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
Results of the 2006 Ship-Borne Neutron Monitor Survey
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.
(International Geophysical Year)
Counting Rate Vs Time
Pressure Vs Time
FIG. 1 NM model
NEUTRON MONITOR PRINCIPLE
Fig. 2 Image Credit :
Paul Evenson, January2009
Image Credit :PSNM
NM response function
Describes the input-output relationship of a signal transducer such as a neuron turning synaptic input into a response.
FIG. 5-2 Sample fit of a segment’s data to a Dorman function, along with the corresponding derivative.
Cutoff Sky Map
geomagnetic cutoff model
“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)
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
Assuming L is a limiting rigidity, Tis a step function
Differential Response fn.
DEVELOP OPTIMAL METHODS( ) FOR EXTRACTING COSMIC RAY SPECTRA FROM LATITUDE SURVEYS.
[Calculate integrals of the Nagashima Response Function using Simpson’s rule]
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
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
- 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
- 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
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
WHAT ARE “PITCH” AND “ROLL” MOTION?
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
The Clinometer Assembly
Fig. 9 Planning for my work
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
1 = An overall normalization
and = The parameters describe the yield function.
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.
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)
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
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.
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.
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)
Result of residuals as a function of modulation level
Mt Washington max =2465 counts/hour
McMurdo max =10600 counts/hour
Fig. 15 Residuals (counts/second) from the fit shown in Fig. 11 as a function of modulation level.
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
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).
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.
The Royal Golden Jubilee Ph.D Program
Prof. Paul Evenson
Prof. David Ruffolo
Assoc.Prof. John Clem
Dr. Alejandro Sáiz
Dr. Andrew Snodin
Dr. Takao Kuwabara
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,
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.
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.
Thank you for your attention
I welcome your questions, suggestions, comments!
Epigram for Today
Lie In Center Of Believe!
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)
FIGURE Western Pacific Segments: using 1980 Cutoffs (Top) vs.Tsyganenko Cutoffs (Bottom)
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.
RESULTS & DISCUSSION
Analysis of the variation of relative count rate with pitch bin
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.
Analysis of the variation of relative count rate with roll bin
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.
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.
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).
Analysis of the counting rate
Fig. 13 Show the averaged counting rate as a function of time (DOY2006).
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).
Rigidity = pc/q determines particle trajectory in magnetic field
FLUX (m2 sr s GeV)-1