Assimilation of autoscaled data and regional and local ionosphericmodels as input sources for real‐time 3‐D International ReferenceIonosphere modeling

M. Pezzopane,1 M. Pietrella,1 A. Pignatelli,1 B. Zolesi,1 and L. R. Cander2

Received 1 March 2011; revised 24 May 2011; accepted 8 June 2011; published 21 September 2011.

[1] This paper describes how the joint utilization of autoscaled data such as the F2 peakcritical frequency foF2, the propagation factor M(3000)F2, and the electron density profilecoming from two reference ionospheric stations (Rome and Gibilmanna), and the regional(Simplified Ionospheric Regional Model Updated) and global (International ReferenceIonosphere) ionospheric models can provide a valid tool for obtaining a real‐time three‐dimensional (3‐D) electron density mapping of the ionosphere. Preliminary results of theproposed 3‐D model are shown by comparing the electron density profiles given by themodel with the ones measured at three testing ionospheric stations (Athens, Roquetes,and San Vito).

Citation: Pezzopane, M., M. Pietrella, A. Pignatelli, B. Zolesi, and L. R. Cander (2011), Assimilation of autoscaled data andregional and local ionospheric models as input sources for real‐time 3‐D International Reference Ionosphere modeling, RadioSci., 46, RS5009, doi:10.1029/2011RS004697.

1. Introduction

[2] Ionospheric models are important for many research,engineering, and educational purposes in providing com-prehensive specification of the three‐dimensional (3‐D)electron density profile [Bilitza, 2002; Sojka et al., 2006;Cander, 2008; Eccles et al., 2011, and references therein].Most of them are global, e.g., the International ReferenceIonosphere (IRI) [Bilitza and Reinisch, 2008] and theNeQuick [Radicella, 2009], in which for a particular locationthe separate input ionospheric characteristics are modeled asa function of latitude, longitude, time of day, season, andepoch of the solar cycle. The basic input data to the iono-spheric models come from past and/or current worldwidenetworks of vertical‐sounding or topside measurements andsatellite observations, from profound theoretical considera-tions, and from various combinations of these. Althoughglobal models of the F2 layer critical frequency foF2 andpropagation factor M(3000)F2, such as those of the ComitéConsultatif International des Radiocommunications [1991]and the Union Radio Scientifique Internationale (URSI)[Rush et al., 1989], represent a valid input source for a 3‐Dmodeling of the ionosphere, regional and local models ofthese ionospheric characteristics can be important comple-ments to characterize those features that may be easilyneglected in global models. They are also good validationtools for global models and should be considered a significantpart of any ionospheric modeling efforts. It is important tomention here that the ionosphere‐related European Coopera-

tion in Scientific and Technology (COST) actions [Bradley,1999; Hanbaba, 1999] have clearly demonstrated thatregional foF2 and M(3000)F2 models can give better resultsthan global models of these ionospheric characteristics. Thisis particularly valid for nowcastingmodels that perform betterthan long‐term prediction models, especially during dis-turbed conditions [Pietrella et al., 2009].[3] Modern real‐time ionosonde observations provide

an extremely valuable data source for addressing differentscientific and application issues related to ionospheric mod-eling. On the basis of these data, much progress has beenmade in recent years in constructing empirical regional andlocal models of foF2 and M(3000)F2 ionospheric character-istics. One of them is the real‐time Simplified IonosphericRegional Model Updated (SIRMUP) [Zolesi et al., 2004;Tsagouri et al., 2005], which has been successfully operatingin the European area within the framework of the EuropeanDigital Upper Atmosphere Server (DIAS) project [Belehakiet al., 2006]. The SIRMUP procedure is based on the ideathat real‐time values of foF2 at one location can be deter-mined from the Simplified Ionospheric Regional Model(SIRM) [Zolesi et al., 1996] by using an effective sunspotnumber (Reff) based on real‐time ionosonde observationsinstead of the smoothed sunspot number R12. The method ofdetermining Reff was introduced and described in detail byHouminer et al. [1993]. Reff is chosen to give the best fitbetween model calculation and real measurements obtainedfrom a grid of ionosondes located in the mapping area. TheSIRMUP has the capability to generate the real‐time updatedfoF2 and M(3000)F2 values on a user‐specified spatial grid.Area coverage can be regional, over a few ionospheric sta-tions, or local, over only one station.[4] In this paper it will be shown how a combined utiliza-

tion of the real‐time autoscaled foF2 and M(3000)F2 data aswell as the real‐time electron density profiles coming from

1Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy.2Rutherford Appleton Laboratory, Didcot, UK.

Copyright 2011 by the American Geophysical Union.0048‐6604/11/2011RS004697

RADIO SCIENCE, VOL. 46, RS5009, doi:10.1029/2011RS004697, 2011

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the reference ionospheric stations of Rome (41.8°N, 12.5°E)and Gibilmanna (37.9°N, 14.0°E) and the SIRMUP modelcan provide a valid tool for improving real‐time 3‐D electrondensity modeling by IRI. The new approach is used to esti-mate the electron density on a regional grid of the ionospherein the central Mediterranean area extending in latitude from30° to 44° and in longitude from −5° to 40° with a 1° × 1°degree resolution. The proposed 3‐D model is presented andvalidated by comparing the corresponding electron densityprofiles with those directly measured at the three testingionospheric stations: Athens (38.0°N, 23.5°E), Roquetes(40.8°N, 0.5°E), and San Vito (40.6°N, 17.8°E).

2. Description of the Proposed 3‐D ElectronDensity Model of the Ionosphere

[5] Under the assumption of space‐sparse ionosphericmeasurements, data assimilation is the process of mergingmeasurement data with a model to estimate the ionospheric

conditions over an area where direct measurements are notavailable. By means of data assimilation, it is possible toexpand the effectiveness of limited measurements by usingthe model and, at the same time, to increase the accuracy ofmodel estimates using the measurements. For this reason, inthe last decademuchwork has been performed to develop andcontinuously test models that after assimilating observationscompute an updated 3‐D image of the ionosphere. TheElectron Density Assimilative Model (EDAM) [Angling andKhattatov, 2006], developed by QinetiQ, uses slant totalelectron content (TEC) GPS ground‐based measurements toadjust an empirical 3‐D climatological distribution of theionospheric electron density. The Utah State UniversityGlobal Assimilation of Ionospheric Measurements (GAIM)model [Schunk et al., 2004] can assimilate both slant TECGPS ground‐based observations and ionosonde electrondensity profiles using a Gauss‐Markov technique, and it hasbeen continuously tested and improved [Thompson et al.,2006; Decker and McNamara, 2007; McNamara et al.,

Figure 1. Flowchart showing the algorithm of the 3‐D electron density model of the ionosphere describedin this paper.

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2007, 2008, 2010, 2011]. In our case data assimilation isperformed with the autoscaled foF2 and M(3000)F2 valuesand the autoscaled electron density profiles.[6] Figure 1 shows the flowchart of the algorithm for the

3‐D electron density model of the ionosphere described inthis paper. The initial step of the algorithm consists of con-sidering the autoscaling performed at some ionospheric sta-tions. In our study, the autoscaling performed by Autoscala[Pezzopane and Scotto, 2005, 2007] on the ionogramsrecorded by the advanced ionospheric sounder designed anddeveloped at the Istituto Nazionale di Geofisica e Vulcano-logia (AIS‐INGV) [Zuccheretti et al., 2003] installed at theionospheric stations of Rome (41.8°N, 12.5°E) and Gibil-manna (37.9°N, 14.0°E) is exploited. The quality of theautoscaled ionograms computed by Autoscala is not checkedas, for instance, QualScan [McNamara, 2006] does for theautoscaled ionograms computed by Automatic Real-TimeIonogram Scaler With True Height analysis (ARTIST)[Reinisch and Huang, 1983] before assimilating them intoGAIM. However, it is noteworthy that during recent yearsseveral routines were developed to considerably increase thereliability and accuracy of Autoscala [Scotto and Pezzopane,2008; Pezzopane and Scotto, 2010].[7] If no station has given as output the autoscaled values

of foF2 and M(3000)F2, the standard IRI‐URSI procedureis launched, and a 3‐D climatological matrix (hereinafterIRI‐URSI) of the electron density is generated. However, ifat least one station has given as output the real‐time auto-

scaled values of the critical frequency foF2 and the propaga-tion factor M(3000)F2, the Reff is calculated on the basis ofthese values [Zolesi et al., 2004; Tsagouri et al., 2005], andit is then used by the SIRM model [Zolesi et al., 1996]to provide a nowcasting of foF2 and M(3000)F2 on a spatialgrid that can be regional or local. In the next step, this foF2

and M(3000)F2 grid of values produced by the SIRMUPprocedure is used as input to the IRI, and a 3‐D updatedmatrix of the electron density (hereinafter IRI‐SIRMUP) isgenerated. At this stage, if no station has an electron densityprofile associated with the performed autoscaling, the pro-cess stops. On the other hand, if at least one ionosphericstation has an electron density profile associated with theperformed autoscaling, an assimilation process of the mea-sured electron density profiles (see section 3) starts: theIRI‐SIRMUP electron densities are updated at a specificheight h, and a further updated 3‐D matrix (hereinafterIRI‐SIRMUP‐P) of the electron density is generated. As incertain cases Autoscala outputs only the ionospheric char-acteristics without producing an electron density profile, it isimportant to underline the necessity of checking whether astation has provided an electron density profile, even thoughit has already given foF2 and M(3000)F2 autoscaled values.For instance, when the ionogram trace is almost totallyblanketed by a strong E sporadic layer except for the last partof the F2 layer trace, Autoscala identifies this asymptoticalending trace of the F2 layer, giving as output foF2 andM(3000)F2. However, under such circumstances these valuesalone could not be sufficient to produce a realistic electrondensity profile.

3. Assimilation Process of the Measured ElectronDensity Profiles

[8] In order to assimilate the measured electron densityprofiles obtained by the autoscaling inversion of the iono-grams recorded at the reference ionospheric stations of Romeand Gibilmanna [Scotto, 2009], the following interpolationprocess between the measured electron density values andthose calculated by the IRI‐SIRMUP procedure is applied.[9] Given a definite height h,

x1 �1; �1ð Þ; x2 �2; �2ð Þ;:::; xi �i; �ið Þ;:::; xn �n; �nð Þf g

represent the geographical points (with i = 1,…, n and wherel and � are the corresponding geographical longitude andlatitude) for which the modeled IRI‐SIRMUP values I of theelectron density

I ½x1ð�1; �1Þ�; I ½x2ð�2; �2Þ�;:::; I ½xið�i; �iÞ�;:::; I ½xnð�n; �nÞ�f g

are known.[10] On the other hand,

x1*ð�1*; �1*Þ; x2*ð�2*; �2*Þ;:::; xjð�j; �jÞ;:::; xmð�m; �mÞ� �

represent the points (with j = 1*,…, m) for which the mea-sured values M of the electron density

M ½x1*ð�1*; �1*Þ�;M ½x2*ð�2*; �2*Þ�;:::;M ½xjð�j; �jÞ�;:::;�

M ½xmð�m; �mÞ�g

Figure 2. Effect of the weight function on the area underconsideration for two different values of s.

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are known (in our case m = 2*). The distance

dij ¼ xið�i; �iÞ � xjð�j; �jÞ ð1Þis then defined.[11] Hence, for each point for which a measured value of

the electron density is available close by, a weight function

Gij ¼ GðdijÞ ¼ exp � d2ij2�2

!ð2Þ

can be defined. The weight function is then equal to 1 at thepoint where the measured value of the electron density isavailable, and it decays as dij increases. Figure 2 shows theeffect of the weight function for two different values of s;the larger the value of s is, the larger the area affected bythe measured values is. Given a generic point xi, the corre-sponding value T of the electron density is calculated on thebasis of the weight function and of the measured electrondensity profiles obtained by Autoscala as follows:

T ½xið�i; �iÞ� ¼Xmj¼1

GijM ½xjð�j; �jÞ� þ 1� Gij

� �I ½xið�i; �iÞ�

� �: ð3Þ

[12] In order to show the differences between the 3‐Dmatrixes IRI‐URSI and IRI‐SIRMUP‐P, correspondingFigures 3, 4, and 5 illustrate horizontal slices, at a fixedheight, and vertical slices, at a fixed latitude and at a fixedlongitude, of the electron density over the central Mediter-

ranean area under consideration extracted from each of thesematrixes for 16 February 2010 at 07:00UT. In particular, withregard to the IRI‐SIRMUP‐P matrix, different maps for dif-ferent values of s are shown. Figures 3, 4, and 5 highlightclearly how, in general, the differences between climatolog-ical models (in this case the IRI‐URSI) and models thatassimilate measured values may be remarkable. Moreover,with regard to the IRI‐SIRMUP‐P matrixes it is evident thatthe larger the value of s is, the larger the area affected by themeasured values is. On the contrary, the lower the value of sis, the smaller the area affected by the measured values is.In this latter case, if the measured values are pretty differentfrom the values of the IRI‐SIRMUP matrix, distinct patchescharacterize the IRI‐SIRMUP‐P matrix as it is visible, forinstance, in Figure 4b at a longitude of 14°E (correspond-ing to the location of Gibilmanna) between about 170 and220 km of altitude. In order to compute Figures 3–5, thesimple MATLAB “contourc” function was used, that ismerely a graphical linear interpolation between the edges ofthe squares of the grid (further information on this MATLABfunction is available at http://www.mathworks.com/help/techdoc/creating_plots/f10‐2524.html#f10‐2614).

4. Preliminary Validation Results

[13] Preliminary validation results of the proposedIRI‐SIRMUP‐P 3‐D model are here shown by comparingthe electron density profiles given by the model with the ones

Figure 3. Maps of the electron density (electrons/cm3) at fixed height 210 km obtained by (a) IRI‐URSIand IRI‐SIRMUP‐P (b) with s = 0.5, (c) s = 1.0, (d) s = 3.0, (e) s = 5.0, and (f) s = 7.0.

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Figure 4. Maps of the electron density (electrons/cm3) at fixed latitude 38°N obtained by (a) IRI‐URSIand IRI‐SIRMUP‐P with (b) s = 0.5, (c) s = 1.0, (d) s = 3.0, (e) s = 5.0, and (f) s = 7.0.

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Figure 5. Maps of the electron density (electrons/cm3) at fixed longitude 14°E obtained by (a) IRI‐URSIand IRI‐SIRMUP‐P with (b) s = 0.5, (c) s = 1.0, (d) s = 3.0, (e) s = 5.0, and (f) s = 7.0.

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measured at some testing ionospheric stations. As shown inFigure 6, the reference ionospheric stations considered asinput for the model are Rome and Gibilmanna, while theionospheric stations considered as test sites are Roquetes,San Vito, and Athens.[14] The data and the electron density profiles measured at

Rome and Gibilmanna are those autoscaled by Autoscalafrom the ionograms recorded by the AIS‐INGV ionosonde,while the data and the electron density profiles measured atRoquetes, San Vito, and Athens are those autoscaled byARTIST [Reinisch et al., 2005; Galkin and Reinisch, 2008]from the ionograms recorded by the DPS4 Digisonde [Bibland Reinisch, 1978]. The release of ARTIST installed atRoquetes and San Vito is ARTIST 4.0; the one installed atAthens is ARTIST 4.5.[15] In order to test the model for quasi‐stationary iono-

spheric conditions and at the solar terminator, the two geo-magnetically quiet days 28 September 2009 from 11:15to 13:45 UT (Kp = 2) and 16 February 2010 from 06:00 to08:45 UT (Kp = 2) were selected. Both periods were partic-ularly appropriate to test the model because both the auto-scaling performed by ARTIST at Roquetes, San Vito, andAthens and the autoscaling performed by Autoscala at Romeand Gibilmanna were available. The results of the test areshown in Figures 7–12 where the electron density profilesobtained by the IRI‐URSI procedure, by the IRI‐SIRMUP‐Pprocedure, and by the ARTIST system are compared. TheIRI‐URSI profiles were calculated to a maximum height of500 km, while the maximum height of the IRI‐SIRMUP‐Pprofiles is equal to 400 km because Autoscala models thetopside as a parabolic layer ending right at that height. Thematrix IRI‐SIRMUP‐P from which the corresponding pro-file at the test site is extracted was calculated by setting s =3.0. This choice of s follows a preliminary testing phase(not shown here) of the model for different values of s wherethe best results were obtained for s = 3.0.[16] Figures 7–9 show that for quasi‐stationary ionospheric

conditions the electron density profile extracted from theIRI‐URSI and from the IRI‐SIRMUP‐P matrixes are prettysimilar, mostly from 12:15 to 13:45 UT, and that both of themare in good agreement with the electron density profilemeasured by ARTIST. This represents further evidence that

the IRI can satisfactorily model an undisturbed and stationaryionosphere.[17] Figures 10–12 show that at the solar terminator the

electron density profile extracted from the IRI‐SIRMUP‐Pmatrix is more representative of the real conditions of theionosphere than the electron density profile extracted fromthe IRI‐URSI matrix. Obviously, the best results wereobtained for San Vito, the test site closest to the input sites ofRome and Gibilmanna. Focusing our attention on the firstplot of Figure 12, we can see that this is the only case forwhich the IRI‐SIRMUP‐P profile underestimates the mea-sured one given as output by ARTIST. In order to facilitateunderstanding this, the autoscaling performed byAutoscala atthe ionogram recorded at Gibilmanna on 16 February 2010 at06:00 UT is shown in Figure 13. The ionogram quality is notso good; the trace is a little truncated, and, consequently, thetrace identified by Autoscala underestimates the real one.This underestimation made by Autoscala, due to the assimi-lation process of the measured electron density profiledescribed in section 3, affects the IRI‐SIRMUP‐P profilecomputed at San Vito. It is worth mentioning here that, ingeneral, the ionograms recorded at Rome and Gibilmannaby the AIS‐INGV ionosonde are of high quality and thatthe reliability of Autoscala is proven good [Pezzopane andScotto, 2007, 2008]. On the contrary, focusing our atten-tion on the first plots of Figures 10 and 11, we can see thatthe IRI‐SIRMUP‐P profile overestimates the measured onegiven as output by ARTIST. The reason for this overesti-mation is probably the lack of ionospheric stations closerto Athens and Roquetes than Rome and Gibilmanna, whichmight provide real‐time electron density profiles to be usedas input for the IRI‐SIRMUP‐P model and consequentlyhelp the model in better representing the real conditions ofthe ionosphere.[18] Figures 14 and 15 illustrate additional results in terms

of the differences ( foF2ARTIST‐DPS4 − foF2IRI‐SIRMUP‐P[s = 3.0]

and foF2ARTIST‐DPS4 − foF2IRI‐URSI) of the critical frequencyfoF2 values obtained at Athens, Roquetes, and San Vito bythe IRI‐URSI procedure, by the IRI‐SIRMUP‐P procedure(with s = 3.0), and by the ARTIST system. They confirm bothprevious conclusions that the IRI‐SIRMUP‐P procedure ismore representative of the real ionospheric conditions than

Figure 6. Map of the central Mediterranean area under study. Red stars represent the ionospheric stationsconsidered as input for the model. Blue stars represent the ionospheric stations considered as test sites.

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Figure

7.Com

parisonam

ongtheprofilesobtained

atAthenson

28Septem

ber2009from

11:15to13:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure

8.Com

parisonam

ongtheprofiles

obtained

atRoq

ueteson

28September20

09from

11:15to

13:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure

9.Com

parisonam

ongtheprofiles

obtained

atSan

Vitoon

28September20

09from

11:15to

13:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure

10.

Com

parisonam

ongtheprofilesobtained

atAthenson

16February2010

from

06:00to08:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure

11.

Com

parisonam

ongtheprofiles

obtained

atRoq

ueteson

16February20

10from

06:00to

08:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure

12.

Com

parisonam

ongtheprofiles

obtained

atSan

Vitoon

16February20

10from

06:00to

08:45UTby

IRI‐SIRMUP‐P

with

s=3.0(green),ARTIST(red),andIRI‐URSI(blue).

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Figure 13. Ionogram (a) recorded at Gibilmanna by the AIS‐INGV ionosonde on 16 February at 06:00 UTand (b) autoscaled by Autoscala. In red is the ordinary trace identified by Autoscala and in green is the cor-responding electron density profile. The AIP output parameters used by Autoscala to estimate the electrondensity profile associated with the reconstructed ordinary trace are given to the right of Figure 13b.

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Figure 15. Compar ison between the dif ferences( foF2ARTIST‐DPS4 − foF2IRI‐SIRMUP‐P[s = 3.0]) (green) and( foF2ARTIST‐DPS4 − foF2IRI‐URSI) (blue) of the critical fre-quency foF2 values obtained at (a) Athens, (b) Roquetes,and (c) San Vito by IRI‐URSI, IRI‐SIRMUP‐P with s =3.0, and ARTIST on 16 February 2010 from 06:00 to08:45 UT.

Figure 14. Comparison between the di f ferences( foF2ARTIST‐DPS4 − foF2IRI‐SIRMUP‐P[s = 3.0]) (green) and( foF2ARTIST‐DPS4 − foF2IRI‐URSI) (blue) of the critical fre-quency foF2 values obtained at (a) Athens, (b) Roquetes,and (c) San Vito by IRI‐URSI, IRI‐SIRMUP‐P with s =3.0, and ARTIST on 28 September 2009 from 11:15 to13:45 UT.

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the standard IRI‐URSI procedure and that the best resultsare obtained for the San Vito test site.

5. Conclusions

[19] In this paper we have proposed a model for whichupdated values of foF2 and M(3000)F2, coming from theregional ionospheric nowcasting model SIRMUP, plus theentire electron density profiles coming from the autoscaledinversion of the ionograms recorded at the reference stations ofRome andGibilmanna, are used as input sources for a real-time3‐D IRI modeling. We have also shown some preliminaryresults illustrating how this approach can give real improve-ment to the regional 3‐D picture of the ionosphere. Furtheradditional tests are planned on geomagnetically disturbedperiods by means of more than two reference ionosphericstations providing real‐time data as input for the model. It willalso be interesting to apply the proposed 3‐D model on otherglobal models such as the NeQuick model [Radicella, 2009].

[20] Acknowledgments. The authors gratefully acknowledge thethree reviewers for their helpful comments and suggestions.

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L. R. Cander, Rutherford Appleton Laboratory, Didcot OX11 0QX, UK.M. Pezzopane, M. Pietrella, A. Pignatelli, and B. Zolesi, Istituto

Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, I‐00143,Rome, Italy. (michael.pezzopane@ingv.it)

PEZZOPANE ET AL.: REAL‐TIME 3‐D IRI MODELING RS5009RS5009

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