Available online at www.sciencedirect.com

Advances in Space Research 42 (2008) 599–609
www.elsevier.com/locate/asr

International Reference Ionosphere 2007: Improvements
and new parameters
D. Bilitza a,b,*, B.W. Reinisch caGSFC, SPDF, Code 672, Greenbelt, USA
Geroge Mason University, Fairfax, USAc
Center for Atmospheric Research, University of Massachusetts, Lowell, USAb

Received 28 June 2007; received in revised form 25 July 2007; accepted 25 July 2007

Abstract
The International Reference Ionosphere (IRI), a joint project of URSI and COSPAR, is the de facto international standard for the
climatological speciﬁcation of ionospheric parameters and as such it is currently undergoing registration as Technical Speciﬁcation (TS)of the International Standardization Organization (ISO). IRI by charter and design is an empirical model based on a wide range ofground and space data. It describes monthly averages of ionospheric densities and temperatures in the altitude range 50–1500 km in
the non-auroral ionosphere. Since its inception in 1969 the IRI model has been steadily improved with newer data and with better mathematical descriptions of global and temporal variation patterns. A large number of independent studies have validated the IRI model incomparisons with direct and indirect ionospheric measurements not used in the model development. A comparison with IRI is often oneof the ﬁrst science tasks by an ionospheric satellite or rocket team.
This paper describes the latest version of the IRI model, IRI-2007, explaining the most important changes that are being introducedwith this version. These include: (1) two new options for the topside electron density, (2) a new model for the topside ion composition, (3)the ﬁrst-time inclusion of a model for the spread F occurrence probability, (4) a NeuralNet model for auroral E-region electron densities,(5) a model for the plasmaspheric electron temperature, and (6) the latest International Geomagnetic Reference Field (IGRF) model forthe computation of magnetic coordinates including their changes due to the secular variation of the magnetic ﬁeld.
Ó 2008 COSPAR. Published by Elsevier Ltd. All rights reserved.
Keywords: Ionosphere; IRI; Global ionospheric models

1. Introduction
The International Reference Ionosphere (IRI) project
was initiated by the Committee on Space Research(COSPAR) and by the International Union of Radio Science (URSI) in the late sixties with the goal of establishingan international standard for the speciﬁcation of ionospheric parameters based on all worldwide available datafrom ground-based as well as satellite observations.
COSPAR and URSI speciﬁcally asked for an empiricalmodel to avoid the uncertainties of the evolving theoreticalunderstanding of ionospheric processes and coupling to the*Corresponding author. Address: Dr. Dieter Bilitza GSFC, code 672
Greenbelt, MD 20771 USA.
E-mail address: dieter.bilitza-1@nasa.gov (D. Bilitza).

regimes below and above. COSPAR’s main interest was
and is in a general description of the ionosphere as partof the terrestrial environment for the evaluation of environmental eﬀects on spacecraft and experiments in space.
URSI’s prime interest is in the electron density part of
IRI for deﬁning the background ionosphere for radiowave
propagation studies and applications. To accomplish thesegoals a joint COSPAR-URSI Working Group was established in 1969 and tasked with the development of themodel. Over the years the membership of this Working
Group has grown to now 52 experts spanning the globe(see Fig. 1). The membership roster is characterized by agood balance in terms of measurement techniques andmodeling teams. Through its members the IRI project
has access to almost all of the important ionospheric data

0273-1177/$34.00 Ó 2008 COSPAR. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.asr.2007.07.048

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D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609
P. Bradley, M. Rycroft, Lj. Cander (U.K.),
K. Rawer, W. Singer (Germany),
A. Alcayde, R. Hanbaba (France),
B. Zolesi, S. Radicella (Italy),
M. Friedrich (Austria),
E. Kopp (Switzerland),D. Altadill (Spain)

L. Triskova, V. Truhlik (Czech Rep)
I. Kutiev (Bulgaria)
I. Stanislawska (Poland),
S. Kouris (Greece)

A. Danilov
V. K. Depuev
T. Gulyaeva
G. Ivanov-Kholodny
E. Kazimirovsky
A. Mikhailov
K. Oyama
K. Igarashi
S. Watanabe

B. ReinischD. Bilitza
T. FullerRowell
K. BiblX. Huang
J. Sojka
D. Anderson
V. Wickwar
L. Scherliess
M. Codrescu
S-R Zhang
C. Mertens

M.-L. Zhang
S.-Y. Su

Kyoung Min

S. Pulinets
O. Obrou
M. AbduR. Ezquer
M. Mosert deGonzalez

J. Adeniyi

A. Poole,
L.-A. McKinnell

K. Mahajan
A.P. Mitra
S.P. Gupta
P.K. Bhuyan

P. Wilkinson
P. Dyson
B. WardFig. 1. Global distribution of IRI members including the newest members (red/gray) and the Steering Committee members (underlined). (Forinterpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this paper.)sources, ground and space, nationally and internationally.
Resolving conﬂicts between the results of diﬀerent measurement techniques and providing guidelines regarding
the reliability of the diﬀerent data sources was and is an
important task before the IRI team. The group has played
an active role in setting guidelines for reliable D-region
measurements and in assembling compilations of the mostreliable rocket data for this region (Rawer, 1974; Friedrichet al., 2001; Friedrich and Torkar, 2001). The current IRI
Steering Committee consists of B. Reinisch (Chair), L.
Triskova (URSI Vice-Chair), M. Friedrich (COSPAR
Vice-Chair), and D. Bilitza (Secretary).
The IRI model is continually upgraded as new data andnew modelling approaches become available and this process has resulted in several major milestone editions of
IRI (Rawer et al., 1978a,b, 1981; Bilitza, 1990, 2001; Bilitza
and Rawer, 1996) progressing from a set of tables for typical conditions, to a global model for all phases of the solar
cycle. More information about the IRI project including
information about the IRI Newsletter and the IRI electronic mailer can be found on the IRI homepage at
http://IRI.gsfc.nasa.gov/.
From early on the model was made available in electronic form as a FORTRAN program (ftp://
nssdcftp.gsfc.nasa.gov/models/ionospheric/iri/) and more
recently also as an interactive web interface accessible fromthe IRE homepage.
Annual IRI meetings are the prime venue for initiating
and coordinating model improvements and new model
developments. During years of COSPAR General Assem-

blies (even years, e.g., 2004, 2006) the meeting is held in
the form of a special COSPAR session. In odd years(non COSPAR years) special week-long IRI Workshops
are held organized by the IRI members in the workshop
country. A list of meetings with links to meeting reports
can be accessed from the IRI homepage. The reports givea good overview of the meeting activities and accomplishments. Progress of the IRI project is documented in a seriesof dedicated issues of Advances in Space Research withpapers from these IRI meetings (for a list see IRI homepage). Papers from the IRI session during the 2004
COSPAR General Assembly in Paris, France were published as Volume 37, Number 5, 2006, and papers fromthe 2005 IRI Workshop in Ebro, Spain recently came out
as Volume 38, Number 5, 2007. The workshop series continued in 2006 with an IRI-session during the COSPAR
General Assembly in Beijing, China in July on the ‘‘Solar
Activity Variations of Ionospheric Parameters” and a special IRI-GPS workshop in Buenos Aires, Argentina in
October. The 2007 IRI workshop will be held in Prague,
Czech Republic and is organized jointly with the European
COST 296 project (see homepage at http://www.ufa.cas.cz/
html/conferences/IRICOST2007/ which also provides
access to all oral workshop presentations.
IRI describes monthly averages of the electron density,
electron temperature, ion composition (O+, H+, N+,++
He+, Oþ
2 , NO , Cluster ), ion temperature, and ion drift
in the current ionospheric altitude range of 50–1500 km.
An eﬀort is underway to also include a measure of the ionospheric variability during the month in terms of a descrip-

D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

tion of monthly quartiles and deciles. Being a data-basedmodel, the accuracy of the model in a speciﬁc region
and/or time period depends on the availability of reliabledata for the speciﬁc region and time. One of the mostimportant data sources for the IRI electron density is theworldwide network of ionosonde stations that has monitored the ionosphere with varying station density since
the nineteen-thirties. IRI predictions are most accurate inNorthern mid-latitudes because of the generally high station density in this part of the globe. At low and high latitudes ionospheric parameters show the steepest gradients,
sharp peaks and deep valleys, e.g., density crests on bothsides of the equator and a trough equatorward of the auroral oval, requiring a high station density to fully record andmonitor the highly variable ionosphere. Unfortunately,
both of these regions have rather sparse ionosonde coverage, partly because of the harsh climate conditions, andas a result the IRI predictions are less accurate at equatorial and auroral latitudes.
Besides the ionosonde network, other data sources forthe model development include the incoherent scatter (IS)radars, several compilations of rocket measurements, andsatellite data from in situ and topside sounder instruments.
The IS radars measure all of the IRI parameters over thefull altitude range, but only a few radars are in operationworldwide. Their data are essential for the description ofvariations with time, season, and solar activity, whereas
the satellite data are a primary source for the descriptionof the global morphology of ionospheric parameters. In
the lower ionosphere the large neutral densities make radarand satellite measurements very diﬃcult or impossible androcket ﬂights are the prime data source for IRI (Friedrich
and Torkar, 2001; Danilov and Smirnova, 1995).
This paper introduces the newest version of the model,
IRI-2007. describing the most important changes in the following chapters: (a) two new options for the topside electron density proﬁle (Section 2), (b) a new model for theelectron density in the auroral E-region (Section 3), (c)plasmaspheric electron temperatures are included for theﬁrst time (Section 4), a much improved model for the topside ion composition (Section 5), and for the ﬁrst time a
speciﬁcation of spread F probability (Section 6).

601

in the upper topside (from about 500 km above the F-peakupward) that increases with altitude reaching about a factor of 3 at 1000 km above the peak (see Fig. 2, upper
panel). The likely causes of this IRI artefact are (1) the limited data base used to develop the original IRI model, primarily Alouette 1 topside sounder data with some AE-C,
and DE-2 in situ data and typical proﬁles from the Jicamarca incoherent scatter radar, and (2) an insuﬃcientweighting of the low densities in the upper topside compared to the F-region densities, which are about an orderof magnitude larger.
To overcome this shortcoming two new options are
introduced in IRI-2007. The ﬁrst is a correction factor
for the 2001 model based on over 150,000 topside proﬁlesfrom Alouette 1, 2, and ISIS 1, 2. This term varies with altitude, modiﬁed dip latitude, and local time (Bilitza, 2004).
With this correction term the IRI model represents the topside sounder data quite well as shown in the bottom panelof Fig. 2. The resulting decrease in IRI TEC will help to

2. Two new options for the topside electron density
For the electron density, recent IRI work has concentrated on the lowest (D and E-region) and on the uppermost (topside) part of the proﬁle. The topside proﬁle isof special importance because of its impact on the total
electron content (TEC), which is the prime parameter
needed for many ionospheric model applications. A number of studies have noted discrepancies between the IRI
model and measurements, especially at high latitudes andduring high solar activities. A detailed description of theseshortcomings and of the ongoing eﬀorts to improve the IRI
topside model was recently published by Bilitza et al.
(2006). At issue is an overestimation of electron densities

Fig. 2. Average ratio between the Alouette/ISIS sounder data and the IRI
model at noon for diﬀerent modiﬁed dip latitude ranges using the current
IRI topside model (IRI-2001, top) and the corrected model (IRI-2007a,bottom). The model and data are normalized to the respective F-peakdensities and heights (Bilitza, 2004).

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D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

overcome diﬀerences recently noted by Jee et al. (2005) incomparisons of IRI-2001 with TOPEX measurements. This
option is called IRI-2007a in the rest of the paper.
The second option (IRI-2007b) is the NeQuick topsidemodel that was developed by S. Radicella and his collaborators over the last decade (Radicella and Leitinger, 2001;
Coisson et al., 2006) and is the most mature of the diﬀerent
proposals for the IRI topside that were described by Bilitza
et al. (2006). The NeQuick topside model uses an Epsteinlayer function with a height-dependent thickness (i.e., scaleheight) parameter and in this way produces a smooth transition from an atomic oxygen ionosphere near the F-peakto a light ion ionosphere higher up. The model parameters
were determined based on ﬁtting this function to ISIS 1, 2
and Intercosmos 19 topside sounder proﬁles. Comparisonswith TOPEX TEC data have shown that NeQuick provides
an improvement over the present IRI TEC predictions(Coisson et al., 2004). IRI uses the latest version of the
NeQuick model as presented by Coisson et al. (2006).
In Fig. 3 the diﬀerent topside options are compared withtopside sounder measurements from ISIS-2. The observed
topside electron density values are plotted versus the model
values using IRI-2001 as well as the two new options. The
panel for IRI-2001 shows the misrepresentation at highaltitudes (i.e., low densities), and the other two panels illustrate that this is no longer a problem for IRI-2007. In Table
1 the standard deviations are listed for the diﬀerent models
for diﬀerent topside sounder data sets including data from
Alouette 1, 2, and ISIS 1, 2. In addition to IRI-2001 andthe two new IRI-2007 options Table 1 also includes themodel proposed by Triskova et al. (2006) based on Atmosphere Explorer and Intercosmos data and primarily
intended for computing absolute ion densities in conjunction with their ion composition model (Triskova et al.,2003). But this model does not allow updating with themeasured F-peak parameters and thus shows much larger
discrepancies to the data than the new 2007 options.
The table and plots document the signiﬁcant improvement in the topside electron density introduced with the
new IRI-2007 topside models. Of the two new options
the NeQuick option provides the better results for all four
data sets.
Both new options will also provide for a smoother transition to plasmaspheric models, which in the past had problems connecting to the IRI (Gallagher et al., 2000), because
IRI values at the ionosphere-plasmasphere boundary weremuch larger than the values from plasmaspheric models. A
very promising new eﬀort is the vary-Chap approach of
Reinisch et al. (2007) that uses instead of the standard
Chapman function with constant scale height, a slightly
more complex Chapman-type function that is derived whenassuming a height-varying scale height. The ﬂexibility ofthe vary-Chap approach simpliﬁes the merging of the IRI
topside proﬁle with a plasmaspheric model, as illustrated
in Fig. 4. This is accomplished by adjusting the parametersthat determine the height-varying scale height function
including the transition height hT that marks the transition

Fig. 3. A comparison of ISIS-2 topside sounder electron density data
versus the model predictions by IRI-2001 (top panel), by IRI-2007a(middle), and by IRI-2007b (bottom). The number of data points is
223,779. Note the over-estimation by IRI-2001 at low densities (highaltitudes).

D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

603

Table 1
Mean and standard deviation (std) of the data-model diﬀerences [(data-model)/data] for the diﬀerent Alouette and ISIS data sets (n = number of proﬁles)ISIS-2

IRI
cor
NeQ
TTS
n

ISIS-1

Alouette-2

Alouette-1u

Alouette-1p

Std

Mean

Std

Mean

Std

Mean

Std

Mean

Std

Mean

10.39
2.97
1.92
8.32
25,214

2.12
0.61
0.31
2.34

7.44
2.72
1.74
3.23
20,105

1.79
0.43
0.21
0.76

9.90
2.04
0.98
4.58
5166

2.23
0.38
0.04
1.66

4.50
2.44
1.96
4.30
19,434

0.50
0.22
0.11
0.99

2.73
1.55
1.48
3.69
12,900

1.01
0.41
0.36
0.76

IRI, IRI-2001; cor, IRI-2007a; NeQ, IRI-2007b; TTS, Triskova et al. (2006) model.

from an oxygen-dominated ionosphere to light ion dominance and the scale height HT at this transition point.
3. Electron density changes in the lower ionosphere
The IRI generally describes the E-region electron density well, but it does not yet include the ionization enhancement at auroral latitudes caused by precipitating particles.
One of the new features in IRI-2007 is a Neural Network(NN) model for this auroral region that was trained witha large volume of EISCAT incoherent scatter data
(700,000 data points) and also with 115 proﬁles obtained
from rocket borne wave propagation experiments (McKinnell et al., 2004; McKinnel and Friedrich, 2006). The model
describes the density variations in terms of local magnetic
time, riometer absorption, local magnetic index K, solar
zenith angle, and atmospheric pressure, the later accounts
for variations with height and season. The riometer absorption and K index track storm-related changes in the Eregion. This modeling approach uses ground-based radio
wave absorption measurements as the proxy to represent

storm-time changes in the E-region. (Fig. 5). Absorption
measurements are accessible online from a number of stations, e.g., data from the Finnish IRIS station are available
at http://www.sgo.ﬁ/Data/Riometer/.
For the non-auroral D-region IRI oﬀers three diﬀerent
options: (1) the standard model based on a small selectionof representative rocket proﬁles (Mechtley and Bilitza,
1974; Bilitza, 1981), (2) the FIRI model (Friedrich andTorkar, 2001; Friedrich et al., 2001) based on a compilation of rocket data with simultaneous radio propagationand in situ measurements, and (3) the Danilov et al.
(1995) model based on a compilation of Russian rocket
data not included in the FIRI set. A special feature of
the Danilov model is the inclusion of representative proﬁlesfor conditions of Winter Absorption Anomaly and Stratospheric Warming. IRI oﬀers three options for the D-region
electron density to illustrate the large uncertainties that still
exists in this altitude domain. Data are limited to the few
locations where rockets can be launched or where incoherent scatter radars operate in the special mode required tomeasure D-region densities. Much more data from many

Fig. 4. Vary-Chap interpolation (dotted line) between the RPI plasmasphere model (Huang et al., 2004) and the IRI peak at a magnetic latitude (Mlat) of
85°N on Jun 25, 2003. Also shown is the a-Chapman proﬁle with constant scale height that provides a good ﬁt near the peak but is much too small higher
up. The right panel shows the derived scale height function with the transition height hT = 1002 km, a scale height HT = 250 km at hT, and a shape factor
b = 1.4. (Reinisch et al., 2007).

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D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

Fig. 5. IMAZ model proﬁles for auroral E-region density for diﬀerent levels of riometer absorption Lv (McKinnel and Friedrich, 2006).

global positions are required to build a reliable global Dregion model for all levels of solar activity for use in IRI.
First E and D region proﬁles were recently obtained with
the Jicamarca incoherent scatter radar and were comparedwith the three IRI options (Chau and Woodman, 2006).
Good agreement was found with the FIRI and Danilov
models. It was noted that densities in the E-region bottomside are smaller than predicted by the standard IRI modeland that the FIRI model provides a better representation
also of this region. The FIRI model formalism, however,is such that it cannot be normalized to an E-peak and thus
it is diﬃcult to continuously merge the FIRI model withthe rest of the IRI proﬁle. Beginning with IRI-2007 FIRI
will therefore be provided as a standalone electron density
model for the lower ionosphere (D- and E- region).

the Akebono data to better understand plasmaspheric processes (see Kutiev et al. (2002) for references).

4. Plasma temperatures
Several new mission-speciﬁc plasma temperature models
have been put forward at IRI meetings. These include theHinotori Te model at 600 km altitude and high solar activity of Oyama et al. (2004), the SROSS-C2 Te model at
500 km and low solar activity of Bhuyan and Chamua(2006), the ROCSAT-1 Ti model at 600 km and high solar
activity of Su and Yeh (2006) (all three are low-inclination
satellites covering the low-latitude ionosphere), the Akebono Te plasmaspheric model of Kutiev et al. (2002), andthe Millstone Hill Te, Ti radar models of Holt et al.
(2002). The plasmaspheric model is now scheduled forinclusion in IRI-2007 as the ﬁrst step towards extending
IRI to plasmaspheric altitudes. The Akebono model was
selected, because it is based on more than 13 years of measurements by the Thermal Electron energy Distribution(TED) instrument, far exceeding the database of otherplasmaspheric models and because a general good agreement has been reported in comparisons with other data
sources. Theoretical models also have relied heavily on

Fig. 6. Electron temperature from satellite database versus dip latitude forhigh (red) and low (blue) solar activity and for summer solstice (upper
panel) and equinox (lower panel); the special invdip latitude is used here
which is close to the dip latitude at middle and low latitudes and close toinvariant latitude at higher latitudes; the solar index is the solar radio ﬂux
at 10.7 cm wavelength. (For interpretation of the references to color in thisﬁgure legend, the reader is referred to the web version of this paper.)D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

605

Fig. 7. Daytime and nighttime latitudinal proﬁles of O+, H+, and He+ densities during equinox as measured by ISS-b () at 1000 km (top panel) and as
predicted by the new IRI model (solid line) and by the earlier IRI standard (dashed line) and Danilov-Yaichnikov option (dash-dot line). The bottom
panel shows a similar comparison for ISIS-2 at 1400 km also at equinox.

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diﬀerences near the equator are not clear yet and need to
be investigated with theoretical models.
5. Ion composition

Fig. 8. Diurnal variation of the Upper Ion Transition Height as given by
several models illustrating the large uncertainties in modelling thisimportant parameter: (a) IRI standard model (see pp. 71–76 in Bilitza,
1990), (b) Danilov and Yaichnikov (1985), (c) Miyazaki (1979) model
based on Taiyo in-situ measurements, (d) Kutiev et al. (1984) based on insitu measurements from OGO-6, IC-2, Alouette-1, and ISS-b, (e)Intercosmos 13 model (Kutiev et al., 1994), and (f) the most recent modelof Truhlik et al. (2004) (TTS) that includes variations with solar activity.

The IRI plasma temperature models currently do not
explicitly include variations with solar activity. There is
an implicit dependence because of the constraint
Tn 6 Ti 6 Te where Tn is the CIRA (1988) neutral temperature which varies with solar activity. The ionosphericelectron temperature indeed does show variation withsolar activity but these variations are generally small
compared to the signiﬁcant increase observed for theelectron density. This is easy to understand since boththe heat gain and heat loss of the electron gas dependon electron density and thus both increase with increasing solar activity compensating each other and producing
only a small net change in electron temperature. Incoherent scatter studies have shown that this change can bepositive or negative depending on the season, altitude,
and time of day. A systematic and global descriptionof these dependencies for IRI requires a large data baseand has to rely on satellite data since the ground-based
Te instrument, the incoherent scatter radar, exists only
at a few locations worldwide. Such a database of satellite
in situ measurements was recently assembled and ﬁrst
results were presented at the 2005 IRI workshop by Bilitza et al. (2007). In Fig. 6, Te values from this databaseare plotted versus magnetic latitude for diﬀerent levels of
solar activity. At mid-latitudes Te increases with solar
activity in summer and decreases in winter and equinox.
This is a result of the relative change of the heating andcooling terms over the solar cycle and is well reproducedby theoretical models. At low and equatorial latitudes
the data show a small increase for solstice and a muchlarger increase for equinox. The causes of these seasonal

The ion composition model has traditionally been theweakest part of the IRI model because of the scarcity ofwell-calibrated global ion density measurements. The present IRI model is largely based on a compilation of Russianhigh-altitude rocket measurements of Danilov andYaichnikov (1985) and Danilov and Smirnova (1995),
and on a limited amount of incoherent scatter radar data.
Working with the satellite in situ measurements from AEC, -E, and Intercosmos 24, Triskova et al. (2003) havedeveloped a new model for the ion composition in the topside ionosphere. Comparisons with other satellite data
(e.g., ISS-b and ISIS-2 in Fig. 7) show that this new model
performs much better than the old IRI model and it wastherefore introduced as the new IRI ion composition
model.
It is important to note that the IRI describes the ioncomposition and not the absolute ion densities. The ioncomposition is the percentage of the density of a speciﬁc
ion versus the total ion density; charge neutrality means
the total ion density is equal to the electron density. To
get absolute ion densities one has to multiply the ion composition percentages with the electron density. Thisapproach has the advantage that charge neutrality is easy
to enforce and the disadvantage that the accuracy of theabsolute IRI ion densities depends not only on the accuracy of the ion composition model but also on the electron
density model (see Section 2).
The IRI team is also investigating modeling approaches
that make use of the upper and lower transition heights
since these are the most characteristic parameters of theion composition proﬁle (Bilitza and Kutiev, 1990). The
lower height marks the point of 50% O+ and 50% molecular ions, whereas the upper height is determined by 50% O+
and 50% light ions (H+, He+). A number of recent modeling studies (e.g., Marinov et al., 2004; Webb et al., 2006)
have used newly available Alouette and ISIS topside sounder data (Huang et al., 2002; Bilitza et al., 2003, 2004) todeduce the global and diurnal variations patterns of theupper transition height and to develop models for thisimportant parameter. However, large discrepancies remain
between the diﬀerent models as shown in Fig. 8 largely due
to the diﬀerent databases used.
6. Other changes (Spread F and IGRF 10)
The IRI-2007 version will for the ﬁrst time include amodel for the occurrence probability of spread F. This will
be a regional model for the Brazilian longitude sector basedon the work of Abdu et al. (2003) using ionosonde observations in Brazil. The model describes the variations of
the probability with latitude, local time, day of year, andsolar activity. Fig. 9 shows that the spread F model repro-

D. Bilitza, B.W. Reinisch / Advances in Space Research 42 (2008) 599–609

607

Fig. 9. Probability of spread F as a function of Local Time (x-axis: LT = 25 is same as LT = 1 AM) and month at the Brazilian ionosonde stations
Fortaleza (upper row) and Cachoeira Paulista (lower row) and an intermediate latitude (middle row) for diﬀerent levels of solar activity (below
F10.7 = 100 – left column, above F10.7 = 180 – right column, and in-between – middle column (Abdu et al., 2003). Illustrating the fact that spread F isprimarily a winter night phenomenon and probabilities increase with solar activity.

duces the well-known fact that this phenomenon is primarily observed near the magnetic equator at nighttime during
September through April. Eﬀorts are underway to model
the global occurrence statistics with the help of topsidesounder data and by combining existing models for theBrazilian and Indian longitude sectors.
The magnetic ﬁeld model in IRI was updated to thelatest generation (10) of the International Geomagnetic

Reference Field (IGRF) (see homepage at http://
www.ngdc.noaa.gov/IAGA/vmod/). The IGRF model isused to compute the magnetic ﬁeld coordinates neededby the IRI model including dipole coordinates as wellas magnetic latitude, dip latitude, modiﬁed dip latitude,
and invariant latitude. For all coordinates the long-term(secular) change of the magnetic ﬁeld is taken into
account.

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7. Summary
This paper presents the latest version of the widely used
International Reference Ionosphere (IRI) model, describing the various improvements and additions that led to thislatest version. Several ongoing IRI activities are brieﬂy
described. All are directed towards future improvementsof the IRI model, most importantly a new approach tomodelling the topside and plasmaspheric electron density
and work towards the inclusion of solar activity variations
for plasmas temperatures. The IRI is a truly international
project with contributions from scientists from all partsof the globe. This wide range of activities has made the
IRI the international standard for ionospheric parameters
and a registration process with the International Standardization Organization (ISO) is currently underway (ISOwebsite).
The IRI Fortran software can be obtained from thesolar-terrestrial models archive of NASA’s Space Physics Data Facility and National Space Science Data
Center at http://nssdcftp/models/ionospheric/iri/iri2007/.
A web interface for computing and plotting IRI values
is accessible from the IRI homepage at http://
IRI.gsfc.nasa.gov.
Acknowledgements
The data and services of NASA’s Space Physics Data
Facility (SPDF) and National Space Science Data Center(NSSDC) have contributed greatly to the success of the
IRI eﬀort. The work reported here was support by NSF
Grant 0417666 and NASA Grant 05-LWS05-161.
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