Understanding Large-Scale Structure in Global Ionospheric Maps With Visual and Statistical Analyses

Verkhoglyadova, Olga; Meng, Xing; Kosberg, Jacob

doi:10.3389/fspas.2022.852222

Cited by 4 publications

(5 citation statements)

References 8 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The script is used to determine the number of HDRs for approximately 10,000 TEC maps selected from 10 years of the JPL GIM data. The occurrence of different HDR counts and its variation with solar cycle phase, season, and geomagnetic activity are examined (Verkhoglyadova et al, 2021(Verkhoglyadova et al, , 2022. For this work, we have modified and improved the labeling script to construct the feature extraction software.…”

Section: Feature Extraction Softwarementioning

confidence: 99%

“…Recently, image processing techniques and machine-learning-based algorithms have been applied to recognize patterns from ionospheric TEC maps or to complete ionospheric TEC maps (Z. Chen et al, 2019;Starr et al, 2022;Sun et al, 2023;Verkhoglyadova et al, 2021Verkhoglyadova et al, , 2022. Motivated by these powerful approaches and their promising performance, we develop feature extraction software based on an image processing library and the prior work of Verkhoglyadova et al (2021) to automatically identify intensification regions in global ionospheric TEC maps.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Statistical Characteristics of Total Electron Content Intensifications on Global Ionospheric Maps

Meng,

Verkhoglyadova,

Chapman

et al. 2024

Space Weather

View full text Add to dashboard Cite

Global ionospheric total electron content (TEC) maps exhibit TEC intensifications and depletions of various sizes and shapes. Characterizing key features on TEC maps and understanding their dynamic coupling with external drivers can significantly benefit space weather forecasting. However, comprehensive analysis of ionospheric structuring over decades of TEC maps is currently lacking due to large data volume. We develop feature extraction software based on image processing techniques to extract TEC intensification regions, that is, contiguous regions with sufficiently elevated TEC values than surrounding areas, from global TEC maps. Applying the software to the Jet Propulsion Laboratory Global Ionospheric Map data, we generate a TEC intensification data set for years 2003–2022 and carry out a statistical study on the number and strength of TEC intensifications. We find that the majority of the TEC maps (about 86%) are characterized with one or two intensification(s), while the rest of the TEC maps have three or more intensifications. Both the number and strength of TEC intensifications exhibit semi‐annual variation that peaks near equinoxes and dips near solstices, as well as an annual asymmetry with larger values around December solstice compared to June solstice. The number and strength of intensifications increase with enhanced solar extreme‐violet irradiance. The strength of intensifications also increases with elevated geomagnetic activity, but the number of intensifications does not. In addition, the number of intensifications is not correlated with the strength of intensifications.

show abstract

Section: Feature Extraction Softwarementioning

confidence: 99%

mentioning

confidence: 99%

Statistical Characteristics of Total Electron Content Intensifications on Global Ionospheric Maps

Meng,

Verkhoglyadova,

Chapman

et al. 2024

Space Weather

View full text Add to dashboard Cite

show abstract

“…The workflow of the feature extraction procedure contains several major steps including computing Laplacian values, applying dilation and erosion, merging and removing objects (Figure S2 in Supporting Information S1). The development, implementation, and application of the feature extraction software are described in detail in Verkhoglyadova et al (2021); Verkhoglyadova et al (2022); Meng et al (2024). Applying the feature extraction software to each JPLD global TEC map during 2003-2022, we have obtained the TEC intensification data set, which records the number of intensifications per TEC map and several characteristics of each intensification (Meng & Verkhoglyadova, 2023).…”

Section: Tec Intensification Data Setmentioning

confidence: 99%

Temporal Variability of Equatorial Ionization Anomaly Crest Locations Extracted From Global Ionospheric Maps

Dunn,

Meng,

Verkhoglyadova

2024

Space Weather

Self Cite

View full text Add to dashboard Cite

The Equatorial Ionization Anomaly (EIA) crest location is known to vary over a variety of temporal scales. For the first time we perform a statistical survey of the temporal variation of the EIA crest location viewed globally and spanning 20 years. We extract the crest location for double‐peaked EIAs from a data set of total electron content intensifications identified on global ionospheric maps from 2003 to 2022. We show that the dominant temporal variations of the crest latitude are annual and semi‐diurnal for the northern crest, and annual and diurnal for the southern crest. For the annual variation, we find that both crests move poleward in local summer and equatorward in local winter, which is more pronounced for the southern crest than the northern crest, and more pronounced at solar minimum than solar maximum. For the diurnal and semi‐diurnal variations in universal time, both crests dip southward around 15UT and the northern crest additionally dips southward around 2.5UT. We consider apparent universal time dependence to be a proxy for the longitudinal distribution of the crest geomagnetic latitude, which exhibits the known wave‐number‐four longitudinal structure of EIA crests. In local time, the EIA crests form earlier than 10LT and move poleward to their maximum distance at 14LT, and remain at constant latitude until 18LT. Solar cycle modulation on the diurnal/semi‐diurnal variations and the local time evolution of the crest latitude is minimal.

show abstract

“…Including a recently published eBook [27] on the applications of statistical methods in the space sciences, there has been a series of publications dedicated to space science research [28][29][30]. For instance, Delzanno and Borovsky [28] point out the importance of a combined system science approach to global magnetospheric models and to spacecraft magnetospheric data.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Delzanno and Borovsky [28] point out the importance of a combined system science approach to global magnetospheric models and to spacecraft magnetospheric data. Telloni [29] highlights works based on statistical analyses of interplanetary and geomagnetic data in the context of space weather prediction, and Verkhoglyadova et al [30] discuss the implementation of a mixture method approach and a computer vision approach in quantitatively addressing the anomalies and high density regions (HDRs) that are present in a global ionospheric map, and how the number of HDRs and their intensities depend on solar and geomagnetic activities.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Dynamical Complexity in Swarm-Derived Geomagnetic Activity Indices Using Information Theory

et al. 2023

View full text Add to dashboard Cite

In 2023, the ESA’s Swarm constellation mission celebrates 10 years in orbit, offering one of the best ever surveys of the topside ionosphere. Among its achievements, it has been recently demonstrated that Swarm data can be used to derive space-based geomagnetic activity indices, similar to the standard ground-based geomagnetic indices monitoring magnetic storm and magnetospheric substorm activity. Recently, many novel concepts originating in time series analysis based on information theory have been developed, partly motivated by specific research questions linked to various domains of geosciences, including space physics. Here, we apply information theory approaches (i.e., Hurst exponent and a variety of entropy measures) to analyze the Swarm-derived magnetic indices from 2015, a year that included three out of the four most intense magnetic storm events of the previous solar cycle, including the strongest storm of solar cycle 24. We show the applicability of information theory to study the dynamical complexity of the upper atmosphere, through highlighting the temporal transition from the quiet-time to the storm-time magnetosphere, which may prove significant for space weather studies. Our results suggest that the spaceborne indices have the capacity to capture the same dynamics and behaviors, with regards to their informational content, as traditionally used ground-based ones.

show abstract

Understanding Large-Scale Structure in Global Ionospheric Maps With Visual and Statistical Analyses

Cited by 4 publications

References 8 publications

Statistical Characteristics of Total Electron Content Intensifications on Global Ionospheric Maps

Statistical Characteristics of Total Electron Content Intensifications on Global Ionospheric Maps

Temporal Variability of Equatorial Ionization Anomaly Crest Locations Extracted From Global Ionospheric Maps

Investigation of Dynamical Complexity in Swarm-Derived Geomagnetic Activity Indices Using Information Theory

Contact Info

Product

Resources

About