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Indices of ionospheric response to solar-cycle epoch
Mv. Space Res. Vol. 13, No.3, pp. (3)25—(3)2*, 1993 Printed in Great Britain. MI rights reserved.
0273—1177193 $15.00 Copyright © 1992 COSPAR
INDICES OF IONOSPHERIC RESPONSE TO SOLAR-CYCLE EPOCH P. A. Bradley Rurhe,fordAppleton Laboratoiy, Chilton, Didcot, Oxon OX1J OQX, U.K.
Indices provide a convenient way of labelling phenomena and of identifying different occasions when these are likely to be similar. Limitations arise when there is poor correlation between the phenomena and the indices, when the dependence is non—linear and when the same index is used simultaneously for different phenomena. Index predictability is also important in some applications. lonisation varies throughout a solar cycle in response to changing photoionisation processes and interaction effects of the solar wind with the Earth’s environment such that indices may be formulated to model the median values of the different ionospheric characteristics. A number of indices have been considered and are in use. Firstly there are solar indices based on solar radiation and representative of position within the solar cycle. These include R1,, and 4’,.,, respectively the 12—month running mean values of ‘the montlify mean of the daily sunspot numbers and the22lO c~t w~velength solar flux values expressed in units of 10 Wm Hz . Then there are ionospheric indices determined from the mean trends in ionospheric characteristics values at a selection of key sounding stations throughout the world. Index 1F2 /1/ applies for foF2 and is derived from noon values at 13 stations. Related index T /2/ is similar, but uses measured data for 30 stations and is based on the mean of the monthly median values of foF2 at each hour. A third family of indices, mapping indices, are evaluated from the fit of key station measurements with figures given by interpolation/extrapolation among specific once—and—for—all maps of values for reference epochs. For example, the index IG /3/ applies for the current CCIR global maps of foF2 /4/. Defi~tive past and predicted future values of these various indices are available from World Data Centres and those of R , 4’ and IG are also published by the International Te1ecomi~nici~ion Uni~ /5-7/. The longest sequence relates to R12 which has been determined almost continuously since 1612. Whatever index is adopted long—term predictions suppose that for the same index value in different solar cycles, or on the rising and falling parts of a given cycle, there will be the same ionisation present. Reference characteristics maps are generated from past measurements and assigned a particular index value, and a law of interpolation/extrapolation is established among these. The goodness of a given index approach is then determined by: (1) the ability to predict the index, (ii) (3)25
(3)26
P. A. Bradley
repeatability of ionospheric response for past and future solar cycles, (iii) the spread of ionospheric characteristics values over the rising and falling parts of a cycle, (iv) the form of variation between the reference map values and (v) the nature of the saturation at high index values. This makes the choice of figure-of—merit for ranking different indices a subjective feature depending on the relative itnportances that are ascribed to these separate factors. The optimum index must always be a compromise with emphasis on adequacy. The ‘best’ index may well differ for the various ionospheric characteristics. For example, according to Muggleton /8/ foE is better correlated with than R This is consistent with E-region lonisation being ~ainly co~crolledby photoionisation. On the other hand foF2 shows a slightly better correlation with sunspot number, which is more closely related to combined photoionisation and magnetic effects. Hitherto and understandably most attention has been paid to the solar-cycle variations of foF2 and changes in M(3000)F2 have received relatively little attention. It has rather been assumed that what is best for foF2 will also be best for the other characteristics. The advantages of ionospheric indices have been extolled by Minnis and Bazzard /9/. There is an added complication with mapping indices. It is not evident to the present author that if a full system of mapping indices were adopted each characteristic could be determined at a given epoch using the same index value. .
The CCIR provides a Recommendation on the choice of indices for long-term predictions /7/. It recommends the use of: (i) R for all predictions more than 12-months ahead of the date of tA~ last observed value, (ii) R or IG or ~ 2 for predicting 4~2 and I12~3000)F~up to six and monthly median values of fc perhaps up to 12 months ahead of the date of the last observed value with substantially equivalent results from any of these indices and (iii) • 2 for predicting monthly median foE and foFl up to six and perha~ps up to 12 months ahead of the date of the last observed values. Reference maps of monthly median foF2, M(3000)F2 and certain other ionospheric characteristics are provided by the CCIR for R = 0 and 100, taken as representative of low and high solar e~5gchs. A linear variation with R, 2 is assumed consistent with these values, except that only ut the case of foF2 there is taken to be complete saturation for R1.,=150 at all locations and times. Empirical formulae for foE aft~ foFl are likewise based on a linear variation with ~ 2 and R respectively, with no saturation for high solar Jpochs. ~t is natural to give prominence to indices that can be used with a linear law of variation, though a better fit to past data sets is clearly achieved with a quadratic or parabolic form. A mapping available only for monthly median foF2 which involves a parabolic solar—cycle dependence on R,~ has been produced by Jones and Obitts /10/. This shows a gi~’dual saturation for the higher R12 which becomes effective differently with geographical position, season and time—of—day. However, there is understandable reluctance to use these maps in conjunction with M(3000)F2 values given from maps for a linear index in applications of ionospheric modelling or when deriving composite propagation parameters such as basic maximum usable frequency /11/.
Ionospheric Response to Solar-Cycle Epoch
(3)27
Despite a scientific preference for the application of physical considerations, in practise most indices are predicted by an adaptation of the McNish-Lincoln procedure /12/. This involves a form of extrapolation to the future on the basis of past trends, with greater uncertainty the longer the lead time. Lengthy past data sets are required to be available but there is no established evidence that some indices can be predicted systematically more accurately than others, or with different lead times, which is in conflict with the CCIR Recommendation /7/. This means that on the basis of predictability there is no fundamental reason for favouring one particular index. Ionospheric indices have the disadvantage of needing the continued operation of certain key ionosonde stations with rapid data dissemination and give rise to some re—calibration complications when stations are closed and others substituted. On the other hand, solar indices are potentially more vulnerable to the possible closure of observing stations. Mapping indices must be completely re—evaluated every time the maps are changed. Where there is a requirement for the simultaneous prediction of several ionospheric characteristics as in modelling or radio—wave propagation assessment the question arises whether each characteristic should be determined by means of its ‘best’ index, or one index used throughout together with mean relationships for other indices on which the different maps are based. Mean expressions relating ~l2 and R,., exist /13, 14/ as also do those between 1G1 and R1 /3/, b~fweenT and R /2/ 2érent and between and R~o2r,A.3, ~L6/. In falling some cases formulae are1F2 quoted the 15, rising and halfdif~f cycles. Despite these differences there is good general support for use of only a single index in long-term predictions, recognising that a short-term forecast might additionally involve a separate perturbation or disturbance index. The IRI is critically dependent upon the adopted values of foF2 and M(3000)F2 and there is evidence that efforts at generating more refined models are being hampered by limitations in the accuracy of the maps of these key characteristics. So there is current international emphasis on the production of improved global and regional maps. But the questions of choice of long—term index, the reference epochs to map and the law of solar-cycle variation to apply (note that a parabolic law effectively involves three sets of reference maps) are extremely important to that process. With a wrong index future mapping efforts will be only partially successful. There is current feeling that R,., is best, but more studies are needed, particularly on ~I~esaturation question. ACKNOWLEDGEMENTS Acknowledgement is made to a number of colleagues for helpful comments on an early draft of this note, particularly L W Barclay, T Gulyaeva, W R Piggott and P Wilkinson. REFERENCES 1.
C.M. Minnis, Ionospheric indices, Advances in Radio Research, Ed J.A. Saxton. Academic Press, London and New York (1964). 13:3-C
(3)28
P. A. Bradley
2.
IPSD, The development of the ionospheric index T, Report IPS—Ril, Ionospheric Prediction Service, Sydney, Australia(1968).
3.
R.Y. Liu, P.A. Smith and J.W. King, A new solar index which leads to improved foF2 predictions using the CCIR Atlas, Telecomm J, .~.Q, 408—414(1983).
4.
CCIR Atlas of ionospheric characteristics, CCIR Report 340, ITU, Geneva (1991).
5.
Telecommunication Journal (published monthly up to December 1991); Telecommunication Magazine (thereafter) ITU, Geneva.
6.
CCIR Monthly Circular of Ionospheric Propagation Indices, ITU, Geneva.
7.
CCIR, Choice of indices for long—term ionospheric predictions, CCIR Recommendation 371, ITU, Geneva(1990).
8.
L.M. Nuggleton, A method of predicting foE at any time and place, Teleconmi J, j~., 413—418(1975).
9.
C M Minnis and G H Bazzard, Some indices of solar activity based on ionospheric and radio noise measurements, ~ Atmos~hTerr Phys, ~j, 213-228(1959).
10.
W.B. Jones and D.L. Obitts, Global representation of annual and solar cycle variation of foF2 monthly median 1954-1958, Telecommunications Research Report OT/ITS/RR3, US Govt Printing Office, Washington(1970).
11.
CCIR, Definitions of maximum and minimum transmission frequencies, CCIR Recommendation 373, ITU, Geneva(l990).
12.
F.G. Stewart and S.M. Ostrow, Improved version of the McNish-Lincoln method for prediction of solar activity, Telecomm J, 228—232(1970). ~,
13.
M. Joachim, Study of correlation of the three basic indices of ionospheric propagation: R12, 1F2 and Nature ~]Q, 289—290(1966) ~,
14.
F.G. Stewart and N. Leftin, Relationship between Ottawa 10.7 cm solar noise flux and Zurich sunspot number, Telecomm J, 159—169(1972). ~,
15.
L.W. Barclay, Variations in the relation between sunspot number and 1F2, J Atmosph Terr Phys, ~j, 547-549(1962).
16.
L.M. Muggleton and S.S. Kouris, Relation between sunspot number and the ionospheric index 1F2, Radio Sci, 1109—1110(1968). ~.,
0273—1177193 $15.00 Copyright © 1992 COSPAR
INDICES OF IONOSPHERIC RESPONSE TO SOLAR-CYCLE EPOCH P. A. Bradley Rurhe,fordAppleton Laboratoiy, Chilton, Didcot, Oxon OX1J OQX, U.K.
Indices provide a convenient way of labelling phenomena and of identifying different occasions when these are likely to be similar. Limitations arise when there is poor correlation between the phenomena and the indices, when the dependence is non—linear and when the same index is used simultaneously for different phenomena. Index predictability is also important in some applications. lonisation varies throughout a solar cycle in response to changing photoionisation processes and interaction effects of the solar wind with the Earth’s environment such that indices may be formulated to model the median values of the different ionospheric characteristics. A number of indices have been considered and are in use. Firstly there are solar indices based on solar radiation and representative of position within the solar cycle. These include R1,, and 4’,.,, respectively the 12—month running mean values of ‘the montlify mean of the daily sunspot numbers and the22lO c~t w~velength solar flux values expressed in units of 10 Wm Hz . Then there are ionospheric indices determined from the mean trends in ionospheric characteristics values at a selection of key sounding stations throughout the world. Index 1F2 /1/ applies for foF2 and is derived from noon values at 13 stations. Related index T /2/ is similar, but uses measured data for 30 stations and is based on the mean of the monthly median values of foF2 at each hour. A third family of indices, mapping indices, are evaluated from the fit of key station measurements with figures given by interpolation/extrapolation among specific once—and—for—all maps of values for reference epochs. For example, the index IG /3/ applies for the current CCIR global maps of foF2 /4/. Defi~tive past and predicted future values of these various indices are available from World Data Centres and those of R , 4’ and IG are also published by the International Te1ecomi~nici~ion Uni~ /5-7/. The longest sequence relates to R12 which has been determined almost continuously since 1612. Whatever index is adopted long—term predictions suppose that for the same index value in different solar cycles, or on the rising and falling parts of a given cycle, there will be the same ionisation present. Reference characteristics maps are generated from past measurements and assigned a particular index value, and a law of interpolation/extrapolation is established among these. The goodness of a given index approach is then determined by: (1) the ability to predict the index, (ii) (3)25
(3)26
P. A. Bradley
repeatability of ionospheric response for past and future solar cycles, (iii) the spread of ionospheric characteristics values over the rising and falling parts of a cycle, (iv) the form of variation between the reference map values and (v) the nature of the saturation at high index values. This makes the choice of figure-of—merit for ranking different indices a subjective feature depending on the relative itnportances that are ascribed to these separate factors. The optimum index must always be a compromise with emphasis on adequacy. The ‘best’ index may well differ for the various ionospheric characteristics. For example, according to Muggleton /8/ foE is better correlated with than R This is consistent with E-region lonisation being ~ainly co~crolledby photoionisation. On the other hand foF2 shows a slightly better correlation with sunspot number, which is more closely related to combined photoionisation and magnetic effects. Hitherto and understandably most attention has been paid to the solar-cycle variations of foF2 and changes in M(3000)F2 have received relatively little attention. It has rather been assumed that what is best for foF2 will also be best for the other characteristics. The advantages of ionospheric indices have been extolled by Minnis and Bazzard /9/. There is an added complication with mapping indices. It is not evident to the present author that if a full system of mapping indices were adopted each characteristic could be determined at a given epoch using the same index value. .
The CCIR provides a Recommendation on the choice of indices for long-term predictions /7/. It recommends the use of: (i) R for all predictions more than 12-months ahead of the date of tA~ last observed value, (ii) R or IG or ~ 2 for predicting 4~2 and I12~3000)F~up to six and monthly median values of fc perhaps up to 12 months ahead of the date of the last observed value with substantially equivalent results from any of these indices and (iii) • 2 for predicting monthly median foE and foFl up to six and perha~ps up to 12 months ahead of the date of the last observed values. Reference maps of monthly median foF2, M(3000)F2 and certain other ionospheric characteristics are provided by the CCIR for R = 0 and 100, taken as representative of low and high solar e~5gchs. A linear variation with R, 2 is assumed consistent with these values, except that only ut the case of foF2 there is taken to be complete saturation for R1.,=150 at all locations and times. Empirical formulae for foE aft~ foFl are likewise based on a linear variation with ~ 2 and R respectively, with no saturation for high solar Jpochs. ~t is natural to give prominence to indices that can be used with a linear law of variation, though a better fit to past data sets is clearly achieved with a quadratic or parabolic form. A mapping available only for monthly median foF2 which involves a parabolic solar—cycle dependence on R,~ has been produced by Jones and Obitts /10/. This shows a gi~’dual saturation for the higher R12 which becomes effective differently with geographical position, season and time—of—day. However, there is understandable reluctance to use these maps in conjunction with M(3000)F2 values given from maps for a linear index in applications of ionospheric modelling or when deriving composite propagation parameters such as basic maximum usable frequency /11/.
Ionospheric Response to Solar-Cycle Epoch
(3)27
Despite a scientific preference for the application of physical considerations, in practise most indices are predicted by an adaptation of the McNish-Lincoln procedure /12/. This involves a form of extrapolation to the future on the basis of past trends, with greater uncertainty the longer the lead time. Lengthy past data sets are required to be available but there is no established evidence that some indices can be predicted systematically more accurately than others, or with different lead times, which is in conflict with the CCIR Recommendation /7/. This means that on the basis of predictability there is no fundamental reason for favouring one particular index. Ionospheric indices have the disadvantage of needing the continued operation of certain key ionosonde stations with rapid data dissemination and give rise to some re—calibration complications when stations are closed and others substituted. On the other hand, solar indices are potentially more vulnerable to the possible closure of observing stations. Mapping indices must be completely re—evaluated every time the maps are changed. Where there is a requirement for the simultaneous prediction of several ionospheric characteristics as in modelling or radio—wave propagation assessment the question arises whether each characteristic should be determined by means of its ‘best’ index, or one index used throughout together with mean relationships for other indices on which the different maps are based. Mean expressions relating ~l2 and R,., exist /13, 14/ as also do those between 1G1 and R1 /3/, b~fweenT and R /2/ 2érent and between and R~o2r,A.3, ~L6/. In falling some cases formulae are1F2 quoted the 15, rising and halfdif~f cycles. Despite these differences there is good general support for use of only a single index in long-term predictions, recognising that a short-term forecast might additionally involve a separate perturbation or disturbance index. The IRI is critically dependent upon the adopted values of foF2 and M(3000)F2 and there is evidence that efforts at generating more refined models are being hampered by limitations in the accuracy of the maps of these key characteristics. So there is current international emphasis on the production of improved global and regional maps. But the questions of choice of long—term index, the reference epochs to map and the law of solar-cycle variation to apply (note that a parabolic law effectively involves three sets of reference maps) are extremely important to that process. With a wrong index future mapping efforts will be only partially successful. There is current feeling that R,., is best, but more studies are needed, particularly on ~I~esaturation question. ACKNOWLEDGEMENTS Acknowledgement is made to a number of colleagues for helpful comments on an early draft of this note, particularly L W Barclay, T Gulyaeva, W R Piggott and P Wilkinson. REFERENCES 1.
C.M. Minnis, Ionospheric indices, Advances in Radio Research, Ed J.A. Saxton. Academic Press, London and New York (1964). 13:3-C
(3)28
P. A. Bradley
2.
IPSD, The development of the ionospheric index T, Report IPS—Ril, Ionospheric Prediction Service, Sydney, Australia(1968).
3.
R.Y. Liu, P.A. Smith and J.W. King, A new solar index which leads to improved foF2 predictions using the CCIR Atlas, Telecomm J, .~.Q, 408—414(1983).
4.
CCIR Atlas of ionospheric characteristics, CCIR Report 340, ITU, Geneva (1991).
5.
Telecommunication Journal (published monthly up to December 1991); Telecommunication Magazine (thereafter) ITU, Geneva.
6.
CCIR Monthly Circular of Ionospheric Propagation Indices, ITU, Geneva.
7.
CCIR, Choice of indices for long—term ionospheric predictions, CCIR Recommendation 371, ITU, Geneva(1990).
8.
L.M. Nuggleton, A method of predicting foE at any time and place, Teleconmi J, j~., 413—418(1975).
9.
C M Minnis and G H Bazzard, Some indices of solar activity based on ionospheric and radio noise measurements, ~ Atmos~hTerr Phys, ~j, 213-228(1959).
10.
W.B. Jones and D.L. Obitts, Global representation of annual and solar cycle variation of foF2 monthly median 1954-1958, Telecommunications Research Report OT/ITS/RR3, US Govt Printing Office, Washington(1970).
11.
CCIR, Definitions of maximum and minimum transmission frequencies, CCIR Recommendation 373, ITU, Geneva(l990).
12.
F.G. Stewart and S.M. Ostrow, Improved version of the McNish-Lincoln method for prediction of solar activity, Telecomm J, 228—232(1970). ~,
13.
M. Joachim, Study of correlation of the three basic indices of ionospheric propagation: R12, 1F2 and Nature ~]Q, 289—290(1966) ~,
14.
F.G. Stewart and N. Leftin, Relationship between Ottawa 10.7 cm solar noise flux and Zurich sunspot number, Telecomm J, 159—169(1972). ~,
15.
L.W. Barclay, Variations in the relation between sunspot number and 1F2, J Atmosph Terr Phys, ~j, 547-549(1962).
16.
L.M. Muggleton and S.S. Kouris, Relation between sunspot number and the ionospheric index 1F2, Radio Sci, 1109—1110(1968). ~.,