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.

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.

Prior to use in operational systems, it is essential to validate ionospheric models in a manner relevant to their intended application to ensure satisfactory performance. For Over-the-Horizon radars (OTHR) operating in the high-frequency (HF) band (3-30 MHz), the problem of model validation is severe when used in Coordinate Registration (CR) and Frequency Management Systems (FMS). It is imperative that the full error characteristics of models is well understood in these applications due to the critical relationship they impose on system performance. To better understand model performance in the context of OTHR, we introduce an ionospheric model validation technique using the oblique ground backscatter measurements in soundings from the Super Dual Auroral Radar Network (SuperDARN). Analysis is performed in terms of the F-region leading edge (LE) errors and assessment of range-elevation distributions using calibrated interferometer data. This technique is demonstrated by validating the International Reference Ionosphere (IRI) 2016 for January and June in both 2014 and 2018. LE RMS errors of 100-400 km and 400-800 km are observed for winter and summer months, respectively. Evening errors regularly exceeding 1,000 km across all months are identified. Ionosonde driven corrections to the IRI-2016 peak parameters provide improvements of 200-800 km to the LE, with the greatest improvements observed during the nighttime. Diagnostics of echo distributions indicate consistent underestimates in model NmF2 during the daytime hours of June 2014 due to offsets of -8° being observed in modelled elevation angles at 18:00 and 21:00 UT.

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.

Lobe reconnection is usually thought to play an important role in geospace dynamics only when the Interplanetary Magnetic Field (IMF) is mainly northward. This is because the most common and unambiguous signature of lobe reconnection is the strong sunward convection in the polar cap ionosphere observed during these conditions. During more typical conditions, when the IMF is mainly oriented in a dawn-dusk direction, plasma flows initiated by dayside and lobe reconnection both map to high latitude ionospheric locations in close proximity to each other on the dayside. This makes the distinction of the source of the observed dayside polar cap convection ambiguous, as the flow magnitude and direction are similar from the two topologically different source regions. We here overcome this challenge by normalizing the ionospheric convection observed by the Super Dual Aurora Radar Network (SuperDARN) to the polar cap boundary, inferred from simultaneous observations from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). This new method enable us to separate and quantify the relative contribution of both lobe reconnection and dayside/nightside (Dungey cycle) reconnection during periods of dominating IMF By. Our main findings are twofold. First, the lobe reconnection rate can typically account for 20% of the Dungey cycle flux transport during local summer when IMF By is dominating and IMF Bz > 0. Second, the dayside convection relative to the open/closed boundary is vastly different in local summer versus local winter, as defined by the dipole tilt angle.