ISO 16698:2019
(Main)Space environment (natural and artificial) — Methods for estimation of future geomagnetic activity
Space environment (natural and artificial) — Methods for estimation of future geomagnetic activity
This document specifies the methods used for estimating geomagnetic indices for time intervals ranging from short-term (hours to a few months) to long-term (months to years). This document is intended for use to predict future geomagnetic indices and space environment.
Environnement spatial (naturel et artificiel) — Méthodes d'estimation de l'activité magnétique future
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INTERNATIONAL ISO
STANDARD 16698
Second edition
2019-12
Space environment (natural and
artificial) — Methods for estimation of
future geomagnetic activity
Environnement spatial (naturel et artificiel) — Méthodes
d'estimation de l'activité magnétique future
Reference number
©
ISO 2019
ISO 16698:2019(E)
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ii © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 1
5 General parameters . 2
5.1 Geomagnetic field variations . 2
5.2 Quiet level and disturbance fields . 2
5.3 K index (local 3 h range index). 2
5.4 Kp, ΣKp, ap and Ap indices (planetary indices) . 3
5.4.1 General. 3
5.4.2 Kp index (planetary 3 h range index) . 3
5.4.3 ΣKp index (planetary daily range index) . 3
5.4.4 ap index (planetary 3 h equivalent amplitude index). 3
5.4.5 Ap index (planetary daily equivalent amplitude index) . 4
5.5 aa index (antipodal amplitude index) . 4
5.6 Dst index (storm time disturbance index) . 4
5.7 ASY and SYM indices (mid-latitude disturbance indices) . 5
5.8 AU, AL, AE and AO indices (auroral electrojet indices) . 5
5.9 am index. 6
5.10 PC index . 7
5.11 Time lag in the derivation and temporal resolution (sampling) . 7
6 Classification of prediction . 8
6.1 General . 8
6.2 Short-term prediction . 8
6.3 Middle-term prediction . 8
6.4 Long-term prediction . 8
7 Methods of prediction . 9
7.1 General . 9
7.2 Prediction based on statistical models. 9
7.2.1 Linear or non-linear prediction filter . 9
7.2.2 Machine learning . 9
7.2.3 Probabilistic prediction . 9
7.3 Prediction based on physical principle . 9
8 Evaluation of prediction efficiency . 9
8.1 Definition of prediction error . 9
8.2 Methods of evaluation .10
9 Compliance criteria .10
9.1 Rationale.10
9.2 Reporting .10
9.3 Documenting.10
9.4 Publishing .11
9.5 Archiving .11
10 Useful Informative Documents .11
Annex A (informative) Websites where geomagnetic indices are available .12
Annex B (informative) Websites where the space weather predictions and/or "now casting"
are presented .13
Annex C (informative) Definition of various skill scores .14
ISO 16698:2019(E)
Annex D (informative) Useful academic documents related with this document's fields are
presented (These are not cited in the document) .15
Bibliography .22
iv © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www .iso .org/ patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www .iso .org/
iso/ foreword .html.
This document was prepared by Technical Committee ISO/TC 20, Aircraft and space vehicles,
Subcommittee SC 14, Space systems and operations.
This second edition cancels and replaces the first edition (ISO 16698:2013), which has been technically
revised. The main changes compared to the previous edition are as follows:
— addition of 5.9 and 5.10;
— update of reference lists of Clause 6.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/ members .html.
ISO 16698:2019(E)
Introduction
This document provides guidelines for specifying the process of estimating future geomagnetic
activity. Geomagnetic indices describe the variation of the geomagnetic field over a certain time period
and provide a measure of the disturbance of the magnetosphere. These indices can be used to estimate
upper atmospheric and plasmaspheric densities and many other space environment models. They are
also used as the input parameters for orbital lifetime prediction and worst-case environment analysis
of electrostatic charging.
The accuracy and method of predicting geomagnetic indices depends on the time scale of prediction.
This document presents existing works based on three categories of time scale:
a) short-term prediction (1 h to a few days);
b) middle-term prediction (a few weeks to a few months);
c) long-term prediction (half a year to one solar cycle).
These are required as input parameters for the magnetospheric magnetic field (ISO 22009), upper
atmosphere (ISO 14222), ionosphere, plasmasphere (ISO 16457), magnetosphere charged particles and
other models of the near-Earth space environment. They also serve as the input parameters for orbital
lifetime prediction and worst-case environment analysis of electrostatic charging.
Three International Standards deal with the Earth's magnetic field, including ISO 16695 on the internal
magnetic field, ISO 22009 on the magnetospheric magnetic field and this document.
vi © ISO 2019 – All rights reserved
INTERNATIONAL STANDARD ISO 16698:2019(E)
Space environment (natural and artificial) — Methods for
estimation of future geomagnetic activity
1 Scope
This document specifies the methods used for estimating geomagnetic indices for time intervals
ranging from short-term (hours to a few months) to long-term (months to years). This document is
intended for use to predict future geomagnetic indices and space environment.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
No terms and definitions are listed in this document.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
4 Symbols and abbreviated terms
Bs Southward component of the interplanetary field
(Bs = 0 when Bz ≥ 0 and Bs = Bz when Bz < 0)
Bz North-south component of the interplanetary field
F10.7 flux Measure of the solar radio flux at a wavelength of 10,7 cm
−22 −2
at the earth's orbit, given in units of 10 W·m
GLat Geographic latitude
GLon Geographic longitude
IMF Interplanetary magnetic field
MLat Geomagnetic latitude
MLon Geomagnetic longitude
MHD Magnetohydrodynamics
Sq Daily geomagnetic field variations during quiet conditions (Solar quiet)
UT Universal time
ISO 16698:2019(E)
5 General parameters
5.1 Geomagnetic field variations
The geomagnetic field consists of internal and external magnetic fields. The internal (main) magnetic
field is produced by source currents that are mostly inside the Earth’s core and by induced currents
present in the solid Earth and the ocean, caused by the temporal variation of external magnetic fields.
The external magnetic field is produced by magnetospheric and ionospheric currents.
The magnetosphere is highly dynamic with time scales ranging from minutes to days. Solar wind is the
ultimate source of magnetospheric dynamics. The role played by the IMF north-south component, Bz,
is particularly important and its southward component, Bs, plays a fundamental role in substorm and
magnetic storm activity through the process of magnetic field line reconnection. Solar wind speed also
plays an essential role in these dynamics.
5.2 Quiet level and disturbance fields
Five days of every month are selected as the Five International Quietest Days using the Kp index
(see 5.4.2). Note that the five quietest days are selected regardless of the absolute level of quietness.
Thus, in a disturbed month, the quietest days may not be very quiet.
Derivation: The quietest days (Q-days) of each month are selected using the Kp indices based on three
criteria for each day: (1) the sum of the eight Kp values, (2) the sum of squares of the eight Kp values
and (3) the maximum of the eight Kp values. According to each of these criteria, a relative order number
is assigned to each day of the month; the three order numbers are then averaged and the days with the
first to fifth lowest mean order numbers are selected as the five international quietest days.
Reference: Website of the Deutsches GeoForschungsZentrum
(http:// www -app3 .gfz -potsdam .de/ kp _index/ qddescription .html).
Once the quiet level is determined using the Five International Quietest Days, disturbance fields can be
obtained as deviations from the quiet level of geomagnetic field.
5.3 K index (local 3 h range index)
The K index is a number in the range of 0 (quiet) to 9 (disturbed) that provides a local classification of
the variations of the geomagnetic field observed after subtraction of the regular daily variation (Sq).
Each activity level relates almost logarithmically to the corresponding disturbance amplitude of the
horizontal field component during a 3 h UT interval. In a day, eight K indices are given in successive 3 h
UT (universal time) intervals (0 h to 3 h, 3 h to 6 h, ., 21 h to 24 h UT).
Derivation: The ranges R for the H and D (or X and Y) components are defined as the expected difference
between the highest and lowest deviation, within the three-hour interval, from a smooth curve (a
regular daily variation) for that element on a magnetically quiet day. Only the larger value of R, i.e. R
for the most disturbed element, is taken as the basis of K. To convert from R to K, a permanent scale
prepared for each observatory is used. Table 1 is an example of the permanent scale for the Niemegk
observatory.
[11] [37] [42]
References: Bartels, et al. [1939] , Mayaud [1980] , Menvielle, et al. [2011] .
Table 1 — Permanent conversion scale from R to K for Niemegk observatory
Range (nT) 0–5 5–10 10–20 20–40 40–70 70–120 120–200 200–330 330–500 ≥500
K value 0 1 2 3 4 5 6 7 8 9
2 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
5.4 Kp, ΣKp, ap and Ap indices (planetary indices)
5.4.1 General
The planetary indices, Kp, ΣKp, ap and Ap, are derived from 13 selected mid-latitude observatories (see
Table 2). The derivation scheme for each index is described in the corresponding subsection.
Table 2 — Thirteen observatories that contributed to the Kp index
Observatory, country Code GLat (°N) GLon (°E) MLat (°) Notes
Meannook, Canada MEA 54,617 246,667 62,5
Sitka, USA SIT 57,058 224,675 60,0
Lerwick, Shetland Is.,UK LER 60,133 358,817 58,9
Ottawa, Canada OTT 45,400 284,450 58,9 Replaced Agincourt in 1969
Uppsala, Sweden UPS 59,903 17,353 58,5 Replaced Lovo in 2004
Eskdalemuir, UK ESK 55,317 356,800 54,3
Brorfelde, Denmark BJE 55,625 11,672 52,7 Replaced Rude Skov in 1984
Fredericksburg, USA FRD 38,205 282,627 51,8 Replaced Cheltenham in 1957
Wingst, Germany WNG 53,743 9,073 50,9
Niemegk, Germany NGK 52,072 12,675 48,8 Replaced Witteveen in 1988
Hartland, UK HAD 50,995 355,517 50,0 Replaced Abinger in 1957
Canberra, Australia CNB −35,317 149,367 −45,2 Replaced Toolangi in 1981
Eyrewell, New Zealand EYR −43,424 172,354 −50,2 Replaced Amberley in 1978
5.4.2 Kp index (planetary 3 h range index)
The Kp index is assigned to successive 3 h UT intervals (0 h to 3 h, 3 h to 6 h, ., 21 h to 24 h UT), giving
eight values per UT day and ranges in 28 steps from 0 (quiet) to 9 (disturbed) with intermediate values
denoted by −, o, or +, resulting in 0o, 0+, 1−,1o, 1+, 2−, 2o, 2+, ., 8−, 8o, 8+, 9− and 9o.
Derivation: The K indices at the 13 observatories given in Table 2 are standardized by means of
conversion tables that have been established through the rather complicated procedure introduced by
[10]
Bartels [1949] . The standardized K indices, called the Ks index, are averaged using weighting factors
to derive the Kp index.
[10] [37] [42]
References: Bartels [1949] , Mayaud [1980] , Menvielle, et al. [2011] .
5.4.3 ΣKp index (planetary daily range index)
ΣKp is the sum of the eight Kp values of the day.
5.4.4 ap index (planetary 3 h equivalent amplitude index)
The Kp index is not linearly related to the geomagnetic disturbances measured in the unit of nT. Instead,
the ap index is introduced as it is roughly proportional to the geomagnetic disturbances. One ap unit
corresponds to approximately 2 nT of geomagnetic variations.
Derivation: The ap index is derived directly from the Kp index by using the conversion table shown in
Table 3.
[12] [37] [42]
References: Bartels and Veldkamp [1954] , Mayaud [1980] , Menvielle, et al. [2011] .
ISO 16698:2019(E)
Table 3 — Conversion table from the Kp index to the ap index
Kp 0o 0+ 1− 1o 1+ 2− 2o 2+ 3− 3o 3+ 4− 4o 4+
ap 0 2 3 4 5 6 7 9 12 15 18 22 27 32
Kp 5− 5o 5+ 6− 6o 6+ 7− 7o 7+ 8− 8o 8+ 9− 9o
ap 39 48 56 67 80 94 111 132 154 179 207 236 300 400
5.4.5 Ap index (planetary daily equivalent amplitude index)
The Ap index is the average of the eight values of the ap index in a UT day.
5.5 aa index (antipodal amplitude index)
The aa index is a simple measure of global geomagnetic activity, which can be traced back continuously
to 1868.
Derivation: The aa index is produced from the K indices of two nearly antipodal magnetic observatories
in England and Australia, which are listed in Table 4. The K indices at the two observatories are
converted back to amplitudes using Table 5. The aa index is computed as an average of the northern and
southern values of amplitude using the weighting factors, λ, shown in Table 4.
[36]
References: Mayaud [1971] .
Table 4 — Observatories in England and Australia contributing to the aa index
Observatory, country Code Period GLat (°N) GLon (°E) MLat (°) λ
Greenwich, England 1868–1925 1,007
Ablinger, England ABN 1926–1956 51,18 359,62 53,4 0,934
Hartland, England HAD 1957– 50,97 355,52 54,0 1,059
Melbourne, Australia 1868–1919 0,967
Toolangi, Australia TOO 1920–1979 −37,53 145,47 −45,6 1,033
Canberra, Australia CNB 1979– −35,30 149,00 −42,9 1,084
Table 5 — Conversion table from the K index at the aa observatories to amplitudes
K index 0 1 2 3 4 5 6 7 8 9
Amplitude 2,3 7,3 15 30 55 95 160 265 415 667
5.6 Dst index (storm time disturbance index)
The Dst index is a measure of the axially symmetric part of the H component along the geomagnetic
equator on the ground and the main physical source is a combination of the equatorial ring current, the
plasma sheet current and the magnetopause current.
Derivation: The Dst index is defined as the average of the disturbance variations of the H component,
D , at the four observatories (i = 1 to 4) listed in Table 6, divided by the average of the cosines of the
i
dipole latitudes at the observatories for normalization to the dipole equator. Dst is computed for each
UT hourly interval from the four observatories.
[54] [55]
References: Sugiura [1964] , Sugiura and Kamei [1991] .
Table 6 — Four observatories contributing to the Dst index
Observatory, country Code GLat (°N) GLon (°E) Dipole Lat (°)
Kakioka, Japan KAK 36,230 140,190 26,0
4 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Table 6 (continued)
Observatory, country Code GLat (°N) GLon (°E) Dipole Lat (°)
San Juan, USA SJG 18,113 293,850 29,6
Honolulu, USA HON 21,320 201,998 21,1
Hermanus, South Africa HER −34,425 19,225 −33,3
5.7 ASY and SYM indices (mid-latitude disturbance indices)
The disturbance fields in mid- and low latitudes are generally not axially symmetric, in particular in the
developing phase of a magnetic storm. To describe the asymmetric and symmetric disturbance fields
in mid-latitudes with a high time resolution of 1 min, longitudinally asymmetric (ASY) and symmetric
(SYM) disturbance indices were introduced and derived for both the H and D components. The SYM-H
index is approximately the same as the Dst index, while its time resolution is 1 min.
Derivation: The ASY/SYM indices are derived from six selected mid-latitude observatories (see Table 7)
in the following four steps: (1) subtraction of the geomagnetic main field and the Sq field to obtain the
disturbance field component, (2) coordinate transformation to a dipole coordinate system by using a
rotation angle that is an angle between the geomagnetic dipole pole position and local geomagnetic
direction, (3) calculation of the longitudinally symmetric indices, SYM-H and SYM-D, by taking averages
of disturbance fields of the six stations and (4) calculation of the asymmetric disturbance indices, ASY-H
and ASY-D, by computing the range between the maximum and the minimum asymmetric fields.
[26] [42]
References: Iyemori, et al. [1992] , Menvielle, et al. [2011] .
Table 7 — Six observatories contributing to the SYM/ASY indices
Observatory, country Code GLat (°N) GLon (°E) MLat (°) MLon (°E) Rotation angle (°)
Memambetsu, Japan MMB 43,9 144,2 34,6 210,2 −16,0
Honolulu, USA HON 21,3 202,0 21,5 268,6 −0,6
Tuscon, USA TUC 32,3 249,2 40,4 314,6 2,02
Fredericksburg, USA FRD 38,2 282,6 49,1 352,2 11,8
Hermanus, South Africa HER −34,4 19,2 −33,7 82,7 −12,7
Alma Ata AAA 43,3 76,9 34,5 153,0 11,0
5.8 AU, AL, AE and AO indices (auroral electrojet indices)
The auroral electrojet indices are measures of the intensity of the auroral electrojets and consist of
four indices, AU, AL, AE and AO. The AU and AL indices are intended to express the strongest current
intensity of the eastward and westward auroral electrojets, respectively. The AE index represents the
overall activity of the electrojets and the AO index provides a measure of the equivalent zonal current.
Derivation: The auroral electrojet indices are derived from geomagnetic variations in the H component
observed at 12 selected observatories along the auroral zone in the northern hemisphere (see Table 8).
The AU and AL indices are respectively defined by the largest and the smallest values thus selected. The
symbols, AU and AL, derive from the fact that these values form the upper and lower envelopes of the
superposed plots of all the data from these stations as functions of UT. The difference, AU minus AL,
defines the AE index and the mean value of the AU and AL, i.e. (AU+AL)/2, defines the AO index.
[42] [30]
References: Davis and Sugiura [1966] , Kamei and Maeda [1981] .
Table 8 — Twelve (and obsolete three) observatories contributing to the AE index
Observatory, country Code GLat (°N) GLon (°E) MLat (°) MLon (°E) Notes
Abisko, Sweden ABK 68,36 18,82 66,06 114,66
Dixon Island, Russia DIK 73,55 80,57 64,04 162,53
ISO 16698:2019(E)
Table 8 (continued)
Observatory, country Code GLat (°N) GLon (°E) MLat (°) MLon (°E) Notes
Cape Chelyuskin, Russia CCS 77,72 104,28 67,48 177,82
Tixie Bay, Russia TIK 71,58 129,00 61,76 193,71
Pebek, Russia PBK 70,09 170,93 63,82 223,31 Opened in 2001/04
Barrow, USA BRW 71,30 203,25 69,57 246,18
College, USA CMO 64,87 212,17 65,38 261,18
Yellowknife, Canada YKC 62,40 245,60 68,87 299,53
Fort Churchill, Canada FCC 58,80 265,90 67,98 328,36
Sanikiluaq, Canada SNK 56,5 280,8 66,6 349,7 Opened in 2007/12
Narssarssuaq, Denmark NAQ 61,20 314,16 69,96 37,95
Leirvogur, Iceland LRV 64,18 338,30 69,32 71,04
Cape Wellen, Russia CWE 66,17 190,17 62,88 241,36 Closed in 1996
Great Whale River, Russia GWR 55,27 282,22 65,45 351,77 Closed in 1984/07
Opened in 1984/09
Poste-de-la-Baleine, Canada PBQ 55,27 282,22 65,45 351,77
Closed in 2007/11
5.9 am index
The am index is designed to measure global geomagnetic activity using a large set of stations
representing all longitudes and possible hemispheric discrepancies. Time resolution of the am index
is 3 h (0 h to 3 h, 3 h to 6 h, ., 21 h to 24 h UT), giving eight values per UT day, same as the Kp index.
However, the index is given in the unit of nT.
Derivation: Stations to derive the am index are divided into groups according to their longitude
(Table 9), with five longitude sectors in the northern hemisphere and four in the southern hemisphere
(there were only three before 1979). In each longitude sector, the K values are averaged and the result
is converted into amplitude using mid-class amplitudes for L9 = 500 nT (L9 being the K=9 lower limit;
[37]
conversion table is given by Mayaud, P. N. [1980] ). The amplitude is multiplied by a weighting factor
to balance the different ranges in longitude of the different sectors and then averaged to give the
hemispheric indices an (North) and as (South). The planetary index am is equal to (an + as)/2.
[35], [37]
References: Mayaud [1968, 1980] .
Table 9 — Observatories that contributed to the am index
Longitudinal
Observatory, country Code Period GLat (°N) GLon (°E) MLat (°)
group
(G1) Magadan, Russia MGD 1967– 60,12 151,02 52,01
Petropavlovsk, Russia PET 1969– 53,10 158,63 45,95
Memambetsu, Japan MMB 1959– 43,91 144,19 35,35
(G2) Arti (Sverdlovsk), Russia ARS 1959– 56,43 58,57 49,13
Novosibirsk, Russia NVS 2002– 55,03 82,90 44,92
Podkammenaya T. Russia POD 1973–2001 61,40 90,00 51,54
Tomsk, Russia TMK 1959–1970 56,47 84,93 46,88
(G3) Hartland, UK HAD 1959– 51,00 355,52 53,9
Niemegk, Germany NGK 1959– 52,07 12,68 51,88
Chambon-la-Forêt, France CLF 1996– 48,03 2,26 49,84
Witteveen, Netherland WIT 1959–1988 52,81 6,67 53,66
(G4) Ottawa, Canada OTT 1975– 45,40 284,45 55,63
6 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Table 9 (continued)
Longitudinal
Observatory, country Code Period GLat (°N) GLon (°E) MLat (°)
group
Fredericksburg, USA FRD 1959– 38,20 282,63 48,4
(G5) Newport, USA NEW 1975– 48,27 242,88 54,85
Victoria, Canada VIC 1959– 48,52 236,58 54,14
Tucson, USA TUC 1959– 32,17 249,27 39,88
(G6) Canberra, Australia CNB 1986– −35,32 149,36 −42,71
Eyrewell, New Zealand EYR 1978– −43,41 172,35 −47,11
Amberley, New Zealand AML 1959–1977 −43,15 172,72 −46,80
Lauder, New Zealand LDR 1979–1985 −43,03 169,41 −49,18
(G7) Gnangara, Australia GNA 1959– −31,78 115,95 −41,93
Martin de Vivies France AMS 1986– −37,80 77,57 −46,39
Toolangi, Australia TOO 1959–1984 −37,53 145,47 −45,38
Canberra, Australia CNB 1979–1985 −35,32 149,36 −42,71
(G8) Kerguelen Is., France PAF 1959– −49,35 70,26 −56,94
Crozet Is., France CZT 1973– −46,43 51,86 −51,35
Hermanus, South Africa HER 1959– −34,43 19,23 −33,98
(G9) Argentine Is., Ukraine AIA 1959– −65,25 295,73 −55,06
Trelew, Argentina TRW 1973– −43,25 294,69 −33,05
South Georgia, UK SGG 1975–1982 −54,28 323,52 −45,57
5.10 PC index
The PC index intends to monitor the geomagnetic activity over the polar caps caused by changes in the
IMF and solar wind, driven by the geoeffective interplanetary electric field. A single station near the
northern or southern pole (Table 10) is used to derive the PCN (northern) or PCS (southern) index. The
index is given in the unit of nT with a time resolution of 1 min.
Derivation: The PC index is deduced from the deviations in the horizontal H and D magnetic field
components from the quiet level at two polar cap stations. More specific and detailed information may
be found in references.
[61], [62], [63]
References: Troshichev, et al. [1979, 1988, 2006] .
Table 10 — Observatories that contributed to the PC index
Observatory Code GLat (°N) GLon (°E) MLat (°)
Thule (Qaanaaq), Greenland THL 77,483 290,773 87,02
Vostok, Antarctica VOS −78,464 106,835 88,07
5.11 Time lag in the derivation and temporal resolution (sampling)
Some of the indices mentioned above have different classes (generations) for operational use. That is,
for quasi-real-time derivation, a different naming convention is used to distinguish from the original
definition with quality-controlled data. For example, in the case of the Dst index, there are Real-Time
(Quick-Look) Dst, Provisional Dst and Final Dst. There are also attempts to increase the temporal
[68]
resolution of the indices (e.g. Gannon and Love [2011] ). (See Annex A.)
ISO 16698:2019(E)
6 Classification of prediction
6.1 General
The accuracy and method of predicting geomagnetic indices depends on the time scale of prediction.
6.2 to 6.4 introduce some of the existing works which are based on a classification of three time-scale
categories: short-term (1 h to a few days), middle-term (a few weeks to a few months) and long-term
(half a year to one solar cycle). Some of them are actually used and the results made available online
(see Annex B).
6.2 Short-term prediction
Stimulated by the space weather programmes, there are many proposed methods and related
research papers for predicting geomagnetic indices in a time scale of 1 h to a few days. These fall
into four categories: (1) linear or non-linear prediction filter, (2) machine learning, (3) probabilistic
prediction with solar wind data and (4) physics-based model (MHD simulation etc). Most of the recent
techniques need real-time solar wind parameters and near-real-time geomagnetic observations as the
input. Predicting solar wind disturbance from solar surface observation may be a key to improving
geomagnetic index predictions.
Examples of prediction:
[40] [51]
Kp, ap and Ap indices: McPherron [1999] (Type 1), Solares, et al. [2016] (Type 1), Boberg, et al.
[14] [16] [59] [65]
[2000] (Type 2), Costello [1998] (Type 2), Thompson [1996] (Type 2), Wing, et al. [2005]
[21] [6] [7]
(Type 2), Detman and Joselyn [1999] (Type 2), Bala, et al. [2009] (Type 2), Bala and Reiff [2012]
[57] [66] [69]
(Type 2), Tan, et al. [2018] (Type 2), Wintoft, et al. [2017] (Type 2), McPherron, et al. [2004]
[50] [25]
(Type 3), Savani, et al. [2017] (Type 3), Haiducek, et al. [2017] (Type 4).
[9] [13]
Dst index: Balikhin, et al. [2001] (Type 1), Boaghe, et al. [2001] (Type 1), Iyemori and Maeda [1980]
[27] [18] [24] [33]
(Type 1), Chandorkar, et al. [2017] (Type 1), Gruet, et al. [2018] (Type 1), Lundstedt [1996]
[53] [49] [15]
(Type 2), Stepanova, et al. [2005] (Type 2), Revallo, et al. [2014] (Type 2), Burton, et al. [1975]
[45] [58]
(Type 3), O’Brien and McPherron [2000] (Type 3), Temerin and Li [2002] (Type 3), Podladchikova
[47] [60] [64]
and Petrukovich [2012] (Type 3), Tobiska, et al. [2013] (Type 3), Tsubouchi and Kubo [2010]
[23] [28]
(Type 3), Fok, et al. [2001] (Type 4), Jordanova, et al. [2010] (Type 4).
[27] [32] [34]
AE indices: Iyemori and Maeda [1980] (Type 1), Li, et al. [2007] (Type 1), Luo, et al. [2013]
[46] [56]
(Type 1), Pallocchia, et al. [2008] (Type 2), Takalo and Timonen [1999] (Type 2), Amariutei and
[5] [32] [31]
Ganushkina [2012] (Type 2), Li, et al. [2007] (Type 3), Kitamura, et al. [2008] (Type 4), Mays, et
[38]
al. [2009] (Type 4).
6.3 Middle-term prediction
There are only a few research papers that use recurrences of geomagnetic disturbances in a time scale
of a few weeks to a few months.
[67]
Example of prediction: Zhou and Wei [1998] (prediction of the Kp index).
6.4 Long-term prediction
There are very few proposed techniques and/or research papers on predicting geomagnetic indices in
a time scale of half a year to one solar cycle, as compared with those on solar activities such as sun spot
numbers or F10.7 flux. However, the sun spot number or F10.7 flux indicates quite different behaviour
from geomagnetic indices such as the aa index during some solar cycles. Therefore, the long-term
prediction method of geomagnetic indices is necessary.
[44] [20]
Examples of prediction: Niehuss, et al. [1996] (prediction of the Ap index), Cliver, et al. [1999]
(prediction of the aa index).
8 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Long-term prediction of solar activities (sun spot number and F10.7 flux) is presented by NOAA/Space
Weather Prediction Center (see Annex B). The possibility of combining the technique of solar activity
prediction with the solar-geomagnetic disturbance relationship has been examined in a number of
studies.
[19] [52]
Examples of solar-geomagnetic disturbance relationship: Clilverd, et al. [1998] , Stamper, et al. [1999] .
7 Methods of prediction
7.1 General
The prediction methods can be split into two broad categories: (1) those based on a statistical model
and (2) those based on a physical principle.
7.2 Prediction based on statistical models
7.2.1 Linear or non-linear prediction filter
This method of prediction uses data from a preceding interval of similar (or longer) length to that of the
period to be predicted. Precision of prediction generally depends on the temporal distance between the
most recent data and the period to be predicted. There are two types of prediction: one uses the index
[67]
of the preceding interval as the input data (see Zhou and Wei [1998] ) and the other uses the solar
[27] [41] [32]
wind parameters (see Iyemori and Maeda [1980] ; McPherron, et al. [1986] ; Li, et al. [2007] ;
[51] [18] [24] [34]
Solares, et al. [2016] ; Chandorkar, et al. [2017] ; Gruet, et al. [2018] ; Luo, et al. [2013] ).
7.2.2 Machine learning
There are several neural-network and deep learning models. This method is applicable for time scales
of several days to one sunspot cycle. It has been concluded that the interplanetary magnetic field and
[59]
solar wind plasma data are significant components for any of the models (see Thomson [1996] ;
[65] [57] [5] [6]
Wing, et al. [2005] ; Tan, et al. [2018] ; Amariutei and Ganushkina [2012] ; Bala, et al. [2009] ;
[7] [49] [66]
Bala and Reiff [2012] ; Revallo, et al. [2014] ; Wintoft, et al. [2017] ).
7.2.3 Probabilistic prediction
This method is based on the periodicity of geomagnetic disturbances such as the sun spot cycle, annual
[29] [64]
or semi-annual variation (see Joselyn [1995] ; Tsubouchi and Kubo [2010] ; Zang and Moldwin
[70]
[2015] ). Predictions made over long time scales (one to ten years) require the prediction of a sunspot
[71]
number (see Feynman and Gu [1986] ). Similar techniques used to predict the F10.7 flux and Ap index
[44] [60]
(e.g. Niehuss, et al. [1996] ; Tobiska, et al. [2013] ) are also available.
7.3 Prediction based on physical principle
This type of prediction is based on numerical MHD simulation of the magnetospheric process or energy
principle. These methods need the solar wind parameters as the input. See, for example, Burton, et al.
[15] [31] [25] [28]
[1975] , Kitamura, et al. [2008] , Haiducek, et al. [2017] , Jordanova, et al. [2010] , Mays, et al.
[38]
[2009] .
8 Evaluation of prediction efficiency
8.1 Definition of prediction error
For a simple time series, the most popular definition of prediction error is as the average of the square
of the differences between the predicted values and the observed values. This provides a reasonable
measure of prediction error.
ISO 16698:2019(E)
8.2 Methods of evaluation
It has been reported that the accuracy of prediction is different for the sunspot maximum and minimum
period. It has also been reported that the accuracy is different for different solar cycles (see Feynman
[71]
and Gu [1986] ). Accuracy is also different depending on the time scale of prediction. The prediction
efficiency shall therefore be given together with the conditions applied for its evaluation.
A prediction can be evaluated using a skill score. In the case of a dichotomous forecast, the true skill
statistics, the Gilbert skill score, the Heidke skill score and others can be used (see Detman and Joselyn
[21]
[1999] ). If predicting continuous-variables, the mean square skill score can be used (see Murphy
[43]
[1988] ). These skill scores are detailed in Annex C.
[48]
Rastätter, et al. [2013] evaluated the performance of various prediction models against the Dst
index, using skill scores.
9 Compliance criteria
9.1 Rationale
The prediction principle and scheme shall be described concisely and clearly. They shall be published as
scientific articles in refereed/peer-review international journals and their references shall be available
to the public. Otherwise, journal-style documents suitable for publication in international journals shall
be accessible to the public.
9.2 Reporting
Prediction results of geomagnetic indices shall be made public for evaluation and application by third
parties (e.g. individuals or institutes who are interested in the prediction results). As a minimum,
digital values of the prediction results shall be given in the same data format as the corresponding
geomagnetic indices, such as the World Data Center exchange format.
9.3 Documenting
The following information relating to prediction shall be clearly documented or displayed.
a) Input:
1) types of data;
2) source of data;
3) time resolution of data;
4) number of data points;
5) time of data acquisition.
b) Output:
1) types of predicting data;
2) time of predicting data;
3) time at which prediction was performed.
c) Miscellaneous:
1) type of prediction method (choose from the four types listed in Clause 4, otherwise describe
briefly);
10 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
2) point of contact.
9.4 Publishing
When the geomagnetic index becomes available, comparison shall be made with the prediction results.
Comparison includes calculating the prediction error, skill score, correlation coefficients and so on, as
listed in Clause 8.
9.5 Archiving
The results of prediction shall be archived and available to the public for evaluation.
10 Useful Informative Documents
Many useful academic documents related with this document's fields have been published. Those are
listed in Annex D.
ISO 16698:2019(E)
Annex A
(informative)
Websites where geomagnetic indices are available
(1) GFZ-Potsdam
http:// www -app3 .gfz -potsdam .de/ kp _index/ (Kp)
(2) Service International des Indices Géomagnetiques (ISGI)
http:// isgi .unistra .fr/ about _indices .php (aa, am, Kp, AE, Dst, PC)
(3) WDC for Geomagnetism, Kyoto
http:// wdc .kugi .kyoto -u .ac .jp/ wdc/ Sec3 .html (AE, Dst, ASY/SYM, RT-AE, RT-Dst)
(4) Arctic and Antarctic Research Institute
http:// pcindex .org/ (PCS)
(5) WDC for Geomagnetism, Copenhagen
ftp:// ftp .space .dtu .dk/ WDC/ indices/ pcn/ (PCN)
(6) US Geological Survey
http:// geomag .usgs .gov/ dst/ (RT-USGS-Dst)
12 © ISO 2019 – All rights reserved
ISO 16698:2019(E)
Annex B
(informative)
Websites where the space weather predictions and/or "now
...
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