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This paper analyses magnetosphere‐ionosphere (M‐I) coupling from a perspective that is independent of inertial reference frame, and delineates how physical theories of M‐I coupling are affected by the principle of relativity. For the first time in the context of M‐I coupling, we discuss the literature from the 1970s on how the low‐velocity limit of the theory of special relativity is applied to electrodynamics. In most M‐I coupling theories, a particular low‐velocity limit applies, known as the "magnetic limit." Two important consequences of this literature are: (a) significant displacement currents in Maxwell's equations break the Galilean invariance of the equations and (b) magnetic fields are not generated by currents created by a net charge density in motion. We show how reference frame‐independent descriptions of M‐I coupling require that ion‐neutral relative velocities and ion‐neutral collisions are key drivers of the physics. Currents are independent of reference frame whereas electric fields depend on reference frame. Starting with the same momentum equations that are typically used to derive Ohm's law, it is possible to express the perpendicular ionospheric current as depending on collisions between ions and neutrals, and electrons and neutrals, without reference to electric fields. Ignoring the relative motion between ions and neutrals results in errors exceeding 100% for estimates of high latitude Joule heating during significant geomagnetic storms, when ion‐neutral velocity differences are largest near the initiation of large‐scale ion convection. Plain Language Summary: Interactions between the magnetized and ionized solar wind, the magnetospheric cavity surrounding Earth, and Earth's ionized upper atmosphere (ionosphere) can create rapid (∼1 km/s) large‐scale motions of the ionosphere during periods known as geomagnetic storms. We use the principle of relativity (PR) to gain insight into the complex physics of these interactions. Relativity states that the physics governing geospace must be independent of the velocity of an observer making measurements of the system. We write key equations governing interactions of the magnetosphere‐ionosphere system in terms of quantities that do not depend on the observer's motion. In doing so, we find that some previous theories had over‐emphasized the importance of a large‐scale electric field that grows during storms, while neglecting important physics related to collisions between the ionized portion of the atmosphere and the un‐ionized "neutral" component that contains much more mass. These collisional interactions create upper atmospheric heating and expansion, and cause large‐scale currents to flow between the ionosphere and magnetosphere, resulting in a multitude of impacts to our technological society. Using the PR, and isolating the physics that is independent of observer motion, led us to a deeper understanding of key physical processes during storms. Key Points: Relativistic transformations applied to electrodynamics are analyzed in the context of magnetosphere‐ionosphere (M‐I) couplingWe present an "Ohm's law" relating horizontal ionospheric currents to quantities that do not vary with inertial reference frameElectrodynamic theories of M‐I coupling that do not account for the relative motion of ions and neutrals are not quantitatively accurate [ABSTRACT FROM AUTHOR]

A newly released, novel ionospheric data set of global gridded vertical total electron content (VTEC) is introduced in this paper. This VTEC data set, provided by Los Alamos National Laboratory (LANL), is derived from very high frequency (VHF; defined as 30–300 MHz) broadband radio‐frequency (RF) measurements of lightning made by U.S. Department of Defense sensing systems on board Global Positioning System (GPS) satellites. This paper presents the new data set (LANL VTEC), discusses the errors inherent in VHF TEC estimation due to ionospheric dispersion, and compares the LANL VTEC to two community standard VTEC gridded products: Jet Propulsion Laboratory's Global Ionospheric Model (JPL GIM) and the CEDAR community's Open Madrigal VTEC gridded measurements of L‐band GNSS (global navigation satellite systems) TEC. We find that the LANL VTEC data have an offset of 3 TECU from CEDAR Madrigal GNSS VTEC and a full‐width‐half‐maximum (FWHM) of 6 TECU. In comparison, the offset between LANL VTEC and the JPL GIM model is −3 TECU, but with a FWHM of 5 TECU. We also compare to Jason‐3 VTEC measurements over the ocean, finding an offset of less than 0.5 TECU and an FWHM of <5 TECU. Because this technique uses a completely different methodology to determine TEC, the sources of errors are distinct from the typical ground‐based GNSS L‐band (GHz) TEC measurements. Also, because it is derived from RF lightning signals, this data set provides measurements in regions that are not well covered by ground‐based GPS measurements, such as over oceans and over central Africa. Plain Language Summary: The ionosphere is a region of the atmosphere that is very important in communications between ground and satellite. For that reason, decades of scientific effort have been put toward developing models of the ionosphere so that we can more accurately predict what the state of the ionosphere is at any given location and time. A general product produced by many of these models is the vertical total electron content (VTEC), which is the vertically integrated electron density at a particular location at a particular time. The majority of these models use measurements of TEC from ground‐based receivers or instruments, meaning that abundant measurements that go into the models often lack data from over the oceans or in technologically limited regions of the world (e.g., Africa). Here, we present a new VTEC data set that is derived from lightning strokes detected with U.S. Department of Defense sensing systems on GPS satellites. Because the data set uses naturally occurring lightning for its source, it does not have the same limitations as ground‐based TEC measurements and can provide an additional source of validation data for ionospheric models. We introduce the data set and compare it with community‐accepted VTEC models and measurements. Key Points: New global gridded vertical total electron content (VTEC) data set derived from radio‐frequency measurements from lightning emissions during the entire year of 2018 has been releasedVTEC product adds new global coverage in areas with few global navigation satellite systems receivers (ocean and continental Africa)The VTEC values, generated from very high frequency radio‐frequency data, show bias in Madrigral data set and differences to Jet propulsion laboratory's global ionospheric model model‐derived VTEC [ABSTRACT FROM AUTHOR]

The atmospheric measurements made by the eight Mars orbiters in operation (as of April 2021) significantly improved our understanding of the Martian weather and climate. However, while some of the existing Mars orbiters will reach their lifetime, innovative and cost-effective observation concepts are requested - not only to guarantee continued observation but also to address potential gaps in the existing observing network. Inspired by the success of the two MarsCube One satellites we have established an observation concept, which is based on a series of cubesats, carried to Mars and injected into a low Mars orbit in a so-called string-of-pearls formation. Over the lifetime of the cubesats of about one Martian year, a series of radio occultation (RO) experiments will be carried out with up to 180 partially overlapping RO measurements per day. For processing of the unique set of observations, tomographic principles are applied to the RO measurements for the reconstruction of high-resolution twodimensional temperature and pressure fields of the lower Martian atmosphere. Unlike the standard Abel transform approach, the derived products are not dependent on spherical symmetry assumptions. Thus, insights into various unresolved atmospheric phenomena are obtained - especially of those which are characterized by distinct horizontal gradients in pressure and temperature, for example, as observed at the day-night terminator, during dust storms, or over complex terrain. [ABSTRACT FROM AUTHOR]

Significant polar topside total electron content (topTEC) enhancement (PTTE) above 1,336 km altitude is reported for the first time. The results are based on GPS measurements during 2008–2019 from NASA's Jason‐2 satellite with zenith‐oriented antennas. The observations show increasing topTEC toward the southern polar cap at geomagnetic latitudes poleward of 65°S, where TEC values are normally very low. A case study for the 2013 St. Patrick's Day storm indicates that the enhancement can exceed 5.5 TEC units above the dayside ambient state, corresponding to 78% increase. Comparisons with COSMIC/FORMOSAT‐3 topTEC measurements above 800 km altitude confirm that PTTE events are observed from both Jason‐2 and COSMIC on the same day. Our statistical analysis of the Jason‐2 data in the southern polar region reveals that PTTE mostly occurs on the dayside, with a seasonal preference of southern summer, and preferentially during geomagnetically disturbed days but can also occur during quiet days. PTTE during storm days shows increased occurrence, magnitude, and deviation from the mean in the cusp region compared with quiet days. Our case analysis indicates that PTTE is observed simultaneously with the effect of tongue of ionization. This suggests that the during storms, dayside F region plasma moving poleward following the antisunward plasma convection may also be part of the PTTE source, and the plasma upflow driven by the polar wind may act to cause PTTE. Plain Language Summary: Significant polar topside total electron content (topTEC) enhancement (PTTE) above 1,336 km altitude is reported for the first time. The results are based on GPS measurements from NASA's Jason‐2 satellite during 2008–2018. The observations show increasing topside TEC toward the southern polar cap where TEC values are normally very low. Comparisons with COSMIC/FORMOSAT‐3 topside TEC measurements confirm that PTTE events are observed from both Jason‐2 and COSMIC on the same day. Our statistical analysis reveals that PTTE mostly occurs in the southern cusp and dayside polar cap, with a seasonal preference of summer, and preferentially during geomagnetically disturbed days but can also occur during quiet days. PTTE during storm days shows increased occurrence, magnitude, and deviation from the mean in the cusp region compared with quiet days. Our case analysis indicates that PTTE is observed simultaneously with the effect of tongue of ionization. This suggests that the during storms, dayside F region plasma moving poleward following the antisunward plasma convection may also be part of the PTTE source, and the plasma upflow driven by the polar wind may act to cause PTTE. Key Points: NASA's Jason‐2 satellite zenith‐viewing GPS total electron content (TEC) measurements spanning 2008–2018 are analyzedSignificant increases of TEC above 1,336 km altitude in the southern polar region are reported for the first timeThe polar topside TEC enhancement (PTTE) appears preferentially during geomagnetic storms and during summer [ABSTRACT FROM AUTHOR]

In the upper troposphere (UT), Global Navigation Satellite System (GNSS) Radio Occultations (ROs) provide accurate air temperatures (<0.5 K) every ∼200 m vertically. We use RO observations from 01/2002 until 12/2018 at 300, 250, and 200 hPa to quantify the tropical upper tropospheric amplification (defined as the ratio of temperature trends in the UT relative to the surface). We compare the RO‐derived results against Atmospheric Infrared Sounder (AIRS), Coupled Model Intercomparison Project Phase 6 (CMIP6) Atmospheric Model Intercomparison Project (AMIP) models, Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA‐2), and European Center for Medium‐range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) data. We find that CMIP6 AMIP models show excellent agreement with independent AIRS and RO observations on the magnitude of the UT warming and show warming that is significantly faster than both reanalyses above 250 hPa. Additionally, AIRS and CMIP6 AMIP present excellent agreement with the RO‐measured tropical tropospheric amplification. Plain Language Summary: In the upper troposphere, Global Navigation Satellite System Radio Occultations (GNSS‐RO) measure the air's refractive index, which depends primarily on the air's temperature. We use these GNSS‐RO temperatures from 01/2002 until 12/2018 at 200, 250, and 300 hPa in the tropics (where the atmosphere experiences the largest amplification in response to surface warming). Routinely, climate models are used to simulate how much the upper atmosphere has warmed in response to surface warming. However, there appears to be a disagreement between observations and models, which today we try to understand. The GNSS‐RO observations have a unique feature of being able to measure the air temperature every 200 m, and show us that that climate models are in close agreement with the GNSS‐RO and other infrared observations. In other words, GNSS‐RO observations show that the upper atmosphere warms faster and the amplification due to surface warming is stronger than what current reanalysis estimate. Independent infrared observations of the Earth's upper troposphere also support the GNSS‐RO findings and are also in very close agreement with the climate models. Interestingly, the reanalysis indicates that at 200 hPa there is no warming observed, contrary to what GNSS‐RO, infrared, and climate models reveal. Key points: Coupled model intercomparison project phase 6 (cmip6) atmospheric model intercomparison project (AMIP) models agree with independent radio occultation and infrared data on the magnitude of the tropical upper tropospheric temperature trendsRadio occultations reveal faster tropical upper tropospheric warming than both modern‐era retrospective analysis for research and applications version 2 (MERRA‐2) and European Center for Medium‐Range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) (above 250 hPa) reanalysesERA‐Interim presents decreasing tropical upper troposphere amplification with altitude, unlike the amplification shown by radio occultations [ABSTRACT FROM AUTHOR]

Physics-based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same data are assimilated. In this study, we used our Multimodel Ensemble Prediction System (MEPS) of DA models to elucidate the similarities and differences in the individual DA model reconstructions of the mid-low latitude ionosphere when the same data are assimilated. Ensemble model averages were also obtained. For this ensemble modeling study, we selected the quiet/storm period of 16 and 17 March 2013 (equinox, solar medium). Five data assimilation models and one physics-based model were used to produce an ensemble mean output for Total Electron Content (TEC), ionospheric peak density (NmF2), and ionospheric peak height (hmF2) for latitudes less than 60° and all longitudes. The data assimilated included ground-based Global Positioning Satellite TEC and topside plasma densities near 800 km altitude derived from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites. Both a simple average and a weighted average of the models were used in the ensemble averaging in order to determine if there was an improvement of the ensemble averages over the individual models. [ABSTRACT FROM AUTHOR]

The Space Weather Forecast Testbed (SWFT) is developed by a team of space weather scientists and mathematicians at the University of Southern California (USC) and Jet Propulsion Laboratory (JPL) to foster the creation of models for space weather forecast by exploration of existing historic data using techniques of machine learning. As an example to demonstrate the potential power of SWFT, we present in this paper a multilinear regression‐based forecast model for solar wind. Solar wind is one of the key drivers for numerous physics‐based models for space weather including thermosphere and ionosphere models. Many attempts have been made to produce forecasts for the solar wind. SWFT provides a unified framework for forecast model formulation, training, and performance assessment. In particular, the preparation of training and validation data by SWFT takes into account the realistic constraints on data latency and forecast lead time. In developing a solar wind forecast model, SWFT allows fast exploration of many metaparameters such as the list of predictive variables and their time history used in constructing a model. We present the impact of metaparameter selection, as well as performance relative to existing solar wind forecast models. Key Points: Space Weather Forecast Testbed (SWFT) provides a useful tool for exploring forecasting space weather using data‐driven techniquesMachine learning approaches can be beneficial for space weather forecastA case study of using SWFT to develop a data‐driven forecast model for solar wind speed demonstrates the utility of SWFT [ABSTRACT FROM AUTHOR]

Prediction of ionospheric state is a critical space weather problem. We expand on our previous research of medium‐range ionospheric forecasts and present new results on evaluating prediction capabilities of three physics‐based ionosphere‐thermosphere models (Thermosphere Ionosphere Electrodynamics General Circulation Model, TIE‐GCM; Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics Model, CTIPe; and Global Ionosphere Thermosphere Model, GITM). The focus of our study is understanding how current modeling approaches may predict the global ionosphere for geomagnetic storms (as studied through 35 storms during 2000–2016). Prediction approach uses physics‐based modeling without any manual model adjustment, quality control, or selection of the results. Our goal is to understand to what extent current physics‐based modeling can be used in total electron content (TEC) prediction and explore uncertainties of these prediction efforts with multiday lead times. The ionosphere‐thermosphere model runs are driven by actual interplanetary conditions, whether those data come from real‐time measurements or predicted values themselves. These model runs were performed by the Community Coordinated Modeling Center (CCMC). Jet Propulsion Laboratory (JPL)‐produced global ionospheric maps (GIMs) were used to validate model TEC estimates. We utilize the True Skill Statistic (TSS) metric for the TEC prediction evaluation, noting that this is but one metric to assess predictive skill and that complete evaluations require combinations of such metrics. The meanings of contingency table elements for the prediction performance are analyzed in the context of ionosphere modeling. Prediction success is between about 0.2 and 0.5 for weak ionospheric disturbances and decreases for strong disturbances. We evaluate the prediction of TEC decreases and increases. Our results indicate that physics‐based modeling during storms shows promise in TEC prediction with multiday lead time. Key Points: Physics‐based predictions of the total ionospheric content are evaluated for 35 stormsPrediction success is estimated below 0.5 and is with line with other geospace model predictionsPhysics‐based modeling shows promise in TEC prediction with multiday lead timeIt is important to evaluate all elements of the contingency matrix and to understand the role of each element in evaluation metrics [ABSTRACT FROM AUTHOR]

Forecasting conditions in the thermosphere and ionosphere is a key outcome expected from space weather research. In this work, we perform numerical simulations using the first‐principles models Global Ionosphere‐Thermosphere Model (GITM) and Thermosphere‐Ionosphere Electrodynamics General Circulation Model (TIE‐GCM) to address the reliability of thermospheric‐ionospheric forecasts. When considering forecasts applicable to periods of geomagnetic activity, careful consideration is required of model inputs, which largely determine how the models will simulate disturbed conditions. We adopt an approach to drive the models with solar wind parameters and the 10.7 cm solar radio flux. This aligns our investigation with recent research and operational activities to forecast solar wind conditions on the Earth a few days in advance. In this work, we examine a weak geomagnetic storm, the June 2012 high‐speed‐stream event, for which we drive GITM and TIE‐GCM with observed solar wind and F10.7 values. We find general agreement between the simulations and observation‐based Global Ionospheric Maps of the total electron content (TEC) response. However, overestimated TEC response is found in the middle to low latitudinal region of the American sector and surrounding areas for both GITM and TIE‐GCM during similar time periods. By conducting numerical modeling experiments and comparing the modeling results with observational data, we find that the overestimated TEC response can be almost equally attributed to the solar wind driving and F10.7 driving during the June 2012 event. We conclude that the accuracy of the high‐latitude electric field and the solar irradiance is crucial to reproduce the TEC response in forecastable‐mode modeling. Key Points: Forecastable global thermosphere‐ionosphere modeling is carried out for a weak geomagnetic stormThe modeled daytime middle‐ to low‐latitude TEC response is primarily driven by the solar wind condition on the first day of the stormOn later days of the storm the solar irradiance plays a comparable role as the solar wind in determining the modeled daytime TEC response [ABSTRACT FROM AUTHOR]

A comprehensive study of all superstorms (minimum Dst ≤ −250 nT) occurring during the space age (after 1957) and their interplanetary and solar causes has been performed. Most superstorms were driven solely by the sheath preceding an interplanetary coronal mass ejection (ICME) or by a combination of the sheath and an ICME magnetic cloud. Only one superstorm was driven solely by a magnetic cloud. There were two superstorms caused by "compound events" with two ICMEs. No superstorms in this study were induced by corotating interaction regions. For the interplanetary shocks antisunward of the ICMEs, the shock normal angles were almost all quasi‐perpendicular. Quasi‐perpendicular shocks theoretically cause greater sheath magnetic field intensities than do quasi‐parallel shocks. Larger shock normal angles statistically corresponded to greater superstorm intensities. Ninety percent of the superstorms occurred either near solar maximum or during the declining phase, 8% of the superstorms occurred during the ascending phase, and 2% of the superstorms occurred during solar minimum. Fifty‐four percent of the superstorms were associated with X‐class solar flares, 36% were associated with M‐class flares, and 5% with C‐class flares. All solar flares related to superstorms occurred in active regions, indicating the importance of active regions to superstorms. Most flares were located in the central meridian or slightly west of it as expected. Two superstorms were caused by limb flares, one on the west limb (confirmed) and the other on the east limb (unconfirmed). The confirmed event was a sheath event led by a Mach 4.1 shock. Key Points: All solar flares that released CMEs associated with superstorms in the space age occurred in active regionsSheaths antisunward of ICMEs contribute to the main phase development for most superstormsThe interplanetary shocks ahead of ICMEs that caused superstorms were all quasi‐perpendicular in nature [ABSTRACT FROM AUTHOR]

Scientific studies using spacecraft radio links, which are shared with communications and navigation functions, have been carried out on almost every solar system exploration mission in the past five decades. They have led to numerous scientific discoveries as well as technological advances. These radio science experiments have investigated the interior structure of every planet in the solar system and several of their satellites, the Moon, and several comets and asteroids and sounded the atmospheres of every planet in the solar system except Mercury, and the atmospheres of Pluto and several large satellites, the Io Plasma Torus, Saturn's and Uranus' rings, and the solar corona. Future experiments at Mercury, the Jovian system, asteroid Psyche, and other targets are currently in various planning and development phases. Over the next 30 years, significant advances in radio and laser link science technologies, including one order of magnitude improvement achievable in range rate and range accuracy and advanced calibration techniques, could enable many additional scientific breakthroughs. Future exploration concepts focus on applications of small spacecraft and entry probes and can include constellations for studies of atmospheric dynamics, interior structures, and surface properties. Selected science‐enabling technologies specific to small spacecraft instrumentation on future missions are under study. Examples include field tests of radio scattering to determine surface properties, constellations for high‐resolution spatial and temporal atmospheric sounding, small science‐quality software‐defined transponders, miniature ultrastable oscillators, and advanced radio‐metric calibrations at the Deep Space Network. Plain Language Summary: Radio links are used to communicate with spacecraft by sending them commands from ground controllers and receiving back science data. The same links are used to examine important properties of planetary atmospheres, surfaces, and interior structure by carefully studying small changes in the radio signal's frequency and other parameters caused by geophysical phenomena when the spacecraft are close to the planets. Improving the radio system on the spacecraft and ground stations can lead to additional scientific discoveries. There is a trend to use small spacecraft to explore the solar system in future, and research teams are preparing instrumentation systems that are compatible with such possible missions. Key Points: Spacecraft telecommunications links are powerful tools to study planetary atmospheres, interiors, and surfaces as proven over five decadesInstrumentation design and calibration techniques have significantly improved, and concepts are developed for additional breakthroughsThere is a trend to miniaturize spacecraft and components and fly them in groups, sometimes in formation flying [ABSTRACT FROM AUTHOR]

As part of its International Capabilities Assessment effort, the Community Coordinated Modeling Center initiated several working teams, one of which is focused on the validation of models and methods for determining auroral electrodynamic parameters, including particle precipitation, conductivities, electric fields, neutral density and winds, currents, Joule heating, auroral boundaries, and ion outflow. Auroral electrodynamic properties are needed as input to space weather models, to test and validate the accuracy of physical models, and to provide needed information for space weather customers and researchers. The working team developed a process for validating auroral electrodynamic quantities that begins with the selection of a set of events, followed by construction of ground truth databases using all available data and assimilative data analysis techniques. Using optimized, predefined metrics, the ground truth data for selected events can be used to assess model performance and improvement over time. The availability of global observations and sophisticated data assimilation techniques provides the means to create accurate ground truth databases routinely and accurately. Key Points: A working team has been established to develop a process for validation of auroral precipitation and electrodynamics modelsValidation of auroral electrodynamic parameters requires generation of ground truth data sets for selected eventsCurrent observations and data assimilation techniques continue to improve the accuracy of global auroral electrodynamic specification [ABSTRACT FROM AUTHOR]

As societal dependence on transionospheric radio signals grows, space weather impact on these signals becomes increasingly important yet our understanding of the effects remains inadequate. This challenge is particularly acute at high latitudes where the effects of space weather are most direct and no reliable predictive capability exists. We take advantage of a large volume of data from Global Navigation Satellite Systems (GNSS) signals, increasingly sophisticated tools for data‐driven discovery, and a machine learning algorithm known as the support vector machine (SVM) to develop a novel predictive model for high‐latitude ionospheric phase scintillation. This work, to our knowledge, represents the first time an SVM model has been created to predict high‐latitude phase scintillation. We use the true skill score to evaluate the SVM model and to establish a benchmark for high‐latitude ionospheric phase scintillation prediction. The SVM model significantly outperforms persistence (i.e., current and future scintillation are identical), doubling the predictive skill according to the true skill score for a 1‐hr lead time. For a 3‐hr lead time, persistence is comparable to a random chance prediction, suggesting that the memory of the ionosphere in terms of high‐latitude plasma irregularities is on the order of, or shorter than, a few hours. The SVM model predictive skill only slightly decreases between the 1‐ and 3‐hr predictive tasks, pointing to the potential of this method. Our findings can serve as a foundation on which to evaluate future predictive models, a critical development toward the resolution of space weather impact on transionospheric radio signals. Plain Language Summary: Society is increasingly dependent on radio signals, particularly those from the Global Navigation Satellite Systems (GNSS), and the technologies (e.g., navigation and financial transactions) that they enable. The integrity and reliability of these signals is threatened by their travel from the GNSS satellites to the ground, which includes passage through a charged region between 100 and 1,000 km known as the ionosphere. Disturbances to the ionosphere from solar energy, or space weather, cause variations in GNSS signals that adversely affect the dependent systems and technologies. Currently, the effect of the ionosphere on these signals cannot be reliably predicted, and the challenge is particularly important at latitudes above 45° where space weather impacts are most direct. We have compiled a large volume of data from the regions important to space weather (i.e., from the Sun to the Earth) to develop a novel machine learning model capable of skillfully predicting disruptions to GNSS signals at high latitudes. To our knowledge, this model is the first of its kind. We find that the new model is capable of more accurate predictions than current methods and position this model as a benchmark on which future predictive models can be measured. Key Points: Support vector machine yields predictive performance roughly double that of persistence; the benefit increases with longer prediction timesElectron precipitation information is critical to the prediction of high‐latitude phase scintillationA benchmark is established for high‐latitude ionospheric phase scintillation using the robust true skill score (TSS) metric [ABSTRACT FROM AUTHOR]

To numerically simulate earthquake‐induced ionospheric disturbances, we extend the Wave Perturbation‐Global Ionosphere‐Thermosphere Model, which was originally developed for tsunami‐ionosphere coupling via gravity waves, to the case of earthquake‐ionosphere coupling via acoustic‐gravity waves. The new Wave Perturbation‐Global Ionosphere‐Thermosphere Model represents epicentral crustal movements by a point source specified with the ground motion data from seismic measurements. The model then solves for the neutral atmospheric perturbations generated by spherical acoustic‐gravity waves and the resulting ionospheric plasma perturbations over the epicentral area. We apply the model to simulate the near‐field ionospheric disturbances during two major earthquake events: the 2011 Tohoku‐Oki, Japan, and the 2015 Illapel, Chile, events. To validate the results, we extract receiver‐to‐satellite total electron content perturbations from the simulations and compare them to the corresponding slant total electron content perturbations from Global Positioning System observations. We find good agreement on magnitudes and arrival times between the simulations and observations. Key Points: We have developed a novel earthquake‐ionosphere coupling model based on a state‐of‐the‐art upper atmospheric modelThe model is capable of simulating ionospheric signatures induced by epicentral crustal movementsModel validation with two earthquake events shows reasonable agreement with observations [ABSTRACT FROM AUTHOR]

Abstract: Solar and interplanetary events can create extreme magnetic storms, such as the Carrington storm in 1859 with intensity up to Dst ∼−1,760 nT. The influence of an idealized, smaller Carrington‐type storm on the thermosphere has been simulated using the nonhydrostatic Global Ionosphere‐Thermosphere Model. For the storm conditions we simulated, the solar wind BZ and velocity were −50 nT and 1,000 m/s, respectively. The corresponding cross polar cap potential reached 360 kV, and the hemispheric power was 200 GW. Consequently, the hemispheric integrated Joule heating exceeded 3,500 GW, which is more than 70 times higher than normal conditions. The thermosphere variations at high latitudes were examined through the comparison of three cases: reference, storm with geomagnetic energy enhancement only, and storm with both solar and geomagnetic energy enhancement. At 400‐km altitude, the neutral density increased by >20 times at certain locations and by >10 times globally averaged. The atmosphere experienced a temperature of 4000 K, more than 1,500 m/s horizontal wind, and exceeding 150 m/s vertical wind. In general, additional energy increase from solar irradiation resulted in 20–30% more perturbation in neutral density and temperature. The exobase (top boundary of the thermosphere) expanded to altitudes >1,000 km, and the buoyancy acceleration (difference between vertical pressure gradient force and gravity force) can be as large as 3 m/s2. The results will help to determine possible extreme responses to interplanetary coronal mass ejections for various phenomena occurring in geospace. [ABSTRACT FROM AUTHOR]

For the first time we derive an analytical expression for energy deposition by propagating monochromatic Alfvén waves in the collisional ionosphere‐thermosphere (IT). Based on empirical models of IT parameters, we show an approximately 10% increase in efficiency of energy deposition at high latitudes and about 150 km altitude by Alfvén waves at 5 Hz as compared to static fields of the same magnitude. We analyze the dependence of the wave energy deposition on geomagnetic activity through a Global Ionosphere‐Thermosphere Model (GITM) simulation of IT conditions during the 13–14 October 2016 geomagnetic storm. The peak Alfvén wave contribution occurs in the E layer and lower part of the F layer. Wave‐induced heating is shown to increase in the daytime and postdusk high‐latitude F layer during the storm due to increased wave‐modified conductivity. We estimate that the Alfvén wave contribution to the IT energy budget can reach about 30% of the value of static Joule heating during a strong storm and that the actual percentage increase is dependent on latitude and altitude. This effect carries important implications for ionospheric dynamics, especially for density enhancement in the daytime cusp, heating in the vicinity of auroral arcs and ion outflow. Key Points: An analytical expression for energy deposition by propagating Alfvén waves in the collisional ionosphere‐thermosphere is derivedThe relative efficiency of energy deposition rate of Alfvén wave (up to 5 Hz in frequency) to static field is estimated to be ∼10% at high latitudes and below 250 km altitudeWe show that Alfvén wave energy deposition can reach about 30% of the value of static Joule heating during a strong storm [ABSTRACT FROM AUTHOR]

The solar minimum period between solar cycles 23 and 24 has generated extensive study, in part because the changes in the upper atmosphere and ionosphere were so dramatic. Thermospheric density during 2008–2009, at the benchmark 400‐km altitude, was shown to be approximately 30% lower than the previous solar minimum during 1996, in observations and in model simulations. Ionospheric densities were also estimated to be lower, by 10% to 20%. However, earlier analyses using data from the global network of Global Navigation Satellite System receivers did not find any significant reduction in global mean total electron content. Recent work reexamining those data using a limited set of receivers, but with consistent processing, identified a 19% reduction (Emmert et al., 2017, https://doi.org/10.1002/2016JA023680). In this study, we compare model simulations of the thermosphere‐ionosphere system during the 2008–2009 solar minimum to its predecessor and estimate a 16% reduction in global mean total electron content. This is consistent with the neutral thermosphere density change seen in model simulations and in satellite drag observations. In the model simulations, the primary driver is a 10% reduction in solar extreme ultraviolet irradiance, with a smaller contribution from lower geomagnetic activity, and a very small decrement due to increase in atmospheric carbon dioxide. Plain Language Summary: The Sun goes through 11‐year activity cycles, best known with regard to the number of sunspots. At solar minimum, when sunspots mostly vanish, the extreme ultraviolet region of the solar spectrum also diminishes. This causes lower temperature and density in the ionosphere and upper atmosphere above 100 km, where the extreme ultraviolet radiation is absorbed. Past solar minimum periods have seemed basically similar with regard to extreme ultraviolet radiation, and other manifestations of solar activity. However, the solar minimum during 2008–2009 was longer and had fewer sunspots than its predecessor during 1996, or than any minimum period in the past century. The thermosphere was also lower in density, and the ionosphere also appeared to be lower in density, but there were some contradictory measurements. Recent reanalysis of ionospheric measurements found better agreement with the thermospheric measurements. Modeling studies attempting to explain the changes in the ionosphere and thermosphere have suggested that they were caused by a decrease of about 10% in solar extreme ultraviolet radiation. Here we show that the model results and the ionospheric measurements are now in good agreement. This demonstrates that solar minima are not all the same and may have implications for understanding the Sun during extended periods of very low activity. Key Points: Reanalysis of ionospheric electron content by Emmert et al. () found it lower during the 2008‐2009 solar minimum than the 1996 minimumModel simulations showed that both ionospheric electron content and thermospheric neutral density were lower during 2008‐2009 than in 1996Thermosphere and ionosphere reductions during the 2008‐2009 solar minimum were consistent in observations and in model simulations [ABSTRACT FROM AUTHOR]

Abstract: Solar wind turbulence within high‐speed streams is reviewed from the point of view of embedded single nonlinear Alfvén wave cycles, discontinuities, magnetic decreases (MDs), and shocks. For comparison and guidance, cometary plasma turbulence is also briefly reviewed. It is demonstrated that cometary nonlinear magnetosonic waves phase‐steepen, with a right‐hand circular polarized foreshortened front and an elongated, compressive trailing edge. The former part is a form of “wave breaking” and the latter that of “period doubling.” Interplanetary nonlinear Alfvén waves, which are arc polarized, have a ~180° foreshortened front and with an elongated trailing edge. Alfvén waves have polarizations different from those of cometary magnetosonic waves, indicating that helicity is a durable feature of plasma turbulence. Interplanetary Alfvén waves are noted to be spherical waves, suggesting the possibility of additional local generation. They kinetically dissipate, forming MDs, indicating that the solar wind is partially “compressive” and static. The ~2 MeV protons can nonresonantly interact with MDs leading to rapid cross‐field (~5.5% Bohm) diffusion. The possibility of local (~1 AU) generation of Alfvén waves may make it difficult to forecast High‐Intensity, Long‐Duration AE Activity and relativistic magnetospheric electrons with great accuracy. The future Solar Orbiter and Solar Probe Plus missions should be able to not only test these ideas but to also extend our knowledge of plasma turbulence evolution. [ABSTRACT FROM AUTHOR]

Abstract: An alternative scenario to the Ngwira et al. (2014, https://doi.org/10.1002/2013JA019661) high sheath densities is proposed for modeling the Carrington magnetic storm. Typical slow solar wind densities (~5 cm−3) and lower interplanetary magnetic cloud magnetic field intensities (~90 nT) can be used to explain the observed initial and main phase storm features. A second point is that the fast storm recovery may be explained by ring current losses due to electromagnetic ion cyclotron wave scattering. [ABSTRACT FROM AUTHOR]

Abstract: Our understanding and specification of solar‐terrestrial interactions benefit from taking advantage of comprehensive data‐intensive approaches. These data‐driven methods are taking on new importance in light of the shifting data landscape of the geospace system, which extends from the near Earth space environment, through the magnetosphere and interplanetary space, to the Sun. The space physics community faces both an exciting opportunity and an important imperative to create a new frontier built at the intersection of traditional approaches and state‐of‐the‐art data‐driven sciences and technologies. This brief commentary addresses the current paradigm of geospace science and the emerging need for data science innovation, discusses the meaning of data science in the context of geospace, and highlights community efforts to respond to the changing landscape. [ABSTRACT FROM AUTHOR]

Abstract: We explore the characteristics, controlling parameters, and relationships of multiscale field‐aligned currents (FACs) using a rigorous, comprehensive, and cross‐platform analysis. Our unique approach combines FAC data from the Swarm satellites and the Advanced Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to create a database of small‐scale (∼10–150 km, <1° latitudinal width), mesoscale (∼150–250 km, 1–2° latitudinal width), and large‐scale (>250 km) FACs. We examine these data for the repeatable behavior of FACs across scales (i.e., the characteristics), the dependence on the interplanetary magnetic field orientation, and the degree to which each scale “departs” from nominal large‐scale specification. We retrieve new information by utilizing magnetic latitude and local time dependence, correlation analyses, and quantification of the departure of smaller from larger scales. We find that (1) FACs characteristics and dependence on controlling parameters do not map between scales in a straight forward manner, (2) relationships between FAC scales exhibit local time dependence, and (3) the dayside high‐latitude region is characterized by remarkably distinct FAC behavior when analyzed at different scales, and the locations of distinction correspond to “anomalous” ionosphere‐thermosphere behavior. Comparing with nominal large‐scale FACs, we find that differences are characterized by a horseshoe shape, maximizing across dayside local times, and that difference magnitudes increase when smaller‐scale observed FACs are considered. We suggest that both new physics and increased resolution of models are required to address the multiscale complexities. We include a summary table of our findings to provide a quick reference for differences between multiscale FACs. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a comprehensive study of occurrence of L‐band scintillation in association with the appearance of sporadic E (Es) along the magnetic dip equator during daytime in 2013. The presence of L‐band scintillation was determined from signals collected with GNSS (Global Navigation Satellite Systems) ground‐based Scintillation Network Decision Aid receivers from five stations situated at the magnetic dip equator. The detection and analysis of Es layers were obtained from GNSS FORMOSAT‐3/Constellation Observing System for Meteorology, Ionosphere, and Climate (F3/C) radio occultation (RO) data. Combining ground‐based data with the limb‐viewing geometry from space provides a unique opportunity to retrieve complementary information about scintillation and association with equatorial E region irregularities (i.e., Es) during daytime. Results for the first time show that daytime scintillation does occur at the magnetic dip equator and the occurrence is associated with the appearance of Es observed using GNSS F3/C RO data. [ABSTRACT FROM AUTHOR]

We revisit three complex superstorms of 19-20 November 2003, 7-8 November 2004, and 9-11 November 2004 to analyze ionosphere-thermosphere (IT) effects driven by different solar wind structures associated with complex interplanetary coronal mass ejections (ICMEs) and their upstream sheaths. The efficiency of the solar wind-magnetosphere connection throughout the storms is estimated by coupling functions. The daytime IT responses to the complex driving are characterized by combining and collocating (where possible) measurements of several physical parameters (total electron content or TEC, thermospheric infrared nitric oxide emission, and composition ratio) from multiple satellite platforms and ground-based measurements. A variety of metrics are utilized to examine global IT phenomena at ~1 h timescales. The role of direct driving of IT dynamics by solar wind structures and the role of IT preconditioning in these storms, which feature complex unusual TEC responses, are examined and contrasted. Furthermore, IT responses to ICME magnetic clouds and upstream sheaths are separately characterized. We identify IT feedback effects that can be important for long-lasting strong storms. The role of the interplanetary magnetic field By component on ionospheric convection may not be well captured by existing coupling functions. Mechanisms of thermospheric overdamping and consequential ionospheric feedback need to be further studied. [ABSTRACT FROM AUTHOR]

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m−2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered. [ABSTRACT FROM AUTHOR]

The ionosphere-thermosphere (IT) energy partitioning for the interplanetary coronal mass ejection (ICME) storms of 16-19 March 2013 and 2015 is estimated with the Global Ionosphere-Thermosphere Model (GITM), empirical models and proxies derived from in situ measurements. We focus on auroral heating, Joule heating, and thermospheric cooling. Solar wind data, F10.7, OVATION Prime model and the Weimer 2005 model are used to drive GITM from above. Thermospheric nitric oxide and carbon dioxide cooling emission powers and fluxes are estimated from TIMED/SABER measurements. Assimilative mapping of ionospheric electrodynamics (AMIE) estimations of hemispheric power and Joule heating are presented, based on data from global magnetometers, the AMPERE magnetic field data, SSUSI auroral images, and the SuperDARN radar network. Modeled Joule heating and auroral heating of the IT system are mostly controlled by external driving in the March 2013 and 2015 storms, while NO cooling persists into the storm recovery phase. The total heating in the model is about 1000 GW to 3000 GW. Additionally, we intercompare contributions in selected energy channels for five coronal mass ejection-type storms modeled with GITM. Modeled auroral heating shows reasonable agreement with AMIE hemispheric power and is higher than other observational proxies. Joule heating and infrared cooling are likely underestimated in GITM. We discuss challenges and discrepancies in estimating and global modeling of the IT energy partitioning, especially Joule heating, during geomagnetic storms. [ABSTRACT FROM AUTHOR]

We present the first complex network theory-based analysis of high-latitude total electron content (TEC) data, including dependencies on interplanetary magnetic field (IMF) clock angle and hemisphere. We examine several network measures to quantify the spatiotemporal correlation patterns in the TEC data for winter and summer months in 2016. We find that significant structure exists in the correlation patterns, distinguishing the dayside and nightside ionosphere, and specific features in the high latitudes such as the polar cap and auroral oval, including the cusp and ionospheric foot points of magnetospheric boundary layers. These features vary with the IMF, exhibiting a strong dependence on the north-south direction and generally larger variations during the winter months in both hemispheres. Our exploratory results suggest that network analysis of TEC data can be used to study characteristic ionospheric spatial scales at high latitudes, thereby extending the utility of these data. We explore mesoscale and large scale (greater than tens of kilometers and greater than hundreds of kilometers, respectively) as a function of winter/summer season, hemisphere, and IMF direction and conclude that the relative importance of different ionospheric scales is not a constant relationship. Together with an identification of important areas of future work, our findings provide a foundation for the application of network analysis techniques to ionospheric TEC. Our results suggest that network analysis can reveal new physical connections in the ionospheric system. [ABSTRACT FROM AUTHOR]

Abstract: Scientific knowledge is acquired in geophysics generally without the benefit of controlled experiments. In this paper, we discuss how scientific inference based on observations occurs in geophysical contexts. We develop a specific approach that uses approximate simultaneity of proposed cause and effect phenomena to infer causality. The approach applies equally well to effect phenomena that follow the cause with a known time delay. We find that, in general, establishing a causal relationship between two phenomena based on simultaneity requires knowledge of how often simultaneity of these phenomena occurs in the absence of causality. We then extend the discussion to using numerical simulations in the scientific inference process. Numerical simulations of physical processes, because they can simulate the values of observations, are often used to infer what physical processes are occurring in nature. We discuss agreement between model output and observations as a basis for inferring the physical processes underlying the observations. We find that an important factor to consider, which we here call the “confusion factor,” is how often it may occur that insufficient model representations of the physical processes nevertheless lead to agreement between model computations and observations. We suggest that models of intermediate or low complexity may have a significant role to play when using geophysical simulations to reach scientific conclusions. [ABSTRACT FROM AUTHOR]