Defense Meteorological Satellite Program Research Articles

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

The use of nighttime lights (NTL) data to proxy for local economic activity is well established in remote sensing and other disciplines. Validation studies comparing NTL data with traditional economic indicators, such as Gross Domestic Product (GDP), underpin this usage in applied studies. Yet the most widely cited validation studies do not use the latest NTL data products, may not distinguish between time-series and cross-sectional uses of NTL data, and usually are for aggregated units, such as nation-states or the first sub-national level, yet applied studies increasingly focus on smaller and lower-level spatial units. To provide more updated and disaggregated validation results, this study examines relationships between GDP and NTL data for 2657 county-level units in China, observed each year from 2012 to 2019. The NTL data used were from three sources: the Defense Meteorological Satellite Program (DMSP), whose time series was recently extended to 2019; and two sets of Visible Infrared Imaging Radiometer Suite (VIIRS) data products. The first set of VIIRS products is the recently released version 2 (V.2 VNL) annual composites, and the second is the NASA Black Marble annual composites. Contrasts were made between cross-sectional predictions for GDP differences between areas and time-series predictions of economic activity changes over time, and also considered different levels of spatial aggregation.

The Origin of Midlatitude Plasma Depletions Detected During the 12 February 2000 and 29 October 2003 Geomagnetic Storms

AbstractLarge amplitude plasma density irregularities have occasionally been detected at night in the midlatitudeFregion during geomagnetic storms. They are often interpreted in terms of equatorial plasma bubbles (EPBs) because midlatitude irregularities have the morphology of EPBs. This study assesses whether morphology can be a determining factor in ascribing the origin of such midlatitude ionospheric irregularities. We address this question by analyzing the observations of the First Republic of China satellite (ROCSAT‐1) and Defense Meteorological Satellite Program (DMSP)‐F14 and ‐F15 satellites during the geomagnetic storms on 12 February 2000 and 29 October 2003. On both days, ROCSAT‐1 detects plasma depletions at midlatitudes in broad longitude regions and DMSP satellites detect isolated severe plasma depletions whose widths and depths are much wider and deeper than those of typical EPBs. The distinguishing characteristics during the storms are the detection of midlatitude depletions only in the Southern Hemisphere and the occurrence of some of these depletions before 19 hr local time and at the longitudes where EPBs are absent in the equatorial region. These characteristics are not explained satisfactorily by the characteristics of EPBs. Considering the detection of some of the midlatitude depletions at the equatorward edge of ionospheric perturbations in midlatitudes, midlatitude depletions are likely ionospheric perturbations that originated from higher latitudes. Because midlatitude depletions can originate from different sources, the morphology alone is not a determining factor of their origin.

What Can We Learn from Nighttime Lights for Small Geographies? Measurement Errors and Heterogeneous Elasticities

Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest.

Simultaneous Observations of a Sporadic E Layer by Digisonde and SuperDARN HF Radars at Zhongshan, Antarctica

AbstractSporadic E (Es) layers could be composed of metallic ions and formed, modified, or transported by the action of convective electric fields in the high latitude ionosphere. In this paper, by utilizing simultaneous observations from Digisonde and Super Dual Auroral Radar Network (SuperDARN) HF radars at Zhongshan Station (ZHS, 69.4°S, 76.4°E), Antarctica, a thin Es layer, which initially formed in the lower F region and descended into the lower E region, with wavelike structures, was recorded by Digisonde on 14 November 2019. The Es layer‐related concurrent ionospheric irregularities were also detected by the SuperDARN ZHS HF radar. By using a global‐scale 2‐D convection map, combined with images from the Special Sensor Ultraviolet Spectrographic Imager instruments onboard Defense Meteorological Satellite Program (DMSP) spacecraft, it is proposed that the flow shears associated with the duskside convective circulation are responsible for the evolution of the Es layer. Moreover, using the HF radar elevation angle data to measure the scatter height, it is strongly suggested that the Es layer was elongated with convection circulation. The electrodynamic processes responsible for the formation and evolution of the Es layer are discussed.

Ionospheric Disturbances in Low‐ and Midlatitudes During the Geomagnetic Storm on 26 August 2018

AbstractPlasma density depletions at midlatitudes during geomagnetic storms are often understood in terms of equatorial plasma bubbles (EPBs) due to their morphological similarity. However, our study reports the observations that reveal the generation of plasma depletions at midlatitudes by local sources. During the geomagnetic storm on 26 August 2018, the Defense Meteorological Satellite Program and Swarm satellites detected plasma depletions at midlatitudes in the Asian sector in the absence of EPBs in the equatorial region. This observation and the total electron content (TEC) maps over Japan demonstrate that traveling ionospheric disturbances (TIDs) are the sources of midlatitude plasma depletions in the Asian sector. Near the west coast of the United States, the development of a narrow TEC depletion band was identified from TEC maps. The TEC depletion band, which is elongated in the northwest–southeast direction, moves toward the west with a velocity of approximately 240 m/s. The TEC at the TEC depletion band is about 5 TEC units (1016 m−2) smaller than the ambient TEC. As this band is confined to the midlatitudes, this phenomenon is not associated with an EPB. The characteristics of the TEC depletion band are consistent with those of medium‐scale TIDs. Observations in the Asian sector and the TEC depletion band over the United States demonstrate that plasma depletions can develop at midlatitudes by local sources. Therefore, the morphological similarity between midlatitude irregularities and EPBs or their coincident occurrence does not provide corroborating evidence of their connection.

Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data to Evaluate Poverty in Southwestern China

Poverty alleviation is one of the most important tasks facing human social development. It is necessary to make accurate monitoring and evaluations for areas with poverty to improve capability of implementing poverty alleviation policies. Here, this study introduced nighttime light (NTL) data to estimate county-level poverty in southwest China. First, this study used particle swarm optimization-back propagation hybrid algorithm to explore the potential relationship between two NTL data (the Defense Meteorological Satellite Program’s Operational Line Scan System data and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite data). Then, we integrated two NTL data at the pixel level to establish a consistent time-series of NTL dataset from 2000 to 2019. Next, an actual comprehensive poverty index (ACPI) was employed as an indicator of multidimensional poverty at county level based on 11 socioeconomic and natural variables, and which could be the reference to explore the poverty evaluation using NTL data. Based on the correlation between the ACPI and NTL characteristic variables, a poverty evaluation model was developed to evaluate the poverty situation. The result showed the great matching relationship between DMSP-OLS and NPP-VIIRS data (R2 = 0.84). After calibration, the continuity and comparability of DMSP-OLS data were significantly improved. The integrated NTL data also reflected great consistency with socioeconomic development (r = 0.99). The RMSE between ACPI and the estimated comprehensive poverty index (ECPI) based on the integrated NTL data is approximately 0.19 (R2 = 0.96), which revealed the poverty evaluation model was feasible and reliable. According to the ECPI, we found that the magnitude of poverty eradication increased in southwest China until 2011, but slowed down from 2011 to 2019. Regarding the spatial scale, geographic barriers are a key factor for poverty, with high altitude and mountainous areas typically having a high incidence of poverty. Our approach offers an effective model for evaluation poverty based on the NTL data, which can contribute a more reliable and efficient monitoring of poverty dynamic and a better understanding of socioeconomic development.

Total water vapour columns derived from Sentinel 5P using the AMC-DOAS method

Abstract. Water vapour is the most abundant natural greenhouse gas in the Earth's atmosphere, and global data sets are required for meteorological applications and climate research. The Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor (S5P) launched on 13 October 2017 has a high spatial resolution of around 5 km and a daily global coverage. Currently, there is no operational total water vapour product for S5P measurements. Here, we present first results of a new scientific total column water vapour (TCWV) product for S5P using the so-called air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) scheme. This method analyses spectral data between 688 and 700 nm and has already been successfully applied to measurements from the Global Monitoring Experiment (GOME) on ERS-2, the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on Envisat and GOME-2 on MetOp. The adaptation of the AMC-DOAS method to S5P data requires an additional post-processing procedure to correct the influences of surface albedo, cloud height and cloud fraction. The quality of the new AMC-DOAS S5P water vapour product is assessed by comparisons with data from GOME-2 on MetOp-B retrieved also with the AMC-DOAS algorithm and with four independent data sets, namely reanalysis data from the European Centre for Medium range Weather Forecast (ECMWF ERA5), data obtained by the Special Sensor Microwave Imager and Sounder (SSMIS) flown on the Defense Meteorological Satellite Program (DMSP) platform 16 and two scientific S5P TCWV products derived from TROPOMI measurements. Both are recently published TCWV products for S5P provided by the Max Planck Institute for Chemistry (MPIC) in Mainz and the Netherlands Institute for Space Research (SRON), Utrecht. The SRON TCWV is limited to clear-sky scenes over land. These comparisons reveal a good agreement between the various data sets but also some systematic differences between all of them. On average, the daily derived offset between AMC-DOAS S5P TCWV and AMC-DOAS GOME-2B TCWV is negative (around −1.5 kg m−2) over land and positive over ocean surfaces (more than 1.5 kg m−2). In contrast, SSMIS TCWV is on average lower than AMC-DOAS S5P TCWV by about 3 kg m−2. Monthly averaged ERA5 TCWV and AMC-DOAS S5P TCWV comparison shows spatial features over both land and water surface. Over land, there are systematic spatial structures. There are larger differences between AMC-DOAS S5P TCWV and ERA5 TCWV in tropical regions. Over sea, AMC-DOAS S5P TCWV is slightly lower than ERA5 TCWV by around 2 kg m−2. The AMC-DOAS S5P TCWV and S5P TCWV from MPIC agree on average within 1 kg m−2 over both land and ocean. TCWV from SRON shows daily global averaged differences to AMC-DOAS S5P TCWV of around 1.2 kg m−2. All of these differences are in line with the accuracy of these products and with the typical range of differences of 5 kg m−2 obtained when comparing different TCWV data sets. The AMC-DOAS TCWV product for S5P provides therefore a valuable new and independent data set for atmospheric applications which also has a higher spatial coverage than the other S5P TCWV products.

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.