NOAA Weather Prediction Center

The coupling of the Van Allen radiation belts to the Earth's atmosphere through precipitating particles is an area of intense scientific interest. Currently, there are significant uncertainties surrounding the precipitating characteristics of medium energy electrons (>20 keV), and even more uncertainties for relativistic electrons. In this paper we examine roughly 10 years of measurements of trapped and precipitating electrons available from the Polar Orbiting Environmental Satellites (POES)/Space Environment Monitor (SEM‐2), which has provided long‐term global data in this energy range. We show that the POES SEM‐2 detectors suffer from some contamination issues that complicate the understanding of the measurements, but that the observations provide insight into the precipitation of energetic electrons from the radiation belts, and may be developed into a useful climatology for medium energy electrons. Electron contamination also allows POES/SEM‐2 to provide unintended observations of >700 keV relativistic electrons. Finally, there is an energy‐dependent time delay observed in the POES/SEM‐2 observations, with the relativistic electron enhancement (electrons >800 keV) delayed by approximately one week relative to the >30 keV electron enhancement, probably due to the timescales of the acceleration processes. Observations of trapped relativistic electron fluxes near the geomagnetic equator by GOES show similar delays, indicating a “coherency” to the radiation belts at high and low orbits, and also a strong link between trapped and precipitating particle fluxes. Such large delays should have consequences for the timing of the atmospheric impact of geomagnetic storms.

In this paper we continue the community‐wide rigorous modern space weather model validation efforts carried out within GEM, CEDAR and SHINE programs. In this particular effort, in coordination among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), modelers, and science community, we focus on studying the models' capability to reproduce observed ground magnetic field fluctuations, which are closely related to geomagnetically induced current phenomenon. One of the primary motivations of the work is to support NOAA SWPC in their selection of the next numerical model that will be transitioned into operations. Six geomagnetic events and 12 geomagnetic observatories were selected for validation. While modeled and observed magnetic field time series are available for all 12 stations, the primary metrics analysis is based on six stations that were selected to represent the high‐latitude and mid‐latitude locations. Events‐based analysis and the corresponding contingency tables were built for each event and each station. The elements in the contingency table were then used to calculate Probability of Detection (POD), Probability of False Detection (POFD) and Heidke Skill Score (HSS) for rigorous quantification of the models' performance. In this paper the summary results of the metrics analyses are reported in terms of POD, POFD and HSS. More detailed analyses can be carried out using the event by event contingency tables provided as an online appendix. An online interface built at CCMC and described in the supporting information is also available for more detailed time series analyses.

Abstract Accurate forecasting of the properties of coronal mass ejections (CMEs) as they approach Earth is now recognized as an important strategic objective for both NOAA and NASA. The time of arrival of such events is a key parameter, one that had been anticipated to be relatively straightforward to constrain. In this study, we analyze forecasts submitted to the Community Coordinated Modeling Center at NASA's Goddard Space Flight Center over the last 6 years to answer the following questions: (1) How well do these models forecast the arrival time of CME‐driven shocks? (2) What are the uncertainties associated with these forecasts? (3) Which model(s) perform best? (4) Have the models become more accurate during the past 6 years? We analyze all forecasts made by 32 models from 2013 through mid‐2018, and additionally focus on 28 events, all of which were forecasted by six models. We find that the models are generally able to predict CME‐shock arrival times—in an average sense—to within ±10 hr, but with standard deviations often exceeding 20 hr. The best performers, on the other hand, maintained a mean error (bias) of −1 hr, a mean absolute error of 13 hr, and a precision (standard deviation) of 15 hr. Finally, there is no evidence that the forecasts have become more accurate during this interval. We discuss the intrinsic simplifications of the various models analyzed, the limitations of this investigation, and suggest possible paths to improve these forecasts in the future.

Abstract Although most studies of the effects of electromagnetic ion cyclotron (EMIC) waves on Earth's outer radiation belt have focused on events in the afternoon sector in the outer plasmasphere or plume region, strong magnetospheric compressions provide an additional stimulus for EMIC wave generation across a large range of local times and L shells. We present here observations of the effects of a wave event on 23 February 2014 that extended over 8 h in UT and over 12 h in local time, stimulated by a gradual 4 h rise and subsequent sharp increases in solar wind pressure. Large‐amplitude linearly polarized hydrogen band EMIC waves (up to 25 nT p‐p) appeared for over 4 h at both Van Allen Probes, from late morning through local noon, when these spacecraft were outside the plasmapause, with densities ~5–20 cm −3 . Waves were also observed by ground‐based induction magnetometers in Antarctica (near dawn), Finland (near local noon), Russia (in the afternoon), and in Canada (from dusk to midnight). Ten passes of NOAA‐POES and METOP satellites near the northern foot point of the Van Allen Probes observed 30–80 keV subauroral proton precipitation, often over extended L shell ranges; other passes identified a narrow L shell region of precipitation over Canada. Observations of relativistic electrons by the Van Allen Probes showed that the fluxes of more field‐aligned and more energetic radiation belt electrons were reduced in response to both the emission over Canada and the more spatially extended emission associated with the compression, confirming the effectiveness of EMIC‐induced loss processes for this event.

A Whole Atmosphere Model (WAM) has been used to explore the possible physical connection between a sudden stratospheric warming (SSW) and the dynamics and electrodynamics of the lower thermosphere. WAM produces SSWs naturally without the need for external forcing. The classical signatures of an SSW appear in the model with a warming of the winter polar stratosphere, a reversal of the temperature gradient, and a breakdown of the stratospheric polar vortex. Substantial changes in the amplitude of stationary planetary wave numbers 1, 2, and 3 occur as the zonal mean zonal wind evolves. The simulations also show a cooling in the mesosphere and a warming in the lower thermosphere consistent with observations. The magnitude of this particular SSW is modest, belonging to the category of minor warming. In the lower thermosphere the amplitude of diurnal, semidiurnal, and terdiurnal, eastward and westward propagating tidal modes change substantially during the event. Since the magnitude of the warming is minor and the tidal interactions with the mean flow and planetary waves are complex, the one‐to‐one correspondence between tidal amplitudes in the lower thermosphere and the zonal mean and stationary waves in the stratosphere is not entirely obvious. The increase in the magnitude of the terdiurnal tide (TW3) in the lower thermosphere has the clearest correlation with the SSW, although the timing appears delayed by about three days. The fast group velocity of the long vertical wavelength TW3 tide would suggest a faster onset for the direct propagation of the tide from the lower atmosphere. It is possible that changes in the magnitude of the diurnal and semidiurnal tides, with their slower vertical propagation, may interact in the lower thermosphere to introduce a terdiurnal tide with a longer delay. An increase in TW3 in the lower thermosphere would be expected to alter the local time variation of the electrodynamic response. The day‐to‐day changes in the lower thermosphere winds from WAM are shown to introduce variability in the magnitude of dayside low latitude electric fields, with a tendency during the warming for the dayside vertical drift to be larger and occur earlier, and for the afternoon minimum to be smaller. The numerical simulations suggest that it is quite feasible that a major SSW, with a magnitude seen in January 2009, could cause large changes in lower thermosphere electrodynamics and hence in total electron content.

[1] Satellite drag data indicate that the thermosphere was lower in density, and therefore cooler, during the protracted solar minimum period of 2007–2009 than at any other time in the past 47 years. Measurements indicate that solar EUV irradiance was also lower than during the previous solar minimum. However, secular change due to increasing levels of CO2 and other greenhouse gases, which cool the upper atmosphere, also plays a role in thermospheric climate, and changes in geomagnetic activity could also contribute to the lower density. Recent work used solar EUV measurements from the Solar EUV Monitor (SEM) on the Solar and Heliospheric Observatory, and the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model, finding good agreement between the density changes from 1996 to 2008 and the changes in solar EUV. Since there is some uncertainty in the long-term calibration of SEM measurements, here we perform model calculations using the MgII core-to-wing ratio as a solar EUV proxy index. We also quantify the contributions of increased CO2 and decreased geomagnetic activity to the changes. In these simulations, CO2 and geomagnetic activity play small but significant roles, and the primary cause of the low temperatures and densities remains the unusually low levels of solar EUV irradiance.

Electromagnetic ion cyclotron (EMIC) waves may contribute to ring current ion and radiation belt electron losses, and theoretical studies suggest these processes may be most effective during the main phase of geomagnetic storms. However, ground‐based signatures of EMIC waves, Pc1–Pc2 geomagnetic pulsations, are observed more frequently during the recovery phase. We investigate the association of EMIC waves with various storm phases in case and statistical studies of 22 geomagnetic storms over 1996–2003, with an associated Dst < −30 nT. High‐resolution data from the GOES 8, 9, and 10 geosynchronous satellite magnetometers provide information on EMIC wave activity in the 0–1 Hz band over ±3 days with respect to storm onset, defined as commencement of the negative excursion of Dst. Thirteen of 22 storms showed EMIC waves occurring during the main phase. In case studies of two storms, waves were seen with higher intensity in the main phase in one and the recovery phase in the other. Power spectral densities up to 500 nT 2 Hz −1 were similar in prestorm, storm, and early recovery phases. Superposed epoch analysis of the 22 storms shows 78% of wave events during the main phase occurred in the He + band. After storm onset the main phase contributed only 29% of events overall compared to 71% during recovery phase, up to 3 days. Some differences between storms were found to be dependent on the solar wind driver. Plasma plumes or an inflated plasmasphere may contribute to enhancing EMIC wave activity at geosynchronous orbit.

Waves in the ultra‐low‐frequency (ULF) band have frequencies which can be drift resonant with electrons in the outer radiation belt, suggesting the potential for strong interactions and enhanced radial diffusion. Previous radial diffusion coefficient models such as those presented by Brautigam and Albert (2000) have typically used semiempirical representations for both the ULF wave's electric and magnetic field power spectral densities (PSD) in space in the magnetic equatorial plane. In contrast, here we use ground‐ and space‐based observations of ULF wave power to characterize the electric and magnetic diffusion coefficients. Expressions for the electric field power spectral densities are derived from ground‐based magnetometer measurements of the magnetic field PSD, and in situ AMPTE and GOES spacecraft measurements are used to derive expressions for the compressional magnetic field PSD as functions of Kp, solar wind speed, and L‐shell. Magnetic PSD results measured on the ground are mapped along the field line to give the electric field PSD in the equatorial plane assuming a guided Alfvén wave solution and a thin sheet ionosphere. The ULF wave PSDs are then used to derive a set of new ULF‐wave driven diffusion coefficients. These new diffusion coefficients are compared to estimates of the electric and magnetic field diffusion coefficients made by Brautigam and Albert (2000) and Brautigam et al. (2005). Significantly, our results, derived explicitly from ULF wave observations, indicate that electric field diffusion is much more important than magnetic field diffusion in the transport and energization of the radiation belt electrons.

Because the material that constitutes a coronal mass ejection expands as it propagates into interplanetary space (where it is referred to as an interplanetary coronal mass ejection, ICME), its sheath differs from other heliophysical sheaths in three ways: (1) the lateral deflection of the solar wind away from the nose of an ICME is reduced; (2) the solar wind tends to pile up in front of an ICME instead of flowing around it; and (3) the ICME sheath is thinner. (We refer here to ICME sheaths that have a preceding bow shock and that therefore are analogous to other heliophysical sheaths.) These three differences are explained here by physical arguments and illustrated with an MHD simulation.

Electron auroral energy flux is characterized by electron hemispheric power (Hpe) estimated since 1978 from National Oceanic and Atmospheric Administration (NOAA) and Defense Meteorological Satellite Program (DMSP) satellites after the estimates were corrected for instrumental problems and adjusted to a common baseline. Similarly, intersatellite adjusted ion hemispheric power (Hpi) estimates come from one MetOp and four NOAA satellites beginning in 1998. The hemispheric power (Hp) estimates are very crude, coming from single satellite passes referenced to 10 global activity levels, where the Hpi estimates are the difference between the total and the electron Hp (Hpi = Hpt‐Hpe). However, hourly averaged NOAA/DMSP Hpe and Hpi estimates correlate well with hourly Polar Ultraviolet Imager (UVI) Hpt and Imager for Magnetopause‐to‐Aurora Global Exploration (IMAGE) far ultraviolet (FUV) Hpe and Hpi estimates. Hpe winter values were larger than summer values ∼65% of the time (when geomagnetic activity was moderate or higher), and Hpe were larger in the summer ∼35% of the time (typically for low geomagnetic activity). Hpe was ∼40% larger at winter solstice than summer solstice for the largest Hp from mostly nightside increases, and Hpe was ∼35% larger in summer than winter for the smallest Hp owing to dayside auroral enhancements. Ion precipitation differed from electron precipitation because it was almost always larger in summer than winter. Hpe and Hpi increased with Kp, solar wind speed (Vsw), and negative Interplanetary Magnetic Field (IMF) B z , similar to previous studies. Hpi also increased strongly with positive B z . For quiet conditions, Hpe increased with increasing 10.7‐cm solar flux (Sa), while Hpi increased with Sa up to Sa ∼115 for all conditions.

[1] A Whole atmosphere Data Assimilation System (WDAS) is used to simulate the January 2009 sudden stratospheric warming (SSW). WDAS consists of the Whole Atmosphere Model (WAM) and the 3-dimensional variational (3DVar) analysis system GSI (Grid point Statistical Interpolation), modified to be compatible with the WAM model. An incremental analysis update (IAU) scheme was implemented in the data assimilation cycle to overcome the problem of excessive damping by digital filter in WAM of the important tidal waves in the upper atmosphere. IAU updates analysis incrementally into the model, thus avoids the initialization procedure (i.e., digital filter) during the WAM forecast stage. The WDAS simulation of the January 2009 SSW shows a significant increase in TW3 (terdiurnal, westward propagating, zonal wave number 3) and a decrease in SW2 (semidiurnal, westward propagating, zonal wave number 2) wave amplitudes in the E region during the warming, which can be attributed likely to the nonlinear wave-wave interactions between SW2, TW3 and DW1 (diurnal, westward propagating, zonal wave number 1). There is a delayed increase in SW2 in the E region after the warming, indicating a modulation by the changing large-scale planetary waves in the loweratmosphere during the SSW. These tidal wave responses during SSW appeared to be global in scale. An extended WAM forecast initialized from WDAS analysis shows remarkably consistent tidal wave responses to SSW, indicating a potential forecasting capability of several days in advance of the effects of the large-scale tropospheric and stratospheric dynamics on the thermospheric and ionospheric variability.

Abstract Between 4 and 10 September 2017, multiple solar eruptions occurred from active region AR12673. NOAA's and NASA's well‐instrumented spacecraft observed the evolution of these geoeffective events from their solar origins, through the interplanetary medium, to their geospace impacts. The 6 September X9.3 flare was the largest to date for the nearly concluded solar cycle 24 and, in fact, the brightest recorded since an X17 flare in September 2005, which occurred during the declining phase of solar cycle 23. Rapid ionization of the sunlit upper atmosphere occurred, disrupting high‐frequency communications in the Caribbean region while emergency managers were scrambling to provide critical recovery services caused by the region's devastating hurricanes. The 10 September west limb eruption resulted in the first solar energetic particle event since 2012 with sufficient flux and energy to yield a ground level enhancement. Spacecraft at L1, including DSCOVR, sampled the associated interplanetary coronal mass ejections minutes before their collision with Earth's magnetosphere. Strong compression and erosion of the dayside magnetosphere occurred, placing geosynchronous satellites in the magnetosheath. Subsequent geomagnetic storms produced magnificent auroral displays and elevated hazards to power systems. Through the lens of NOAA's space weather R‐S‐G storm scales, this event period increased hazards for systems susceptible to elevated “radio blackout” (R3‐strong), “solar radiation storm” (S3‐strong), and “geomagnetic storm” (G4‐severe) conditions. The purpose of this paper is to provide an overview of the September 2017 space weather event, and a summary of its consequences, including forecaster, post‐event analyst, and communication operator perspectives.

[1] A whole atmosphere model has been used to simulate the changes in the global atmosphere dynamics and electrodynamics during the January 2009 sudden stratospheric warming (SSW). In a companion paper, it has been demonstrated that the neutral atmosphere response to the 2009 warming can be simulated with high fidelity and can be forecast several days ahead. The 2009 warming was a major event with the polar stratospheric temperature increasing by 70 K. The neutral dynamics from the whole atmosphere model (WAM) was used to drive the response of the electrodynamics. The WAM simulation predicted a substantial increase in the amplitude of the 8-hour terdiurnal tide in the lower thermosphere dynamo region in response to the warming, at the expense of the more typical semidiurnal tides. The increase in the terdiurnal mode had a significant impact on the diurnal variation of the electrodynamics at low latitude. The changes in the winds in the dayside ionospheric E region increased the eastward electric field early in the morning, and drove a westward electric field in the afternoon. The initial large increase in upward drifts gradually moved to later local times, and decreased in magnitude. The change in the amplitude and phase of the electrodynamic response to the SSW is in good agreement with observations from the Jicamarca radar. The agreement with observations serves to validate the whole atmosphere dynamic response. Since WAM can forecast the neutral dynamics several days ahead, the simulations indicate that the electrodynamic response can also be predicted.

Abstract The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) is a NASA-sponsored field campaign to study wintertime snowstorms focusing on East Coast cyclones. This large cooperative effort takes place during the winters of 2020–23 to study precipitation variability in winter cyclones to improve remote sensing and numerical forecasts of snowfall. Snowfall within these storms is frequently organized in banded structures on multiple scales. The causes for the occurrence and evolution of a wide spectrum of snowbands remain poorly understood. The goals of IMPACTS are to characterize the spatial and temporal scales and structures of snowbands, understand their dynamical, thermodynamical, and microphysical processes, and apply this understanding to improve remote sensing and modeling of snowfall. The first deployment took place in January–February 2020 with two aircraft that flew coordinated flight patterns and sampled a range of storms from the Midwest to the East Coast. The satellite-simulating ER-2 aircraft flew above the clouds and carried a suite of remote sensing instruments including cloud and precipitation radars, lidar, and passive microwave radiometers. The in situ P-3 aircraft flew within the clouds and sampled environmental and microphysical quantities. Ground-based radar measurements from the National Weather Service network and a suite of radars located on Long Island, New York, along with supplemental soundings and the New York State Mesonet ground network provided environmental context for the airborne observations. Future deployments will occur during the 2022 and 2023 winters. The coordination between remote sensing and in situ platforms makes this a unique publicly available dataset applicable to a wide variety of interests.

[1] The thermospheric response at satellite altitudes along low Earth orbit is subject to the energy deposition locally, i.e., at high altitudes, and the vertical wave propagation from the energy injection at lower altitudes. In this study, a general circulation model has been run to investigate the source of nonhydrostatic effects and the sensitivity of the vertical wind and neutral density at satellite orbits to the energy deposited at low and high altitudes. Through comparing the simulations with and without the Joule heating enhancement above 150 km altitude, the impact of the heating at low and high altitudes on the high-altitude thermosphere has been separated. The numerical simulations show that most of the nonhydrostatic effects at high altitudes (300 km) arise from sources below 150 km and propagate vertically through the acoustic wave. The heating above 150 km is responsible for a large increase of the average vertical velocity (40 m/s) and neutral density (50%) at 300 km and higher altitudes.

It has long been recognized that whistler‐mode waves can be trapped in plasmaspheric whistler ducts which guide the waves. For nonguided cases these waves are said to be “nonducted”, which is dominant for L < 1.6. Wave‐particle interactions are affected by the wave being ducted or nonducted. In the field‐aligned ducted case, first‐order cyclotron resonance is dominant, whereas nonducted interactions open up a much wider range of energies through equatorial and off‐equatorial resonance. There is conflicting information as to whether the most significant particle loss processes are driven by ducted or nonducted waves. In this study we use loss cone observations from the DEMETER and POES low‐altitude satellites to focus on electron losses driven by powerful VLF communications transmitters. Both satellites confirm that there are well‐defined enhancements in the flux of electrons in the drift loss cone due to ducted transmissions from the powerful transmitter with call sign NWC. Typically, ∼80% of DEMETER nighttime orbits to the east of NWC show electron flux enhancements in the drift loss cone, spanning a L range consistent with first‐order cyclotron theory, and inconsistent with nonducted resonances. In contrast, ∼1% or less of nonducted transmissions originate from NPM‐generated electron flux enhancements. While the waves originating from these two transmitters have been predicted to lead to similar levels of pitch angle scattering, we find that the enhancements from NPM are at least 50 times smaller than those from NWC. This suggests that lower‐latitude, nonducted VLF waves are much less effective in driving radiation belt pitch angle scattering.

A coupled magnetosphere ionosphere thermosphere (CMIT 2.0) model has been developed. It is capable of self‐consistently calculating global ionospheric electric fields that include the imposed magnetospheric convection field, neutral wind dynamo and penetration electric fields. The CMIT 2.0 simulated ionospheric F 2 region ion vertical drift velocities at the magnetic equator were compared with those measured by ground‐based instruments during the April 2–5, 2004, storm. CMIT 2.0 captured the temporal variations seen in the measurements during both the quiet and active periods. These temporal variations corresponded mainly to the variations in the high latitude electric fields driven by changes in solar wind conditions. CMIT 2.0, however, overestimated the magnitudes of the variations of the vertical drifts. In addition, CMIT 2.0 simulated the observed pre‐reversal enhancement well. This enhancement was driven mostly by the neutral wind dynamo.

Objective quantification of model performance based on metrics helps us evaluate the current state of space physics modeling capability, address differences among various modeling approaches, and track model improvements over time. The Coupling, Energetics, and Dynamics of Atmospheric Regions (CEDAR) Electrodynamics Thermosphere Ionosphere (ETI) Challenge was initiated in 2009 to assess accuracy of various ionosphere/thermosphere models in reproducing ionosphere and thermosphere parameters. A total of nine events and five physical parameters were selected to compare between model outputs and observations. The nine events included two strong and one moderate geomagnetic storm events from GEM Challenge events and three moderate storms and three quiet periods from the first half of the International Polar Year (IPY) campaign, which lasted for 2 years, from March 2007 to March 2009. The five physical parameters selected were NmF2 and hmF2 from ISRs and LEO satellites such as CHAMP and COSMIC, vertical drifts at Jicamarca, and electron and neutral densities along the track of the CHAMP satellite. For this study, four different metrics and up to 10 models were used. In this paper, we focus on preliminary results of the study using ground‐based measurements, which include NmF2 and hmF2 from Incoherent Scatter Radars (ISRs), and vertical drifts at Jicamarca. The results show that the model performance strongly depends on the type of metrics used, and thus no model is ranked top for all used metrics. The analysis further indicates that performance of the model also varies with latitude and geomagnetic activity level.

Abstract Led by NOAA’s Storm Prediction Center and National Severe Storms Laboratory, annual spring forecasting experiments (SFEs) in the Hazardous Weather Testbed test and evaluate cutting-edge technologies and concepts for improving severe weather prediction through intensive real-time forecasting and evaluation activities. Experimental forecast guidance is provided through collaborations with several U.S. government and academic institutions, as well as the Met Office. The purpose of this article is to summarize activities, insights, and preliminary findings from recent SFEs, emphasizing SFE 2015. Several innovative aspects of recent experiments are discussed, including the 1) use of convection-allowing model (CAM) ensembles with advanced ensemble data assimilation, 2) generation of severe weather outlooks valid at time periods shorter than those issued operationally (e.g., 1–4 h), 3) use of CAMs to issue outlooks beyond the day 1 period, 4) increased interaction through software allowing participants to create individual severe weather outlooks, and 5) tests of newly developed storm-attribute-based diagnostics for predicting tornadoes and hail size. Additionally, plans for future experiments will be discussed, including the creation of a Community Leveraged Unified Ensemble (CLUE) system, which will test various strategies for CAM ensemble design using carefully designed sets of ensemble members contributed by different agencies to drive evidence-based decision-making for near-future operational systems.

Acquiring quantitative metrics‐based knowledge about the performance of various space physics modeling approaches is central for the space weather community. Quantification of the performance helps the users of the modeling products to better understand the capabilities of the models and to choose the approach that best suits their specific needs. Further, metrics‐based analyses are important for addressing the differences between various modeling approaches and for measuring and guiding the progress in the field. In this paper, the metrics‐based results of the ground magnetic field perturbation part of the Geospace Environment Modeling 2008–2009 Challenge are reported. Predictions made by 14 different models, including an ensemble model, are compared to geomagnetic observatory recordings from 12 different northern hemispheric locations. Five different metrics are used to quantify the model performances for four storm events. It is shown that the ranking of the models is strongly dependent on the type of metric used to evaluate the model performance. None of the models rank near or at the top systematically for all used metrics. Consequently, one cannot pick the absolute “winner”: the choice for the best model depends on the characteristics of the signal one is interested in. Model performances vary also from event to event. This is particularly clear for root‐mean‐square difference and utility metric‐based analyses. Further, analyses indicate that for some of the models, increasing the global magnetohydrodynamic model spatial resolution and the inclusion of the ring current dynamics improve the models' capability to generate more realistic ground magnetic field fluctuations.