Defense Meteorological Satellite Program Research Articles

Ion precipitation in the cusp for northward IMF and its relationship with magnetosheath flow

If the interplanetary magnetic field (IMF) has a northward component, a portion of the solar wind ions flowing in the high-latitude magnetosheath drastically alters the flow direction owing to lobe reconnection and follows the Earth's magnetic field lines toward the low-altitude cusp. Partly because of this folded path, the relationship between the speed of ion flow in the magnetosheath and the energy of the precipitating ions in the low-altitude cusp remains unclarified. Herein, we examined particle data from 11 years of observations by Defense Meteorological Satellite Program satellites to obtain 1990 cases through an automated event identification of the cusp. This corresponds to the largest number of cusp ion events reported to date for a stable northward IMF. The results revealed a positive correlation between the energy of the precipitating ions and the estimated flow speed in the magnetosheath, which answers the question that has remained unexplained for decades: why is the brightness of the cusp proton aurora more strongly correlated with the solar wind dynamic pressure than with the solar wind number density? We suggest additional energizations of the exhausted ions from lobe reconnection in the outflow region because of the turbulent electric field formed by the opposite flow of two ion populations—one in the tailward-directed magnetosheath flow and the other in the earthward-directed outflow jet.Graphical

Global Distribution of EMIC Waves and Its Association to Subauroral Proton Precipitation During the 27 May 2017 Storm: Modeling and Multipoint Observations

AbstractRecent simulation studies using the RAM‐SCB model showed that proton precipitation contributes significantly to the total energy flux deposited into the subauroral ionosphere thereby affecting the magnetosphere‐ionosphere coupling. In this study, we use the BATS‐R‐US + RAM‐SCB model to understand the evolution of ElectroMagnetic Ion Cyclotron (EMIC) waves in the inner magnetosphere, their correspondence to the proton precipitation into the subauroral ionosphere, and to assess the performance of the model in reproducing the EMIC wave‐particle interactions. During the 27 May 2017 storm, Arase and RBSP‐A satellites observed typical signatures of EMIC waves in the inner magnetosphere. Within this interval, Defense Meteorological Satellite Program (DMSP) and National Oceanic and Atmospheric Administration (NOAA)/MetOp satellites observed significant proton precipitation in the dusk‐midnight sector. Simulation results show that H‐ and He‐band EMIC waves are excited within regions of strong temperature anisotropy near the plasmapause. The simulated growth rates of EMIC waves show a similar trend to that of the EMIC wave power observed by the Arase and RBSP‐A satellites, suggesting that the model can reproduce the EMIC wave activity qualitatively. The simulated H‐band waves in the dusk sector are stronger than He‐band waves possibly due to the presence of excess protons in the boundary conditions obtained from the BATS‐R‐US code. The precipitating proton fluxes reproduced by the simulation with EMIC waves are found to agree reasonably well with the DMSP and NOAA/MetOp satellite observations. It is suggested that EMIC wave scattering of ring current ions can account for proton precipitation observed by the DMSP and MetOp satellites during the 27 May 2017 storm.

Influence of Supraglacial Lakes on Accuracy of Inversion of Greenland Ice Sheet Surface Melt Data in Different Passive Microwave Bands

The occurrence of Supraglacial Lakes (SGLs) may influence the signals acquired with microwave radiometers, which may result in a degree of uncertainty when employing microwave radiometer data for the detection of surface melt. Accurate monitoring of surface melting requires a reasonable assessment of this uncertainty. However, there is a scarcity of research in this field. Therefore, in this study, we computed surface melt in the vicinity of Automatic Weather Stations (AWSs) by employing Defense Meteorological Satellite Program (DMSP) Ka-band data and Soil Moisture and Ocean Salinity (SMOS) satellite L-band data and extracted SGL pixels by utilizing Sentinel-2 data. A comparison between surface melt results derived from AWS air temperature estimates and those obtained with remote sensing inversion in the two different bands was conducted for sites below the mean snowline elevation during the summers of 2016 to 2020. Compared with sites with no SGLs, the commission error (CO) of DMSP morning and evening data at sites where these water bodies were present increased by 36% and 30%, respectively, and the number of days with CO increased by 12 and 3 days, respectively. The omission error (OM) of SMOS morning and evening data increased by 33% and 32%, respectively, and the number of days with OM increased by 17 and 21 days, respectively. Identifying the source of error is a prerequisite for the improvement of surface melt algorithms, for which this study provides a basis.

Mesoscale Auroral Curls in Antarctica

AbstractThe morphology and motion of auroras have been widely studied due to their indications on magnetospheric processes. Here, we report a new kind of “auroral curls,” which have wavelengths in the mesoscale (∼100 km) and propagate azimuthally. Utilizing data from the Chinese Antarctic Zhongshan Station (the all‐sky imager and the high‐frequency radar), the Active Magnetosphere and Planetary Electrodynamics Response Experiment and the Defense Meteorological Satellite Program, we analyze an event occurred on 23 April 2019. We find these curls are fine structures in the poleward boundary of multiple arcs. Corresponding field‐aligned currents manifest as a series of longitudinally arranged pairs, while ionospheric flow velocities nearby oscillate with periods in the Pc 5 band. Observational evidence suggests these curls are connected with ultra‐low frequency (ULF) waves, which opens the possibility of using auroras to globally image ULF waves.

Validation of the IRI-2020 topside ionosphere options through in-situ electron density observations by low-Earth-orbit satellites

The topside ionosphere extends from the F2-layer peak, where the electron density reaches its absolute maximum in the ionosphere, to the overlying plasmasphere and magnetosphere. In the topside ionosphere, the electron density decreases with height with a vertical variation rate strongly dependent on height itself. The last version of the International Reference Ionosphere (IRI) model, i.e., IRI-2020, describes this complex behavior through four topside options based on different sub-models (i.e., options) developed from the 1970s to the present. All these options have in common the F2-layer peak as an anchor point, while they differ in their topside electron density profile and/or plasma effective scale height formulations. In this work, we perform a validation of the accuracy of the four IRI-2020 topside options based on the comparison against in-situ electron density observations by Gravity Recovery and Climate Experiment (GRACE), Ionospheric Connection Explorer (ICON), and Defense Meteorological Satellite Program (DMSP) F15 low-Earth-orbit satellites. Datasets used in this study encompass observations recorded from 1999 to 2022, covering different diurnal, seasonal, and solar activity conditions, on a global basis and for the height range 400–850 km above the ground. The nearly two solar cycles dataset facilitated the evaluation of IRI-2020 topside options ability to reproduce the spatial and time variations of the topside ionosphere for different solar activity conditions. The weaknesses and strengths of each IRI-2020 topside option are highlighted and discussed, and suggestions on how to improve the modeling of the challenging topside ionosphere region within the IRI model are provided for future reference.

Poynting Flux Input to the Auroral Ionosphere: The Impact of Subauroral Polarization Streams and Dawnside Auroral Polarization Streams

AbstractThe Poynting vector (Poynting flux) from Earth's magnetosphere downward toward its ionosphere carries the energy that powers the Joule heating in the ionosphere and thermosphere. The Joule heating controls fundamental ionospheric properties affecting the entire magnetosphere‐ionosphere‐thermosphere system, so it is necessary to understand when and where the Poynting flux is significant. Taking advantage of new data sets generated from DMSP (Defense Meteorological Satellite Program) observations, we investigate the Poynting flux distribution within and around the auroral zone, where most magnetosphere‐ionosphere (M‐I) dynamics and thus Joule heating occurs. We find that the Poynting flux, which is generally larger under more active conditions, is concentrated in the sunlit cusp and near the interface between Region 1 and 2 currents. The former concentration suggests voltage generators drive the cusp dynamics. The latter concentration shows asymmetries with respect to the interface between the Region 1 and 2 currents. We show that these reflect the controlling impact of subauroral polarization streams and dawnside auroral polarization streams on the Poynting flux.

Inter‐Hemispheric Energy Input Into the Ionosphere‐Thermosphere System During Magnetic Storms: What We Can and Cannot Learn From DMSP Observations

AbstractWe present a long‐term superposed epoch analysis and statistical study with 427 magnetic storms caused by coronal mass ejections and the subsequent magnetospheric energy input into the ionosphere‐thermosphere system. Electron and ion precipitating energy flux data along with plasma drift velocity and magnetic field data (used for Earth‐bound Poynting flux computations) are used in this study. By carefully exploring conjugated inter‐hemispheric energy inputs as a function of storm intensity and seasons, we find that near two‐decades of Defense Meteorological Satellite Program observations indicate that the northern hemisphere (NH) receives slightly more energy than the southern hemisphere (SH) (Poynting flux and integrated electron/ion precipitating energy flux), with the NH receiving more energy as the storm becomes more intense. However, for the Poynting flux case, we find that generally the SH receives more energy when the east‐west component of the interplanetary magnetic field (IMF) becomes highly positive (By ≥ +5 nT), whereas this pattern reverses for cases when IMF By is highly negative (By ≤ −5 nT). The inter‐hemispheric interpretation for electron and ion precipitation energy inputs is ambiguous due to a severe lack of conjugated observations around the midnight sector for both hemispheres.

Lower Band Chorus Wave Scattering Causing the Extensive Morningside Diffuse Auroral Precipitation During Active Geomagnetic Conditions: A Detailed Case Study

AbstractThe diffuse aurora is a natural phenomenon observed over the Earth's polar region. Compared with the nightside diffuse aurora, the brightness of the dayside diffuse aurora (0600–1800 magnetic local time (MLT)) is relatively weak, thus requiring more stringent observation conditions. Therefore, the current understanding of what causes the dayside diffuse aurora is still quite limited. Here, we present an intense morningside diffuse aurora (0600–1000 MLT) event observed on 1 January 2016 during the recovery phase of the substorm, using conjugate observations of wave and particle spectrum from the Radiation Belt Storm Probes and auroral emission from the Special Sensor Ultraviolet Spectrographic Imagers on the Air Force Defense Meteorological Satellite Program (DMSP/SSUSI). We perform calculations of diffusion coefficients and simulations of the electron fluxes for this event. Our results show that the chorus waves are the primary contributors to the formation of the morningside diffuse aurora, with precipitated electron energies ranging from a few keV to tens of keV. The lower band chorus shows significant pitch angle scattering efficiency for electrons with energies from 5 to 20 keV. The upper band chorus waves induce acceleration effects on 1–20 keV electrons. We suggest that the upper band chorus waves accelerate low‐energy electrons to higher energies, enabling them to engage in the scattering process of the lower band chorus waves. Our study makes a contribution to recent research on the formation mechanisms of diffuse aurora and deepens our understanding of wave‐particle interactions leading to dayside electron precipitation.

Investigating the Influence of River Geomorphology on Human Presence Using Night Light Data: A Case Study in the Indus Basin

Human settlements have historically thrived near rivers due to enhanced navigation and trade, and the availability of water supply and resources. The use of night light data, representing economic activities, provides a novel approach to studying the interactions between human activity and rivers over time. Here, we use the Defense Meteorological Satellite Program (DMSP) stable night light data from 2000 to 2013 as a proxy for human presence and activities to quantify the statistical relationships between night light presence and intensity in the Indus Basin, Asia. We test how these data are affected by proximity to trunk channels and by channel type (single/multi-thread) in the study area. We find that night light presence is enhanced by 26% within a 0 to 5 km proximity range of the Indus River and its tributaries, relative to the basin as a whole. We interpret this to represent increased human presence and activity within this zone. However, the mean intensity is lower near the river and higher away from the river, signifying denser settlements, such as towns and cities, which are preferentially located away from the Indus and its tributaries. Moreover, the enhancement of lit pixels signifying human presence and activities is increased by 18% near single-thread sections of the Indus River, compared to segments of the Indus displaying multi-thread morphologies. We suggest that this is due to the enhanced stability of single-threaded channels, relative to mobile multi-threaded channel reaches. This study demonstrates how night lights are an important tool in studying the relationship between human presence and river dynamics in large catchments such as the Indus, and we suggest that these data will have an important role in assessing differential flood spatial and social vulnerability at a regional scale.

Calculating the High‐Latitude Ionospheric Electrodynamics Using a Machine Learning‐Based Field‐Aligned Current Model

AbstractWe introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML‐AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017

BackgroundMalaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogeneity in sociodemographic and environmental risk factors over time and across diverse geographical and climatological regions make outbreak prediction challenging. Data-driven approaches accounting for spatiotemporal variability could offer potential for location-specific early warning tools for malaria. MethodsIn this case study, we developed and internally validated a data fusion approach to predict malaria incidence in Pakistan, India, and Bangladesh using geo-referenced environmental factors. For 2000–17, district-level malaria incidence rates for each country were obtained from the US Agency for International Development's Demographic and Health Survey datasets. Environmental factors included average annual temperature, rainfall, and normalised difference vegetation index, obtained from the Advancing Research on Nutrition and Agriculture (known as AReNA) project conducted by the International Food Policy Research Institute in 2020. Data on night-time light intensity was derived from two satellites of the National Oceanic and Atmospheric Administration Defense Meteorological Satellite Program—Operational Linescan System: Nighttime Lights Time Series Version 4, and VIIRS Nighttime Day/Night Band Composites version 1. A multi-dimensional spatiotemporal long short-term memory (M-LSTM) model was developed using data from 2000–16 and internally validated for the year 2017. The M-LSTM model consisted of four hidden layers, each with 100 LSTM units; a fully connected layer was used, followed by linear regression, to predict the malaria incidence rate for 2017 using spatiotemporal partitioning. Model performance was measured using accuracy and root mean squared error. Country-specific models were produced for Bangladesh, India, and Pakistan. Bivariate geospatial heatmaps were produced for a qualitative comparison of univariate environmental factors with malaria rates. FindingsMalaria incidence was predicted with 80·6% accuracy in districts across Pakistan, 76·7% in districts across India, and 99·1% in districts across Bangladesh. The root mean squared error was 7 × 10–4 for Pakistan, 4·86 × 10–6 for India, and 1·32 × 10–5 for Bangladesh. Bivariate maps showed an inverse relationship between night-time lights and malaria rates; whereas high malaria rates were found in areas with high temperature, rainfall, and vegetation. InterpretationMalaria outbreaks could be forecasted using remotely measured environmental factors. Modelling techniques that enable simultaneously forecasting ahead in time as well as across large geographical areas might potentially empower regional decision makers to manage outbreaks early. FundingNIHR Oxford Biomedical Research Centre Programme and The Higher Education Commission of Pakistan.

Abstract MP77: Both Racial/Ethnic Residential Segregation and Exposure to Outdoor Artificial Light at Night May Impact Cardiovascular Health but Perhaps Not Through Self-Reported Sleep

Introduction: Due to structural racism, minoritized racial/ethnic groups are overrepresented in racially segregated areas of concentrated disadvantage in which residences may be less protective against outdoor artificial light at night (ALAN). Both racial/ethnic residential segregation (RRS) and ALAN are associated with disparities in both sleep duration, potentially through ALAN exposures in segregated areas disrupting melatonin production, and cardiovascular health (CVH). However, few studies have investigated pathways between RRS and ALAN, sleep, and CVH. We sought to investigate sleep duration as a potential mediator between RRS and ALAN exposures and CVH among US adults. Hypothesis: We hypothesized that (1) ALAN would disproportionately burden minoritized racial/ethnic groups, (2) sleep duration would mediate associations between both RRS and ALAN and CVH, and (3) associations would vary by race/ethnicity. Methods: We used data collected from 2011 National Health Interview Survey adult participants reporting sleep duration (short [<7 hours(h)]), recommended [7-9 h], long [>9 h]) and CVH (defined as yes vs. no to all: never/former smoking, BMI 18-<25 kg/m 2 , meets physical activity guidelines, and no prior diagnosis of dyslipidemia, hypertension, or pre-diabetes/diabetes). Participants’ home addresses were geographically linked to the 2012 American Community Survey 5-year estimates to assess RRS, measured by the local Getis-Ord G i * statistic (z-scores) categories: low (z<0), medium (0≤z≤1.96), and high (z>1.96). Quintiles of residential ALAN were estimated from 2010-2011 US Defense Meteorological Satellite Program’s Operational Linescan System values. We used robust Poisson regression adjusted for sociodemographic characteristics, estimated mediation through sleep duration with the Sobel’s test, and assessed effect modification by race/ethnicity. Results and Conclusions: Among 18,057 participants (mean age±SE =45±0.2 years); 35%, 44%, and 21% resided in low, medium, and highly segregated neighborhoods, respectively. ALAN was highest among non-Hispanic White adults. Prevalence of short and long sleep duration overall were 31% and 3% and highest among Black adults (39% and 4%). High (vs. low) RRS was associated with a higher prevalence of CVH (PR=1.13 [95% CI:1.01-1.26]). However, higher ALAN (Q5 vs. Q1) was associated with a lower prevalence of CVH (PR=0.79 [95% CI:0.66-0.95]). Sleep did not appear to mediate associations, which did not vary by race/ethnicity. In conclusion, self-reported sleep did not mediate associations between RRS or ALAN and CVH. Nonetheless, further study using objective measures is warranted given the biological plausibility. The findings/conclusions in this research are those of the authors and do not necessarily represent the views of the Research Data Center, National Center for Health Statistics, or CDC.

Significant Midlatitude Bubble‐Like Ionospheric Super‐Depletion Structure (BLISS) and Dynamic Variation of Storm‐Enhanced Density Plume During the 23 April 2023 Geomagnetic Storm

AbstractThis paper investigates the midlatitude ionospheric disturbances over the American/Atlantic longitude sector during an intense geomagnetic storm on 23 April 2023. The study utilized a combination of ground‐based observations (Global Navigation Satellite System total electron content and ionosonde) along with measurements from multiple satellite missions (GOLD, Swarm, Defense Meteorological Satellite Program, and TIMED/GUVI) to analyze storm‐time electrodynamics and neutral dynamics. We found that the storm main phase was characterized by distinct midlatitude ionospheric density gradient structures as follows: (a) In the European‐Atlantic longitude sector, a significant midlatitude bubble‐like ionospheric super‐depletion structure (BLISS) was observed after sunset. This BLISS appeared as a low‐density channel extending poleward/westward and reached ∼40° geomagnetic latitude, corresponding to an APEX height of ∼5,000 km. (b) Coincident with the BLISS, a dynamic storm‐enhanced density plume rapidly formed and decayed at local afternoon in the North American sector, with the plume intensity being doubled and halved in just a few hours. (c) The simultaneous occurrence of these strong yet opposite midlatitude gradient structures could be mainly attributed to common key drivers of prompt penetration electric fields and subauroral polarization stream electric fields. This shed light on the important role of storm‐time electrodynamic processes in shaping global ionospheric disturbances.

A Combined Effect of the Earth's Magnetic Dipole Tilt and IMF By in Controlling Auroral Electron Precipitation

AbstractAuroral particle precipitation is usually assumed to be equally strong for both signs of the By component of the interplanetary magnetic field (IMF). This is also the case in most currently used precipitation models, which parameterize solar wind driving by empirical coupling functions. However, recent studies have showed that geomagnetic activity is significantly modulated by the signs and amplitudes of IMF By and the Earth's dipole tilt angle Ψ. This so called explicit By dependence is not yet included in any current precipitation models. In this paper, we quantify this By dependence for auroral electron precipitation for the first time. We use precipitation measurements of the Defense Meteorological Satellite Program (DMSP) Special Sensor J instruments from years 1995–2022. We show that the dawnside electron precipitation at energies 13.9–30 keV is greater at auroral latitudes for opposite signs of By and Ψ in both hemispheres, while the dusk sector is mostly unaffected by By and Ψ. For energies below 6.5 keV the By dependence is strong poleward of the auroral oval in the summer hemisphere, also exhibiting a strong dawn‐dusk asymmetry. We also show that By dependence of precipitation modulates ionospheric conductance.

Evolution of a long-duration transpolar arc during very quiet period

In this study, we explore the evolution of long-duration transpolar arcs observed during an exceptionally quiet period by the Fengyun-3D and Defense Meteorological Satellite Program satellites on 17 January 2019. Leveraging the extensive field of view of WAI, we captured the complete structure and evolution of the TPA over a very quiet period exceeding 7 h, with AE<30 nT. The TPA initially manifested at the poleward boundary of the auroral oval in the dawn sector, gradually migrating towards the dusk as the y-component of the interplanetary magnetic field (IMF BY) transitioned from negative to positive. Throughout this phase, the TPA underwent a distortion, transforming from a straight line to an “l-shape”. Following a reversal in interplanetary magnetic field BY to negative, the TPA retraced its path towards dawn and ultimately dissipated when the IMF turned southward. Of particular interest is the observation that when the TPA approached the noon-midnight line, small-scale spiral structures became apparent within the TPA. This suggests the presence of intricate small-scale magnetic field topologies or plasma instabilities/shears in the source region. These observations highlight the likelihood of complex field and particle dynamics in the high-latitude reconnection region and the twisted tail plasma sheet.

Auroral Characteristics Related to AU&AL Indices

AbstractAuroral images of the N2 Lyman‐Birge‐Hopfield emissions from Polar Ultraviolet Imager (UVI) for 1.5 years are used to investigate the auroral characteristics related to the AU and AL indices that represent the directly driven and unloading processes in the solar wind‐magnetosphere‐ionosphere coupling, respectively. Findings include: (a) Growing AL mainly relates to the nightside aurora and tends to keep the general auroral morphology. (b) As AU increases, the aurora brightens and expands more globally, especially in the midnight to postmidnight sector. (c) The regional auroral power (AP), equatorward boundary, poleward boundary, and peak intensity change quasi‐linearly with intensifying AU and AL. (d) The rates of change depend on the MLT and AU/AL levels. The same dataset has been used to construct the empirical Feature Tracking of Auroral Precipitation (FTA) model which specifies the global energy flux and mean energy determined by the AE index (FTA‐AE). As an extension of FTA‐AE, the relationships of the auroral emission with the AU&AL indices were derived to construct the FTA‐AU&AL model which specifies a more consistent aurora during different magnetospheric driving modes compared to FTA‐AE. Comparisons of AP from the Defense Meteorological Satellite Program Special Sensor Ultraviolet Spectrographic Imagers (SSUSI) measurements and empirical auroral models show that the FTA‐AE and ‐AU&AL models predicted larger AP than the Fuller‐Rowell and Evans (1987) model and the OVATION‐prime model did. As the activity level increased, all four models tended to underestimate the AP but the FTA APs increased relatively faster and were therefore more consistent with the data.

Ionospheric Conductances Due To Electron and Ion Precipitations: A Comparison Between EISCAT and DMSP Estimates

AbstractEnergetic particle precipitation is the major source of electron production that controls the ionospheric Pedersen and Hall conductances at high latitudes. Many studies use empirical formulas to estimate conductances. The particle precipitation spectra measured by the Defense Meteorological Satellite Program (DMSP) Special Sensor J are often used as the input to the empirical formulas. In this study, we evaluate the empirical formulas of ionospheric conductances during four different types of auroral precipitation conditions based on 63 conjugate events observed by DMSP and EISCAT. The conductances calculated from the DMSP data with the empirical formulas are compared with those based on EISCAT measurements with the standard equations. The best correlation between these two is found when the empirical Robinson formulas (Robinson et al., 1987, https://doi.org/10.1029/ja092ia03p02565) are used in the presence of diffuse electron precipitation without ions. In the presence of ion precipitation, the correlation coefficients are smaller, but the correlation improves when the Galand formulas (Galand & Richmond, 2001, https://doi.org/10.1029/1999ja002001) are used to estimate the contribution of ion precipitation to the conductances. We also found that pure ion precipitation can cause the increase of conductances up to 2–7 S for Pedersen and 2.5–10 S for Hall conductances, which is positively correlated with the auroral electrojet index. Overall, the empirical formulas applied to the DMSP particle spectra underestimate the ionospheric conductances.

Localized Plasma Density Peak at Middle Latitudes During the April 2023 Geomagnetic Storm

AbstractThis paper conducts a multi‐instrument analysis of a latitudinal plasma density peak at the middle latitudes during the early recovery phase of the April 2023 geomagnetic storm. The total electron content (TEC), peak density of the F layer, and the in situ plasma density from Swarm and Defense Meteorological Satellite Program (DMSP) satellites all capture this peak feature. This narrow latitudinal peak structure appeared around 50°N and extended from 40°E to 150°E in longitude with a prolonged duration of about 8 hr from sunset to midnight. This mid‐latitude peak reveals a noticeable equatorward motion and a slight westward shift. According to the plasma composition observations from DMSP satellites, this peak structure shows an O+ ions dominance, which means that this peak is more likely to be formed by an internal rather than an external source from the plasmasphere. Meanwhile, the middle latitude Fabry–Perot interferometer (FPI) observed strong equatorward thermospheric winds, and the peak height of the F layer presented a visible elevation, which suggests that the equatorward wind lifting caused the plasma density enhancement. Besides, the O/N2 ratio significantly decreased at lower and middle latitudes, and ion drift observations showed a distinct subauroral westward channel. Based on these simultaneous measurements, this structure's sharp equatorward and poleward boundaries might be related to the O/N2 ratio change and the subauroral polarization stream (SAPS) flow separately.

Magnetic Local Time and Interplanetary Magnetic Field By Variation of Cusp Location Dependence on Dipole Tilt

AbstractWe produced a database of over 41,000 ionospheric cusp locations using 40 years of energetic particle measurements from 14 Defense Meteorological Satellite Program (DMSP) satellites. We limited the database to periods when the Auroral Electrojet (AE) was <100 nT and the Interplanetary Magnetic Field (IMF) measurements were available, then calculated the magnetic latitude (MLAT), magnetic local time (MLT) and the dipole tilt (Λ) for each boundary, multiplying Λ by −1 in the southern hemisphere. We then binned the data in running one‐hour bins from 8.5 to 15.5 MLT. To obtain the dependence of the MLAT of the cusp boundary on Λ and IMF By, we performed linear fits on the MLAT versus Λ distributions, separated by ±IMF By. The dependence (degrees MLAT/degrees Λ) is asymmetric in both MLT and hemisphere as well as IMF By. In the northern hemisphere, the dependence for By > 0 (By < 0) is greatest in the afternoon (morning) sector for both poleward and equatorward boundaries. The opposite is true in the southern hemisphere. However, in the noon sector, the dependence is nearly the same for all boundaries and By sign. In addition, separation by Λ sign shows dramatically greater dependence variance for Λ > 0 than for Λ < 0 in the afternoon and morning sectors (but not in the noon sector). The observed asymmetries revealed in this work are thought to be due to the effect of By on reconnection and the location of the reconnection X line.

Occurrence Probability of Magnetic Field Disturbances Measured With Swarm: Mapping the Dynamic Magnetosphere‐Ionosphere Coupling

AbstractThe exchange of kinetic and electromagnetic energy by precipitation and/or outflow and through field‐aligned currents are two aspects of the ionosphere‐magnetosphere coupling. A thorough investigation of these processes is required to better understand magnetospheric dynamics. Building on our previous study using the Defense Meteorological Satellite Program spectrometer data, here we use Swarm vector field magnetometer data to describe the auroral zone morphology in terms of east‐west magnetic field perturbations. We define a threshold for detecting magnetic fluctuations based on the power spectral density of ΔBEW, and derive the disturbed magnetic field occurrence probability (dBOP) at low [0.1–1 Hz] and high [2.5–5 Hz] frequencies. High‐frequency distributions of dBOP reveal a dayside‐nightside asymmetry, whereas low‐frequency dBOP exhibits a persistent morphological asymmetry between the dawn‐to‐noon and the dusk‐to‐midnight sectors, peaking at dawn. Notably, weak solar wind conditions are associated with an increase in the dBOP asymmetric patterns. At low frequency in particular, while the dBOP seems to be primarily constant at dawn, the dusk dBOP decreases during quiet times, inducing a relatively larger dawn‐dusk asymmetry in such conditions. Furthermore, based on a comparison analysis between low‐frequency dBOP and auroral electron precipitation occurrence probability, we suggest that both types of distribution offer a more comprehensive understanding of the large‐scale auroral zone when considered concurrently. Our interpretation is that the dBOP at low frequencies reflects a quasi‐steady state circulation of energy, while the high‐frequency dBOP reflects the regions of rapid changes in the magnetosphere. The dBOP is therefore a crucial source of information regarding the magnetosphere‐ionosphere coupling.