AbstractPhysics‐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.

The refilling of the plasmasphere following geomagnetic storms remains one of the longstanding and interesting problems in ionosphere–magnetosphere coupling research. The objective of this paper is the formulation and development of a one-dimensional (1D) refilling model using the flux-corrected transport method, a numerical method that is well-suited to handling problems with shocks and discontinuities. In this paper, the developed methodology has been validated against exact, analytical benchmarks, and good agreement has been obtained between these analytical benchmarks and numerical results. The objective of this research is the development of a three-dimensional (3D) multi-ion model for ionosphere–magnetosphere coupling problems in open and closed line geometries.

The objective of this paper is the development of a kinetic model for plasmasphere refilling following geomagnetic storms. The kinetic model is based on the “particle‐in‐cell” method, a method based on the simulation of particle motion and thus well suited to high altitude, low‐density regimes, where the plasma transport equations are not valid. The model was validated with exact, analytical benchmarks, which are provided in this paper. The refilling results obtained from the kinetic model were then compared with results from a recently developed hydrodynamic solution methodology based on the “flux‐corrected transport” method, and the limitations of hydrodynamic modeling for low‐density flow at high altitudes were explored.

The objective of this paper is the application of a newly developed flux-corrected transport based hydrodynamic solution methodology to the plasmasphere refilling problem following a geomagnetic storm. The flux-corrected transport method is extremely well-suited to the solution of nonlinear partial differential equations with shocks and discontinuities. In this solution methodology, every ion species is modeled as two separate fluids originating from the northern and southern hemispheres. We present refilling results that include three ion (H+, He+, and O+) species and two neutrals (H and O). We believe that with additional modifications, the model can be adapted to the solution of other ionosphere-magnetosphere coupling problems. Plain Language Summary The paper applies a newly developed multispecies hydrodynamic model to the plasmasphere refilling problem following geomagnetic storms. We believe that with additional development, the model can be applied to other ionosphere-magnetosphere coupling problems.

Much theoretical and observational work has been devoted to studying the occurrence of F region polar cap patches in the Northern Hemisphere; considerably less work has been applied to the Southern Hemisphere. In recent years, the Madrigal database of mappings of total electron content (TEC) has improved in Southern Hemisphere coverage, to the point that we can now carry out a study of patch frequency and occurrence. We find that Southern Hemisphere patch occurrence is very similar to that of the Northern Hemisphere with a half‐year offset, plus an offset in universal time of approximately 12 hr. This is further supported by running an ionospheric model for both hemispheres and applying the same patch‐to‐background technique. Further, we present a simple physical mechanism involving a sunlit dayside plasma source concurrent with a dark polar cap, which yields a patch‐to‐background pattern very much like that seen in the TEC mappings for both hemispheres.

To address challenges of assessing space weather modeling capabilities, the Community Coordinated Modeling Center is leading a newly established International Forum for Space Weather Modeling Capabilities Assessment. This paper presents preliminary results of validation of modeled foF2 (F2 layer critical frequency) and TEC (total electron content) during the first selected 2013 March storm event (17 March 2013). In this study, we used eight ionospheric models ranging from empirical to physics‐based, coupled ionosphere‐thermosphere and data assimilation models. The quantities we considered are TEC and foF2 changes and percentage changes compared to quiet time background, and the maximum and minimum percentage changes. In addition, we considered normalized percentage changes of TEC. We compared the modeled quantities with ground‐based observations of vertical Global Navigation Satellite System TEC (provided by Massachusetts Institute of Technology Haystack Observatory) and foF2 data (provided by Global Ionospheric Radio Observatory) at the 12 locations selected in middle latitudes of the American and European‐African longitude sectors. To quantitatively evaluate the models' performance, we calculated skill scores including correlation coefficient, root‐mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (yield), and timing error. Our study indicates that average RMSEs of foF2 range from about 1 MHz to 1.5 MHz. The average RMSEs of TEC are between ~5 and ~10 TECU (1 TEC Unit = 1016 el/m2). dfoF2[%] RMSEs are between 15% and 25%, which is smaller than RMSE of dTEC[%] ranging from 30% to 60%. The performance of the models varies with the location and metrics considered.

Space weather deposits energy into the high polar latitudes, primarily via Joule heating that is associated with the Poynting flux electromagnetic energy flow between the magnetosphere and ionosphere. One way to observe this energy flow is to look at the ionospheric electron density profile (EDP), especially that of the topside. The altitude location of the ionospheric peak provides additional information on the net field‐aligned vertical transport at high latitudes. To date, there have been few studies in which physics‐based ionospheric model storm simulations have been compared with topside EDPs. A rich database of high‐latitude topside ionograms obtained from polar orbiting satellites of the International Satellites for Ionospheric Studies (ISIS) program exists but has not been utilized in comparisons with physics‐based models. Of specific importance is that the Alouette/ISIS topside EDPs spanned the timeframe from 1962 to 1983, a period that experienced very large geomagnetic storms. We use a physics‐based ionospheric model, the Utah State University Time Dependent Ionospheric Model (TDIM), to simulate ionospheric EDPs for quiet and storm high‐latitude passes of ISIS‐II for two geomagnetic storms. This initial study finds that under quiet conditions there is good agreement between model and observations. During disturbed conditions, however, a large difference is seen between model and observations. The model limitation is probably associated with the inability of its topside boundary to replicate strong outflow conditions. As a result, modeling of the ionospheric outflows needs to be extended well into the magnetosphere, thereby moving the upper boundary much higher and requiring the use of polar wind models.

The Utah State University Global Assimilation of Ionospheric Measurements‐Gauss Markov model has been used to investigate the distribution of ionospheric plasma during storm times over the continental United States. Storm periods dramatically increase the effects of space weather on the ionosphere and upper atmosphere, leading to impacts on over‐the‐horizon radars, Global Positioning System location determination, spacecraft charging, power grid overloads, and disruption of the Federal Aviation Administration Wide Area Augmentation System to name a few. Four storm periods were investigated where strong storm‐enhanced densities (SEDs) were present: two strong, October 2003 and November 2003, and two moderate, August 2010 and August 2011. It was found that a fundamental difference in the SED formation exists between the strong and moderate storms. For the strong storms, the SED was formed from the plasma in the northern equatorial anomaly crest, with the plasma in the SED channel lifting the closer it came to the high latitudes. For the moderate storms, the SED appeared to be unconnected to the northern anomaly crest but was rather produced locally in the SED channel, along with no corresponding increase in layer height associated with the SED evident in the model.

We have used total electron content (TEC) values from low, middle, and high latitudes recorded over the American continent and density and ion temperature measured in situ by the DMSP-F15 and F17 satellites during the geomagnetic storms of 3-4 August 2010 and 5-6 August 2011 to study the formation and dynamics of plasma density enhancements that developed during these two storms. Common to both storms are the timing of the main phase that extends between 20 and 24 UT and their seasonality with both storms occurring near the end of the Northern Hemisphere summer solstice. During both storms, TEC data show incipient equatorial anomalies lacking a poleward expansion beyond 20 degrees magnetic latitude. Two large-scale TEC enhancements were observed at middle latitudes showing a complicated pattern of structuring and merging. The first TEC enhancement corresponds to a storm-enhanced density (SED) seen between 21 and 01 UT on the following day. The second TEC enhancement was observed over Central America, located equatorward of the SED and apparently moving northward. However, careful analysis of the TEC values indicates that this second TEC enhancement is not transported from lower latitudes through a superfountain effect. Instead, the enhanced plasma has a local origin and is driven by a southward directed meridional wind that moves plasma up the tilted magnetic field lines. DMSP flights passing over the second TEC enhancement show a reduction of the ion temperature, confirming an adiabatic expansion of the plasma as it moves up the field lines. It is concluded that the midlatitude TEC enhancements do not arise from a low-latitude ionospheric fountain effect.

A new field-aligned current system in the high-latitude ionosphere, the terminator field-aligned currents, was recently discovered by Zhu et al. (2014). A series of modeling, observational, and theoretical studies need to be performed in order to get a full picture of the behavior and properties of this newly discovered current system, understand the underlying physics, and explore its effects on the electrodynamics and plasma dynamics of the high-latitude ionosphere. As a first step in this direction, we performed a systematic study on the seasonal, solar, and geomagnetic dependencies of the general properties of the terminator field-aligned currents. The study was conducted by using a physics-based data assimilation model, Ionospheric Dynamics and Electrodynamics Data Assimilation (IDED-DA) Model, with the ingestion of observational data.

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 = 10 16 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.

The Heliophysics community must have a quantitative, predictive understanding of the dynamically variable escape of gravitationally trapped volatile matter from atmospheres, driven by energetic processes. This loss depletes atmospheres of selected constituents, causing dramatic changes in bulk surface pressure as well as composition, as has perhaps occurred most dramatically at Mars. In geospace, the process dissipates solar wind energy to produce ionospheric outflows that feed back on dynamics of the solar wind interaction with Earth. Proposed mechanisms include the upward ambipolar electric field associated with electron heating, Joule heating, wave-particle electron and ion heating interactions, and ponderomotive effects. It is unclear if waves interact with particles primarily in a cyclotron resonant mode, in a lower hybrid exchange of electron and ion energy, or in a bulk ponderomotive mode. Future studies will require observation of magnetospheric and thermospheric boundary conditions applied to the exobase transition region, and the response of atmospheric gas, ions, and electrons to the ensuing battle between energetic forcing, collisional dissipation, and gravity. Such studies will determine the mechanisms of energetic mass escape and the degree to which planetary mass loss is drawn from above by energetic evacuation or driven from below by energetic pressurization.

A growing number of global magnetohydrodynamic (MHD) simulations of the Earth's magnetosphere have included some form of ionospheric outflow at the inner boundary. This has been done either using a classical polar wind approach, where only pressure gradient and ambipolar forces are considered, or with a subset of the non-classical polar wind, where a plethora of acceleration mechanisms create a faster, more oxygen-rich polar wind. This study is the first to couple a robust, complete treatment of the classical and non-classical polar wind to a global magnetosphere model. The Generalized Polar Wind (GPW) model is used to drive oxygen and hydrogen outflow in the Block Adaptive Tree Solar wind Roe-type Upwind Scheme (BATS-R-US) model. A synthetic storm is simulated, and results are compared to simulations using classic polar wind approximations. It is found that the additional oxygen outflow provided by GPW has a number of important effects on storm dynamics, ranging from ring current energization to tail mass-loading prior to substorm onset. These results are discussed in the context of other approaches to include outflow in global models. It is found that the geoeffectiveness of outflowing subpopulations, such as dayside cusp or nightside auroral outflow, is dependent on the others, leading to a more complex magnetospheric response compared to previous studies that used idealized outflow prescriptions from only a single source region.

Ion outflow from the Earth's ionosphere was first proposed in the mid 1960s. Since then, a myriad of measurements and numerical simulations have clearly established that ion outflow (O+, H+) is an important ionosphere-magnetosphere coupling mechanism. The heavy O+ ions have been observed in several regions of the magnetosphere, including the plasma sheet, lobe, and distant tail, and they have been shown to significantly affect magnetospheric processes. To fully understand the effect of ion outflow on the magnetosphere, it is important to establish the conditions under which the outflow is possible, the spatial distribution of the outflow, and the energy distribution of the escaping ions. These issues have been extensively studied during the last four decades, and the results appear in an extensive literature. Here, the focus is on the modeling associated with plasma outflow from the Earth's ionosphere. The paper is based on a Yosemite 2014 presentation and covers past (Classical Polar Wind), present (Generalized Polar Wind), and future (anticipated) ion outflow modeling efforts.

The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and middle to low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

To address challenges of assessment of modeling capabilities, the CCMC (Community Coordinated Modeling Center) initiated a series of community-wide model validation projects, such as the GEM, CEDAR and GEM-CEDAR Modeling Challenges. The CEDAR ETI (Electrodynamics Thermosphere Ionosphere) Challenge focused on the ability of ionosphere-thermosphere (IT) models to reproduce basic IT system parameters, such as electron and neutral densities, NmF2, hmF2, and TEC. Model-data time series comparisons were performed for a set of selected events with different levels of geomagnetic activity (quiet, moderate, storms). The follow-on CEDAR-GEM Challenge aims to quantify geomagnetic storm impacts on the IT system. On-going studies include quantifying the storm energy input, such as increase in auroral precipitation and Joule heating, and quantifying the storm-time variations of neutral density and TEC. The community-wide model validation activities involve international collaborations (e.g., between the CCMC and UK Met Office) to enhance the studies. In this paper, we focus on results of validation of IT models for reproducing storm impacts on TEC. In order to quantify storm impacts on TEC, we considered several parameters: TEC changes compared to quiet time (the day before storm), TEC difference between 24-hour intervals, and maximum increase/decrease during the storm. We investigated the spatial and temporal variations of the parameters during storm events (e.g., 2006 AGU storm) using ground-based GPS TEC measurements in several longitude sectors where data coverage is relatively better. The latitudinal variations were also studied. We obtained modeled TEC from various IT models. The parameters from the models were compared with each other and with the observed values. We quantified performance of the models in reproducing the TEC variations during the storm using skill scores. Model output and observational data used for the challenge will be permanently posted at the CCMC website (http://ccmc.gsfc.nasa.gov) as a resource for the space science communities to use.