Uncertainty quantification of the DTM2020 thermosphere model

Aims The semi-empirical Drag Temperature Models (DTM) calculate the Earth's upper atmosphere's temperature, density, and composition. They were applied mainly for spacecraft orbit computation. We developed an uncertainty tool that we implemented in the DTM2020 thermosphere model. The model is assessed and compared with the recently HASDM neutral density released publicly in 2020. Methods The total neutral density dataset covers all high-resolution CHAMP, GRACE, GOCE, and SWARM data spanning almost two solar cycles. We constructed the uncertainty model using statistical binning analysis and least-square fitting techniques, allowing the development of a global sigma error model to function the main variabilities driving the thermosphere state. The model is represented mathematically by a nonlinear manifold approximation in a 6-D space parameter. Results The results reveal that the altitude parameter presents the most notable error range during quiet and moderate magnetic activity ( [[EQUATION]] ). However, the most considerable uncertainty appears during severe or extreme geomagnetic activities. The comparison with density data provided by the SET HASDM database highlights some coherent features on the mechanisms occurring in the thermosphere. Moreover, it confirms the tool's relevance to provide a qualitative database of neutral densities uncertainties values deduced from the DTM2020 model.

Accurate 3D fireball trajectory and orbit calculation using the 3D-FireTOC automatic Python code

The disruption of asteroids and comets produces cm-sized meteoroids that end up impacting the Earth’s atmosphere and producing bright fireballs that might have associated shock waves or, in geometrically-favorable occasions excavate craters that put them into unexpected hazardous scenarios. The astrometric reduction of meteors and fireballs to infer their atmospheric trajectories and heliocentric orbits involves a complex and tedious process that generally requires many manual tasks. To streamline the process, we present a software package called SPMN 3D Fireball Trajectory and Orbit Calculator (3D-FireTOC), an automatic Python code for detection, trajectory reconstruction of meteors, and heliocentric orbit computation from video recordings. The automatic 3D-FireTOC package comprises of a user interface and a graphic engine that generates a realistic 3D representation model, which allows users to easily check the geometric consistency of the results and facilitates scientiï¬c content production for dissemination. The software automatically detects meteors from digital systems, completes the astrometric measurements, performs photometry, computes the meteor atmospheric trajectory, calculates the velocity curve, and obtains the radiant and the heliocentric orbit, all in all quantifying the error measurements in each step. The software applies corrections such as light aberration, refraction, zenith attraction, diurnal aberration and atmospheric extinction. It also characterizes the atmospheric flight and consequently determines fireball fates by using the α − β criterion that analyses the ability of a fireball to penetrate deep into the atmosphere and produce meteorites. We demonstrate the performance of the software by analyzing two bright fireballs recorded by the Spanish Fireball and Meteorite Network (SPMN).

Calibration of fish-eye lens and error estimation on fireball trajectories: application to the FRIPON network

Context. Fireball networks are developing over the whole planet, with the aim of recovering meteorites and at the same time determining their orbits. The ultimate goal of such networks is to identify the parent bodies of meteorite families to achieve this, orbit accuracy is critical. Yet, the determination of an orbit relies on a long and complex reduction process including: (1) astrometry, with heavy distortion for fish-eye lenses, (2) estimation of the external bias on the observation, (3) fit of the trajectory, (4) deceleration model, and (5) actual orbit computation. Aims. Our goal is to compute accurate trajectories with an estimate of internal and external errors as realistic as possible, taking advantage of the dense observation network FRIPON (Fireball Recovery and InterPlanetary Observation Network), which comprises more than 100 cameras in France and Europe. In particular, we pay special attention to the distortion of images due to fish-eye lenses. In the present paper, we describe the analytical protocol that allows us to compute trajectories and their uncertainties. Methods. We developed a general distortion model to be used on the FRIPON fish-eye cameras. Such a model needs to be accurate even at low elevation, as most fireball observations are performed low on the horizon. The radial distortion is modelled by a nine-degree odd polynomial, hence by five parameters. In addition, we used three parameters to describe the geometry of the camera and two for non-symmetrical distortion. Lastly, we used a new statistical method taking systematic errors into account, which allows us to compute realistic confidence intervals. We tested our method on a fireball that fell on 2017-08-94 UT 00:06. Results. The accuracy of our astrometrical model for each camera is 2 arcmin (1σ), but the internal error on the fireball of 2017-08-94 UT 00:06 measurement is 0.7 arcmin (better than 1/10 pixel). We developed a method to estimate the external error considering that each station is independent and found it equal to 0.8 arcmin. Real residuals are coherent with our estimation of internal and external error for each camera, which confirms the internal consistency of our method. We discuss the advantages and disadvantages of this protocol.

Optimizing asteroid orbit computation forGaiawith normal points

Context.In addition to the systematic observations of known solar-system objects (SSOs), a continuous processing of new discoveries requiring fast responses is implemented as the short-term processing ofGaiaSSO observations, providing alerts for ground-based follow-up observers. The common independent observation approach for the purposes of orbit computation has led to unrealistically large ephemeris prediction uncertainties when processing realGaiadata.Aims.We aim to provide ground-based observers with a cloud of sky positions that is shrunk to a fraction of the previously expected search area by making use of the characteristic features ofGaiaastrometry. This enhances the efficiency ofGaiaSSO follow-up network and leads to an increased rate of asteroid discoveries with reasonably constrained orbits with the help of ground-based follow-up observations ofGaiaasteroids.Methods.We took advantage of the separation of positional errors ofGaiaSSO observations into a random and systematic component. We treated theGaiaobservations in an alternative way by collapsing up to ten observations that correspond to a single transit into a single so-called normal point. We implemented this input procedure in theGaiaSSO short-term processing pipeline and the OpenOrb software.Results.We validate our approach by performing extensive comparisons between the independent observation and normal point input methods and compare them to the observed positions of previously known asteroids. The new approach reduces the ephemeris uncertainty by a factor of between three and ten compared to the situation where each point is treated as a separate observation.Conclusions.Our new data treatment improves the sky prediction for theGaiaSSO observations by removing low-weight orbital solutions. These solutions originate from excessive curvature of observations, introduced by short-term variations ofGaiaattitude on the one hand, and, as a main effect, shrinking of systematic error bars in the independent observation case on the other hand. We anticipate that a similar approach may also be utilized in a situation where observations from a single observatory dominate.

Short arc orbit determination and imminent impactors in the Gaia era

Short-arc orbit determination is crucial when an asteroid is first discovered. In these cases usually the observations are so few that the differential correction procedure may not converge. We developed an initial orbit computation method, based on systematic ranging, which is an orbit determination technique that systematically explores a raster in the topocentric range and range-rate space region inside the admissible region. We obtained a fully rigorous computation of the probability for the asteroid that could impact the Earth within a few days from the discovery without any a priori assumption. We tested our method on the two past impactors, 2008 TC3 and 2014 AA, on some very well known cases, and on two particular objects observed by the European Space Agency Gaia mission.