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)

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

Feasibility study of a PocketQube platform to host an ionospheric impedance probe

Since the advent of CubeSat spacecraft, universities and private entities have been successfully designing and launching satellites at a fraction of the traditional cost. These satellites still accommodate useful scientific payloads. Another recently established satellite format is the PocketQube (PQ) - one eighth the size of a CubeSat – with the aim of further reducing launching costs. However, this brings with it the challenge of working with substantially smaller power, mass and volume budgets. Accurate ionospheric modelling requires the use of electron density measurements at the topside of the ionosphere which could be obtained via distributed in-situ sensing. This makes a low cost PQ constellation ideal for this application. In order to assess the feasibility of the PQ format, a preliminary study was conducted about the design of a PQ technology demonstrator capable of carrying a scientific payload. In this paper, the design approaches are discussed, keeping in mind the design budget restrictions as well as the constraints imposed by the ionospheric sensor.The research work disclosed in this publication is funded by the ENDEAVOUR Scholarship Scheme (Malta). The scholarship is part-financed by the European Union – European Social Fund (ESF) under Operational Programme II – Cohesion Policy 2014-2020, “Investing in human capital to create more opportunities and promote the well-being of societypeer-reviewe

Data ingestion and assimilation in ionospheric models

<p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Times;">Current understanding of the ionospheric behaviour has been obtained through different observations, modelling and theoretical studies. Knowledge of the ionospheric electron density distribution and its fluctuations, high quality data sets, as well as reliable data ingestion and assimilation techniques are essential for models predicting ionospheric characteristics for radio wave propagation and for other applications such as satellite tracking navigation, etc., to mitigate the ionospheric effects on radio wave propagation. Effect of the ionosphere on Global Navigation Satellites System (GNSS) accuracy is one of the main factors limiting the reliability of GNSS applications.</p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Times;">In accord with the objectives of the European COST 296 project, (Mitigation of Ionospheric Effects</p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Times;">on Radio Systems, MIERS) under an international collaboration some new results have been achieved in collecting and processing high quality ionospheric data, in adaptation of the ionospheric models to enable data ingestion and assimilation, and in validation and improvement of real-time or near-real time ionospheric ionisation electron density reconstruction techniques.</p> <br /&gt

Feasibility study of a PocketQube platform to host an ionospheric impedance probe

Since the advent of CubeSat spacecraft, universities and private entities have been successfully designing and launching satellites at a fraction of the traditional cost. These satellites still accommodate useful scientific payloads. Another recently established satellite format is the PocketQube (PQ) - one eighth the size of a CubeSat – with the aim of further reducing launching costs. However, this brings with it the challenge of working with substantially smaller power, mass and volume budgets. Accurate ionospheric modelling requires the use of electron density measurements at the topside of the ionosphere which could be obtained via distributed in-situ sensing. This makes a low cost PQ constellation ideal for this application. In order to assess the feasibility of the PQ format, a preliminary study was conducted about the design of a PQ technology demonstrator capable of carrying a scientific payload. In this paper, the design approaches are discussed, keeping in mind the design budget restrictions as well as the constraints imposed by the ionospheric sensor.The research work disclosed in this publication is funded by the ENDEAVOUR Scholarship Scheme (Malta). The scholarship is part-financed by the European Union – European Social Fund (ESF) under Operational Programme II – Cohesion Policy 2014-2020, “Investing in human capital to create more opportunities and promote the well-being of societypeer-reviewe