Observations of the Drift of Plasma Depletions Using SWARM Constellation and LISN TEC Measurements
1The University of Texas at Dallas, United States of America; 2Institut de Physique du Globe de Paris, France; 3Boston College, United States of America; 4Uppsala University, Sweden
During the early commissioning phase of the SWARM mission, the distance between the trajectories of all three satellites of the constellation was tens of km and the temporal separation was only a few minutes. This unique geometry allows us to conduct multiple and almost simultaneous in-situ measurements through the same low-latitude plasma depletion to investigate their spatial coherence and the motion of structures embedded within the equatorial plasma bubbles. We have used number density measured with the Langmuir Probe (LP) on board each of the three satellites of the SWARM constellation during December 2013 and concurrent TEC values obtained by ground-based GPS receivers to fully diagnose the bubble characteristics at multiple scale sizes. TEC values measured on the ground indicated that the plasma depletions moved with a velocity near 50 m/s and had a westward tilt of order 10°. Density depletions observed with SWARM indicated that the bubble velocities were also ~50 m/s. We have also found the velocity of density structures within the bubbles with scale sizes less than 100 km. This presentation will show results for several specific days of SWARM observations during passes throughout the South American continent.
Characteristics Of Polar Cap Patches Observed By Multi-Instruments
1University of Michigan, United States of America; 2University of Calgary, Canada
Polar cap patches refer to the islands of high F-region plasma density within the polar cap. Their formation on the dayside and deformation on the nightside are not well understood. The F-layer ionosphere density is strongly influenced by electric field, thermospheric wind as well as soft particle precipitation. This study combines observations from multiple instruments, including Resolute Bay incoherent scatter radar, GPS TEC and LEO satellites, to investigate the effects of highly structured electric fields and winds on the modulation of polar cap patches. We will also discuss variations of the auroral emissions associated with the patch evolution.
American Polar Cap Patches are Denser and more Structured than European Ones
University of Oslo, Norway
The Swarm satellites offer an unprecedented tool to survey polar cap patches, which are the main space weather issue in the polar caps. Using a new algorithm that automatically identifies polar cap patches in the plasma density data measured by Swarm, we computed the seasonal distributions of the patches detected between December 2013 and July 2016. We observe clear seasonal variations of the patch occurrence rate in both hemispheres. In the Northern hemisphere (NH), polar cap patches are mainly winter phenomena, with an occurrence rate enhanced during local winter and minimal during local summer. In the Southern hemisphere, the patch occurrence rate is also higher during local winter than during local, but the seasonal difference is not as marked as in the NH.
Additionally, we show that in the NH, patches that have been created above the American sectors exhibit larger densities and stronger fluctuations than the ones created over European sectors, and that this trend is reversed in the SH. As the electron density gradients and irregularities associated with patches can degrade HF radio and Global Navigation Satellite Systems (GNSS) signals, this study may have important implications for space weather forecasts.
Analysis of Ionospheric Patches Based on Swarm Langmuir Probe and TEC Data
1Johns Hopkins University Applied Physics Laboratory, United States of America; 2University of Bath, Claverton, Bath, BA2 7AY, United Kingdom
Dense, fast-moving regions of ionization called patches are known to occur in the high-latitude ionosphere. This investigation uses Swarm Langmuir probe and upward-looking GPS data to detect patches in both hemispheres. Statistical occurrence rates are produced from analysis of all the data from 2016. Patch formation theories characterize the phenomenon as occurring during winter or equinox, with plasma from the sunlit ionosphere drawn across a dark polar cap by magnetospheric convection. However, a recent statistical study by Noja et al.  using CHAMP upward-looking GPS data indicates that this is not the case in the southern hemisphere, with detections peaking in summer in the southern hemisphere. This investigation applies the same patch filter methodology to Swarm’s upward-looking GPS data in order to validate the CHAMP findings, and addresses potential limitations of that dataset using in situ Langmuir probe electron density measurements. Results are validated using independent, ground-based GPS tomographic images of the ionosphere from the MIDAS algorithm.
Noja, M., C. Stolle, J. Park, and H. Lühr (2013), Long-term analysis of ionospheric polar patches based on CHAMP TEC data, Radio Sci., 48, 289–301, doi:10.1002/rds.20033.
Characteristics of Electron Density Variations at Equator Crossings
1Swedish Institute of Space Physics, Sweden; 2Mbarara University of Science and Technology, Uganda
We present characteristics of electron density variations and irregularities at kilometer scales observed with the Swarm satellites at equator crossings.
Comparison between IRI and Electron Density Swarm Measurements during the St. Patrick Storm Period
1Istituto Nazionale di Geofisica e Vulcanologia, Italy; 2Dipartimento di Fisica e Astronomia, Università di Bologna, Italy; 3Serco Italia S.P.A, Italy
Preliminary Swarm Langmuir probe measurements recorded during March 2015, a period of time including the St. Patrick storm, are considered. Swarm electron density values are compared with the corresponding output given by the International Reference Ionosphere (IRI) model, according to its three different options for modelling the topside ionosphere. The similarity of trends embedded in the Swarm and IRI time series is investigated in terms of Pearson correlation coefficient. The analysis shows that the electron density representations made by Swarm and IRI are different for both quiet and disturbed periods, independently of the chosen topside model option. Main differences between trends modelled by IRI and those observed by Swarm emerge, especially at equatorial latitudes, and at northern high latitudes, during the main and recovery phases of the storm.
Moreover, very low values of electron density, even lower than 2 × 104 cm−3, were simultaneously recorded in the evening sector by Swarm satellites at equatorial latitudes during quiet periods, and at magnetic latitudes of about ±60° during disturbed periods. The obtained results are an example of the capability of Swarm data to generate an additional valuable dataset to properly model the topside ionosphere.
NeSTAD: A Tool to Tag Electron Density Anomalies with Swarm Data
1Istituto Nazionale di Geofisica e Vulcanologia, Italy; 2SpacEarth Technology, Italy
The identification and characterization of the ionospheric irregularities is of paramount importance to study how the forcing from outer space and lower atmosphere determines the ionospheric variability. The NeSTAD (Ne Single Track Anomaly Detection) algorithm is a recently developed tool able to support an ad hoc tagging of electron density (Ne) anomalies evaluated on Swarm Langmuir Probe electron density data. Directly interfacing with the Swarm data repository, NeSTAD is able to ingest Langmuir Probe (EFIx_PL and Plasma Preliminary) and Ionospheric Bubble Index (IBI/TMS) data, together with Dst index (derived the from NASA-omniweb portal to providing the geomagnetic characterization). NeSTAD is able to assign to the measurements acquired along each track, i.e. a portion of Swarm data covering a region of interest in a given time interval, some “anomaly parameters”, that identifies anomalous behaviour of the electron density. The anomaly parameters, introduced in detail in the paper, are obtained from the derivative of the relative variation of the electron density along each satellite. Starting from such quantity, evaluated track by track for each of the three Swarm satellites, outlier analyses are performed to identify the anomaly parameters. Such track anomaly parameters can then be used to define “tagging criteria” to tag anomalies of interest for different applications, such as ionospheric irregularities formation studies, lithosphere-atmosphere-ionosphere coupling studies, etc. The NeSTAD has been developed in the frame of the SAFE (SwArm for Earthquake Study, http://safe-swarm.ingv.it) project, funded by ESA in the frame of STSE Swarm+Innovation. NeSTAD is written in MATLAB and implemented to work on both Linux and Windows operative systems. In the present contribution, the main characteristics of the algorithm and examples of application in the above mentioned field of research are presented.
Relationship between Plasma Density Gradients and Swarm GPS Data
1University of Oslo, Norway; 2Delft University of Technology, Delft, The Netherlands
GPS signals are subject to disturbances in the polar regions, caused in part by clouds of high density plasma (polar cap patches). For the Swarm satellites, this noise results in positioning errors in the order of centimeters.
In this study, we use data from the GPS receiver and compare it to in situ density gradient data from the Langmuir probes.
We find that when GPS satellites are in front (azimuth φ=0±20°) of the Swarm, there is a direct proportionality between the density gradient dn/ds and the GPS observable dL4/dt. The same is true for when GPS satellites are positioned behind the Swarm satellite (azimuth φ=180±20°).Our results suggest that dL4/dt measurements from any satellite can be used to extrapolate the distribution of the plasma density gradient in the surrounding volume of the satellite, so that plasma density gradients can be detected from GPS receiver data alone.
Ground Based Kinematic GNSS Contribution Dealing with Space Weather Observations
University of Latvia, Latvia
The five-minute resolution GNSS observation results are computed in kinematic mode by scientific post-processing software for the 30 continuously operating GNSS reference stations covering territory of Latvia. The cases of disturbed coordinates are searched among computed results in four selected periods: the week of St.Patrick’s Day storm in March 2015, June and September 2015, and January 2016. The events of computed coordinate disturbances are found. They are noticed as a features of the ionospheric scintillation, which causes the failed coordinate appearance. The statistics of the disturbance occurrences is analyzed in comparison with a geomagnetic storms registered by international services. Events of both disturbances and domes of affected GNSS reference stations are listed and the comparison with a list of geomagnetic storms is performed. Graphs of occurrences of coordinate disturbances at the GNSS continuously operating reference stations are designed. The subset of most affected GNSS reference stations is discovered.
Conclusion is carried out that the five-minute resolution GNSS observations results computed in kinematic mode for the GNSS ground based continuously operating reference stations are representing a reasonable contribution for recognition of space weather anomalies.
Swarm for Space Weather monitoring
1GFZ Potsdam, Germany; 2DTU Space, Denmark; 3TGO, Tromsø University, Norway; 4DLR Neustrelitz, Germany; 5TUD, The Netherlands; 6STFC RAL, UK; 7MFGI, Hungary; 8ISS, Romania; 9BGS NERC, UK
ESA’s Swarm LEO satellite constellation mission provides high precision measurements of magnetic field, plasma and neutral densities, and electric field. On board GPS observables are used for sounding ionospheric and plasmaspheric total electron content. Continuous data sets from LEO satellites, including Swarm have been used for developing empirical models of the temporal occurrence and local distribution of typical structures in near-Earth space, like the expansion of the auroral oval, the location of the plasmapause, or plasma structures in the F region ionosphere. Among others, these phenomena can harm, for example, continuous radio navigation and communication (e.g., Galileo, GPS) through the development of severe ionospheric plasma gradients, and the intensity and location of auroral currents indicates the probability of geomagnetically-induced currents, e.g., during geomagnetic storms.
ESA’ Space Situational Awareness/Space Weather segment (SSA SWE) runs the “Swarm Utilization Analyses” (SUA) study for integration of Swarm products into ESA’s SSA SWE webportal, where day-by-day Swarm observations, combined with information from empirical models, are used to provide nowcast of such events. This paper will therefore report on recent results from the SUA study, including implementations and other potential space weather products.
This paper will also report on developments of the existing Field-Aligned Current, the Total Electron Content, and Ionospheric Bubble Index products, currently provided as continuous Swarm Level-2 Category-2 products.
Determination of CASSIOPE Topside Ionospheric Total Electron Content Using GPS Precise Point Positioning Techniques
University of New Brunswick, Canada
Since the advent of satellite technology, there has been an increased need for accurate information on plasma density variation within the ionosphere. Such information can subsequently be used to improve the modeling and forecasting of ionospheric conditions under varying states of plasma activity. As part of the Enhanced Polar Outflow Probe (e-POP) payload on the Canadian CAScade, Smallsat and IOnospheric Polar Explorer (CASSIOPE) small satellite, the GPS Attitude, Positioning, and Profiling (GAP) experiment’s dual-frequency GPS receivers and associated zenith-facing antennas (GAP-A) can be utilized to derive plasma density variation estimates above the satellite. To provide these estimates, a specialized precise point positioning (PPP) software package is under development that will be used to post-process the raw carrier-phase and pseudorange observables obtained from up to three of the four GAP-A GPS receivers. This new software package will make use of both the standard PPP and array-aided PPP (A-PPP) techniques. As the A-PPP total electron content (TEC) estimation technique requires data from multiple, collocated receivers with fixed baseline offsets, the GAP-A receivers/antennas are particularly well suited for utilization. The A-PPP technique will provide more robust TEC estimates through use of parameter constraints within the least-squares algorithm associated with the use of collocated receivers/antennas.
Subsequently-derived GAP-A high-resolution TEC estimates can be used to improve the spatial resolution of current ionospheric plasma density determinations through densification of existing datasets used to generate various ionospheric models. The determination of TEC is essential to the continued understanding of the solar-terrestrial impact of the ionosphere on navigation systems with polar regions being of ever-increasing importance.
Modeling the Sq and Equatorial Electrojet Magnetic Fields from 3 years of Swarm Data
1University of Colorado Boulder, United States of America; 2NOAA National Centers for Environmental Information (NCEI), United States of America; 3Institut de Physique du Globe de Paris, France
The Dedicated Ionospheric Field Inversion (DIFI) is a Swarm level-2 processing chain calculating spherical harmonic models of the ionospheric magnetic field at mid- to low-latitudes. DIFI includes descriptions of the seasonal and solar cycle variations and provides both the primary and secondary (induced) magnetic fields at ground and satellite altitudes. The DIFI-2 model, released in May 2016, was based on more than two years of Swarm data and data from 79 ground observatories. It revealed some new features of the Sq current system, including a peculiar seasonal variability and a wave-4 longitudinal variability in the Southern hemisphere. Here we present a new model, DIFI-3, based on three years of Swarm data. The larger time interval provides a better local time coverage due to the slow increase of the local time difference between the lower pair of satellites and the upper satellite. We exploit this better coverage to investigate the robustness of the Sq features found in DIFI-2 by calculating models from subsampled datasets.