Using the local ensemble transform Kalman filter for upper atmospheric modelling

The Advanced Ensemble electron density (Ne) Assimilation System (AENeAS) is a new data assimilation model of the ionosphere/thermosphere. The background model is provided by the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) and the assimilation uses the local ensemble transform Kalman filter (LETKF). An outline derivation of the LETKF is provided and the equations are presented in a form analogous to the classic Kalman filter. An enhancement to the efficient LETKF implementation to reduce computational cost is also described. In a 3 day test in June 2017, AENeAS exhibits a total electron content (TEC) RMS error of 2.1 TECU compared with 5.5 TECU for NeQuick and 6.8 for TIE-GCM (with an NeQuick topside)

Using extreme value theory for determining the probability of carrington‐like solar flares

By their very nature, extreme space weather events occur rarely and, therefore, statistical methods are required to determine the probability of their occurrence. Space weather events can be characterised by a number of natural phenomena such as X‐ray (solar) flares, solar energetic particle (SEP) fluxes, coronal mass ejections and various geophysical indices (Dst, Kp, F10.7). In this paper extreme value theory (EVT) is used to investigate the probability of extreme solar flares. Previous work has assumed that the distribution of solar flares follows a power law. However such an approach can lead to a poor estimation of the return times of such events due to uncertainties in the tails of the probability distribution function. Using EVT and GOES X‐ray flux data it is shown that the expected 150‐year return level is approximately an X60 flare whilst a Carrington‐like flare is a one in a 100‐year event. In the worst case the 150‐year return level is an X90 flare whist a Carrington flare is a one in 30‐year event. It is also shown that the EVT results are consistent with flare data from the Kepler space telescope mission

Using WACCM-X neutral densities for orbital propagation:Challenges and solutions

Atmospheric drag is a major perturbation in Low Earth Orbit (LEO). The neutral density obtained from atmospheric models is a major source of uncertainty in drag calculations and therefore orbital propagation in LEO. Many atmospheric models are available, with fast empirical models most commonly used. We explore the challenges and benefits of using numerical models, specifically the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) as part of the Community Earth System Model (CESM). Numerical models provide higher resolution of thermospheric structures, along with more accurate neutral density forecasts through assimilative models such as the Advanced Ensemble electron Density Assimilation System (AENeAS). Solutions are presented to overcome the challenges of using numerical models for neutral densities

On the use of multi-model ensemble techniques for ionospheric and thermospheric characterisation

Space weather can have a negative impact on a number of radio frequency (RF) systems, with mitigation by ionospheric and thermospheric modelling one approach to improving system performance. However, before a model can be adopted operationally its performance must be quantified. Taylor diagrams, which show a model’s standard deviation and correlation, have been extended to further illustrate the model’s bias, standard deviation of error and mean square error in comparison to observational data. By normalising the statistics, multiple parameters can be shown simultaneously for a number of models. Using these modified Taylor diagrams, the first known long term (one month) comparison of three model types – empirical, physics and data assimilation - has been performed. The data assimilation models performed best, offering a statistically significant improvement in performance. One physics model performed sufficiently well that it is a viable background model option in future data assimilation schemes. Finally, multi-model thermospheric ensembles (MMEs) have been constructed from which the thermospheric forecasts exhibited a reduced root mean square error compared to non-ensemble approaches. Using an equally weighted MME the reduction was 55% and using a mean square error weighted approach the reduction was 48%

What to Do When the F10.7 Goes Out?

The solar radio flux at 10.7 cm, known as F10.7, is a critical operational space weather index. However, without a clear backup, any interruption to the service can result in substantial errors in model outputs. In this paper we show the impact of one such outage in March 2022 on the models TIE-GCM and NeQuick, and present a number of alternative solutions that could be used for future outages. The analysis is extended to the F10.7 time series since 1951 and the approach resulting in the smallest reconstruction error of F10.7 uses the solar radio flux observations at alternative wavelengths (the best giving a percentage error of 3.1%). Alternatively, use of Sunspot Number, a regular, robust alternative observation, results in a mean percentage error of 8.2% and is also a reliable fallback solution. Additionally, analysis of the error on the use of the conversion between the 12-month rolling sunspot number (R12) and its conversion to F10.7 is included

Improved forecasting of thermospheric densities using multi-model ensembles

This paper presents the first known application of multi-model ensembles to the forecasting of the thermosphere. A multi-model ensemble (MME) is a method for combining different, independent models. The main advantage of using an MME is to reduce the effect of model errors and bias, since it is expected that the model errors will, at least partly, cancel. The MME, with its reduced uncertainties, can then be used as the initial conditions in a physics-based thermosphere model for forecasting. This should increase the forecast skill since a reduction in the errors of the initial conditions of a model generally increases model skill. In this paper the Thermosphere–Ionosphere Electrodynamic General Circulation Model (TIE-GCM), the US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar Exosphere 2000 (NRLMSISE-00), and Global Ionosphere–Thermosphere Model (GITM) have been used to construct the MME. As well as comparisons between the MMEs and the “standard” runs of the model, the MME densities have been propagated forward in time using the TIE-GCM. It is shown that thermospheric forecasts of up to 6 h, using the MME, have a reduction in the root mean square error of greater than 60 %. The paper also highlights differences in model performance between times of solar minimum and maximum

On the Use of SuperDARN Ground Backscatter Measurements for Ionospheric Propagation Model Validation

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 modeled elevation angles at 18:00 and 21:00 UT

Lensing from small-scale travelling ionospheric disturbances observed using LOFAR

Observations made using the LOw-Frequency ARray (LOFAR) between 10:15 and 11:48 UT on the 15th of September 2018 over a bandwidth of approximately 25-65 MHz contain discrete pseudo-periodic features of ionospheric origin. These features occur within a period of approximately 10 min and collectively last roughly an hour. They are strongly frequency dependent, broadening significantly in time towards the lower frequencies, and show an overlaid pattern of diffraction fringes. By modelling the ionosphere as a thin phase screen containing a wave-like disturbance, we are able to replicate the observations, suggesting that they are associated with small-scale travelling ionospheric disturbances (TIDs). This modelling indicates that the features observed here require a compact radio source at a low elevation and that the TID or TIDs in question have a wavelength <~30 km. Several features suggest the presence of deviations from an idealised sinusoidal wave form. These results demonstrate LOFAR-s capability to identify and characterise small-scale ionospheric structures

The interaction of Escherichia coli O157 :H7 and Salmonella Typhimurium flagella with host cell membranes and cytoskeletal components

Bacterial flagella have many established roles beyond swimming motility. Despite clear evidence of flagella-dependent adherence, the specificity of the ligands and mechanisms of binding are still debated. In this study, the molecular basis of Escherichia coli O157:H7 and Salmonella enterica serovar Typhimurium flagella binding to epithelial cell cultures was investigated. Flagella interactions with host cell surfaces were intimate and crossed cellular boundaries as demarcated by actin and membrane labelling. Scanning electron microscopy revealed flagella disappearing into cellular surfaces and transmission electron microscopy of S. Typhiumurium indicated host membrane deformation and disruption in proximity to flagella. Motor mutants of E. coli O157:H7 and S. Typhimurium caused reduced haemolysis compared to wild-type, indicating that membrane disruption was in part due to flagella rotation. Flagella from E. coli O157 (H7), EPEC O127 (H6) and S. Typhimurium (P1 and P2 flagella) were shown to bind to purified intracellular components of the actin cytoskeleton and directly increase in vitro actin polymerization rates. We propose that flagella interactions with host cell membranes and cytoskeletal components may help prime intimate attachment and invasion for E. coli O157:H7 and S. Typhimurium, respectively