reinecke, J.P.L., Moraal, H., Potgieter, M.S., Mc- Donald, F.B., and Webber, W.R., “Different Crossovers”, Proc. 25th Int. Cosmic Ray Conf. (Durban) 2, 49–52, 1997. 5. Lin, Z., J.W. Bieber and P. Evenson, “Electron trajectories in a model magnetosphere: Simulation and observation under active conditions”, J. Geophys. Res., 100, 23,543-23,549, 1995.

  24. REFERENCES Page 24 6. Flückiger, E.O. and Kobel, E., “Aspects of Combining Models of the Earth's Internal and External Magnetic Fields”, J. Geomag. GeoElec., 42, 1123-1128, 1990. 7. Clem, J.M., Bieber, J.W., Evenson, P., Hall, D., Humble, J.E., and Duldig, M., “Contribution of Obliquely Incident Particles to Neutron Monitor Counting Rate”, J. Geophys. Res., 102, 26919, 1997. 8. Bieber, J.W., Clem, J., Duldig, M.L., Evenson, P., Humble, J.E. and Pyle, R., “A continuing yearly neutron monitor yearly survey: Preliminary results from 1994-2001”, Proc. 27th Intl. Cosmic Ray Conf.(Hamburg) 10, 4087-4090, 2001. 9. Smith, C. W., and Bieber, J. W., “Detection of Steady Magnetic Helicity in Low-Frequency IMF Turbulence”, Proc. 23rd Internat. Cosmic Ray Conf. (Calgary), 3, 493-496, 1993. 10. Bieber, J.W. and Evenson, P., “Spaceship Earth — an Optimized Network of Neutron Monitors”, Proc. 24th Intl. Cosmic Ray Conf. (Rome) 4, 1078-1081, 1995.

  25. Page 25 Thank you for your attention I welcome your questions, suggestions, comments! Epigram for Today Lie In Center Of Believe!

  26. SUPPLEMENT SLIDES Page 27 Result of Nagashima 1989 latitude surveys Fig. 16 Display Nagashima 1989 latitude surveys , the relationship between the simulated counting rate and cutoff rigidity (GV), at Solar maximum (above dots) and solar minimum (below dots)

  27. SUPPLEMENT SLIDES Page 28 Spectrum Crossover FIGURE Western Pacific Segments: using 1980 Cutoffs (Top) vs.Tsyganenko Cutoffs (Bottom)

  28. SUPPLEMENT SLIDES Page 29 FIGURE Course plots for the 8 surveys used in this paper. Each is labeled at 5-day intervals by the start year of the survey (e.g. 7 for 1997/98). “Segment” codes are given in the inset. Selected vertical cutoff contours are labeled.

  29. SUPPLEMENT SLIDES Page 30 Apparent Cutoff

  30. SUPPLEMENT SLIDES Page 31

  31. SUPPLEMENT SLIDES Page 32 RESULTS & DISCUSSION Analysis of the variation of relative count rate with pitch bin Pitch Bins BIN Mean Sigma SigmaMu Cases -5 0.99 0.17 0.01 211.00 -4 1.00 0.14 0.01 378.00 -3 0.99 0.15 0.01 715.00 -2 1.00 0.14 0.00 1445.00 -1 1.00 0.08 0.00 3374.00 0 1.00 0.00 0.00 6476.00 1 1.01 0.09 0.00 3395.00 2 1.00 0.14 0.00 1514.00 3 1.00 0.16 0.01 815.00 4 1.00 0.15 0.01 468.00 5 1.00 0.20 0.01 312.00 Fig. 9 Show the example of variation of the relative count rate with pitch bin of ship of the data in year 2006. The black points (□)are the input data all of the data are just plotted “on top of” each other to be sure that there are no funny values (we usually call these “fliers”). The red points (o) are the average of all the black points. The blue points (o)show the deviation of the red points from 1.00 expanded by a factor of ten, with statistical error bars.

  32. SUPPLEMENT SLIDES Page 33 Analysis of the variation of relative count rate with roll bin Pitch Bins BIN Mean Sigma SigmaMu Cases -5 0.98 0.16 0.01 250.00 -4 0.98 0.20 0.01 464.00 -3 0.99 0.16 0.01 950.00 -2 0.99 0.13 0.00 1932.00 -1 1.00 0.08 0.00 3524.00 0 1.00 0.01 0.00 6476.00 1 1.00 0.07 0.00 3464.00 2 1.00 0.15 0.00 1983.00 3 1.01 0.19 0.01 970.00 4 1.02 0.18 0.01 488.00 5 1.00 0.15 0.01 277.00 Fig. 10 Show the example of variation of the relative count rate with roll bin of ship of the data in year 2006. The black points (□)are the input data all of the data are just plotted “on top of” each other to be sure that there are no funny values (we usually call these “fliers”). The red points (o)are the average of all the black points. The blue points (o)show the deviation of the red points from 1.00 expanded by a factor of ten, with statistical error bars.

  33. SUPPLEMENT SLIDES Page 34 Analysis of the apparent cutoff Fig. 11 Apparent cutoff calculated (GV) during the Seattle-McMurdo of the year 2006-2007 latitude survey compared with time. The missing data occurs during DOY 330 due to the problem of data recorder.

  34. SUPPLEMENT SLIDES Page 35 Analysis of the barometric-pressure Fig. 12 Show the barometric-pressures were read by digiquartz barometer in millimeters of mercury (mmHg) as a function of time (DOY2006).

  35. SUPPLEMENT SLIDES Page 36 Analysis of the counting rate Fig. 13 Show the averaged counting rate as a function of time (DOY2006).

  36. SUPPLEMENT SLIDES Page 37 Analysis of the modulation level Mt Washington max =2465 counts/hour McMurdo max =10600 counts/hour Fig. 14 Show the modulation level of McMurdo simulated Mt. Washington as a function of time (DOY2006).

  37. SUPPLEMENT SLIDES Page 38

  38. SUPPLEMENT SLIDES Page 39

  39. DoiInthanon (16.8 GV) Rigidity = pc/q determines particle trajectory in magnetic field

  40. INTRODUCTION Hypothetical Spectrum FLUX (m2 sr s GeV)-1 16.8 GV Rigidity (GV)

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