Defense Meteorological Satellite Program Research Articles

Correcting the Saturation Effect in DMSP/OLS Stable Nighttime Light Products Based on Radiance-Calibrated Data

Nighttime light (NTL) products have become emerging instruments for studying human activity patterns in various applications, including demarcating urban areas, estimating the residential population, and monitoring the economic livelihood of cities. However, the deployment of such products, particularly the Defense Meteorological Satellite Program (DMSP)/Operational Line Scan (OLS) stable NTL data, is also subject to issues of data quality and methodological biases, including interannual inconsistency, saturation and blooming effect, and, in particular, the saturation problem, posing a challenge for further applications. This study proposed a novel saturation correction method based on regression model and radiance-calibrated NTL data (SARMRC) to correct the saturation effect in annual stable NTL data. The proposed method was applied to mainland China. The results show that SARMRC can effectively recover the light intensity distribution within the saturated areas of the stable NTL data. The corrected images were proven to be more spatially consistent with the reference National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) data and can better reflect the temporal development of cities compared to existing saturation correction methods (e.g., the index-based vegetation adjusted NTL urban index (VANUI) method and the interpolation method). The superior performance of SARMRC can be attributed to: 1) better utilization of both radiance-calibrated and stable NTL products and 2) the employment of training pixel selection and logarithmic model as well as double-year adjustment. The new method is expected to improve the data quality of DMSP/OLS stable NTL data for analyzing both local and regional socioeconomic activities.

High‐Latitude Electrodynamics Specified in SAMI3 Using AMPERE Field‐Aligned Currents

AbstractA new technique has been developed to determine the high‐latitude electric potential from observed field‐aligned currents (FACs) and modeled ionospheric conductances. FACs are observed by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), while the conductances are modeled by Sami3 is Also a Model of the Ionosphere (SAMI3). This is a development of the Magnetosphere‐Ionosphere Coupling approach first demonstrated by Merkin and Lyon (2010), https://doi.org/10.1029/2010ja015461. An advantage of using SAMI3 is that the model can be used to predict total electron content (TEC), based on the AMPERE‐derived potential solutions. 23 May 2014 is chosen as a case study to assess the new technique for a moderately disturbed case (min Dst: −36 nT, max AE: 909 nT) with good GPS data coverage. The new AMPERE/SAMI3 solutions are compared against independent GPS‐based TEC observations from the Multi‐Instrument Data Analysis Software (MIDAS) by Mitchell and Spencer (2003), and against Defense Meteorological Satellite Program (DMSP) ion drift data. The comparison shows excellent agreement between the location of the tongue of ionization in the MIDAS GPS data and the AMPERE/SAMI3 potential pattern, and good overall agreement with DMSP drifts. SAMI3 predictions of high‐latitude TEC are much improved when using the AMPERE‐derived potential as compared to Weimer's (2005), https://doi.org/10.1029/2005ja011270 model. The two potential models have substantial differences, with Weimer producing an average 77 kV cross‐cap potential versus 60 kV for the AMPERE‐derived potential. The results indicate that the 66‐satellite Iridium constellation provides sufficient resolution of FACs to estimate large‐scale ionospheric convection as it impacts TEC.

Tax Revenue, Night Lights and Underground Economy: Evidence from China

This objective of this paper is to assess the correlation among economic growth, tax revenues, tax evasion and tax reforms in China. Especially, we explore the usefulness of a special proxy for economic activity: the amount of nightlight that can be observed from outer space as a measure of economic growth to measure its impact on tax revenue. Empirical analyses GDP and taxes were based on the data of National Statistical Yearbook of China from 1991 to 2020. The night-lights data was gathered from the United States Air Force Defense Meteorological Satellite Program (DMSP). Kuznets approach was used to estimate the correlation between China’s GDP and taxes. The theoretical model to measure and calculate the sum of night illumination brightness was designed. We used the SUR-OLS method and the sum of night lights data to estimate its impact on China’s tax revenues. We have found that the total tax revenue increases with the growth of GDP, revealing that China’s GDP has not yet reached the Kuznets inflection point where the elasticity of tax revenue is equal to zero. That is, China’s current GDP does not show serious tax evasion. To confirm the correlation between GDP and direct and indirect taxes, we have found that GDP and indirect tax revenue shows a J-shaped curve. However, the relationship between GDP and direct tax holds an N-shaped curve, indicating that indirect tax revenue is less likely to lead to tax evasion than direct tax revenue. The evidence suggests that there is a significant positive correlation between the sum of night lights and GDP, and the impact of sum of night lights on total tax revenue is also positive, but it is insignificant.

Transpolar Arcs: Seasonal Dependence Identified by an Automated Detection Algorithm

AbstractTranspolar arcs (TPAs) are auroral features that occur polewards of the main auroral oval suggesting that the magnetosphere has acquired a complicated magnetic topology. They are primarily a northward interplanetary magnetic field (IMF) auroral phenomenon, and their formation and evolution have no single explanation that is unanimously agreed upon. An automated detection algorithm has been developed to detect the occurrence of TPAs in UV images captured from the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instrument onboard the Defense Meteorological Satellite Program (DMSP) spacecraft, in order to further study their occurrence. Via this detection algorithm TPAs are identified as a peak in the average radiance intensity poleward of 12.5° colatitude, in two or more of the wavelengths/bands sensed by SSUSI. Using the detection algorithm for the years 2010 to 2016, over 5000 images containing TPAs are identified. The occurrence of these TPAs shows a seasonal dependence, with more arcs being visible in the winter hemisphere. The orbital plane of DMSP has been investigated as a possible explanation of the dependences in the results of the detection algorithm. For the spacecraft of interest this leads to a preferential observation of the northern hemisphere with the detection algorithm missing TPAs in the southern hemisphere around 01–06 UT. No seasonal bias has been found for these spacecraft. We discuss the ramifications of these findings in terms of proposed TPA generation mechanisms and suggest reasons for the seasonal dependence including it being a reflection of probability of seeing TPAs due to visibility.

Developing Improved Time-Series DMSP-OLS-Like Data (1992–2019) in China by Integrating DMSP-OLS and SNPP-VIIRS

Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS) data are valuable records of nighttime lights (NTLs) in analyzing socioeconomic development. However, inconsistencies between these data have severely restricted long time-series analyses. Published time-series NTL data sets are not widely available or accurate because the DMSP-OLS calibration is inadequate and some missing data in the SNPP-VIIRS data are seldom considered for patching. To address these issues, we calibrated DMSP-OLS data (1992&#x2013;2013) by using a quadratic model based on a &#x201C;pseudo-invariant pixel&#x201D; method. Thereafter, an exponential smoothing model was used to predict and patch missing data in the monthly SNPP-VIIRS data (2013&#x2013;2019). Outliers and noise were also removed from the annual data. In addition, a sigmoid model was employed to generate improved simulated DMSP-OLS (SDMSP-OLS) data (2013&#x2013;2019), which were appended with the calibrated DMSP-OLS data (1992&#x2013;2013) to develop improved DMSP-OLS-like data (1992&#x2013;2019) in China. Finally, we qualitatively and quantitatively compared these data with published NTL data to examine data availability. Results showed that choosing invariant pixels to calibrate DMSP-OLS data can minimize discontinuity. The correlation between the SNPP-VIIRS data synthesized by the patched monthly SNPP-VIIRS data and the official annual SNPP-VIIRS data in 2015 (<inline-formula> <tex-math notation="LaTeX">$R^{2} =0.931$ </tex-math></inline-formula>) and 2016 (<inline-formula> <tex-math notation="LaTeX">$R^{2} =0.930$ </tex-math></inline-formula>) was higher than those of the two existing correction methods with <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values below 0.90. Spatial patterns of pixels in the improved SDMSP-OLS data in 2013 were more similar with the DMSP-OLS data than those in the published data. Strong correlations likewise existed between the total (average) pixel values of the improved SDMSP-OLS data (2013&#x2013;2019) and the DMSP-OLS data in 2012. We also found that the improved DMSP-OLS-like data held strong linear correlations with different statistics, the average <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values of which were 0.931 and 0.654 at the national and provincial levels, respectively. Meanwhile, the average regression <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values between the two published data sets and statistics were 0.858/0.506 and 0.911/0.611, respectively. Our study has proven that the improved DMSP-OLS-like data (1992&#x2013;2019) have immense potential to effectively evaluate socioeconomic development and anthropic activities.

Special Sensor Microwave Imager/Sounder Updates for the Global Precipitation Measurement V07 Data Suite

Observations from the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the Defense Meteorological Satellite Program F16, F17, F18, and F19 spacecrafts provide a significant portion of the microwave radiometer data within the Global Precipitation Measurement (GPM) mission constellation. In preparation for the GPM Version 7 (V07) data release, SSMIS corrections developed over a decade ago and incorporated in GPM Version 5 (V05) are reexamined and updated. The calibration updates presented here include pointing parameters affecting geolocation and viewing geometry, along-scan bias adjustments to account for scan edge falloffs and sun angle corrections to account for heating anomalies including an emissive reflector. To address errors in the V05 geolocation, the sensor roll, pitch, yaw, half cone angle, and timing offsets are reanalyzed and updated. The along-scan bias adjustment is updated in a manner consistent with recent Special Sensor Microwave Imager updates to account for variations in scene temperature. Finally, significant improvements to the SSMIS sun angle correction are made by using data from the entire mission, extending the corrections to include the higher frequency channels, and deriving a more consistent channel-to-channel correction. From V05 to V07, the geolocation adjustment is approximately 5–10 km, the earth incidence angle difference is 0–0.4°, and the average brightness temperature change is 0–2 K, but individual pixels may be up to several kelvin difference depending on sensor and channel. The result of these updates is a significant improvement in the quality and long-term consistency of the SSMIS data that are included in the GPM V07 dataset.

A random forest method for constructing long-term time series of nighttime light in Central Asia

The nighttime light (NTL) data from Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) have been extensively used to characterize spatiotemporal variations of human activities on the ground. However, inconsistency of these two datasets hampers their applications for long-term analysis. Hence, the current paper managed to introduce the Random Forest model (RF) for constructing a long-term time series of NTL with considering topographical and climatic influences. Performance of the RF was compared with that of several common curve estimation methods, namely linear regression, quadratic regression, cubic regression, logistic regression and Biphasic Dose Response (BDR) model based on two datasets in overlapping years of 2012 and 2013. Relative importances of natural factors were quantified with the initial RF model with all variables inputted into, and four typical RF models with relatively better performance were screened on this basis. The results showed that VIIRS data, latitude and longitude, elevation and precipitation were inputted into RF models in turn and their simulation accuracies gradually increased. According to accuracy indicators, RF models with topographical and climatic factors as input variables were far superior to the BDR which performed better than other curve estimation methods. In particular, the RF model with VIIRS data, latitude and longitude as input variables had higher simulation accuracy and less computation amounts was recommended as the best-fit RF model for the inter-calibration of NTL data in Central Asia. Afterwards, two continuous time series of NTL from 1992 to 2018 generated respectively with the best-fit RF and BDR were compared and results indicated that calibrated data with the RF were more consistent with DMSP-OLS data and Landsat 8 satellite images. Besides, the scope and brightness of NTL with RF had a significant positive correlation with log-transformed socioeconomic factors, confirming the availability of RF. The current paper offers a new thought to settle inconsistency of NTL data from two sensors with considering influences of natural factors, which is expected to help understand and explore complex interactions between natural environment and human activities in the arid Central Asia.

Outdoor light at night and autism spectrum disorder in Shanghai, China: A matched case-control study

BackgroundSeveral environmental factors have been identified to be associated with autism spectrum disorder (ASD) over the past decades. However, evidence is limited for the effect of exposure to outdoor light at night (LAN) on ASD in China and even elsewhere in the world. MethodsParticipants in this study were from a multi-stage sampling survey on ASD conducted between June 2014 and October 2014 among children aged 3–12 years in Shanghai, China. All participants underwent a two-stage screening of ASD via questionnaire, and then, suspected cases were finally diagnosed by clinical examination. For data analyses, each ASD case was randomly matched with 10 healthy controls by age and sex. The LAN data were extracted from the stable lights product of the US Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) according to geolocation information of residential addresses. Mean levels of exposure to LAN during the 3 years after birth and 1 year before birth were calculated. We used conditional logistic regression models to examine the association between LAN and ASD. ResultsWe investigated 84,934 children from 96 kindergartens, 55 primary schools, and 28 special education schools, and 203 children were diagnosed as ASD cases. A total of 1727 children (157 ASD cases and 1570 healthy controls) were included in the final analyses. Brighter LAN exposures after and before birth were significantly associated with higher risk of ASD. After adjusting for potential covariates, adjusted odd ratios and 95% confidence intervals associated with per unit increase in LAN were 1.066 (1.027, 1.107) during the 3 years after birth and 1.046 (1.018, 1.075) during the 1 year before birth. ConclusionsResults of our study concluded brighter LAN exposure was significantly associated with higher risk of ASD among Chinese children, which suggested that outdoor LAN could be a potential risk factor of ASD.

Cross-Sensor Nighttime Lights Image Calibration for DMSP/OLS and SNPP/VIIRS with Residual U-Net

Remote sensing of nighttime lights (NTL) is widely used in socio-economic studies of economic growth, urbanization, stability of power grid, environmental light pollution, pandemics and military conflicts. Currently, NTL data are collected with two sensors: (1) Operational Line-scan System (OLS) onboard the satellites from the Defense Meteorology Satellite Program (DMSP) and (2) Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP (SNPP) and NOAA-20 satellites from the Joint Polar Satellite System (JPSS). However, the nighttime images acquired by these two sensors are incompatible in spatial resolution and dynamic range. To address this problem, we propose a method for the cross-sensor calibration with residual U-net convolutional neural network (CNN). The CNN produces DMSP-like NTL composites from the VIIRS annual NTL composites. The pixel radiances predicted from VIIRS are highly correlated with NTL observed with OLS (0.96 &lt; R2 &lt; 0.99). The method can be used to extend long-term series of annual NTL after the end of DMSP mission or to cross-calibrate same year NTL from different satellites to study diurnal variations.

Extending the DMSP Nighttime Lights Time Series beyond 2013

Data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) sensors have been archived and processed by the Earth Observation Group (EOG) at the National Oceanic and Atmospheric Administration (NOAA) to make global maps of nighttime images since 1994. Over the years, the EOG has developed automatic algorithms to make Stable Lights composites from the OLS visible band data by removing the transient lights from fires and fishing boats. The ephemeral lights are removed based on their high brightness and short duration. However, the six original satellites collecting DMSP data gradually shifted from day/night orbit to dawn/dusk orbit, which is to an earlier overpass time. At the beginning of 2014, the F18 satellite was no longer collecting usable nighttime data, and the focus had shifted to processing global nighttime images from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data. Nevertheless, it was soon discovered that the F15 and F16 satellites had started collecting pre-dawn nighttime data from 2012 onwards. Therefore, the established algorithms of the previous years were extended to process OLS data from 2013 onwards. Moreover, the existence of nighttime data from three overpass times for the year 2013–DMSP satellites F18 and F15 from early evening and pre-dawn, respectively, and the VIIRS from after midnight, made it possible to intercalibrate the images of three different overpass times and study the diurnal pattern of nighttime lights.

Optimal estimation of total precipitable water from INSAT‐3D/3DR Imagers

AbstractTotal precipitable water (TPW) is an important parameter for weather prediction apart from study of the hydrological cycle and climate change. Presently, TPW is generated operationally from infrared sounders on board INSAT‐3D and 3DR. However, the Sounder provides observations at a coarser resolution of 10 km over a limited region of coverage, and takes about 60 min to scan the Indian landmass. The Imager, in contrast, provides observation over a larger geographical region (full disc) at the interval of 30 min and a finer spatial resolution of 4 km. To exploit this advantage, an optimal estimation (OE) technique has been attempted to retrieve TPW from thermal infrared split‐window observations of INSAT‐3D/3DR Imagers in clear‐sky conditions. Assessment of the retrieved TPW is carried out for data of one year over land and ocean regions, separately against the three independent reference TPW products, acquired from radiosondes, Special Sensor Microwave Imager Sounder (SSMIS) on board Defense Meteorological Satellite Program (DMSP) F17 satellite, and fifth‐generation European Centre for Medium‐Range Weather Forecasts ReAnalysis (ERA5). The validation analysis of the retrieved TPW over land against the radiosonde observations and ERA5 TPW products for the entire period shows a root‐mean‐square error (RMSE) of less than 6 mm. An RMSE of better than 4 mm is observed over ocean, when compared with the operational TPW products of the SSMIS and ERA5 TPW products. Moreover, the RMSE of the retrieved TPW shows consistency for each month that clearly implies the robustness of the developed algorithm. The developed algorithm has been proposed for operational implementation at the Meteorological and Oceanographic Data Archival and Dissemination Centre (MOSDAC) hosted by Space Applications Centre, Ahmedabad and India Meteorological Department (IMD), New Delhi, India.

Observational Properties of 15MLT‐PCA in the Southern Hemisphere and the Switching Effects of IMF By on 15MLT‐PCA Occurrence

AbstractBased on Special Sensor Ultraviolet Spectrographic Imager on Defense Meteorological Satellite Program spacecraft (DMSP/SSUSI) observations in the Northern Hemisphere, a particular polar cap arc observed at ∼1,500 magnetic local time (MLT) sector was identified and was named 15MLT‐PCA. A 15MLT‐PCA model proposed for the Northern Hemisphere suggests that the 15MLT‐PCA is caused by a lobe reconnection related to the tilt angle and lobe field line twisting due to a long‐lasting positive interplanetary magnetic field (IMF) By condition. However, it is unclear if the 15MLT‐PCA can be observed in the Southern Hemisphere and how the IMF By influences its occurrence and location. Using the long‐term DMSP/SSUSI observations in the Southern Hemisphere, we confirmed that the 15MLT‐PCA could be observed in the Southern Hemisphere in summer under long‐lasting negative IMF By and predominantly positive IMF Bx. The ion energy dispersion and some other statistical properties are also investigated. Further, we showed that the IMF By has a switching effect on the occurrence of the 15MLT‐PCA using multiple cases. We found that the 15MLT‐PCA disappear as soon as the IMF By changed to an unfavorable condition, but it seems that the favorable conditions need to be maintained for ∼1 hr for the occurrence of 15MLT‐PCA. We also found that the IMF By magnitude is well correlated to the MLT location of the 15MLT‐PCA. We suggest that all the results support the 15MLT‐PCA model and imply that a magnetotail lobe reconnection should be common in the summer hemisphere because the well‐known Parker Spiral favors meeting the model's IMF requirements.

Inhibition of F3 Layer at Low Latitude Station Sanya During Recovery Phase of Geomagnetic Storms

AbstractA special F2 layer stratification structure named F3 layer occurs frequently in equatorial and low latitude ionosphere during summer daytime. In this study, a new phenomenon of decreasing occurrence of the F3 layer, and narrowing differences of virtual heights between the F3 and F2 layers in the recovery phase of geomagnetic storms is reported. We named this phenomenon as the inhibition of F3 layer event (IFLE). Using the ionosonde observations during summer of 2012–2015 at Sanya (18.3°N, 109.6°E, dip latitude 12.6°N), we found that IFLE occurred during 14 geomagnetic storms (−127 nT ≤ Dstmin ≤ −22 nT), which was accompanied by the thinning and lowering bottom ionosphere, and decreasing the crest‐to‐trough ratio of total electron content (TEC). Together with the ion drift data measured by Defense Meteorological Satellite Program F18, we suggest that the IFLE is mainly caused by the westward disturbance dynamo electric field (DDEF; downward drift velocity), taking disadvantage of the formation of the F3 layer. The observed decrease in the crest‐to‐trough ratio of TEC also indicates that the westward DDEF should prompt IFLE by providing less plasma from the equatorial region to the low latitude. Hence, IFLE then can be a good indicator to show how the magnetosphere‐ionospheric coupling process affects the low and equatorial ionosphere. Notably, the results also indicate that even a very weak geomagnetic storm can generate significant changes in ionospheric state at low latitude.

Low‐Latitude Zonal Ion Drifts and Their Relationship With Subauroral Polarization Streams and Auroral Return Flows During Intense Magnetic Storms

AbstractWe analyze horizontal plasma drifts measured by the Defense Meteorological Satellite Program satellites during two intense magnetic storms. It is found, for the first time, that westward plasma flows associated with subauroral polarization streams (SAPS) in the dusk‐evening sector penetrate continuously to equatorial latitudes. The westward ion drifts between subauroral and equatorial latitudes occur nearly simultaneously. The latitudinal profile of the westward ion drifts at low latitudes (approximately within ±30° magnetic latitude [MLat]) is relatively flat, and the westward ion drifts at the magnetic equator reach 200–300 m s−1. In the dawn‐morning sector, eastward ion drifts at subauroral latitudes are also SAPS. The storm‐time dawnside auroral boundary moves to ∼±55° MLat, and the dawnside SAPS penetrate to ∼±20° MLat at 0930 local time. A dawnside SAPS flow channel appears to exist, although it is not as well defined as the duskside SAPS flow channel. Thermospheric wind data measured by the Challenging Minisatellite Payload satellite are analyzed, and zonal disturbance winds are derived. Disturbance winds can reach equatorial latitudes rapidly near midnight but are limited to ±40° geographic latitude or higher near noon. The effects of disturbance winds on the zonal ion drifts at middle and low latitudes are discussed. It is suggested that both the westward ion drifts at middle and low latitudes in the dusk‐evening sector and the eastward ion drifts at middle and lower latitudes in the dawn‐morning sector are caused primarily by penetration of the SAPS and auroral electric fields.

Topside Measurements at Jicamarca During the 2019-2020 Deep Solar Minimum.

We present measurements of the equatorial topside ionosphere above Jicamarca made during extremely low solar flux conditions during the deep solar minimum of 2019-2020. Measurements were made in October, 2019, February, 2020, and September, 2020. The main features observed are a large and extended decrease in noontime temperatures unlike that seen in studies at moderate solar flux levels, predawn ionospheric heating as early as 0300 LT, large day-to-day variability in the O+/H+ transition height, and negligible helium ion concentration at all altitudes. Data from the Ion Velocity Meter (IVM) instrument onboard the Ionospheric Connection Explorer (ICON) and the Topside Ionospheric Plasma Monitor (SSIES) onboard the Defense Meteorological Satellite Program (DMSP) satellites are used to assess agreement with ISR data and assist with the analysis of the predawn heating phenomena. We also analyze the data in light of the SAMI2-PE model which shows less agreement with the data than at higher solar flux. The main areas of discrepancy with the data are outlined, such as the absence of significant predawn heating, less pronounced decreases in noontime temperatures, and much higher O+ fractions at high altitudes, particularly in September. Finally, a sensitivity analysis of the model to various forcing agents such as neutral winds, plasma drifts, solar flux, and heat flow is performed. A discussion is presented on bridging the discrepancies in future model runs. Novel techniques of clutter removal and noise power bias correction are introduced and described in the appendices.

Validation of SSUSI-derived auroral electron densities: comparisons to EISCAT data

Abstract. The coupling of the atmosphere to the space environment has become recognized as an important driver of atmospheric chemistry and dynamics. In order to quantify the effects of particle precipitation on the atmosphere, reliable global energy inputs on spatial scales commensurate with particle precipitation variations are required. To that end, we have validated auroral electron densities derived from the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) data products for average electron energy and electron energy flux by comparing them to EISCAT (European Incoherent Scatter Scientific Association) electron density profiles. This comparison shows that SSUSI far-ultraviolet (FUV) observations can be used to provide ionization rate and electron density profiles throughout the auroral region. The SSUSI on board the Defense Meteorological Satellite Program (DMSP) Block 5D3 satellites provide nearly hourly, 3000 km wide high-resolution (10 km×10 km) UV snapshots of auroral emissions. These UV data have been converted to average energies and energy fluxes of precipitating electrons. Here we use those SSUSI-derived energies and fluxes as input to standard parametrizations in order to obtain ionization-rate and electron-density profiles in the E region (90–150 km). These profiles are then compared to EISCAT ground-based electron density measurements. We compare the data from two satellites, DMSP F17 and F18, to the Tromsø UHF radar profiles. We find that differentiating between the magnetic local time (MLT) “morning” (03:00–11:00 MLT) and “evening” (15:00–23:00 MLT) provides the best fit to the ground-based data. The data agree well in the MLT morning sector using a Maxwellian electron spectrum, while in the evening sector using a Gaussian spectrum and accounting for backscattered electrons achieved optimum agreement with EISCAT. Depending on the satellite and MLT period, the median of the differences varies between 0 % and 20 % above 105 km (F17) and ±15 % above 100 km (F18). Because of the large density gradient below those altitudes, the relative differences get larger, albeit without a substantially increasing absolute difference, with virtually no statistically significant differences at the 1σ level.

Local and conjugate ionospheric total electron content variation during the 21 June 2020 solar eclipse

• Ionospheric TEC showed an asymmetric latitudinal depletion around totality path. • Ionospheric disturbances in both local and conjugate eclipse regions were analyzed. • Eclipse-induced ionospheric bow wave structures and TIDs were identified. This paper studies the ionospheric response to a low-latitude annular solar eclipse event on 21 June 2020 at both eclipse and conjugate regions using a dense network of Global Navigation Satellite Systems receivers, Defense Meteorological Satellite Program and Swarm satellites data, as well as ionosonde measurements over the Asian-Oceania sector. The large scale ionospheric variation and small scale wave-like perturbations during the eclipse were analyzed by using high-resolution Total Electron Content (TEC) maps and in-situ electron density/temperature data. The main results are as follows: (1) A local TEC reduction of 4–7 TEC Unit ( ∼ 30–50%) was identified along the totality path, with larger depletion in the southern edge of totality path than the northern edge. (2) The equatorial ionization anomaly in the Asian sector exhibited a complicated variation pattern with a slightly different longitudinal/local time and altitudinal response, which showed considerable TEC/ Ne depletion in the East Asian sector and at ∼ 850 km close to local afternoon during the eclipse, but a slight TEC/ Ne enhancement around the Indian sector and at ∼ 500 km in the post-eclipse periods. (3) Large ionospheric perturbations were identified that traveled at approximately the same velocity as the supersonic moon shadow, and the ionospheric bow wave features were also triggered by the solar eclipse. (4) The Oceania TEC in the Southern Hemisphere conjugate location experienced a coincident minor reduction and wave-like fluctuations during the eclipse, likely indicating some possible interconnections between the eclipse and the conjugate ionospheres.

Longitudinal Dependence of Ionospheric Poynting Flux in the Northern Hemisphere During Quite Times

AbstractThis study reports the longitudinal dependence of the field‐aligned Poynting flux in the Northern Hemisphere (NH) based on 11 years' (1999–2009) observations at ∼800 km altitude by the Defense Meteorological Satellite Program (DMSP) F13 satellite. Seasonal variations of the longitudinal distributions of the Poynting flux in both geographic and geomagnetic coordinates were statistically investigated. The net Poynting flux, which is the sum of downward and upward fluxes, is downward and peaks in the magnetic local time pre‐noon sector and near the geomagnetic pole. In geographic coordinates there is a longitudinal peak of the net Poynting flux that occurs between ∼130° and 160°W. The net Poynting flux is, in general, stronger in the western hemisphere than in the eastern hemisphere and larger in summer than in winter. These results indicate that the magnetospheric energy deposition into the northern polar upper atmosphere has obvious longitudinal and seasonal variations.

Diurnal UT Variation of Low Latitude Geomagnetic Storms Using Six Indices

AbstractA quasi‐semidiurnal type pattern was observed earlier in the diurnal UT variation of the geomagnetic storms studied using mainly Kyoto Dst (disturbance storm‐time) index. However, the pattern has been argued as apparent due to uneven longitude distribution of the four Dst observatories. Unlike earlier studies, this paper investigates the diurnal UT variation of the storms automatically identified in six available indices including Kyoto Dst, USGS (United States Geological Survey) Dst, SymH (symmetric‐H), RC (ring current), Dcx (corrected extended Dst), and AER (Atmospheric and Environmental Research) in 50, 50, 36, 21, 5, and 7 years, respectively. The indices are derived using 4, 4, 12, 14, and 15 ground observatories (with maximum longitude separations of ∼120°, 120°, 70°, 110°, and 50°) and four DMSP (Defense Meteorology Satellite Program) satellites, respectively. The UT distribution of the storm intensity (minimum value of an index during the storm main phase) in all indices shows a striking quasi‐semidiurnal type variation with maxima around 06–08 UT and 21–23 UT and minima around 03–05 UT and 13–15 UT. Similar quasi‐semidiurnal variation is also observed in the computed values of the main energy input in the ring current. The variation correlates well with the variations of the dipole tilt angles μ and θ involved in the equinoctial hypothesis and Russell‐McPherron (RM) effect, respectively. These observations indicate that the quasi‐semidiurnal variation is real.

Spatial allocation of anthropogenic carbon dioxide emission statistics data fusing multi-source data based on Bayesian network

A gridded social-economic data is essential for geoscience analysis and multidisciplinary application. Spatial allocation of carbon dioxide statistics data is an important issue in the context of global climate change, which involves the carbon emissions accounting and decomposition of responsibility for carbon emission reductions. In this research a new spatial allocation method for non-point source anthropogenic carbon dioxide emissions (ACDE) fusing multi-source data using Bayesian Network (BN) was introduced. In addition to common-used DMSP (Defense Meteorological Satellite Program), PD (population density) and GDP (Gross Domestic Production) data, the land cover and vegetation data was imported into the model as prior knowledge to optimize the model fitting. The prior knowledge here was based on the understanding that ACDE was dominated by human activities and has strong correlations with land cover and vegetation conditions. A 1 km gridded ACDE map integrated emissions form point-source and non-point source was generated and validated. The model predicts ACDE with high accuracies and great improvement can be observed when fusing land cover and vegetation as prior knowledge. The model can achieve successful statistics data downscaling on national scale provided adequate sample data are available, offering a novel method for ACDE accounting in China.