230 IEEE TRANSACTIONS ON BROADCASTING, VOL. 34, NO. 2, JUNE 1988

SHORTWAVE PROPAGATION PREDICTION METHODOLOGIES

John M. Goodman Michael H. Reilly

Ionospheric Effects Branch Space Science Division

Naval Research Laboratory Washington, DC 20375-5000

ABS TRACT

The status of ionospheric propagation prediction models is examined, with particular emphasis on the use of these models by the short wave broadcast community . Their stand-alone capability for forecasts is found to be limited by the use of monthly-median, statistical averages of archived ionospheric data, as well as by the use of imprecise control parameter inputs, such as the sunspot number. A variety of developing technologies are discussed for improvement of prediction models. Improvement may result from observations of coronal holes and other relevant solar features for long- and short- term ionospheric predictions. Also discussed are a variety of other ionospheric measurement schemes for short-term ionospheric predictions, such as the use of vertical-incidence, oblique-incidence, and backscatter sounders, and the use of remote ionospheric sensing from space. The application of this class of measurements for adaptive HF broadcasting systems is discussed. Incorporation of ray-tracing into propagation calculations in the prediction model is also considered.

INTRODUCTION

It is generally recognized that HF is the most precarious radiofrequency regime in terms of skywave propagation effects, and this personality may result in either positive or negative features in connection with broadcasting. The successful transmission of programs using the shortwave band must account for a number of parameters, including: location of source transmitter, time and duration of program, and the specified target area for the program. In addition, major attention should be paid to phenomenological parameters of the propagation medium, such as the ionospheric heights and critical frequencies, which ultimately determine the broadcast coverage for a specified frequency. Broadcast coverage prediction will depend upon an ability to predict the

ionospheric conditions. These predictions typically involve the exploitation of models of ionospheric structure which are coupled to some appropriate radiowave propagation algorithm. The ionosphere is typically modelled by spatial and temporal functions and some external parameters reflecting solar and magnetic activity control. Usually, the geography for the prediction problem is known, and the ionospheric conditions are prescribed by the model, after one or more input control parameters have been specified. This places too much burden on a single parameter like the sunspot number, and the result is often unsatisfactory.

This paper reviews existing HF performance prediction models from the standpoint of the errors which arise in both the ionospheric models which are exploited and the propagation methods which are used. A central theme is the recognition that HF system performance predictions agree best with reality when prediction models are updated with measured data. This is not surprising, since ionospheric variability

is substantial, and typically only median representations of ionospherically-dependent parameters admit to the modelling process. A number of approaches by which variability may be accounted for or "tracked" are no doubt possible, but this suggests that the spectrum "planning" process be made m n r e flexible.

There are a number of methods by which the process of spectrum planning is accomplished. The ITU has long recognized that the HF skywave channel is a valuable resource, and its technical arm, the CCIR, has developed a series of methodologies which are to be applied by the various administrations for optimization of communication and broadcast performance, while limiting the potential for interference with other users. These methods represent, in some sense, the very best the community can do in the long-term prediction of ionospheric behavior, which determines the behavior of the channel itself. The various recipes which are descriptive of the processes by which radiowaves interact with the ionosphere, while diverse, are probably not as critical in the prediction process. Consequently, ionospheric predictions will be emphasized in the first part of this paper.

It is worth recognizing that the term prediction has a rather elusive meaning, depending upon the nature of the requirement for knowledge about the future. In the case of the ionosphere. the distinction is made between long-term predictions and short-term predictions. Long-term predictions of ionospheric behavior may typically be based upon climatological models developed from historical records for specified solar and/or magnetic activity levels, season, time of day, geographical area involved, and so on. Very often, the ionospheric prediction is itself based upon a prediction of the solar activity level. In short, the long-term prediction process relies upon the recognition of loosely established tendencies as they relate to relatively simple (and extraterrestrial) driving parameters, and the result is usually an estimate of median behavior. Two sources of error are evidenced in long-term predictions: one owing to an imprecise estimate of the driving parameter, such as sunspot number, and the second arising from ionospheric variability not properly accounted for in the model. Given these difficulties, it may appear surprising that the process can possibly yield useful results, and yet it often does. Long-term predictions are necessary in HF broadcast planning and in other spectrum management activities where significant lead times are involved. Short-term predictions involve time scales from minutes to days. The term forecast is sometimes used to describe those prediction schemes which are based upon established cause-and- effect relationships, rather than simple tendencies based upon crude indices. In the limit, a short-term forecast becomes a real-time ionospheric assessment or a nowcast. In the context of HF communications, real-time-channel-evaluation (or RTCE) systems, such as oblique sounders, may be exercised to provide a nowcast. Such procedures are of use in adaptive HF

0018-9316/88/0600-0230$01.00 0 1988 IEEE

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compunication systems. The term hindcast is sometimes used to describe an a posteriori analysis of ionospherically-dependent system disturbances. Solar control data are usually available for this purpose, possibly also ionospheric observation data.

The error associated with any prediction method is critically dependent upon the parameter being assessed, the lead-time for the prediction, and other factors. One of the most important parameters in the prediction of the propagation component of HF communication performance is the maximum electron density of the ionosphere, since this determines the communication coverage at a specified broadcast (or transmission) frequency. It is well known that the ordinary ray critical frequency, given by the term foF2, may be simply related to maximum F2 layer electron density. and foF2, together with the effective ray launch angle, will determine the so- called Maximum Usable Frequency (or MUF) for a specified transmission distance. Thus, the capability to predict foF2 or the maximum electron density of the ionosphere by a specified method is a necessary step in the performance prediction of HF systems which depend upon skywave propagation.

The next section discusses the use of ionospheric models in the present-day prediction process. This is followed by a discussion of robust and adaptive HF schemes. Then two sections follow which consider present schemes and future improvements for long-term and short-term predictions. The final section presents conclusions.

ON THE USE OF IONOSPHERIC PREDICTION MODELS

The nature of ionospheric variability is quite complex, since it results from temporal and geographical variabilities in upper atmospheric chemistry, ionization production and loss mechanisms, particle diffusion and electrodynamical phenomena. As indicated earlier, general tendencies are fairly well modelled, and a large component of the variability is understood from a physical point of view. But, alas, understanding of cause-and-effect does not always translate into a prediction capability. This is because the sources of disturbance are not adequately monitored as they occur and propagate, or the science which leads from sources to prediction of effects is incomplete.

There are a number of simplified models which have been developed for the purpose of making ionospheric or propagation predictions, or for use in theoretical studies. A survey of ionospheric models has been provided by Goodman [l], following a review by Kohnlein [ 2 ] , 'and a mini-review of models has recently been published by Rush [ 3 ] . It serves no purpose to review the full history of ionospheric model development in this paper, although it is quite interesting to follow the evolution from the earliest simple profile models to the relatively complex global models presently available. Some of the models which have been used for purposes of prediction in recent years include those due to Bent et a1 [4], the International Reference Ionosphere (IRI) [5,6], and the Ching-Chiu model [7,8]. Of more interest to the HF community are models which are specific to those bottomside properties of the ionosphere which impact the skywave propagation most directly. Those models which are largely based upon the very substantial data base derived from vertical- incidence sounders appear to be the ones of choice. For a number of years a considerable amount of effort has been directed toward the analysis of this data base and in the development of suitable mapping techniques and numerical methods for predicting ionospheric properties. Global maps of ionospheric

properties have been published, and these data form the basis for a significant number of semi-empirical and climatological (statistical) models of the ionosphere [9]. Some of these include ITS-78 [lo], HFMUFES [ll], IONCAP[ 121, and RADARC [13,14,15]. The CCIR has also developed methods for estimating field strength and transmission loss based upon empirical data of this type, and a computer method for propagation prediction was developed for the WARC-HFBC under the aegis of the International Frequency Regulation Board, an organ of the ITU. The reader is referred to CCIR Reports 2 5 2 , 252-2, and 894-1, as well as CCIR recommendation 621 contained in the 1986 "Green Book" [16] for more information on WARC-HFBC-84 computer method.

The internationally sanctioned method for HF propagation prediction, emphasizing requirements of the broadcast service, is embodied in HFBC-84. a derivative of the method described in CCIR Report 252. It is basically a climatological model subject to all of the variabilities one would expect from median models. Another generally-accepted model is IONCAP, which is a level above HFBC-84 in complexity and includes more options, but it is decidedly directed toward the analysis of point-to-point services, rather than HF broadcast. RADARC is the OTH radar equivalent of IONCAP, although the former has an area coverage capability. Steps are now being taken at NRL to incorporate an area coverage format within the options available in IONCAP, making IONCAP more useful for HF broadcast coverage and performance analysis. Both IONCAP and early versions of RADARC allow for the specification of up to four ionospheric profiles along the ray trajectory. A more complex model developed by SRI International, called AMBCOM [17], admits up to forty one independent ionospheric profiles along the raypath for use in two-dimensional ray tracing. This feature may allow more flexibility for those instances in which the spatial resolution in the ionospheric specification (provided by specified sensors) is refined.

The U.S. Air Force has developed a class of ionospheric models which are designed to accommodate the insertion of "live" ionospheric data from satellites, terrestrial sensors, and solar observables. The first such model was the so-called Air Force 4-D model [18]. The most recent one is the ICED model [19], which inputs an effective sunspot number, as determined to fit foF2 data from a global network of vertical ionosonde stations, and a geomagnetic Q-index, associated with in-situ satellite data on auroral characteristics. Exploitation of this data allows, to some degree, for incorporation of dynamical ionospheric behavior. The model should therefore be applicable to HF broadcasting predictions, and should be particularly appropriate for the modelling of high latitude effects. It also appears that the topside profile is relatively accurately modelled in ICED, although this is more relevant to considerations of transionospheric propagation.

Recent work [20] has been directed toward the calculation of ionospheric profiles on a global scale in response to physical driving parameters, such as the underlying neutral composition, temperature, and wind; the magnetospheric and equatorial electric field distributions; the auroral precipitation pattern; and the solar E W spectrum. A subset of these parameters has been used similarly in profile calculations for the development of a semi-empirical, low-latitude ionospheric model (SLIM) [21]. This kind of approach is computationally very intensive, but the use of coefficient maps from these calculations, which depend on the appropriate parameters values, appears feasible. The development

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of programs of this type is required in order to eliminate the use of oversimplified driving parameters in prediction models and to describe completely the chain of events which are involved in the solar wind-magnetosphere-ionosphere-atmosphere sys tem.

A number of transportable models have been developed to make use of the growing availability of micro- and mini-computers [22]. The use of electronic mail connection to solar and ionospheric assessment services, such as those provided by NOAA, is placing capability for prediction service in the field where it may be needed, rather than at central establishments with large main frame computers. One of the first micro-computer models to be developed for general use by the public was MINIMUF [23], which is part of the PROPHET family of programs [24]. Other models have followed including MICROMUF [25,26,], MICROPREDIC [27], MiniFTZ2, as described by Gerdes [28], and a microcomputer version of the WARC- HFBC procedure [29].

Although there is some concern that accuracy may be sacrificed in the development of the microcomputer models, this concern is tempered by the following considerations. First, there have been no in-depth studies as yet which show that the large main frame prediction models significantly outperform their smaller cousins, at least in the prediction of a simple parameter such as the MUF where there is a common basis for comparison. Secondly, in the world of RTCE and ionospheric assessment technology, which may be used for frequent updating of the model input conditions, small microcomputer models may perform quite adequately. This is because temporal updating procedures typically involve the application of scale factors which effectively suppress the physics which may be contained within the more elegant mainframe model. Thus, more rapid temporal updating leads to a convergence in the performance metric of competing models. The same may also be said of spatial extrapolation using models, although in this case an "update" involves the number and location of ionospheric control points used in the extrapolation process. Naturally, one would prefer the flexibility of the larger, more elegant model if the capability to update in either space or time is limited. It should be noted that a number of government agencies and firms are translating the large main frame programs such as IONCAP to run on personal computers, thus making the relative accuracy question mute. A microcomputer implementation of IONCAP, termed IONCAST, has been developed at NRL in connection with its high latitude HF propagation program [30]. A separate implementation of IONCAP has been developed by ITS and is available through NTIS [31].

ROBUST AND ADAPTIVE HF SCHEMES

Military interest in the HF band has been rekindled recently, owing to the development of new techniques which offer the promise of improved performance. In the military arena, there is increasing emphasis on digital data transmission and the development of a viable and secure digital voice capability. Some of the other new techniques may also have application for the non-military broadcast services. Generically, these schemes fall into two broad categories: adaptive HF and robust HF. Adaptive HF techniques are many, but the general purpose is that of following the changes in the environment and matching the system parameters to optimize communication performance. Robust HF schemes include those which provide sufficient margin to overcome the anticipated propagation perturbations, without adapting to them. Although there are variations to the themes, we find generally that adaptive techniques are "MOF-seeking" in nature,

while robust schemes may be optimal under multipath or multimedia conditions. Robust architectures are motivated by the need to communicate relatively low data rate, high priority messages through severely disturbed environments in a timely manner and without error. To do this, heroic measures are usually involved. To communicate in the tactical world, involving an environment which is more predictable and usually less pathological, higher data rates are possible. But measures are still needed to communicate with a high degree of reliability in the " tot a 1 " environment , including other - u s e r interference, deliberate jamming, ambient noise, ionospheric effects, and lack of operator training. Modern adaptive HF developments have provided a suite of countermeasures to these problems. Some, but not all of these techniques, may be applicable to the area of broadcast. This fact is not obvious, since one typically must develop broadcast schedules well in advance of operation, and the total system is not centrally controlled. In short, there is little flexibility of the disadvantaged receiver of the broadcast to adapt effectively. Nevertheless, the most obvious robust measures are normally applied at the transmitter (such as increased power and simulcast operation), while hoping that the receiver can find the best channel (i.e., adapt).

The application of adaptive schemes to the broadcast environment depends upon whether or not the system is cooperative in nature or non-cooperative. Military broadcast systems are typically cooperative although there are noteworthy counter examples. As such, it is possible in some instances to develop handshaking and feedback schemes. Moreover, it is possible to deploy radios characterized by advanced modems to recipients of the broadcast which allow for the incorporation of powerful error-detection-and- correction (EDAC) coding schemes, as well as channel equalization, for the elimination of intersymbol interference in digital transmission. Wideband or spread spectrum signalling may be used for a variety of tasks, such as: interference excision, jam avoidance, low-probability-of-intercept (LPI) communications, and the exploitation of multipath for implicit diversity.

In the non-cooperative broadcast world, there are severe restrictions on what can be done. One of the schemes which may be applicable in the area of non- cooperative broadcast is that of transmission control, emphasizing broadcast relay station diversity as opposed to frequency diversity. For a specified broadcast coverage area, which is not overly distended, there is an optimal frequency range which will provide the best broadcast quality. Unfortunately, if a limited set of transmission frequencies are pre-specified and limited to a single broadcast transmitter site, there is no guarantee that the broadcast quality on one (or indeed any) of the pre-assigned broadcast channels has been optimized in the real environment. Precise real-time ionospheric behavior information is of some use in the single transmitter case, but principally for understanding the quality of performance being achieved, rather than correcting for it. It is possible, however, that a transmitter could be equipped to react to ionospheric conditions through appropriate beam steering and shaping procedures. It must be emphasized however, that there is a limit to what one can do in this area since the ionosphere largely defines the radio signal footprint in the broadcast area. Beam steering and shaping in the vertical plane simply modify the signal-to-noise contours within the footprint.

In the limit of multiple broadcast relay stations however, the application of global ionospheric information may have utility in the situation of a

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limited set of fixed transmission frequencies. Range is one obvious parameter of interest in the process of frequency selection for achieving the best broadcast quality to a given target area, since the maximum observable frequency (MOF) depends so strongly upon it. The other important factors relate to ionospheric characteristics and variability at each ionospheric control point (ICP). For present purposes, an ICP is defined as a relative maximum point in the magnitude of curvature along the ray path. For single hop modes, the ICP is typically near the midpoint of the path. We note that at a given universal time, the ICP positions and local times may be vastly different for two widely separated relay stations which are on an east-west baseline, depending on the ranges involved. In addition, the ICP coordinates are always different for different relay stations and specified (limited-extent) target areas. Naturally, for distended target areas, there will be at least as many ICPs as there are test points within the desired broadcast area. Furthermore, multihop and multimode conditions will tend to increase the number of ICPs to be considered. The game is now to specify the ionosphere over the region containing the ICPs. This specification along with the relevant transmitter to target area geometries will allow for real-time estimation of the broadcast signal laydown. The issue of ICP distribution is fundamental in an understanding of performance prediction as well as the application of ionospheric assessment to approach the ideal of adaptive HF broadcast.

There are a number of methods which can contribute to the development of a real-time ionospheric specification, which may be used for adaptive adjustment of HF system parameters. Critical in the development of such a methodology are: the type and locations of sensing devices, which are employed for estimating specified ionospheric parameters, and the ionospheric model, which is used to extrapolate the data into regions of space or time for which data are unavailable. The spatial extrapolation requirements of a model could, in principle, be relaxed through a sufficient amount of ionospheric monitoring. However, a procedure or model is always required in the process of forecasting future developments. This model should contain enough physics to provide for meaningful short-term forecasts, given sufficient information about initial conditions and disturbance source terms. The updated model would gracefully degrade to climatology as the input data ages (i.e.. becomes uncorrelated with future reality). Analogous statements could be made for the spatial extrapolation requirements of a model. Models which have been specifically designed to approximate this ideal have been developed by the U.S. Air Force. Examples include the Air Force 4-D Model [18] and, more recently, the ICED model [19]. It is noteworthy that these models are ionospheric specification models and not HF performance prediction models, although they could be exploited for this purpose. IONCAP and PROPHET HF performance prediction methodologies have the capability of update, although they were not designed with that process in mind. Specific update methods are considered later.

Given the possibility of improved ionospheric specification for adaptive HF schemes, this places more burden on the propagation model in the prediction algorithm. A further improvement in accuracy over present control-point methods is provided by using ray tracing. Three-dimensional (3D) ray tracing methods are now being applied in instances which require an accurate relation between

known launch angles, or other known data entities, at one end of the ray path, and geolocation of the other end of the ray path. An example is geolocation of a remote transmitter from measured angle-of-arrival of the signal at the receiver(s). A well-known 3D ray tracing program, based on numerical solution of the Hamiltonean or Haselgrove equations, was developed by Jones and Stephenson [32]. More recently, a 3D ray tracing program. based on analytic solution of the Euler-Lagrange equations for each raypath increment, was developed by Reilly and Strobe1 [33] and combined with a global ionospheric model [15]. The program was applied to the transmitter location problem, where it was found that geolocation and signal intensity results were very sensitive to the propagation algorithm in several cases where the ICPs were located in tilted ionospheric regions (e.g., near sunrise or sunset terminators, the equatorial anomaly, sub-auroral trough boundaries, auroral boundaries, TIDs, irregularities, etc.), especially when the raypaths were in the general direction of these tilts. One can thus anticipate a significant dependence of broadcast coverage footprint on the selection of propagation algorithm in these cases. This may indicate a need for 3D ray tracing in the propagation algorithm, particularly for the purpose of handling pathological situations, but this has to be balanced against increased computer time requirements. It would at least be useful to include 3D ray tracing in research directed toward improving the ionospheric model, which often progresses by comparing calculated propagation results with experiment.

TOWARD IMPROVEMENT OF LONG-TERM PREDICTIONS

Long-term prediction of ionospheric behavior depends critically upon a reliable representation of past ionospheric data and a known correlation with solar activity, which is the derivative of yet another prediction process [34]. Because of the general lack of a truly accurate representation or model of the ionosphere, which i s compounded by the tendency to "drive" these models with a single parameter such as sunspot naber, long-term predictions are not dependable. This is because short-term, apparently stochastic disturbance sources or factors, which occur in the actual physical process, are not properly accounted for in the prediction method. Thus, long-term methods for prediction are used to derive coarse guidance. The hope is that they at least reflect the median behavior.

There are long-term tendencies in the solar flux. CCIR Recommendation 371-5 [35], dealing with the choice of indices for long-term predictions of ionospheric behavior, recommends that predictions which are for dates more than one year ahead of the current period be treated differently than for periods which are less. If predictions are for epochs of more than 12 months in the future, the 12- month running mean sunspot number is to be used for the prediction of all ionospheric parameters, including: foF2. M(3000)F2. foF1, and foE. The 12- month average is employed to average out the shorter period disturbances, which may disguise the long-term tendency of solar flux and its influence on the median ionospheric parameters. For shorter lead times, several indices, including a measure of the 10.7 cm solar flux, as well as the sunspot number, produce equivalent answers in connection with prediction of the parameters foF2 and M(3000)FZ. As far as the lower ionospheric parameters foFl and foE are concerned, it turns out that the 10.7 cm solar flux is the best index for periods up to six months

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into the future and perhaps even longer. The fact that actual flux (even at 10.7 cm which does not itself interact with the ionosphere) best represents the solar ionization flux, which produces the E and F1 regions of the ionosphere, is well known and is implicit in the CCIR recommendations.

In the design stage, the driving parameters of a prediction model are allowed to take on a range of values, and the system is designed to encompass the results of the calculations. While sunspot number may be an adequate driving parameter for this purpose, it is not optimum for predicting events which will occur in particular days, weeks, or months in the future. Over the past decade, mounting evidence has accumulated [36] which shows that coronal holes and particular large sunspot groups on the sun are the real sources of high-speed solar wind streams, which feed most immediately into high latitude ionospheric effects and are later felt elsewhere. Observed effects are ionospheric storms, shifted and expanded auroral rings, depressed critical frequencies at mid-latitudes, etc. In other words, a sunspot number which totals all the spots, is too crude a parameter to predict these effects. Instead, the idea would be to view coronal holes and pertinent sunspot regions from the earth, account for the correct number of days for solar rotation to carry these solar features to the central meridian, and then add 2-3 days for the solar wind perturbation to reach the earth. Hence, ionospheric effects could be predicted from solar observations about a week in advance. If one accounts for the fact that several of these solar source features last many solar rotations, then corresponding effects can be confidently predicted to recur every 27-28 days. This is the basis for prediction of effects from solar observations with lead times up to several months. These developments point to the redesign of ionospheric models on the basis of correlating synoptic ionospheric parameter data with a different batch of relevant solar parameters. Shorter-term forecasts (on the scale of hours) may be related to the class of solar flare-related "sudden ionospheric disturbances (SIDS)," which are associated with bursts of short-wavelength electromagnetic radiation.

TOWARD IMPROVEMENT IN SHORT-TERM PREDICTIONS

A prediction scheme based on solar observations, once developed, can be the basis for improvements in short-term, as well as long-term forecasts. On the other hand, improvement for short-term forecasts has already been shown to result from ionospheric observations. The general area of short-term forecasting and spatial projection of ionospheric data is discussed in CCIR documentation [16]. Of interest in the current context is work related to the use of real-time foF2 or MOF measurements to improve near-term predictions.

Considerations for short-term updated forecasts, based on foF2 measurements by vertical-incidence ionosondes, may be found in articles by Rush [37] and Rush and Edwards [38]. Also of interest are papers by McNamara [39.40]. It was found that mid-latitude foF2 measurements at a location could be used to improve median model predictions for foF2 at a point removed in space and time out to approximately 500 km. in a north-south direction, out to approximately 1000 km. in an east-west direction, and ahead by times on the order of one hour. A procedure based on correlation coefficients was also proposed [36] which would include update measurements at multiple stations. The preceding numbers depend to some extent on environmental conditions; further

information is given in the aforementioned references. A severe requirement for an updating system based on ionospheric sounders is that it be capable of collecting the ionospheric data and distributing it to the prediction modules, where it is processed and predictions are made, all within the space of an hour or so. This requirement is more manageable when predictions and measurements can be confined to smaller geographical areas. The question of data distribution is central in any communication system involving network of sounders. Various schemes have been suggested including the use of a separate set of robust HF order wires for network management and data dissemination, modulation of the sounder waveforms to provide for data transmission between nodes, satellite connectivity, and even meteor-burst communication.

Other updating schemes are based on fitting the input parameters of the ionospheric model to ionospheric sounder data. For example, a single effective sunspot number for the ICED model [19] is determined to best fit the model to experimental foF2 data from several vertical-incidence sounders. A very similar procedure could be followed for a network of oblique-incidence sounders. In this instance, we obtain the observed junction frequency between the high-ray and low-ray modes on the oblique ionogram, which we shall call the maximum observable frequency, MOF. In the cases for which nose extension on the ionogram trace causes a departure between the highest frequency observed and the defined MOF, we simply excise the anomalous extension from consideration. This procedure is justified, since the extension is typically due to side-scatter or related effects, and is not accounted for in available models. The MOF values defined in this way can now be used to determine an effective sunspot number or an effective 10.7 cm. flux as input to the prediction model. A different use of sounder data for updating a climatological model has been developed in recent years [39]. In this scheme an effective 10.7 cm. flux or pseudoflux is associated with each sounder MOF datum at the sounder ICP, which we denote as a sounder control point (SCP). This pseudoflux value is determined by the requirement that the prediction model yields the observed MOF. The focus of attention in the preceding study has been on the one-hop mode data, and without detailed knowledge of the ionospheric trajectory, the SCP position is assigned to be the great-circle midpath point. For a network of sounders, there is a geographically distributed set of SCPs with associated effective flux values at any given time (e.g., the most recent flux determination). If the prediction model were perfect, or at worst different from reality by only a "global" fixed bias, the set of SCP pseudofluxes would be equal. This concept, whereby one develops a grid of pseudofluxes, has been used to develop a method for predictine. MOF values on an unsounded path with its associated ICP, and we distinguish between this ICP and the preceding sounder SCPs in the following description. One updating option is to use the effective flux for the SCP nearest the ICP in the prediction model, and then apply it to obtain the MOF prediction on the unsounded path. Without any updating method of this kind, typical MOF prediction errors on unsounded paths are in the range 2-4 MHz. With a fresh update (i.e., within about one hour), the upper bound of MOF prediction error drops to within 1 MHz, if the SCP is within about 300 km. of the ICP. A second option for updating offers further improvement under certain circumstances. If a triangle of SCPs can be found which is small enough and surrounds the ICP in question, and the updates at all three SCPs are fresh

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in the preceding sense, then an effective flux for the ICP can be found by linear interpolation of the three SCP effective fluxes in latitude and longitude to the ICP position. Small enough SCP triangles in this study [ 4 1 ] were found to be such that no two SCPs are separated by more than about 700 km. in an east-west orientation or about 400 km. in a north- south orientation. Under these circumstances, the upper bound of MOF prediction errors were found to be about 0 . 5 MHz in this second updating option and within 1 MHz if the updates are kept to within about 1 hour of the prediction. Another interesting feature is that updates which precede the prediction by exactly 2 4 hours are found, on average, to reduce the MOF error by about 1 MHz relative to the worst case situation which occurs at a delay of about twelve hours. This reflects the underlying diurnal variation. Of course, these numbers are statistical averages based on limited, mid-latitude data sets, but they serve to establish the viability of these updating schemes, based on geographic variation of the input parameters of the prediction model.

Other updating schemes may be used in the future. For example, a backscatter sounder could be used to advantage in broadcasting applications. In a fixed frequency mode, it operates like an HF OTH radar. The return signal, given as intensity vs time delay, can be converted in a timely manner to intensity vs range with the use of an ionospheric propagation prediction model. This leads directly to a specification of the broadcast coverage footprint at that frequency. In a sweep-frequency mode it has the potential of being used for ionospheric specification in a region of interest. It should be noted that there are still some uncertainties in the analysis of backscatter returns especially in regions where strong gradients exist. As a consequence, more research is necessary before the backscatter sounder schemes may be fully exploited. Another class of updating scheme will become available in the 1990s. This is based on ionospheric remote sensing from space at short wavelengths ( e . g . , optical imagery, vacuum uV airglow measurements, x-ray data, etc.). These techniques [ 4 2 , 4 3 ] promise to provide timely, supplementary information on electron density profiles which can be used for updates in an improved global ionospheric specification model.

A COMMENT ON INTERNATIONAL COOPERATION

It is important for the HF broadcast community to recognize the significant number of modern vertical- incidence-sounder (VIS) and oblique-incidence-sounder (01s) assets which are now becoming available. In many instances the deployment of these assets is coordinated, and compilation of sounder coordinates and other data are available to the potential user. On the international level and under the aegis of Commission G of URSI, an Ionosonde Network Advisory Group (INAG) has been established to coordinate activities, disseminate information, and share new developments in ionospheric characteriiation by this technique. Paralleling the substantial data base derived from VIS instruments, efforts are now underway to compile similar data from 01s networks [ 4 4 ] . This should be useful in the characterization of HF circuits over ocean areas, where VIS data are sparse, and this should also improve global climatological model predictions in these areas. Two other URSI Commission G working groups deal with ionospheric informatics and mappinglmodelling; and these groups participate in the organization of various scientific campaigns in conjunction with other international organizations. In recent years studies involving networks of ionospheric diagnostic devices, including sounders, have been initiated

[ 4 5 , 4 6 ] . International cooperation in data collection campaigns and data sharing will no doubt lead to an improvement in our understanding of the ionosphere, as well as in the development of new procedures applicable to a real-time assessment of the global ionosphere. These measures pertain to the automation of data collection, scaling of ionograms, and rapid data dissemination to users. Hopefully these developments may benefit the HF broadcast community.

CONCLUSIONS

An overview of prominent ionospheric propagation prediction models was given, and their use for shortwave broadcasting applications was discussed. The backbone of these programs is a climatological or monthly median ionospheric model, which does not account for a substantial amount of short-term fluctuations. Since all such ionospheric models suffer significant error from this class of disturbance, the choice of prediction model often depends to a large extent on availability of computer assets, transportability of the model, ease of use, and related issues. On the other hand, there are certain longer period, spatially dependent variations, which are better described by the more detailed models, such as day-night transitions, equatorial anomaly regions, high latitude auroral and sub-auroral trough regions, etc. Some improvement from the use of these prediction models is thereFore expected. There is also an increasing tendency for large main frame models to be incorporated in microcomputers. Thus, we shall see the most advanced models and methods available to even the most unsophisticated user, and these models will ultimately replace some of the well-known skeletonized models which were developed for microcomputers in the 7 0 ’ s and early 8 0 ’ s . In the near term, we anticipate that models such as IONCAP may be incorporated within external forecasting systems such as PROPHET as an option. In addition similar models may be incorporated within advanced modems which imploy microprocessors for network management and control.

Long-term predictions are likely to be required for broadcast planning for some time to come. It is unclear to what extent incremental improvements in long-term modelling will provide for anything but small incremental improvements in long-term prediction capability. Computer procedures and display formats may be improved, however, and these cosmetic changes will add value, since they will allow the analyst the facility to examine the projected data more coherently and in a variety of scenarios. One potential area for long-term performance improvement may arise as the result of a newly-developed scheme for mapping the tendencies of high latitude propagation from 1 week to several months in advance, based upon observation of the

features. evolution of coronal holes and related solar

The preceding approach should also benefit short- term predictions. Other approaches, based on ionospheric soundings, have been discussed. They have been shown to be viable for updating prediction models for short-term use. This approach has been found to be particularly useful for local removal of the DC bias errors in ionospheric models, which result from the use of monthly medians and imprecise driving parameters, such as the sunspot number. Updates are particularly relevant for the effective use of adaptive HF schemes. However, a present ionospheric specification decorrelates rapidly when compared with future reality. The update must be

236

performed rapidly. The best application of update for broadcast planning may well be in the context of relay station diversity. Thus, the broadcast planner could envision real-time resource management. The resources available in the future may involve backscatter sounder technology, as well as overhead imagery tailored to provide ionospheric "weather" maps. These data sources would be coupled to existing assets, such as conventional vertical and oblique sounders and total electron content sensors activated by GPS transmissions. All of this information could be merged with the real-time solar- terrestrial data available through various data services [47]. Relatively high-quality ionospheric information may result from inserting this data into sophisticated ionospheric models which are presently being developed. The possibility exists for the construction of a real-time ionosphere to serve a number of users, not unlike that which has been envisioned by the U.S. Air Force to serve its customers.

[71

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