Assimilative Mapping Of Ionospheric Electrodynamics Research Articles

Comparing the cross polar cap potentials measured by SuperDARN and AMIE during saturation intervals

Assimilative Mapping of Ionospheric Electrodynamics (AMIE) and Super Dual Auroral Radar Network (SuperDARN) are two commonly used techniques to measure cross polar cap potential (ΦPC). In this study, I compare ΦPC inferred from AMIE with that inferred from SuperDARN during saturation intervals. Measurements from Defense Meteorological Satellite Program (DMSP) and polar cap (PC) index are also used to help estimate true ΦPC. Seven saturation events in 2000 were selected. For each event, I ran the AMIE software driven by magnetometer data only, by magnetometer data and SuperDARN data, and by SuperDARN data only. Then I compared ΦPC obtained from AMIE with that from SuperDARN. I found that: (1) ΦPC inferred from SuperDARN is significantly lower than that inferred from other techniques including AMIE when ΦPC is large (e.g., greater than 150 kV); (2) ΦPC inferred from AMIE with SuperDARN input is much higher than ΦPC inferred from SuperDARN; (3) ΦPC inferred from AMIE with magnetometer input tends to give the same results as that inferred from AMIE with magnetometer and SuperDARN input; (4) ΦPC inferred from AMIE with magnetometer input is, in general, in agreement with ΦPCinferred from AMIE with SuperDARN input. It is suggested that reason for the low values of SuperDARN‐derived ΦPC during saturation intervals is that the SuperDARN algorithm to compute ΦPC from measurements is not applicable to such intervals.

Intense dayside Joule heating during the 5 April 2010 geomagnetic storm recovery phase observed by AMIE and AMPERE

When the interplanetary magnetic field (IMF) is northward, dawnward, or duskward, magnetic merging between the IMF and the geomagnetic field occurs near the cusp of the magnetosphere. While these periods are usually considered “quiet,” they can lead to intense, but highly localized, energy deposition into the dayside ionosphere. We identify such an occurrence during a series of two geomagnetic storms on 5 April 2010. Using data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) for the first time as an input to the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) algorithm, we show that during the recovery phase of the first storm there is intense ionospheric Joule heating in the dayside polar regions. This is associated with an intense field‐aligned current pair near the noon meridian that is associated with northward IMF and a strong IMF By component. AMIE outputs are used to drive the thermosphere‐ionosphere‐mesosphere electrodynamics general circulation model to demonstrate that the intense levels of Joule heating can lead to anomalous thermospheric density enhancements and traveling disturbances.

Statistical study of the effect of ULF fluctuations in the IMF on the cross polar cap potential drop for northward IMF

[1] Recent studies showed that, regardless of the orientation of the Interplanetary Magnetic Field (IMF), ULF wave activity in the solar wind can substantially enhance the convection in the high latitude ionosphere, suggesting that ULF fluctuations may also be an important contributor to the coupling of the solar wind to the magnetosphere‐ionosphere system. We conduct a statistical study to understand the effect of ULF power in the IMF on the cross polar cap potential, primarily focusing on northward IMF. We have analyzed the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) calculations of the polar cap potential, a IMF ULF index that is defined as the logarithm of Pc5 ULF power in IMF, and solar wind velocity and dynamic pressure for 249 days in 2003. We find that, separated from the effects of solar wind speed and dynamic pressure, the average cross polar cap potentials show a roughly linear dependence on the ULF index, with a partial correlation coefficient of 0.19. Highly structured convection flow patterns with a number of localized vortices are often observed under fluctuating northward IMF. For such a convection configuration, it is hard to estimate properly the cross polar cap potential drop, as the enhanced flows around the vortices that may be associated with IMF fluctuations do not necessarily yield a large potential drop. Thus, despite the relatively small correlation coefficient, the linear trend we found gives support to the significant role of IMF ULF fluctuations on the coupling of the solar wind to the magnetosphere‐ionosphere system.

Comparison of Joule heating associated with high-speed solar wind between different models and observations

To gain an improved quantitative understanding of the solar wind/magnetosphere/ionosphere coupling processes, the capabilities of different models and observations to represent the variations of ionospheric forcing associated with high-speed solar wind streams are compared for year 2005. We investigate the high-latitude forcing from the measurements of DMSP satellite, empirical model Weimer05 and Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure, with ground magnetometer data only (AMIE 1) or with both ground magnetometer and DMSP convection data (AMIE 2). The yearly averages of the northern hemisphere integrated Joule heating (IJH) calculated from AMIE 1 and 2 are about 41% and 85% larger than that from Weimer05, respectively. A consistent 9-day periodicity is shown in both the cross polar cap potential and IJH, which corresponds to the 9-day oscillation in the high-speed solar wind streams. A band-pass filter centered at 9 day is used to examine the sensitivity of the IJH calculated from different sources to the solar wind condition. The comparison shows that the sensitivity of IJH from AMIE 1 and 2 are about 2.2 and 2.5 times larger than that from Weimer05, respectively.

Deducing storm timeFregion ionospheric dynamics from 3-D time-varying imaging

[1] The inversion algorithm for Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE) has been created to gain insight into ionospheric dynamics, particularly when direct measurement is unavailable. We extend the capabilities of EMPIRE here, in order to demonstrate its effectiveness on densities obtained from real data. We apply this method to real Ionospheric Data-Assimilation 4-Dimensional (IDA4D) data from storm time measurements, focusing on the midlatitude F2 layer. EMPIRE is used to estimate midlatitude field-aligned and field-perpendicular drifts. The estimated upward drifts from EMPIRE are validated against measurements obtained from the Millstone Hill incoherent scatter radar zenith antenna. The horizontal × drifts are compared to the assimilative mapping of ionospheric electrodynamics (AMIE) model, which estimates drifts from data sources independent of those used in IDA4D. Results show that the direction and magnitude of the × drifts (and therefore the electric fields) may be deduced from imaging based primarily on total electron content data, although altitude variation is not significantly discernible. We also indicate that the initial uplift of the storm-enhanced density may have been more strongly influenced by field-aligned contributions of neutral winds and diffusion than the electric fields.

Energy input into the upper atmosphere associated with high-speed solar wind streams in 2005

A 9 day periodic oscillation in solar wind properties, geomagnetic activity, andupper atmosphere has been reported for the year 2005. To understand the energytransfer processes from the high‐speed solar wind streams into the upper atmosphere, weexamined Joule heating and hemispheric power (HP) from the assimilative mapping ofionospheric electrodynamics (AMIE) outputs for 2005. There are clear 9 day periodvariations in all AMIE outputs, and the 9 day periodic oscillation in the global integratedJoule heating is presented for the first time. The band‐pass filter centered at 9 dayperiod shows that both Joule heating and HP variations are correlated very well to theneutral density variation. It indicates that the energy transfer process into the upperatmosphere associated with high‐speed solar wind streams is a combination of Jouleheating and particle precipitation, while Joule heating plays a dominant role. Thesensitivities of Joule heating and HP to the solar wind speed are close to 0.40 and0.15 GW/(km/s), respectively.

Saturation of transpolar potential for large Y component interplanetary magnetic field

This study examines the response of the transpolar potential to a large Y component interplanetary magnetic field (IMF By). The transpolar potential responds nonlinearly and saturates for large IMF By in the Lyon‐Fedder‐Mobarry (LFM) global MHD simulation, just as it does for large southward IMF (−Bz). Data from Defense Meteorological Satellite Program (DMSP) satellites and Assimilative Mapping of Ionospheric Electrodynamics (AMIE) results confirm the saturation of the transpolar potential during large IMF By. The magnitude of the saturated transpolar potential is significantly smaller for large IMF By than for large negative IMF Bz. This indicates that transpolar potential saturation does not depend on the strength of the Region 1 current. However, the magnitude of the IMF at which the transpolar potential becomes nonlinear and begins to exhibit saturation behavior is the same for large By as it is for large Bz. Furthermore, when the IMF (By or Bz) reaches the value that produces saturation, the magnetosheath becomes magnetically dominated, with β < 1. This suggests that the saturation of the transpolar potential is related to a change in the force balance in the magnetosheath from a plasma‐pressure‐dominated magnetosheath to a magnetically‐dominated magnetosheath.

Thermospheric density enhancements in the dayside cusp region during strong BY conditions

Tri‐axial accelerometer data from the Challenging Minisatellite Payload (CHAMP) satellite have revealed the thermospheric density and its variability in unprecedented detail. The data often contain regions of high density located in the cusp sector at high latitudes. In this paper we provide the first detailed explanation of a high latitude density enhancement observed by CHAMP, focusing on the August 24, 2005 interval. The Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (TIMEGCM) was driven by high‐fidelity high‐latitude inputs specified by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) algorithm, and reproduced the main features of the density enhancements. The TIMEGCM and AMIE provide a global framework for interpretation of the CHAMP densities. Our simulations reveal that the observed density enhancement in the dayside cusp region resulted from unexpectedly large amounts of energy entering the Ionosphere‐Thermosphere system at cusp latitudes during an interval of strong (+20 nT) BY.

On the causes of plasmaspheric rotation variability: IMAGE EUV observations

IMAGE EUV observations demonstrate that the plasmasphere usually does not corotate as assumed in simple convection models, even at low L shells. We carry out a statistical survey of plasmaspheric rotation rates over several months of IMAGE EUV data in 2001, using two different measurement techniques. We test the prevailing hypothesis, that subcorotation is due to enhanced auroral zone Joule heating driving equatorward thermospheric winds, by testing for correlation of rotation rates with several geomagnetic indices. Azimuthal features such as “notches” are tracked in local time over a single pass of the IMAGE satellite, both visually and using an automated cross‐correlation routine. Each technique provides an estimate of the plasmasphere's rotation rate. We find a weak correlation between rotation rate and Dst, Kp, AE, the midnight boundary index (MBI), and Joule heating estimates from assimilative mapping of ionospheric electrodynamics (AMIE) at L = 2.5, but not at L = 3.5. In general, lower rotation rates correspond to higher auroral and geomagnetic activity. We also make the first direct observation of plasmaspheric superrotation. The plasmaspheric rotation rate is found to be highly variable on multiday timescales, but the typical state of the plasmasphere is subcorotation, with inferred mean values ranging from 88% to 95% of corotation, depending on L shell. In addition, a statistical analysis shows that rotation rates near dusk are generally lower than those at dawn, suggesting that local time and magnetospheric convection contribute to the variation in rotation rate as well. We conclude that the cause of variability in plasmaspheric rotation rate is a combination of storm phase, local‐time‐dependent convection, and westward ionospheric drift.

Reversed ionospheric convections during the November 2004 storm: Impact on the upper atmosphere

Using the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure, a particular period (2000–2350 UT on 9 November) in the November 2004 storm is studied. During this time interval, IMF Bz was strongly northward along with a high solar wind dynamic pressure, favorable conditions to form reversed convection in the polar region. Indeed, the AMIE outputs show strong reversed convection cells in both hemispheres for a long period (>1 h), which have rarely been observed. The impact on the thermospheric neutral wind has been investigated using the AMIE outputs as the electrodynamic inputs of the National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model. After the ionospheric convection reversed, the neutral wind distribution at 400 km altitude changed correspondingly, and the difference wind patterns reversed in the polar cap region. By comparing the temporal variations of the difference ion convection and the difference neutral wind, it is found that horizontal neutral winds respond to the reversed convection with some time delay. The neutral wind response time (e‐folding time) clearly has an altitudinal dependence varying from 45 min at 400 km altitude to almost 1.5 h at 200 km. The vertical component vorticity has a similar magnitude and distribution to previous studies in the northward Bz condition and changes the sign when the convection pattern is reversed. Comparison between the CHAMP observed cross‐track wind and the simulated neutral wind exhibits a general agreement, and the temporal variations of CHAMP cross‐track wind indicate a strong effect of the ion drag force on neutral winds.

Electric field variability and model uncertainty: A classification of source terms in estimating the squared electric field from an electric field model

Joule heating by high‐latitude electric fields is thought to be underestimated by electric field models, and it has been conjectured that the source of the underestimation is “electric field variability,” although the interpretation of this term is not necessarily straightforward. We perform a classification of source terms in estimating the squared magnitude of electric field from an electric field model, and find that the phenomenon summarily referred to as electric field variability canonically decomposes into two distinct components: small‐scale electric field variability, and resolved‐scale model uncertainty. The latter contribution is a statistical estimation uncertainty, and not related to physical small‐scale fluctuations. We argue that the two sources should be characterized separately. An illustration is given in a comparison of the Joule heating measured by the Sondrestrom incoherent scatter radar during a 40‐h period containing a storm, with the Joule heating modeled by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure, after removing the Sondrestrom data from the AMIE assimilation. A quantitative assessment of the relative importance of the two sources is drawn from a recent satellite study.

Comparison of AMIE‐modeled and Sondrestrom‐measured Joule heating: A study in model resolution and electric field–conductivity correlation

Joule heating by high‐latitude ionospheric electric fields is thought to be underestimated by models, and it has been conjectured that the source of the underestimation is “electric field variability,” which is often defined as electric field structure below the resolution of the model. We investigate this and related issues by (1) comparing the Joule heating measured by the Sondrestrom incoherent scatter radar during a 40 h period containing a storm with that modeled by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure and (2) employing an magnetosphere‐ionosphere (M‐I) coupling model to analyze the theoretical dependence of Joule heating estimates on the spatial resolution of the inputs. We find that as compared with Sondrestrom measurements, a much larger contribution from correlation between conductance and squared electric field (positive for AMIE and negative for Sondrestrom) partially compensates for a much smaller mean‐squared electric field, such that the overall average Joule heating rate modeled by AMIE is 29% less than measured by Sondrestrom. The underestimation of the mean‐squared electric field was not associated with small‐temporal‐scale variability. Surprisingly, the M‐I coupling model finds that coarse spatial resolution causes overestimation of the Joule heating rate, owing to the finding that the subresolution‐scale spatial fluctuations in conductance and squared electric field are anticorrelated. When comparing estimates of the total Joule heating over a period of time, the increased Joule heating arises as a larger contribution from temporal correlation between conductance and squared electric field, which overcompensates for the reduced mean‐squared electric field. Therefore, the difference in the Sondrestrom and AMIE correlation contributions might be explained by a difference in spatial resolution.

Magnetohydrodynamic simulations of transient transpolar potential responses to solar wind density changes

Magnetohydrodynamic (MHD) simulations are used to examine the response of the transpolar potential (ΦTP) to changes in the solar wind density during periods of constant solar wind electric field. For increases (decreases) in the solar wind density ΦTP responds immediately by increasing (decreasing) from the steady state values. In both cases the response of ΦTP is transient, decaying to near initial steady state values even when the density change persists. The magnitude of the ΦTP response is proportional to both the rate of erosion of the dayside magnetopause and the ionospheric Pedersen conductance. In our MHD simulations ΦTP is driven entirely by the dayside merging rate and is insensitive to changes in the nightside reconnection rate. The observed relationship between the modeled dayside merging rate and ΦTP is well characterized by an L‐R circuit equation derived from integrating Faraday's Law around the Region 1 current loop. The inductive time constant for variations in the transpolar potential was found to be 6.5 (13) minutes for simulations using ionospheric Pedersen conductances of 6 (12) mhos. This corresponds in both cases to a magnetosphere‐ionosphere inductance of 65 Henries. Observations of the transpolar potential derived using the assimilative mapping of ionospheric electrodynamics (AMIE) model are presented and shown to be consistent with the simulation results.

Tracking of polar cap ionospheric patches using data assimilation

Ionospheric F‐region patches are 2–10 larger than background electron densities in the polar ionosphere. The EISCAT Svalbard incoherent radar (ESR) observed a sequence of patches between 2000–2200 UT on 12 December 2001. In this paper the source of these structures is investigated using several other data sets, together with a convection‐driven trajectory analysis. The data are assimilated into Ionospheric Data Assimilation Three Dimensional (IDA3D). The background model used is the National Center for Atmospheric Research‐Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (NCAR TIMEGCM). The trajectory analysis is based on maps of ionospheric convection obtained from the Assimilative Mapping of Ionospheric Electrodynamics (AMIE). In addition to patches, a tongue of ionization (TOI) is investigated. It is shown that patches formed part of the TOI. It is tempting to conclude the TOI and the patches originate at midlatitudes. However, the IDA3D and trajectory analysis suggest that they were transported toward noon from the morning and afternoon sectors near 62° geographic latitude. Thus for this case the TOI and patches did not originate at midlatitudes. This work represents advances in the field of patch research. A new capability to perform an analysis of patch origin and fate, using three‐dimensional (3‐D) ionospheric assimilation and 2‐D trajectory analysis codes, is demonstrated for a sequence of patches observed 12 December 2001. The current resolution of the technique is not able to identify detailed patch formation mechanisms. However, by it can track the plasma back in time to locations and times where patch formation mechanisms operate.

Ground observation and AMIE‐TIEGCM modeling of a storm‐time traveling ionospheric disturbance

This paper reports the first comparison between comprehensive observations of equatorward moving traveling ionospheric disturbance at midlatitudes and thermospheric general circulation model with high‐latitude energy input based on data assimilation. A prominent traveling ionospheric disturbance (TID) was observed during the major magnetic storm of 31 March 2001. The TID propagated from north to south over Japan with phase speeds of 370–640 m/s. The assimilative mapping of ionospheric electrodynamics (AMIE) technique was used as input to the thermosphere‐ionosphere‐electrodynamics general circulation model (TIEGCM) to investigate generation and propagation of the observed TID. In the model, two Joule heating enhancements in the high‐latitude dayside sector produced two distinct traveling atmospheric waves (TADs), which propagated to Japan in the midnight sector as enhancements in thermospheric temperature and southward wind speed. The phase speed of the TADs was much faster (∼1100 m/s) in the model, probably due to the overestimation of Joule heating in the model. The second TAD corresponds to the observed prominent TID, while signatures of the first TAD were also seen in the observed ionosonde data. The observed TID was characterized by a decrease in southward wind speed, causing a significant F‐layer height decrease and a temporal enhancement of F‐layer peak density. These characteristics were reproduced by the model as a rarefaction of the second TAD. The temporal enhancement of F‐layer peak density was because of the vertical shear of meridional wind. The absolute value of F‐layer electron density in the model was several factors smaller than that observed, probably because of the underestimation of the supply of O+ ions from the plasmasphere.

Magnetospheric energy budget during huge geomagnetic activity using Cluster and ground‐based data

The Cluster spacecraft crossed the magnetopause at the duskward flank of the tail while the European Incoherent Scatter (EISCAT) radars and magnetometers observed the ionosphere during a sequence of intense substorm‐like geomagnetic activity in October 2003. We attempt to estimate the local and global energy flow from the magnetosheath into the magnetotail and the ionosphere under these extreme conditions. We make for the first time direct observational estimates of the local solar wind power input using Cluster measurements. The global power input based on Cluster observations was found to be between 17 and 40 TW at the onset of the substorm intensification. However, spacecraft observations and global modelling of the magnetotail suggest that it is most probably closer to 17 TW. This is more than two times lower than the predicted ε parameter value (37 TW). Energy deposition in the ionosphere has been estimated locally with EISCAT and globally with the assimilated mapping of ionospheric electrodynamics (AMIE) technique. The amount of the global solar wind power input (17 TW) that is dissipated via Joule heating in the ionosphere is found to be 30%. The corresponding ratio based on empirical estimates is only 3%. However, empirical proxies seem to underestimate the magnitude of the Joule heating rate as compared to AMIE estimates (∼ a factor 4) and the ε parameter is more than twice as large as the Cluster estimate. In summary, the observational estimates provide a good balance between the energy input to the magnetosphere and deposition in the ionosphere. Empirical proxies seem to suffer from overestimations (ε parameter) and underestimations (Joule heating proxies) when pushed to the extreme circumstances during the early main phase of this storm period.

Statistical analysis of ionospheric potential patterns for isolated substorms and sawtooth events

Abstract. We present here results which contrast isolated substorms with individual sawtooth events. Sawtooth events are defined as quasi-periodic, large-amplitude oscillations in the energetic particle flux with a periodicity of 2–4 h observed at the geosynchronous orbit. Sawtooth events have several similarities to isolated substorms leading therefore, to different opinions about whether sawtooth events are just an intense periodic form of substorms or if they deserve a category of their own. To help resolve this, we examine the ionospheric potential patterns in the northern polar region for isolated substorms and sawtooth events using the assimilative mapping of ionospheric electrodynamics (AMIE) technique. First we show a statistical analysis of isolated substorm potential patterns. In order to examine the seasonal variation, isolated substorms are identified by mid-latitude positive bay in the north-south geomagnetic perturbation in each season, respectively. Superposed epoch analysis (SEA) is applied to obtain the typical polar potential patterns for each season. By examining the time evolution of the potential patterns and cross polar cap potential (CPCP) for isolated substorms during each season, we find only subtle seasonal variations in the results obtained using the AMIE analysis. This provides a basis for comparison with sawtooth events in the next step. From the averaged potential patterns of 213 isolated substorms and those of 184 individual sawtooth events, we find the sawtooth events show signatures similar to subtorms: the DP 1 potential pattern develops and dominates the polar region after the onset. However, the DP 1 potential cell of sawtooth events encompasses a larger area than that of isolated substorms. Moreover, the CPCP of sawtooth is stronger than that of isolated substorms. It is also shown that the sawtooth events displays greater variability between individual events than isolated substorms. We conclude that in terms of ionospheric electrodynamics, the sawtoothe events have features that are similar to those of isolates substorms, though larger in spatial extent and in magnitude.

An analog forecast model for the high‐latitude ionospheric potential based on assimilative mapping of ionospheric electrodynamics archives

We review an emerging technique for ionospheric forecast whereby empirical models and data assimilation techniques are combined and show that the blended technique produces a diminished result compared to using the empirical models alone. We then present a technique for the nowcast/forecast of ionospheric potential patterns using an analog forecast technique. This is a new type of model for describing ionospheric potential patterns based on matching solar wind conditions and available ground observations to previously archived assimilative mapping of ionospheric electrodynamics (AMIE) runs. The model combines the best features of a data assimilation–based model with the availability and forecast potential of an empirically based model. We define a set of comparison metrics, show quantitatively how this model compares with the Weimer (1996) model and detail the performance for a May 1998 event.

Comparison of satellite ion drift velocities with AMIE deduced convection patterns

The Assimilative Mapping of Ionospheric Electrodynamics (AMIE) model has been used in a wide range of studies pertaining to the magnetosphere, ionosphere and thermosphere. In these studies historical data from several different data sources (electric fields from radars and satellites, electric currents from satellites, magnetic perturbations from satellites and ground-based magnetometers) have been assimilated. In its real-time mode (rt-AMIE), only data from an array of ground-based magnetometers are assimilated and convection patterns are produced in 1-min increments. However, the reliability of these real-time patterns for applications involving ionosphere–thermosphere specifications and forecasts has never been systematically tested. To address this issue, a comparison of a 1-year dataset of DMSP F13 cross-track ion drift velocities with AMIE convection patterns, based on data from 80 ground-based magnetometers, has been conducted. First, for each high-latitude DMSP velocity observation, the corresponding AMIE value was calculated. Then, the measured and calculated cross-track ion drift velocities along the high-latitude pass were compared and criteria were established to determine whether or not the AMIE patterns adequately fit the measurements. The comparisons were done for a full year (1998) of satellite crossings of the northern polar region (4300 consecutive satellite crossings). The comparisons indicate that the AMIE patterns adequately represented the DMSP observations about 32% of the time, which is a significant improvement over statistical convection patterns (6% of the time). This is particularly impressive in view of the fact that only a limited number of ground-based magnetometers were included in the AMIE patterns used in this study.

A statistical analysis of the assimilative mapping of ionospheric electrodynamics auroral specification

The assimilative mapping of ionospheric electrodynamics (AMIE) technique utilizes a wide range of electrodynamics measurements to determine high‐latitude maps of the electric potential, electron particle precipitation (average energy and total energy flux), and ionospheric conductance (Hall and Pedersen). AMIE does this by conducting a least squares fit to the difference between the data and a background model. This fit is then added to the background model. This allows for a very stable technique with even minimal amounts of data. The background models are typically statistical models that are driven by the solar wind and interplanetary magnetic field or the hemispheric power index. This study presents results of a statistical validation of the AMIE conductance and particle precipitation calculations and quantifies how using ground magnetometer derived measurements improves upon the result obtained using only a background statistical model. Specifically, we compare AMIE using the Fuller‐Rowell and Evans (1987) model of particle precipitation and ionospheric conductances to DMSP particle precipitation measurements during the period from May to November 1998. The conductances are derived from the particle precipitation using the Robinson et al. (1987) formulation. The Fuller‐Rowell and Evans (1987) results show low (39–21% with increasing AE) energy flux integrals with respect to DMSP auroral passes and differences in mean electron energies. The AMIE runs, in which ground‐based magnetometers were used to modify the particle precipitation using the formulation by Ahn et al. (1983) and Ahn et al. (1998), show significant improvement in correlation to the observational data. We show that it more accurately predicts the particle precipitation than when using only the background model, especially in the 1800–0300 MLT nightside sectors where solar conductance is not significant. In addition, the AMIE results show a clear increase in accuracy with increasing number of magnetometers in a sector.