Critical issues in ionospheric data quality and implications for scientific studies

Ionospheric data are valuable records of the behavior of the ionosphere, solar activity, and the entire Sun-Earth system. The data are critical for both societally important services and scientific investigations of upper atmospheric variability. This work investigates some of the difficulties and pitfalls in maintaining long-term records of geophysical measurements. This investigation focuses on the ionospheric parameters contained in the historical data sets within the National Oceanic and Atmospheric Administration National Geophysical Data Center and Space Physics Interactive Data Resource databases. These archives include data from approximately 100 ionosonde stations worldwide, beginning in the early 1940s. Our study focuses on the quality and consistency of ionosonde data accessible via the primary Space Physics Interactive Data Resource node located within the National Oceanic and Atmospheric Administration National Geophysical Data Center and the World Data Center for Solar-Terrestrial Physics located in Boulder, Colorado. We find that, although the Space Physics Interactive Data Resource archives contained an impressive amount of high-quality data, specific problems existed involving missing and noncontiguous data sets, long-term variations or changes in methodologies and analysis procedures used, and incomplete documentation. The important lessons learned from this investigation are that the data incorporated into an archive must have clear traceability back to the primary source, including scientific validation by the contributors, and that the historical records must have associated metadata that describe relevant nuances in the observations. Although this report only focuses on historical ionosonde data in National Oceanic and Atmospheric Administration databases, we feel that these findings have general applicability to environmental scientists interested in using long-term geophysical data sets for climate and global change research.Peer ReviewedPostprint (published version

Pioneer 10 Doppler data analysis: disentangling periodic and secular anomalies

This paper reports the results of an analysis of the Doppler tracking data of Pioneer probes which did show an anomalous behaviour. A software has been developed for the sake of performing a data analysis as independent as possible from that of J. Anderson et al. \citep{anderson}, using the same data set. A first output of this new analysis is a confirmation of the existence of a secular anomaly with an amplitude about 0.8 nms$^{-2}$ compatible with that reported by Anderson et al. A second output is the study of periodic variations of the anomaly, which we characterize as functions of the azimuthal angle $\varphi$ defined by the directions Sun-Earth Antenna and Sun-Pioneer. An improved fit is obtained with periodic variations written as the sum of a secular acceleration and two sinusoids of the angles $\varphi$ and $2\varphi$. The tests which have been performed for assessing the robustness of these results are presented.Comment: 13 pages, 6 figures, minor amendment

Toward an improved representation of middle atmospheric dynamics thanks to the ARISE project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions

CEDAR Electrodynamics Thermosphere Ionosphere (ETI) Challenge for systematic assessment of ionosphere/thermosphere models: Electron density, neutral density, NmF2, and hmF2 using space based observations

In an effort to quantitatively assess the current capabilities of Ionosphere/Thermosphere (IT) models, an IT model validation study using metrics was performed. This study is a main part of the CEDAR Electrodynamics Thermosphere Ionosphere (ETI) Challenge, which was initiated at the CEDAR workshop in 2009 to better comprehend strengths and weaknesses of models in predicting the IT system, and to trace improvements in ionospheric/thermospheric specification and forecast. For the challenge, two strong geomagnetic storms, four moderate storms, and three quiet time intervals were selected. For the selected events, we obtained four scores (i.e., RMS error, prediction efficiency, ratio of the maximum change in amplitudes, and ratio of the maximum amplitudes) to compare the performance of models in reproducing the selected physical parameters such as vertical drifts, electron and neutral densities, NmF2, and hmF2. In this paper, we present the results from comparing modeled values against space-based measurements including NmF2 and hmF2 from the CHAMP and COSMIC satellites, and electron and neutral densities at the CHAMP satellite locations. It is found that the accuracy of models varies with the metrics used, latitude and geomagnetic activity level

CEDARâ GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against groundâ based GPS TEC measurements during the 2006 AGU storm event (14â 15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physicsâ based, coupled ionosphereâ thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el mâ 2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.Key PointsTEC and TEC changes during a storm predicted by ionosphere models were compared with groundâ based GPS TEC measurementsSkill scores (e.g., RMSE, NRMSE, and Yields) were calculated for five latitude regions in the selected eight longitude sectorsModel performance strongly depends on the quantities considered, the type of metrics used, and the latitude consideredPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139943/1/swe20516.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139943/2/swe20516_am.pd