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Evaluation of the STORM model storm-time correctionsfor middle latitude

D. Buresova a,*, L.-A. McKinnell b, T. Sindelarova a, B.A. De La Morena c

a Institute of Atmospheric Physics, Bocni II 1401, 14131 Prague 4, Czech Republicb Hermanus Magnetic Observatory, P.O. Box 32, Hermanus 7200, South Africa

c INTA-Atmospheric Sounding Station “El Arenosillo”, Mazagon, 21130 Huelva, Spain

Received 5 February 2009; received in revised form 23 September 2009; accepted 30 September 2009

Abstract

This paper presents results from the Storm-Time Ionospheric Correction Model (STORM) validation for selected Northern andSouthern Hemisphere middle latitude locations. The created database incorporated 65 strong-to-severe geomagnetic storms, whichoccurred within the period 1995–2007. This validation included data from some ionospheric stations (e.g., Pruhonice, El Arenosillo) thatwere not considered in the development or previous validations of the model. Hourly values of the F2 layer critical frequency, foF2, mea-sured for 5–7 days during the main and recovery phases of each selected storm were compared with the predicted IRI 2007 foF2 with theSTORM model option activated. To perform a detailed comparison between observed values, medians and predicted foF2 values thecorrelation coefficient, the root-mean-square error (RMSE), and the percentage improvement were calculated. Results of the compara-tive analysis show that the STORM model captures more effectively the negative phases of the summer ionospheric storms, while electrondensity enhancement during winter storms and the changeover of the different storm phases is reproduced with less accuracy. TheSTORM model corrections are less efficient for lower-middle latitudes and severe geomagnetic storms.� 2010 COSPAR. Published by Elsevier Ltd. All rights reserved.

Keywords: Ionosphere; Geomagnetic storms; STORM model; International Reference Ionosphere (IRI)

1. Introduction

Ionospheric parameters exhibit variations on a widerange of time-scales, ranging from long-term changesdown to days, hours or minutes. It is well known that amajor cause of irregular ionospheric variability is geomag-netic storms (Rishbeth and Mendillo, 2001). In particularsevere geomagnetic storms create complicated changes inthe complex morphology of the electric fields, tempera-ture, winds and composition and affect all ionosphericparameters. Current understanding of the response ofthe ionosphere to geomagnetic storms has been obtainedthrough different observations, modelling and theoretical

studies. Several outstanding reviews on ionospheric reac-tion to geomagnetic storm-induced disturbances havebeen published in the last decade (e.g., Rishbeth andField, 1997; Rishbeth, 1998; Buonsanto, 1999; Danilov,2001; Ondoh and Marubashi, 2001; Prolss, 2004). Accord-ing to long-term ionospheric observations above Euro-pean middle latitudes, storm-induced variations of theF2 region ionisation during the storm main phase oftenchange from large enhancements (positive phase) to deple-tions (negative phase). Such a change in polarity of thestorm effect makes a systemic description and predictionof the disturbed ionosphere rather complicated. Stronglongitudinal and latitudinal asymmetries or the completelydifferent behaviour of the stormy ionospheric F2 regionabove two comparable locations are frequently observed(Prolss, 1995). Moreover, the distribution of storm effectsmay vary substantially from one event to another.

0273-1177/$36.00 � 2010 COSPAR. Published by Elsevier Ltd. All rights reserved.

doi:10.1016/j.asr.2010.06.007

* Corresponding author.E-mail addresses: buresd@ufa.cas.cz (D. Buresova), L.McKinnell@

ru.ac.za (L.-A. McKinnell), tersin@ufa.cas.cz (T. Sindelarova), morenacb@inta.es (B.A. De La Morena) .

www.elsevier.com/locate/asr

Available online at www.sciencedirect.com

Advances in Space Research 46 (2010) 1039–1046

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Large-scale numerical simulations and studies haveshown that there is an increasing understanding of thestorm scenarios/mechanisms and influences of storm onsettime, intensity and season on the consequent changes in theionospheric state of ionisation (e.g., Fuller-Rowell et al.,1994; Cander and Mihajlovic, 1998; Muchtarov andKutiev, 1998; Araujo-Pradere et al., 2002; Araujo-Pradereand Fuller-Rowell, 2002). Nevertheless, some features ofthis phenomenon are still not clear and hardly predictable.Szuszczewicz et al. (1998) pointed out that the agreementbetween observations and model-generated values tendsto be more qualitative than quantitative, and the quantita-tive tests tend to be insufficiently reliable. Fuller-Rowellet al. (2000) showed how difficult it is to model the stormeffects on the ionosphere above a single station. One ofthe main conclusions of the study was that the current abil-ity to predict the ionospheric response to storm-induceddisturbances is significantly lower than recent knowledgeof the physical processes.

The International Reference Ionosphere (IRI) modelsufficiently estimates corrections for the ionospheric effectson radio wave propagation under geomagnetically quietconditions. The lack of a comprehensive understandingof storm-time behaviour led to the development of a simpleempirical model using existing extensive ionospheric datasets guided by simulations with a coupled thermosphere–ionosphere model (Fuller-Rowell et al., 1996), and startingfrom the 2001 version, such an empirical Storm-Time Ion-ospheric Correction Model (STORM) has been incorpo-rated in the IRI (Bilitza, 2001; Araujo-Pradere andFuller-Rowell, 2000). It was designed to be a function ofthe intensity of the geomagnetic storm and depends on lat-itude and season. The STORM model was developed usingdata from 75 ionosondes, incoherent scatter radars, theISIS and Alouette topside sounders, and in situ instru-ments on several satellites and rockets for 43 storms. Thedesign of the STORM model relies on the theory thatlong-living negative storm effects are due to regions inwhich the neutral composition is changed. The prevailingthermospheric summer-to-winter circulation, which trans-ports the molecular rich gas equatorward, explains the sea-sonal dependence: appearance of the prevailing negativephase in summer and characteristic positive phases in win-ter (Prolss, 1993; Fuller-Rowell et al., 1996).

Several validations of the STORM model were under-taken for different levels of solar activity, seasons and loca-tions. The largest validation was carried out by Araujo-Pradere and Fuller-Rowell (2002) and Araujo-Pradereet al. (2004). The model output was compared with theobserved ionospheric response at 15 selected Northernand Southern Hemisphere stations during 14 strong stormsthat occurred during the years 2000–2001. The comparisonshowed that the model captures the decrease in electrondensity particularly well in summer and equinox at mid-lat-itudes and high latitudes, but is less accurate in winter.Visually, the prediction given by the STORM model fol-lows the observed changes for many of the cases, but does

not do sufficiently well in the summer hemisphere. Theauthors came to the conclusion that the model is on aver-age 33% improved over the monthly mean. Similar resultshave been obtained by Araujo-Pradere and Fuller-Rowell(2001) for the Bastille Day event (July 2000) and by MiroAmarante et al. (2007), who compared the STORM correc-tions with ionosonde data obtained at 15 stations duringtwo severe storms of October and November 2003. Theirresults indicated that for the storm maximum day theSTORM model reduced on average the root-mean-squareerror (RMSE) from 0.36 to 0.22.

The present extensive evaluation of the STORM outputsis aimed at the middle latitudes where simulation of geo-magnetic storm effects is partially complicated by the prob-able regional nature of the composition changes as a resultof localized auroral heating (Araujo-Pradere and Fuller-Rowell, 2004). The created database incorporated 65strong-to-severe geomagnetic storms, which occurredwithin the period 1995–2005. In the analysis, we used datafrom some ionospheric stations (e.g., Pruhonice, El Areno-sillo), which were not included in the development or theformer validations of the model.

This paper presents an extensive evaluation of theSTORM model performance at middle latitudes. In Sec-tion 2, the data sources and methods used for the currentevaluation are described, while in Section 3 recent resultsof the evaluation of the STORM model storm-time correc-tions over selected middle latitude ionospheric stations arepresented and discussed.

2. Data sources and method

The present extensive evaluation of the STORM outputsis aimed at the middle latitudes, with the coordinates of thestations used for this evaluation listed in Table 1. The cre-ated database incorporates 65 strong-to-severe magneticstorms that occurred within the period from 1995 to2005. The study is carried out using geomagnetic and ion-ospheric data available in the World Data Centre for Solar-Terrestrial Physics at Chilton (WDC1) http://www.ukssd-c.ac.uk/wdcc1, in the Digital Ionogram Database of theCentre for Atmospheric Research, UMass, Lowell http://ulcar.uml.edu/DIDBase/, in the COST 271 databasehttp://www.wdc.rl.ac.uk/cgi-gin/ionosondes/cost_data-base.pl, and provided by individual ionospheric stations.Ionospheric parameters used are manually edited hourlyfoF2 values for the initial, main and partly for the recoveryphases of the analysed magnetic storms (at least for a 5-dayperiod) for each station and corresponding monthly medi-ans. The parameter simulation has been performed by run-ning the online model available at the IRI web site (http://omniweb.gsfc.nasa.gov/vitmo/iri_vitmo.html). The stormmain phase is defined by a decrease of the Dst index(decrease in magnetic field strength) and the subsequentrecovery phase by its gradual reversal to quiet conditions.Strong storm conditions were defined when Dst 6 �100 nT

1040 D. Buresova et al. / Advances in Space Research 46 (2010) 1039–1046

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for at least two consecutive hours and storm conditionsprevail till Dst < �50 nT.

In order to reliably compare results of the current eval-uation of the model performance with those obtained byAraujo-Pradere and Fuller-Rowell (2002), we used thesame statistical approach to the measured and model-gen-erated data analysis: the accuracy of the model has beenquantified by evaluating the daily RMSE between themodel and observed values and comparing this with theRMSE value calculated with predictions made using themonthly median IRI prediction with STORM optionswitched off. Eqs. (1) and (2) were used for this analysis:

RMSE ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiPni¼1ðmi � oiÞ2Pn

i¼1m2i

s: ð1Þ

Here mi and oi are the model outputs (prediction) and theobserved values, respectively.

I ¼ RMSEmm �RMSESTORM

RMSEmm

� 100%; ð2Þ

where I is the percentage improvement, RMSEmm is theRMSE calculated for the IRI with the STORM optionswitched off and RMSEstorm is the RMSE calculated withthe option activated.

3. Analysis of the results and discussions

An example of the observed foF2 variation and the qual-ity of the STORM model corrections is shown in Fig. 1afor the storm on 14–18 May 1997 for four European mid-dle latitude stations. The observed and model-simulated F2region peak response is described in terms of the foF2 ratioto monthly median (RfoF2). For this event the large nega-tive effect above the higher-middle latitude stations, Juli-usruh and Chilton, has been observed during thenighttime of the storm maximum day and during the fol-lowing night, which corresponds with the results of Kutiev

Table 1List of the NH and SH middle latitude ionospheric stations included inthis study.

Name of theionospheric station

Geographic latitudeand longitude

Magnetic latitudeand longitude

Juliusruh 54.60�N, 13.4�E 54.3�N, 99.7�EChilton 51.6�N, 358.7�E 54.1�N, 83.2�EPruhonice 50.0�N, 14.6�E 49.7�N, 98.5�ERome 41.9�N, 12.5�E 42.3�N, 93.2�ETortosa 40.8�N, 0.5�E 46.3�N, 80.9�EEl Arenosillo 37.1�N, 353.2�E 41.4�N, 72.3�EGrahamstown 33.3�S, 26.5�E 33.9�S, 89.4�EPort Stanley 51.7�S, 302.2�E 40.6�S, 10.3�E

-150

-100

-50

0

50

Dst

, nT

0

0.4

0.8

1.2

1.6

Rfo

F2

Juliusruh (54.6°N; 13.4°E)

Chilton (51.6°N; 358.7°E)

14/5/97 15/5/97 16/5/97 17/5/97 18/5/97 19/5/97Days

0

0.4

0.8

1.2

1.6

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

Rome (41.9°N; 12.5°E)

Tortosa (40.8°N; 0.5°E)

-140-120-100

-80-60-40-20

020

Dst

, nT

0

0.4

0.8

1.2

1.6

Rfo

F2

Juliusruh (54.6°N; 13.4°E)

Chilton (51.6°N; 358.7°E)

16/2/99 17/2/99 18/2/99 19/2/99 20/2/99 21/2/99Days

0

0.4

0.8

1.2

1.6

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

Tortosa (40.8°N; 0.5°E)

El Arenosillo (37.1°N; 353.2°E)

(a) (b)

Fig. 1. Effects of May 1997 (left side panels) and February 1999 (right side panels) geomagnetic storms on F2 layer peak electron density. Top panels ofboth (a) and (b) plots illustrate hourly Dst variation for entire period analysed. Panels below display observed values and output of the STORM model asfoF2 ratio for May 1997 (a) and February 1999 (b) storms. The dashed line shows the output of the IRI model, the full line is the observation. An emptysquare represents the daily RMSE for STORM, and the cross is the IRI with STORM option switched off. Time is in UT.

D. Buresova et al. / Advances in Space Research 46 (2010) 1039–1046 1041

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et al. (1998). Kutiev et al. (1998) studied the dynamics ofionospheric disturbances above 13 ionosonde stations cov-ering European middle latitudes within coordinates 40–60�N and 10�W–40�E during several isolated geomagneticstorms that occurred in the summer months of 1981–1984. They pointed out that the main decrease of the Flayer electron density appeared on the first and secondnights following the storm onset and disappeared afterthe next sunrise. The evaluation undertaken here, however,showed that during the May 1997 storm the lower-middlelatitude stations, Rome and Tortosa, exhibited the largestdeviation from the median towards the opposite sign dur-ing the daytime of the storm maximum and followingday, while, particularly above Tortosa, the night time neg-ative effect was insignificant. A similar, but less expressed,twin-peaked positive effect was also observed on the 16thMay for Chilton. The positive deviation occurred duringlate evening and night hours before the storm onsetdecreased with decreasing latitude.

As a reaction to geomagnetic disturbances, the STORMmodel forecasted a less than 20% decrease in electron den-sity for all stations (dashed line in Fig. 1) lasting fromabout noon of 15 May till noon of the next day. It didnot recognize the electron density enhancement beforethe storm onset and positive effects during the main andrecovery phase. The model improved the foF2 representa-

tion by 28% for Juliusruh, and its efficiency was signifi-cantly lower for the rest of the stations (9.5% forChilton; 7.6% for Tortosa). In the case of Rome, theRMSE was slightly worse than that from climatology(�14.7%).

Latitudinal differences in ionospheric response to storm-induced disturbances are also well seen from plots repre-senting the course of February 1999 storm effects on F2region peak ionisation (right side panels of Fig. 1). Thestorm culminates during the daytime of 18 February. Dur-ing the storm maximum day El Arenosillo displayed a pre-vailing positive effect, while over the higher-middlelatitudes both negative and positive phases of the stormhave been observed (largest for Juliusruh and Chilton).The RMSE for the STORM option showed an improve-ment over the monthly median for Tortosa and El Areno-sillo (12,4% and 18%, respectively), while the modelcorrections were inefficient for higher-middle latitude sta-tions Juliusruh and Chilton (�17.2% and �18.5%,respectively).

A severe geomagnetic storm culminated on 8 November2004 when the Dst index reached its minimum of �373 nTat 06:00 a.m. UT. A short recovery phase over the subse-quent few hours was followed by another step-by-stepdecrease with a minimum value of �289 nT at 09:00 a.m.UT of 10 November (top panels of Fig. 2). A significant

-400

-300

-200

-100

0

10 0

Dst

, nT

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

Juliusruh (54.6°S; 13.4°E)

Pruhonice (50.0°N; 14.6°E)

7/11/04 8/11/04 9/11/04 10/11/04 11/11/04 12/11/04Days

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

Chilton (51.6°N; 358.7°E)

El Arenosillo (37.1°N; 353.2°E)

-400

-300

-200

-100

0

100

Dst

, nT

7/11/04 8/11/04 9/11/04 10/11/04 11/11/04 12/11/04Days

0

0.4

0.8

1.2

1.6

Rfo

F2

Grahamstown (33.3°S; 26.5°E)

Stanley (51.7°S; 302.2°E)

0

0.4

0.8

1.2

1.6

Rfo

F2

(a) (b)

Fig. 2. Effects of November 2004 event on F2 layer peak electron density as was observed and simulated for four Northern (left side panels) and twoSouthern Hemisphere middle latitude stations (right side panels). Top panels of both (a) and (b) plots illustrate hourly Dst variation for entire periodanalysed. Panels below display observed values and output of the STORM model as foF2 ratio. The dashed line shows the output of the IRI model, the fullline is the observation. An empty square represents the daily RMSE for STORM, and the cross is the IRI with STORM option switched off. Time is in UT.

1042 D. Buresova et al. / Advances in Space Research 46 (2010) 1039–1046

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enhancement at the storm onset and subsequent decreaseof electron density during the storm main phase wasobserved above all four European stations (left side panelsof Fig. 2). The summer SH higher-middle latitude stationPort Stanley recorded only a moderate enhancement atthe storm onset while for lower-middle latitude stationGrahamstown when compared with climatology nochanges were observed (right side panels of the same fig-ure). A sharp positive phase at the storm onset or substan-tial enhancement of the F2 region peak electron densityseveral hours to a day before the geomagnetic storm onset,so-called pre-storm enhancements (15 from 65 events ana-lysed) belong to the still not clear and hardly predictablefeatures of ionospheric disturbances (Buresova and Lastov-icka, 2008). Araujo-Pradere and Fuller-Rowell (2004) men-tioned that a probable way to capture this behaviour intothe model is to design an additional short-period filter,obtained from residuals (model calculated � observed val-ues) of the storm sample, as the input of the STORM (inte-gral of ap index over previous 33 h) does not allow forreproducing high-frequency features. Although theSTORM model did not capture the enhancement, underes-timated the decrease of electron density at 8 November andalternation of the polarity of the storm effect for all NH

and SH stations, it improved the foF2 representation forboth peaks (November 8 and 9) of the event on averageby 53% for Port Stanley, by 33% for Juliusruh and Gra-hamstown and by 19% for Chilton and Pruhonice. TheSTORM model failed to predict the positive phase of thestorm for El Arenosillo.

Within the period of 22–29 July 2004 an intense triplegeomagnetic storm occurred. Fig. 3 represents a course ofDst index (bottom panels) and ionospheric reaction tostorm-induced disturbances above selected summer NHand winter SH middle latitude stations (left side and rightside panels, respectively). As given by the RMSE, the qual-ity of the STORM model corrections for all peak days andfor the European region was decreasing with decreasinglatitude. The highest improvement on the monthly medianwas obtained for Juliusruh (33%). Only at El Arenosillo, ingeneral, and at Chilton and Tortosa during the secondpeak day, was the sharp increase in foF2 observed, andthe model performed worse than the monthly median.Comparing to NH, for SH the STORM predictions wereless efficient (the highest improvement was 8.2% forGrahamstown).

An overall summary of the evaluation results of theSTORM model storm-time corrections for both Northern

-200

-150

-100

-50

0

50

Dst

, nT

0

0.4

0.8

1.2

1.6

Rfo

F2

Juliusruh (54.6°N; 13.4°E)

Chilton (51.6°N; 358.7°E)

22/7/04 23/7/04 24/7/04 25/7/04 26/7/04 27/7/04 28/7/04 29/7/04Days

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

0

0.4

0.8

1.2

1.6

Rfo

F2

Tortosa (40.8°N; 0.5°E)

El Arenosillo (37.1°N; 353.2°E)

-200

-150

-100

-50

0

50

Dst

, nT

Grahamstown (33.3°S; 26.5°E)

Stanley (51.7°S; 302.2°E)

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

22/7/04 23/7/042 4/7/04 25/7/04 26/7/04 27/7/04 28/7/04 29/7/04Days

0

0.4

0.8

1.2

1.6

2

2.4

Rfo

F2

(a) (b)

Fig. 3. Effects of July 2004 event on F2 layer peak electron density as it was observed and simulated for four Northern (left side panels) and two SouthernHemisphere middle latitude stations (right side panels). Top panels of both (a) and (b) plots illustrate hourly Dst variation for entire period analysed.Panels below display observed values and output of the STORM model as foF2 ratio. The dashed line shows the output of the IRI model, the full line is theobservation. An empty square represents the daily RMSE for STORM, and the cross is the IRI with STORM option switched off. Time is in UT.

D. Buresova et al. / Advances in Space Research 46 (2010) 1039–1046 1043

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and Southern Hemisphere is presented in Fig. 4. Left sidepanels of the figure represent the mean improvement calcu-lated for all analysed storm culmination days (forwardslashed bars) and for the entire stormy periods (cross-hatched bars). The prime observation from the figure forNH is the decreasing ability of the model to simulate stormeffects with decreasing latitude. An efficiency of the modelcorrections seems to be considerably lower for SH anddecreases with increasing latitude, though we need hereto involve more ionospheric stations in the analysis. Theimprovement of a recovery phase representation is signifi-cantly lower. As for seasonal dependence of the qualityof the storm-time corrections (right side panels of Fig. 4),the model gives better results for summer storms. The out-come corresponds well with the results of Araujo-Pradereand Fuller-Rowell (2004).

A statistical picture of the occurrence of negative andpositive phases during 65 strong-to-severe geomagneticstorm peak days for the period from 1995 to 2005 for threeEuropean stations, which is given in Fig. 5, could partiallyexplain the finding. In general, the changeover from onetype of effect to the other is more common for winter thanfor summer, and the occurrence of such behaviour

increases with decreasing latitude. During summer (May–August) all three stations display a more frequent appear-ance of only the negative effect during the main phase ofthe analysed storms. Considering both winter and summerperiods the higher-middle latitude station Juliusruh showsa much higher appearance of only the negative phase (34events) or both phases (29 events) during a strong tointense geomagnetic storm than the appearance of onlythe positive phase (two events). The summer–winter differ-ence in storm phase appearance above Juliusruh is rela-tively small. When compared with Juliusruh the higher-middle latitude station Chilton shows a similar distributionof storm phases and the more frequent appearance of thenegative phase in summer. The lower-middle latitude sta-tion El Arenosillo exhibits a shift to the more frequentappearance of the positive phase and alternation of thepolarity of the storm effect, especially during wintertimegeomagnetic storms (Buresova et al., 2007). However,although the design of the STORM model takes intoaccount a coexistence of a positive (20–40� midlatitudebin) and negative (40–60� midlatitude bin) phase in thewinter hemisphere (Araujo-Pradere and Fuller-Rowell2004), the changes in the storm effect polarisation during

0

2

4

6

8

10

12

14

16

18

Mea

n im

pro

vem

ent,

%

Juliusruh Chilton Pruhonice Rome Tortosa ElArenosillo

Northern Hemisphere

Storm maximum days

Entire disturbed period

0

5

10

15

20

25

Mea

n im

pro

vem

ent,

%

Winter NH Summer NH Equinox NH

0

2

4

6

8

10

12

14

16

18

Mea

n im

pro

vem

ent,

%

GrahamstownPortStanley

Southern Hemisphere

Storm maximum days

Entire disturbed period

0

5

10

15

20

25

Mea

n im

pro

vem

ent,

%

Winter SH Summer SH Equinox SH

Fig. 4. Overall summary of the STORM model evaluation results for Northern (top panels) and Southern Hemisphere (bottom panels). Left side panelsrepresent the mean improvement calculated for all analysed storm culmination days (forward slashed bars) and for the entire stormy periods (crosshatchedbars). Right side panels are for seasonal dependence of the quality of the model predictions.

1044 D. Buresova et al. / Advances in Space Research 46 (2010) 1039–1046

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the storm main phase at middle latitude remains an unre-solved problem.

4. Conclusions

An extensive evaluation of the STORM model storm-time corrections which focused on middle latitudes was car-ried out using data from 65 strong-to-severe space weatherevents that occurred within the period from 1995 to 2005.The results show that for middle latitudes:

� In general, the STORM model improves a storm-timefoF2 representation over the monthly median predictionfor both storm maximum day and whole analysed per-iod averages. At the peak of the disturbance the modelgives best results for summer storms and for Europeanhigher-middle latitudes. At the NH the effectiveness ofthe model storm-time corrections is decreasing withdecreasing latitude. For the SH the trend seems to beopposite (larger investigation is necessary). An improve-ment of a recovery phase representation is significantlylower.� The model partially fails in capturing an alternation of

the storm positive and negative effects.� The STORM model is not able to reproduce correctly

the storm-induced rapid changes in the daily course offoF2 (e.g., initial rapid positive ionospheric response tothe storm onset).� The largest differences between the observed and model-

reproduced magnitude of the storm effect was obtainedfor the negative phases.

Acknowledgements

This work has been supported by a Research Grant un-der the National Research Foundation (NRF) Key Inter-

national Science Capacity (KISC) Initiative Grant UID63719, and also by Grant QS300120506 of the GrantAgency of the Academy of Sciences of the Czech Republicand by Grant 205/08/1356 of the Grant Agency of theCzech Republic. We also thank World Data Centre for So-lar-Terrestrial Physics at Chilton, UK, the Digital Iono-gram Database of the Centre for Atmospheric Research,UMass, Lowell, US, and Juliusruh, Ebro, El Arenosilloand Rome ionospheric observatories for supplying us withdata.

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Fig. 5. Occurrence of negative and positive phases during a geomagnetic storm main phase above three European stations, Juliusruh (Ju), Chilton (Ch)and El Arenosillo (Ar), for a winter and summer period (according to the type of thermospheric circulation) within the period 1995–2005 (from Buresovaet al., 2007).

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