vr: a new index to represent the regional geomagnetic activity
DESCRIPTION
Vr: A New Index to Represent the Regional Geomagnetic Activity. Dongmei Yang, Yufei He, Chuanhua Chen, Yahong Yuan 2010-9-21 Changchun. Outline. Introduction Data Processing Results and Discussion Conclusion. Outline. Introduction Data Processing Results and Discussion Conclusion. - PowerPoint PPT PresentationTRANSCRIPT
Vr: A New Index to Represent the Regional Ge
omagnetic Activity
Dongmei Yang, Yufei He, Chuanhua Chen, Yahong Yuan
2010-9-21
Changchun
Outline
• Introduction
• Data Processing
• Results and Discussion
• Conclusion
Outline
• Introduction
• Data Processing
• Results and Discussion
• Conclusion
The disturbances revealed by the first differences could be seen in all the observatories simultaneously which reminded us that the source for the disturbances was in the magnetosphere.
The first differences also showed 27 solar-cycle recurrences. The feature was quite similar with the Kp’s.
There are some disturbances that Kp could not describe.
Another new index might be needed for people to understand the change of the magnetic field.
Outline
• Introduction
• Data Processing
• Results and Discussion
• Conclusion
Data
• Minute data for the year 2008 from the following observatories– Chinese observatories– Global observatories
• CLF, MMB, HON and SJG• Data downloaded from INTERMAGNET website
Method
• Vr index calculation: – Calculating the first differences of the minute values o
f the geomagnetic horizontal component (H D/X Y).– calculating the hourly standard deviations of the abov
e first differences.– Subtracting background noises (0.1nT) from the hourl
y standard deviations– In case that the hourly standard deviation was less th
an 0.1nT, the Vr value was assigned to be 0.
Noise level of 1s data
• Noise Level achieved– D 0.06nT– H 0.07nT– Z 0.07nT– F 0.04nT
Outline
• Introduction
• Data Processing
• Results and Discussion
• Conclusion
Results and Discussion
• Relationship between Vr and other indices
• Temporal Change of Vr– Changes with the 27 solar rotation cycle – Seasonal change
• Spatial change of Vr– Latitudinal dependences (not talked today)– Longitudinal dependences
(Local time dependences)
SJG MMB CLF HON WMQ
KP 0.77462 0.757963 0.767482 0.751112
0.745843
AP 0.768873 0.717089 0.745654 0.723117
0.716811
Correlation between Vr and other indices
MZLy = 4. 1981x + 0. 8526
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
MZLy = 24. 484x - 7. 2058
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
LYHy = 5. 7662x + 1. 6468
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
WHNy = 5. 4122x + 1. 4586
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
QZHy = 7. 189x + 2. 2576
0
10
20
30
40
50
0 2 4 6 8 10
∑ SDDH/ nT•mi n-1
∑Kp
LYHy = 34. 413x - 3. 999
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
WHNy = 32. 345x - 5. 2062
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
QZHy = 42. 926x - 0. 5726
0
50
100
150
200
250
300
0 2 4 6 8 10
∑ SDDH/ nT•mi n-1
∑ap/2nT
MZLy = 4. 1981x + 0. 8526
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
MZLy = 24. 484x - 7. 2058
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
LYHy = 5. 7662x + 1. 6468
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
WHNy = 5. 4122x + 1. 4586
0
10
20
30
40
50
0 2 4 6 8 10
SDD
∑Kp
QZHy = 7. 189x + 2. 2576
0
10
20
30
40
50
0 2 4 6 8 10
∑ SDDH/ nT•mi n-1
∑Kp
LYHy = 34. 413x - 3. 999
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
WHNy = 32. 345x - 5. 2062
0
50
100
150
200
250
300
0 2 4 6 8 10
SDD
∑ap/2nT
QZHy = 42. 926x - 0. 5726
0
50
100
150
200
250
300
0 2 4 6 8 10
∑ SDDH/ nT•mi n-1
∑ap/2nT
The first differences also showed 27 solar-cycle recurrences. The feature was quite similar with the Kp’s.
Monthly Means for H/X Component
0
2
4
6
8
10
12
1 10 19 28 37 46 55 64 73 82 91 100 109 118 127 136 145 154 163 172 181 190 199 208 217 226 235 244 253 262 271 280
WMQ
SDDH- 1HR-月总和
按月排
按时段排
0
2
4
6
8
10
12
1 10 19 28 37 46 55 64 73 82 91 100 109 118 127 136 145 154 163 172 181 190 199 208 217 226 235 244 253 262 271 280
WMQ
SDDH- 1HR-月总和
按月排
按时段排
SDDD-1HR-月总和
0
2
4
6
8
10
12
14
16
1 16 31 46 61 76 91 106 121 136 151 166 181 196 211 226 241 256 271 286
WMQ
SDDD-1HR-月总和
0
2
4
6
8
10
12
14
16
1 16 31 46 61 76 91 106 121 136 151 166 181 196 211 226 241 256 271 286
WMQ
Monthly Means for D/Y Component
Local time dependence of Vr
Observatories used in the study
IAGA code
Latitude
(°)
Longitude
(°)
Local time differences
referred to UTC
CLF 48.02 2.27 0
WMQ 43.80 87.70 6h
MMB 43.91 144.19 10h
HON 21.32 202.00 13h
SJG 18.12 293.85 20h
Annual MeansSDDH- 1HR-年总和
0
20
40
60
80
100
120
140
160
180
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24时段s
ddh
SJ G MMB CLF HON WMQ
SDDD- 1HR- 年总和
0
200
400
600
800
1000
1200
1400
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
SJ G MMB CLF HON WMQ
sum归一
0
0. 01
0. 02
0. 03
0. 04
0. 05
0. 06
0. 07
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
SJ G MMB CLF HON WMQ
sum归一
0
0. 01
0. 02
0. 03
0. 04
0. 05
0. 06
0. 07
0. 08
0. 09
0. 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
SJ G MMB CLF HON WMQ
H/X component
D/Y component
1
02
3
4
5
6
7
6
8
9
1011
1213
12
1415
16
17
18
1918
20
21
2223
24
SDDD-peak-aver
1
02
3
4
5
6
76
8
9
1011
1213
12
1415
16
17
18
1918
20
21
2223
24
SDDH-peak-aver
Outline
• Introduction
• Data Processing
• Results and Discussion
• Conclusion
Conclusion
• Vr is an index that can be used to detect geomagnetic disturbances from the magnetosphere. Vr has clear physical meaning.
• Vr can detect geomagnetic disturbances not only those Kp and ap detect but also some small disturbances that Kp and ap can not detect. So Vr is more sensitive to the geomagnetic activities than Kp and ap.
• Vr can be easily calculated by individual observatory so it can be used as a regional index and can serve people in quasi real time.
END
Thanks for your attention