It is well-known that equatorial plasma bubbles (EPBs) are highly correlated to the post-sunset rise of the ionosphere on a climatological basis. However, when proceeding to the daily EPB development, what controls the day-to-day/longitudinal variability of EPBs remains a puzzle. In this study, we investigate the underlying physics responsible for the day-to-day/longitudinal variability of EPBs using the Sami3 is A Model of the Ionosphere (SAMI3) and the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X). Simulation results on October 20, 22, and 24, 2020 were presented. SAMI3/WACCM-X self-consistently generated midnight EPBs on October 20 and 24, displaying irregular and regular spatial distributions, respectively. However, EPBs are absent on October 22. We investigate the role of gravity waves on upwelling growth and EPB development and discuss how gravity waves contribute to the distributions of EPBs. Of particular significance is that we found the westward wind associated with solar terminator waves and gravity waves causes midnight vertical drift enhancement and collisional shear instability, which provides conditions favorable for upwelling growth and EPB development. The converging and diverging winds associated with solar terminator waves and midnight temperature maximum also affect the longitudinal distribution of EPBs. The absence of EPBs on October 22 is related to the weak upward drift induced by weak westward wind associated with solar terminator waves.

The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum usable ionospheric frequency foF2 and the propagation factor M(3000)F2. At the U.S. Naval Research Laboratory (NRL), a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.

A novel model called PyIRI was recently developed. It offers a fully Python alternative to the widely used FORTRAN International Reference Ionosphere (IRI) model to construct the ionospheric electron density for the entire day and on the entire global grid in one computation, which has a significantly lower computational overhead. PyIRI introduced a novel approach to the computation of the global and diurnal functions and their matrix multiplication with Consultative Committee on International Radio (CCIR) coefficients, that enabled this global approach for the density specification. Since the IRI-based Real-Time Assimilative Model (IRTAM) produces coefficients in a similar format as CCIR coefficients, the PyIRI software was extended to be able to work with IRTAM coefficients using the same computationally efficient approach. This technical note describes the PyIRTAM software and shows examples of how to use it. PyIRTAM is 21 times more efficient than the classical IRTAM. PyIRTAM tool is made publicly available.

A novel Python module called PyIRTAM was developed in addition to the previously released PyIRI model. The PyIRI computational approach was extended to work with Real-Time Assimilative Model (IRTAM) coefficients. This enables global approach to the density specification, utilizing computation of the global and diurnal functions and their multiplication with coefficients in the matrix form. PyIRTAM tool is made publicly available through PyPI and GitHub.

ANCHOR is a novel assimilative model developed at the U.S. Naval Research Laboratory. It extracts ionospheric parameters from RO and ionosonde data and assimilates them as point measurements into the maps of the background parameters using Kalman Filter approach. This paper introduces the ANCHOR algorithm, discusses its coordinate system and background, explains the background covariance formation, discusses the extraction of the ionospheric parameters from the data and the assimilation process, and, finally, shows the results of the observing system simulation experiment.

The Ionospheric Data Assimilation Four-Dimensional (IDA4D) technique has been coupled to Sami3 is Another Model of the Ionosphere (SAMI3). In this application, ground- and space-based GPS Total Electron Content (TEC) data have been assimilated into SAMI3, while in situ electron densities, autoscaled ionosonde NmF2 and reference GPS stations have been used for validation. IDA4D/SAMI3 shows that Night-time Ionospheric Localized Enhancements (NILE) are formed following geomagnetic storms in November 2003 and August 2018. The NILE phenomenon appears as a moderate, longitudinally extended enhancement of NmF2 at 30-40o N MLAT, occurring in the late evening (20-24 LT) following much larger enhancements of the equatorial anomaly crests in the main phase of the storms. The NILE appears to be caused by upward and northward plasma transport around the dusk terminator, which is consistent with eastward polarization electric fields. Independent validation confirms the presence of the NILE, and indicates that IDA4D is effective in correcting random errors and systematic biases in SAMI3. In all cases, biases and root-mean-square errors are reduced by the data assimilation, typically by a factor of 2 or more. During the most severe part of the November 2003 storm, the uncorrected ionospheric error on a GPS 3D position at 1LSU (Louisiana) is estimated to exceed 34 m. The IDA4D/SAMI3 specification is effective in correcting this down to 10-m.

Whole atmosphere models that fully capture the propagation of wave dynamics from lower to upper atmosphere are believed sufficient to reproduce the type of short-term variability in the neutral upper atmosphere that produces observed variations in ionospheric parameters. However, recent studies suggest that upper atmospheric observations are needed to accurately represent short-term variability in both planetary-scale mass transport and tidal behavior crucial to representing the structure of the thermosphere and the wind-dynamo coupling in the ionosphere. To address this, we use atmospheric specifications from the prototype High-Altitude Navy Global Environmental Model (HA-NAVGEM) from the ground to 92 km to nudge the Whole Atmosphere Community Climate Model extended version (WACCM-X) coupled to the Navy Highly Integrated Thermosphere Ionosphere Demonstration System (Navy-HITIDES) ionospheric model. The HA-NAVGEM data assimilation/forecast system is run in two configurations: a reference experiment for the time period December 2012-March 2013, where satellite-based middle atmospheric observations (SABER temperature retrievals; Aura MLS temperature, ozone, and water vapor retrievals; and SSMIS microwave radiances) are included between 20-90 km; and a perturbed experiment, during the same time period, in which the middle atmospheric observations are removed. The resulting nudged simulations using WACCM-X coupled to Navy-HITIDES are used to study the impact of upper atmospheric observations in reproducing the observed short-term variability in the thermosphere-ionosphere system, both in terms of the thermospheric structure and the ionospheric response via wind-dynamo coupling. The role of solar thermal and lunar gravitational tides is discussed, as well as the impact of observations on the weather of the day in the lower thermosphere.

A newly-released, novel ionospheric dataset of global gridded vertical total electron content (VTEC) is introduced in this paper. This VTEC dataset, 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 dataset (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 has 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 a 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 dataset provides measurements in regions that are not well covered by ground-based GPS measurements, such as over oceans and over central Africa.