Prior to the GPS era of global diagnostics for the ionosphere's total electron content (TEC), a remarkable degree of insight into TEC storm effects was achieved using low Earth orbit and geostationary satellite radio beacon observations. Long-term studies at individual stations, networks of stations, and campaign-mode case studies revealed the complex seasonal, local time, and latitude and longitude effects upon TEC during geomagnetic storms. Theory and simulations were used to successfully explain the roles of electrodynamical mechanisms, Joule heating, thermospheric dynamics, and neutral composition changes within the general context of solar wind–magnetosphere–plasmasphere–ionosphere/thermosphere coupling during storms. This paper gives a brief review of the status of past work, presents a new summary of TEC average patterns from pre-GPS data sets, and suggests avenues of research needed to advance the GPS-era yield from TEC storm studies.
 The use of total electron content (TEC) data derived from the Global Positioning System (GPS) has revolutionized ionospheric physics in ways similar to the advent of ionosondes in the 1930s and incoherent scatter radars in the 1960s. Global and regional networks of GPS receivers are capable of providing TEC in near real time over large geographic areas, with the exception of large ocean areas where ground-based GPS receivers cannot easily be deployed. There is a growing impact of GPS-based research upon three foci of current-day ionospheric science (understanding ionospheric structuring, creating forecasting capabilities, and data assimilative modeling). From an application perspective, TEC and its structuring have profound effects upon radio communications and navigation systems, requiring the development of both nowcasting and forecasting techniques.
 Our goal here is to provide a brief summary of the TEC storm phenomenon. This is possible because of the significant accomplishments achieved prior to the GPS era, both in defining TEC morphology patterns and in discovering all of the physical drivers of F region storm patterns, as demonstrated by modeling. That era ended in the early 1980s, and a new generation of TEC experts using GPS has emerged in recent years. Thus, in utilizing the remarkable GPS capabilities now at hand, attention should be given to the areas of actual need and not to using wonderfully new diagnostics simply to rediscover known morphologies and the physics behind them.
2. Historical Context
 The response of the ionosphere to geomagnetic activity, commonly called ionospheric storms, is an old topic in space physics. The field has been enriched by remarkable sets of large-scale studies and review articles, beginning with Sato  and Matsushita , who found it necessary only to describe the ionospheric response as a positive phase (or increase type) followed by a negative phase (or decrease type). While not cast in the terminology of current-day space physics, nor in the graphical representation styles of contemporary space science, a serious reading of Matsushita  reveals virtually all of the known characteristics of F region storms: (1) the short positive phase lasts longer with decreasing latitude, followed by a prolonged negative phase that is stronger with increasing latitude; (2) when the positive phase has a noticeable local time component, its maximum amplitude occurs near 1800 LT at subauroral latitudes, earlier at higher latitudes, and later at lower latitudes; and (3) the influence of season is to have positive storms more pronounced in winter and negative storms in summer.
 The earliest studies of ionospheric storms gave emphasis to the negative phase because it was the statistically dominant component; that is, its duration is much longer than the positive phase. The choices of mechanisms proposed to account for such effects centered on changes in the composition (and therefore chemistry) of the thermosphere, as well as dynamical effects due to electric fields. For the positive phase, electrodynamics was also the suggested cause, and simulations were conducted as far back as the 1950s [Sato, 1957]. Obayashi  proposed overall scenarios that involved enhanced chemistry and plasma transport and specifically how the new TEC observations then becoming available might be related to whistler observations of ionization above the ionosphere (i.e., what today we would call plasmasphere-ionosphere coupling). The only mechanism not really stressed in the early studies was the role of storm time thermospheric winds, though that would happen soon [Jones and Rishbeth, 1971].
Matsushita  showed that there are common elements to all ionospheric storms, and thus the statistical treatment of such perturbations has probably helped us learn more about the basic mechanisms of storms than those that come from case studies. However, it is the case studies that show how mechanisms that operate “on the average” can have extreme magnitudes, and thus theory and simulation work must be able to handle the largest spatial and temporal effects proposed for a given mechanism. The GPS-based studies of storms are still very few in number, and thus broad statistical treatments of TEC storm patterns are not yet possible. During solar cycle 20, however, when TEC was studied using geostationary satellite radio beacons, comprehensive data sets were obtained, and these will be the focus of our study.
 In the most recent comprehensive review of ionospheric storms, Prölss  does not dwell excessively on the negative phase of ionospheric storms since the physics and chemistry of enhanced loss rates were well understood at the time, mostly because of Prölss' own work with the ESRO-4 satellite and ground-based ionosondes. The positive phase, however, was left as a challenge in that several types of enhancements, each with its own mechanisms, were introduced, and a comprehensive synthesis was not achieved. Prölss' review dealt overwhelmingly with the ionosphere's peak electron density (Nmax) derived from ionosonde data; total electron content (TEC) was mentioned only once, and TEC data sets were not shown in any of the paper's 25 figures. In the current era of GPS-dominated observations, TEC is the parameter most often used in ionospheric storm studies. Thus we begin with a brief overview of past TEC measurements and model results of TEC during ionospheric storms and then proceed with a major new study of average patterns. A more comprehensive review of all past TEC storm effects, detailing observational results from a variety of diagnostic systems and summarizing modeling studies for TEC, will be presented by M. Mendillo (Storms in the ionosphere: Total electron content patterns and processes, submitted to Reviews of Geophysics, 2005).
3. Studies at Single Sites
Figure 1 gives an example of TEC behavior during a geomagnetic storm as observed from the Air Force Cambridge Research Laboratories (AFCRL) observatory in Sagamore Hill, Hamilton, Massachusetts. Such observations for a magnetic latitude of 54° (L∼3) show that at a subauroral site, the positive phase is particularly strong during the late afternoon hours on the first day of the storm and that it is followed by a much longer negative phase. The average of 28 storms from Sagamore Hill (Figure 1b) shows these patterns to be consistent features. The cause of a “dusk effect” followed by a “trough effect” was debated rather vigorously throughout the 1970s; excellent historical summaries of the competing theories and interpretations are given by Prölss  and Buonsanto . Realizing that either neutral winds or electrodynamics could provide the uplifting to regions of reduced loss (thereby allowing solar production effects to dominate) to account for the positive phase, the crucial experimental need was to measure either a sudden onset of strong equatorward winds from auroral heating or the prompt appearance of electric fields of magnetospheric origin. The pivotal experiment came at Millstone Hill [Evans, 1973] with observations during the same storm (14 May 1969) shown in Figure 1. Data from the incoherent scatter radar and a local ionosonde are shown in Figure 2. Abrupt increases in the F layer's peak density (Nmax) and height (hmax) occurred simultaneously with an onset of strong westward drifts. Taken together, these offered convincing proof of a rapid penetration of magnetospheric convection electric fields to midlatitudes, causing the observed cross-L (upward and westward) drifts.
 A consequence of strong westward convection is the introduction of postsunset ionospheric plasma into the dusk area. Evans  pointed out that this is equivalent to saying that the plasmapause contraction noted during storms has an ionospheric signature, that is, the sharp termination of the dusk effect as seen in Figures 1 and 2. Figure 3 shows that it is a regular feature at subauroral latitudes from the eastern United States to western Canada. Figures 1, 2, and 3 thus show that the TEC of the subauroral ionosphere is governed by well-known magnetospheric convection patterns spanning the dusk sector (∼1500–2100 LT).
3.2. Simulation Studies of the TEC Positive Phase
 Modeling of the positive phase became a hot topic in the 1970s. Both neutral dynamics [e.g., Jones and Rishbeth, 1971; Davies, 1974] and electrodynamics [e.g., Tanaka and Hirao, 1973; Anderson, 1976] were used as drivers, each with some success. In Figure 4a, the development of midlatitude electron density altitude profiles under the influence of a suddenly imposed eastward electric field are given, leading to topside enhancements causing TEC to be “remarkably increased” [Tanaka and Hirao, 1973]. The confinement of such patterns to the dusk meridian was then investigated by Anderson , specifically examining the consequences of the zonal drifts of magnetospheric origin observed by Evans  in conjunction with the role played by meridional winds. In Figure 4b, the larger magnitude of the dusk effect and its rapid termination clearly occur when storm time winds are augmented by the strong westward plasma drifts.
4. Multisite TEC Studies During Geomagnetic Storms
 Encouraged by the discovery of the dusk effect at their Sagamore Hill TEC observing station, the Air Force Cambridge Research Laboratory mounted an effort to observe TEC from polar cap stations to the tropics. Figure 5 (left) shows this set of stations with their ray path subionospheric points. This network provided fundamental insights into the behavior of TEC during storms, an example of which is given in Figure 5 (right) [Mendillo and Klobuchar, 1975].
 In Figure 6, the TEC data from this storm are presented using a latitude versus local time grid. The important result to flow from this format is to notice that the dusk effect is seen to be a subauroral feature linked to TEC maxima that occur earlier at higher latitudes and later at lower latitudes.
 Thus the pattern shown in Figure 6 can be interpreted as a large-scale positive phase spanning all of North America, with a southeast to northwest alignment, from the Caribbean to polar latitudes. Because of its electrodynamical origin, this pattern is established early in a storm and, as the north-south latitude chain of stations rotates past the noon meridian, the onset of a TEC positive phase is experienced first at high latitudes and then at lower ones.
 A crucial message from Figure 6 was that the TEC storm effects grew in magnitude at lower midlatitudes, and thus emphasis should be placed on sites away from subauroral regions. The study by Lanzerotti et al.  did that and played a pivotal role in linking effects observed at Arecibo to those observed simultaneously at Sagamore Hill. Their results from 12 storms from 1968–1970 appear in Figure 7a. The subauroral site showed the classic pattern of a “dusk effect” positive phase, followed by a sharp transition to “trough effects” at 0300 LT and the negative phase on the following days. At Arecibo, the daytime enhancement was followed by a persistent “ledge” extending into the nighttime hours and no prominent daytime negative phase. Lanzerotti et al. stressed that magnetospheric convection maps to the ionosphere as three-dimensional motions: vertical, zonal, and meridional. A schematic (Figure 7b), very popular at the time, from Chappell  was used by Lanzerotti et al. to relate the “peeling away” or “detachment” of the plasmasphere in the afternoon quadrant to the northward, as well as westward and vertical, motions experienced in the ionosphere.
Lanzerotti et al.  thus showed for the first time the presence of convection effects upon the TEC at lower latitudes. At L ≤ 2, the plasmasphere is rarely, if ever, “peeled away,” and thus convection is entirely within a plasmasphere reduced in size. While the long-lived TEC storm time effect related to the equatorial ionization anomaly (EIA) is its diminution [Basu and Das Gupta, 1968], early in a storm, the EIA is enhanced [Raghavarao and Sivaraman, 1973]. Extremely dramatic increases in the EIA can occur during very large storms [see Rasmussen and Greenspan, 1993, and references therein], and thus the horizontal (meridional) motion of this positive gradient can bring high TEC values to lower midlatitudes, creating the postsunset “ledge.” The true legacy, then, of the Lanzerotti et al.  study was to portray that poleward horizontal transport is of equal importance to vertical motions and that they are unified via the magnetospheric convection–plasmasphere–ionosphere connection.
5. New Statistical Study of TEC During Storms
 Observations during 180 individual storms spanning the years 1967–1976, using the AFCRL chain in Figure 5, constitute the largest TEC storm database prior to the GPS era. These data sets have been reanalyzed following the methods described by Mendillo  to arrive at average local time results for TEC percent departures from monthly mean conditions. Figure 8 gives the overall pattern obtained from auroral to lower midlatitudes over a 4-day storm period. There are several important effects portrayed in Figure 5.
 1. Following the onset of a geomagnetic storm, the TEC is enhanced in the early morning hours of the first day because of the ionization of the thermosphere by low-energy particle precipitation from the magnetosphere. This results in large enhancements of the ionospheric nighttime TEC, as shown at high latitudes at the left of Figure 5.
 2. Following sunrise on day 1, a positive phase in TEC occurs that has two components, a broad daytime enhancement due to storm-induced equatorward winds and a postnoon enhancement that gets larger and later in local time from high to lower latitudes, a consequence of magnetospheric convection. The separation of the wind-induced and convection-induced TEC enhancements is most pronounced near L = 2.
 3. The termination of the day 1 positive phase “dusk effect” is most dramatic at subauroral latitudes where the trough/plasmapause boundary suddenly appears at midlatitudes. The precipitation-induced poleward wall of the trough causes TEC enhancements throughout the nighttime period, with the intrusion of the trough to lower latitudes.
 4. On day 2 of the storm period, a negative phase in TEC occurs from midlatitudes to high latitudes, with the trough most prominent after midnight (i.e., 0300 LT on day 3).
 5. Days 3 and 4 of the storm period show a recovery to daytime prestorm conditions at most latitudes, yet signatures of the nighttime trough and the double maxima near L = 2 persist to the very end of the storm period.
6. Seasonal Effects in TEC Storms
 It has long been appreciated that the F layer undergoes strong seasonal effects. The additional perturbations that occur during geomagnetic storms thus have very different prestorm conditions to modify. Characterization of the seasonal storm effects in TEC is thus a way to assess changes in the “system response functions” of the ionosphere to external stress. The ionospheric storm is thus nature's way of conducting an active experiment, the differential responses to “normal” and “disturbed” input serving to help us understand the highly coupled solar-terrestrial system.
 In the years ahead, when sufficient storm patterns are available from the near-global network of GPS stations, studies of seasonal effects will be possible. During solar cycle 20, however, when TEC was being measured at ∼20 stations worldwide, cases studies were conducted by Schödel et al.  and Essex et al. , allowing simultaneous assessment of winter versus summer hemisphere responses during two large storms (17 June and 17 December 1971). For the far greater number of storms observed by the AFCRL chain near 70°W, statistical patterns can be obtained. Thus, dividing the data sets used to obtain Figure 8 into three seasons, average characteristics for winter, equinox, and summer conditions are given in Figure 9.
 The dominant message to come from Figure 9 is that all of the characteristic signatures of TEC storm effects occur in all seasons. However, their modulation in magnitude is linked to ambient conditions [Fuller-Rowell et al., 1996]. Thus, for winter periods (when the so-called seasonal anomaly results in higher electron densities in the F layer than are found in summer), a geomagnetic storm simply amplifies the ambient production-dominated ionosphere: The TEC positive phase is greater during wintertime geomagnetic storms. Under local summer conditions, when the ambient F layer loss rates are at their annual maxima, a storm further increases loss, and the TEC negative phase is stronger. Thus vertical motions in winter are more effective in making “dusk effect” enhancements when the O/N2 ratio is high; summer storms cause reductions of an already low O/N2 ratio, resulting in severe and prolonged negative phase TEC storms.
7. Summary and Conclusions
 Current research on ionospheric storms and, in particular, the use of GPS to portray disturbance patterns in TEC, rests upon a significant foundation of prior work. Given the large number of case studies and statistical patterns obtained in the pre-GPS era, calling for more observations seems unnecessary if the goal is to characterize at midlatitudes the local time, latitude, and seasonal patterns for typical storms, as well as the extreme perturbations found during very strong storms. However, global coverage to study seasonal effects as a function of the severity of the geomagnetic storm will shed considerable insights on the competing mechanisms for positive and negative phases. Within the polar cap, where past TEC data are sparse because of geometrical limitations imposed by observations of satellites in geostationary orbit, GPS can provide higher elevation angle determinations of TEC and thus of the irregular production and convective motions of TEC perturbations in a region very much undersampled.
 The storm time mechanisms of neutral winds, composition changes, and electric fields that drive storm time F layer perturbations from the auroral zone to the equator have all been identified and are well modeled [e.g., Fuller-Rowell et al., 2000]. However, to our knowledge, there has been only one global circulation model study tailored specifically to TEC storm effects from GPS [Lu et al., 1998], conducted soon after storm documentations started to appear from GPS data sets [Ho et al., 1996, 1998]. Thus there is a considerable need for additional model studies for TEC and especially for models that include the full topside ionosphere and time-dependent plasmaspheric contributions to GPS-derived TEC. Such efforts have started for the thermosphere, as recently demonstrated for the negative phase by Fuller-Rowell et al.  and for solar cycle storm effects by Burns et al. . In areas of latitude structure, the intrusion of the equatorial fountain effect to lower midlatitudes (causing a TEC enhancement) and the equatorward extent of strong O/N2 reductions from auroral heating (causing a TEC depletion) converge near 20° magnetic latitude, and thus attention focused on that region is needed [Pi et al., 2003; Hajj et al., 2004]. Successful modeling of the diurnal behavior of TEC for several days of a storm in the L = 1.1–1.5 regime is, perhaps, the greatest challenge facing large-scale solar-terrestrial effects upon the F layer.
 This work was supported by research grants to Boston University from AFCRL, ONR, and NSF. Discussions with Jules Aarons and Carlos Martinis, and analysis work by Joei Wroten, are gratefully acknowledged.