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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Analysis of Data from a Calibration Neutron Monitor at DoiInthanon and a Ship-Borne Neutron Monitor

Presented By

WarapornNuntiyakul

5238713 SCPY/D

- Overview of the relevant theoretical literature
- Methodology
- Results and Discussion of work-to-date
- [including addressing major difficulties encountered]
- Summary and Conclusion
- Possible future directions
- Acknowledgement
- References

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 et al. (2000)
- Nagashima et al. (1989)

Page 7

SURVEY TECHNIQUE

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. -- Credit: Bieber et al. 2003

SURVEY TECHNIQUE

Cutoff Sky Map

To improve

2

geomagnetic cutoff model

- DGRF Magnetic Field Model : Definitive International Geomagnetic Reference Fieldplus Tsyganenko 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 Effective cutoff rigidity sky map for 43.92 OS, 76.64 OW at 2330 UT on day 75 of 1995. Vertical cutoff is 8.23 GV and apparent cutoff is 8.65 GV. Solid dots show locations where cutoffs are calculated for the ring approximation -- Credit: Clem et al., 1997)

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

DEVELOP OPTIMAL METHODS (Nagashima method) 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

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

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

Image Credit: http://www.dfi.uchile.cl/ec_web/htm/cosmic_rays_network.html

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

Good Results

(glitches are removed from the data set )

See the physical effects of interest

Fit all the data together using SURVEY

(We should get the best of the Yield function parameters)

Produce the spectra of latitude surveys

Quality = 7.5303E+00

Figure 1-1Data (box) and model fit (line) to the moderated bare latitude survey in 1994-1995 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

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.

We called “the goat” when the fit errors are smooth and near zero except for a rather definite time interval that they go somewhat negative.

A

B

Goat existence

Goat existence

Data Gap

~DOY368-369

Removed the goat

C

Goat existence

Figure 1-2Residuals (counts/second) from

the fit shown in Figure 1-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

Goat existence

B

A

Figure 1-3 Residuals (counts/second) from the fit shown in Figure 1-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

x = no problem

Quality = 4.0460E+00

Figure 2-1Data (box) and model fit (line) to the moderated bare latitude survey in 1995-1996 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

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.

A

C

Figure 2-2Residuals (counts/second) from

the fit shown in Figure 2-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 2-3 Residuals (counts/second) from the fit shown in Figure 2-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 4.3571E+01

Figure 3-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 1995-1996 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

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.

A

Data Gap

~DOY 432-445

C

Figure 3-2Residuals (counts/second) from

the fit shown in Figure 3-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 3-3 Residuals (counts/second) from the fit shown in Figure 3-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 5.1740E+01

Figure 4-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 1996-1997 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

B

Data Gap

~ DOY 400-409

Data Gap

~ DOY 359-361

Removed the bad counts

Removed the bad counts

C

Figure 4-2Residuals (counts/second) from

the fit shown in Figure 4-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

Removed the bad counts

Removed the bad counts

A

B

Figure 4-3Residuals (counts/second) from the fit shown in Figure 4-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 4.6057E+01

Figure 5-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 1997-1998 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

Data Gap

~DOY 305-308

C

Figure 5-2Residuals (counts/second) from

the fit shown in Figure 5-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

B

Figure 5-3Residuals (counts/second) from the fit shown in Figure 5-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 2.5470E+01

Figure 6-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 1998-1999 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

B

Data Gap

~DOY 314-320

Data Gap

~DOY 443-445

Removed

Bad Mod

Data Gap

~DOY 377-425

Data Gap

~DOY 307-312

Removed Bad Mod

Removed

Bad Mod

Figure 6-2Residuals (counts/second) from

the fit shown in Figure 6-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

C

B

Figure 6-3Residuals (counts/second) from the fit shown in Figure 6-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 2.7758E+01

Figure 7.1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 1999-2000 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

C

Figure 7-2Residuals (counts/second) from

the fit shown in Figure 7-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 7-3Residuals (counts/second) from the fit shown in Figure 7-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2000-2001 Survey – Neutron Monitor

x = no problem

Quality = 6.2524E+01

Figure 8-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2000-2001 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

Forbushdecrease(FD) is 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.

Removed FD

B

Removed FD during DOY 465-470

A

Removed FD

Figure 8-2Residuals (counts/second) from

the fit shown in Figure 8-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

C

Removed FD

B

A

Figure 8-3Residuals (counts/second) from the fit shown in Figure 8-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

Quality = 1.0521E+01

Figure 9-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2001-2002 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

B

C

Figure 9-2Residuals (counts/second) from

the fit shown in Figure 9-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

B

Figure 9-3Residuals (counts/second) from the fit shown in Figure 9-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2002-2003 Survey – Neutron Monitor

x = no problem

Quality = 4.7706E+01

Figure 10Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2002-2003 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

C

Figure 10-2Residuals (counts/second) from

the fit shown in Figure 10-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 10-3Residuals (counts/second) from the fit shown in Figure 10-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2003-2004 Survey – Neutron Monitor

x = no problem

Quality = 2.1498E+01

Figure 11-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2003-2004 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

B

C

Figure 11-2Residuals (counts/second) from

the fit shown in Figure 11-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 11-3Residuals (counts/second) from the fit shown in Figure 11-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2004-2005 Survey – Neutron Monitor

x = no problem

EQ = various EQuipment problems

FD = Forbush Decrease

Quality = 2.737E+01

Figure 12-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2004-2005 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashima et al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

Removed

FD

Removed

FD during

DOY383-387

C

Figure 12-2Residuals (counts/second) from

the fit shown in Figure 12-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

Removed FD

B

Removed FD

Removed FD

Figure 12-3Residuals (counts/second) from the fit shown in Figure 12-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2005-2006 Survey – Neutron Monitor

x = no problem

Quality = 4.9700E+00

Figure 13-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2005-2006 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

C

Figure 13-2Residuals (counts/second) from

the fit shown in Figure 13-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

A

Figure 13-3Residuals (counts/second) from the fit shown in Figure 13-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

2006-2007 Survey – Neutron Monitor

x = no problem

EQ = various EQuipment problems

FD = Forbush Decrease

Quality = 1.8139E+01

Figure 14-1Data (box) and model fit (line) to the moderated neutron monitor latitude survey in 2006-2007 survey. The parameters in the figure show the best fit in my research (Left) and in Nagashimaet al., 1989 (Right).

Line symbol: we show the model achieved after several iterations of my fitting routine.

A

Removed all of the decreasing modulation

Removed all of the decreasing modulation

C

Figure 14-2Residuals (counts/second) from

the fit shown in Figure 14-1

A as a function of time

B as a function of modulation level

Cas a function of barometric-pressure (mmHg)

Removed all of the decreasing modulation

Removed all of the decreasing modulation

Removed all of the decreasing modulation

A

B

Figure 14-3Residuals (counts/second) from the fit shown in Figure 14-1 as a function of Apparent Cutoff Rigidity (GV).

A analyze by using the best parameters from Nagashima et al., 1989

B analyze by using the best parameters from my research

- 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.

- Check one more time, examining fit deviation vs. time for each season, to
- make sure that obvious glitches are removed from the data set now.
- [processing]
- See closely the original Nagashima parameters with some improvements
- to axis ranges for greater clarity, and including all plots in a single PDF
- file for ease of viewing/printing by focusing to the fit deviation vs. cutoff
- rigidity for each survey year. [processing]
- Start to see the physical effects of interest! should be a systematic
- deviation/distortion that gradually changed as we moved into solar max. and
- gradually changed back again as we moved back into solar min.
- a next refinement will be to fit all the data together using SURVEY,
- which must improve the deviation somewhat and hopefully reduce the
- scatter.

acknowledgement

The Royal Golden Jubilee Ph.D Program

[โครงการปริญญาเอกกาญจนาภิเษก]

Prof. Paul Evenson

Prof. David Ruffolo

Assoc.Prof. John Clem

Dr. Andrew Snodin

Dr. Alejandro Sáiz

Dr. Takao Kuwabara

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.

Page 25

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.

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