Defense Meteorological Satellite Program Research Articles

Does artificial light-at-night exposure contribute to the worldwide obesity pandemic?

Worldwide overweight and obesity rates are on the rise, with about 1 900 billion adults being defined as overweight and about 600 million adults being defined as obese by the World Health Organization (WHO). Increasing exposure to artificial light-at-night (ALAN) may influence body mass, by suppression of melatonin production and disruption of daily rhythms, resulting in physiological or behavioral changes in the human body, and may thus become a driving force behind worldwide overweight and obesity pandemic. We analyzed most recent satellite images of night time illumination, available from the US Defense Meteorological Satellite Program (DMSP), combining them with country-level data on female and male overweight and obesity prevalence rates, reported by the WHO. The study aims to identify and measure the strength of association between ALAN and country-wide overweight and obesity rates, controlling for per capita GDP, level of urbanization, birth rate, food consumption and regional differences. ALAN emerged as a statistically significant and positive predictor of overweight and obesity (t>1.97; P<0.05), helping to explain, together with other factors, about 70% of the observed variation of overweight and obesity prevalence rates among females and males in more than 80 countries worldwide. Regional differences in the strength of association between ALAN and excessive body mass are also noted. This study is the first population-level study that confirms the results of laboratory research and cohort studies in which ALAN was found to be a contributing factor to excessive body mass in humans.

Sea turtle nesting patterns in Florida vis‐à‐vis satellite‐derived measures of artificial lighting

AbstractLight pollution contributes to the degradation and reduction of habitat for wildlife. Nocturnally nesting and hatching sea turtle species are particularly sensitive to artificial light near nesting beaches. At local scales (0.01–0.1 km), artificial light has been experimentally shown to deter nesting females and disorient hatchlings. This study used satellite‐based remote sensing to assess broad scale (~1–100s km) effects of artificial light on nesting patterns of loggerhead (Caretta caretta), leatherback (Dermochelys coriacea) and green turtles (Chelonia mydas) along the Florida coastline. Annual artificial nightlight data from 1992 to 2012 acquired by the Defense Meteorological Satellite Program (DMSP) were compared to an extensive nesting dataset for 368, ~1 km beach segments from this same 21‐year period. Relationships between nest densities and artificial lighting were derived using simultaneous autoregressive models to adjust for the presence of spatial autocorrelation. Though coastal urbanization increased in Florida during this period, nearly two‐thirds of the surveyed beaches exhibited decreasing light levels (N = 249); only a small fraction of the beaches showed significant increases (N = 52). Nest densities for all three sea turtle species were negatively influenced by artificial light at neighborhood scales (&lt;100 km); however, only loggerhead and green turtle nest densities were influenced by artificial light levels at the individual beach scale (~1 km). Satellite monitoring shows promise for light management of extensive or remote areas. As the spectral, spatial, and temporal resolutions of the satellite data are coarse, ground measurements are suggested to confirm that artificial light levels on beaches during the nesting season correspond to the annual nightlight measures.

How does sprawl differ across cities in China? A multi-scale investigation using nighttime light and census data

Timely and accurate measurement of urban sprawl is indispensable for assessing its environmental and societal impacts. However, few studies have examined urban sprawl in cities across China. In this study, we quantified urban sprawl in different cities across China from 1990 to 2010 by combining the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) nighttime light images and national census data. We found that the annual growth rate of urban areas was 2.45% greater than that of the urban population in China from 1990 to 2010, indicating an overall trend of urban sprawl. Small and medium cities in west China had the highest level of sprawl over time. We conclude that much more attention should be given to the prevention of excessive urban expansion in small and medium cities in west China.

Determination of the Earth's plasmapause location from the CE‐3 EUVC images

AbstractThe Moon‐based Extreme Ultraviolet Camera (EUVC) aboard China's Chang'e‐3 (CE‐3) mission has successfully imaged the entire Earth's plasmasphere for the first time from the side views on lunar surface. An EUVC image on 21 April 2014 is used in this study to demonstrate the characteristics and configurations of the Moon‐based EUV imaging and to illustrate the determination algorithm of the plasmapause locations on the magnetic equator. The plasmapause locations determined from all the available EUVC images with the Minimum L Algorithm are quantitatively compared with those extracted from in situ observations (Defense Meteorological Satellite Program, Time History of Events and Macroscale Interactions during Substorms, and Radiation Belt Storm Probes). Excellent agreement between the determined plasmapauses seen by EUVC and the extracted ones from other satellites indicates the reliability of the Moon‐based EUVC images as well as the determination algorithm. This preliminary study provides an important basis for future investigation of the dynamics of the plasmasphere with the Moon‐based EUVC imaging.

Filamentary field-aligned currents at the polar cap region during northward interplanetary magnetic field derived with the Swarm constellation.

ESA’s Swarm constellation mission makes it possible for the first time to determine field-aligned currents (FACs) in the ionosphere uniquely. In particular at high latitudes, the dual-satellite approach can reliably detect some FAC structures which are missed by the traditional single-satellite technique. These FAC events occur preferentially poleward of the auroral oval and during times of northward interplanetary magnetic field (IMF) orientation. Most events appear on the nightside. They are not related to the typical FAC structures poleward of the cusp, commonly termed NBZ. Simultaneously observed precipitating particle spectrograms and auroral images from Defense Meteorological Satellite Program (DMSP) satellites are consistent with the detected FACs and indicate that they occur on closed field lines mostly adjacent to the auroral oval. We suggest that the FACs are associated with Sun-aligned filamentary auroral arcs. Here we introduce in an initial study features of the high-latitude FAC structures which have been observed during the early phase of the Swarm mission. A more systematic survey over longer times is required to fully characterize the so far undetected field aligned currents.

World energy consumption pattern as revealed by DMSP-OLS nighttime light imagery

Remotely sensed nighttime light (NTL) from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) provides a spatially consistent and cost-effective mean to estimate energy consumption pattern. While previous researches have documented the application of NTL to predict electric power consumption (EPC) with varying degrees of success, few have systematically studied the possible factors affecting the EPC-NTL relationship. Moreover, no substantial research effort has been made to relate overall energy consumption (OEC) to NTL. This study investigated key factors governing the EPC/OEC-NTL relationship by examining the influences of affluence, urbanization, technology, temperature, and NTL pattern. Results show that EPC increased with higher per capital GDP, urbanization rate, and high-technology exports, and lower agricultural development, both globally and regionally. Meanwhile, EPC generally reduced with higher temperature and more agglomerate human activities. A strong OEC-NTL relationship was found; but the influencing factors to the OEC-NTL relationship varied across regions due to the natures of energy use. These factors must be considered especially for the studies of less-affluent regions where NTL was undetectable by the DMSP-OLS sensor.

SNOW DEPTH ESTIMATION USING TIME SERIES PASSIVE MICROWAVE IMAGERY VIA GENETICALLY SUPPORT VECTOR REGRESSION (CASE STUDY URMIA LAKE BASIN)

Abstract. Lake Urmia is one of the most important ecosystems of the country which is on the verge of elimination. Many factors contribute to this crisis among them is the precipitation, paly important roll. Precipitation has many forms one of them is in the form of snow. The snow on Sahand Mountain is one of the main and important sources of the Lake Urmia’s water. Snow Depth (SD) is vital parameters for estimating water balance for future year. In this regards, this study is focused on SD parameter using Special Sensor Microwave/Imager (SSM/I) instruments on board the Defence Meteorological Satellite Program (DMSP) F16. The usual statistical methods for retrieving SD include linear and non-linear ones. These methods used least square procedure to estimate SD model. Recently, kernel base methods widely used for modelling statistical problem. From these methods, the support vector regression (SVR) is achieved the high performance for modelling the statistical problem. Examination of the obtained data shows the existence of outlier in them. For omitting these outliers, wavelet denoising method is applied. After the omission of the outliers it is needed to select the optimum bands and parameters for SVR. To overcome these issues, feature selection methods have shown a direct effect on improving the regression performance. We used genetic algorithm (GA) for selecting suitable features of the SSMI bands in order to estimate SD model. The results for the training and testing data in Sahand mountain is [R²_TEST=0.9049 and RMSE= 6.9654] that show the high SVR performance.

Modes of high‐latitude auroral conductance variability derived from DMSP energetic electron precipitation observations: Empirical orthogonal function analysis

AbstractWe provide the first ever characterization of the primary modes of ionospheric Hall and Pedersen conductance variability as empirical orthogonal functions (EOFs). These are derived from six satellite years of Defense Meteorological Satellite Program (DMSP) particle data acquired during the rise of solar cycles 22 and 24. The 60 million DMSP spectra were each processed through the Global Airlglow Model. Ours is the first large‐scale analysis of ionospheric conductances completely free of assumption of the incident electron energy spectra. We show that the mean patterns and first four EOFs capture ∼50.1 and 52.9% of the total Pedersen and Hall conductance variabilities, respectively. The mean patterns and first EOFs are consistent with typical diffuse auroral oval structures and quiet time strengthening/weakening of the mean pattern. The second and third EOFs show major disturbance features of magnetosphere‐ionosphere (MI) interactions: geomagnetically induced auroral zone expansion in EOF2 and the auroral substorm current wedge in EOF3. The fourth EOFs suggest diminished conductance associated with ionospheric substorm recovery mode. We identify the most important modes of ionospheric conductance variability. Our results will allow improved modeling of the background error covariance needed for ionospheric assimilative procedures and improved understanding of MI coupling processes.

Combining DMSP/OLS Nighttime Light with Echo State Network for Prediction of Daily PM2.5 Average Concentrations in Shanghai, China

The objective of this study is to investigate the potential of nighttime light data, acquired with Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) owned by National Oceanic and Atmospheric Administration (NOAA), in predicting urban daily particulate matter (PM)2.5 with an aerodynamic diameter of less than 2.5 µm average concentrations. To achieve the purpose, we firstly extracted two night light indices, the Nighttime Light Intensity Index (NLII) and the Nighttime Saturated Light Area Index (NSLAI) from DMSP/OLS images. Through Gaussian fitting of the relationship between the indices and the daily PM2.5 concentrations data released by the government, we found that the intraday nighttime light indices were all more relevant with the PM2.5 average concentrations of the next day in Shanghai. Therefore, the 56 sets of data, the light indices were collected from 3 November 2013 to 28 December 2013, the daily PM2.5 concentrations data were collected from 4 November 2013 to 29 December 2013, and these were divided into two parts. The first 40 sets were used for training the model of echo state network (ESN). The last 16 sets were used for testing. The value of R2 of predicted results was as high as 0.6318. In summary, the effectiveness of nighttime light data that used for the prediction of urban daily PM2.5 average concentrations was verified in this study.

Problems with mapping the auroral oval and magnetospheric substorms.

Accurate mapping of the auroral oval into the equatorial plane is critical for the analysis of aurora and substorm dynamics. Comparison of ion pressure values measured at low altitudes by Defense Meteorological Satellite Program (DMSP) satellites during their crossings of the auroral oval, with plasma pressure values obtained at the equatorial plane from Time History of Events and Macroscale Interactions during Substorms (THEMIS) satellite measurements, indicates that the main part of the auroral oval maps into the equatorial plane at distances between 6 and 12 Earth radii. On the nightside, this region is generally considered to be a part of the plasma sheet. However, our studies suggest that this region could form part of the plasma ring surrounding the Earth. We discuss the possibility of using the results found here to explain the ring-like shape of the auroral oval, the location of the injection boundary inside the magnetosphere near the geostationary orbit, presence of quiet auroral arcs in the auroral oval despite the constantly high level of turbulence observed in the plasma sheet, and some features of the onset of substorm expansion.

Early morning irregularities detected with spaceborne GPS measurements in the topside ionosphere: A multisatellite case study

AbstractWe present observations of the equatorial plasma bubbles (EPB) in the topside ionosphere at early morning hours (05–08 LT) in the recovery phase of the 18–19 February 2014 geomagnetic storm. This rare type of irregularities was detected in the Pacific sector using GPS measurements on board several low‐Earth‐orbit (LEO) satellites. We use a multisatellite constellation consisted of the three Swarm and one TerraSAR‐X satellites, that on 19 February flew in the same region and at similar altitudes ~500 km. The EPB occurrence in the LEO GPS data was observed for several consecutive orbits from ~11 UT to 16–17 UT on 19 February 2014, which suggests the following: (1) rather long duration (hours) of favorable conditions for EPB generation, (2) formation and evolution of EPB over wide longitude range of the Pacific Ocean, and (3) possible movement of the EPB region in the westward direction (with dawn). Registration of the early morning EPB in LEO GPS data was supported by concurrent in situ (Swarm and DMSP (Defense Meteorological Satellite Program)) and ground‐based (ionosonde and GPS) measurements. LEO‐based GPS technique is found to be essential and promising data source to study the topside EPB over regions with lack of the ground‐based facilities. In addition, we use the Prompt Penetration Model and the Thermosphere‐Ionosphere Electrodynamics Global Circulation Model (TIE‐GCM) to identify the possible mechanisms responsible for the observed phenomenon. The model simulation results indicate the occurrence of the zone with the enhanced vertical plasma drift (~40–45 m/s) owing to the disturbance dynamo action in the predawn/dawn sector during 09–17 UT.

Correlation between Poynting flux and soft electron precipitation in the dayside polar cap boundary regions.

Observations have revealed large Poynting flux and soft electron precipitation around the cusp region, which have strong impacts on the polar ionosphere/thermosphere. Simulations also confirmed that Poynting flux and soft electron precipitation significantly change the neutral density and dynamics around the dayside polar cap boundary regions. However, no detailed study has been conducted to show if they should coincide with each other or not. Our analysis of Defense Meteorological Satellite Program (DMSP) satellite data reveals a complex correlation between them. Poynting flux and soft particle precipitation are coincident in some cases (match cases), but a clear displacement between them can also be identified in others (nonmatch cases). In the 29 cusp crossings from F13 we investigated, the ratio between nonmatch and match cases is close to 1:4. In nonmatch cases, the displacement between the Poynting flux enhancement and soft particle precipitation enhancement can be as large as 1° in geomagnetic latitude.

A novel data assimilation technique for the plasmasphere

AbstractWe present a novel technique for imaging and data assimilation of the topside ionosphere and plasmasphere. The methodology is based upon the three‐dimensional variational technique (3DVAR), where an empirical background model is utilized. However, to prevent nonphysical vertical variation in density estimates, we devise statistical methods to enforce a roughness penalty in the traditional 3DVAR optimization. The upward looking total electron content (TEC) observations from the Global Positioning System (GPS) receiver on board Constellation Observing System for Meteorology, Ionosphere and Climate satellites are utilized in the assimilation algorithm. The estimation results show reasonable agreement with in situ density measurements of Defense Meteorological Satellite Program satellites and Van Allen Probes derived densities during geomagnetically quiet and severe storm time conditions, respectively. These preliminary results demonstrate great potential for the use of GPS TEC measurements from low‐Earth orbit satellites in monitoring and studying the morphology and dynamics of large‐scale structures of the electron density in the topside ionosphere and plasmasphere.

Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data

Data from the U.S. Defense Meteorological Satellite Program’s Operational Line-scan System are often used to map impervious surface area (ISA) distribution at regional and global scales, but its coarse spatial resolution and data saturation produce high inaccuracy in ISA estimation. Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite’s Day/Night Band (VIIRS-DNB) with its high spatial resolution and dynamic data range may provide new insights but has not been fully examined in mapping ISA distribution. In this paper, a new variable—Large-scale Impervious Surface Index (LISI)—is proposed to integrate VIIRS-DNB and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data for mapping ISA distribution. A regression model was established, in which LISI was used as an independent variable and the reference ISA from Landsat images was a dependent variable. The results indicated a better estimation performance using LISI than using a single VIIRS-DNB or MODIS NDVI variable. The LISI-based approach provides accurate spatial patterns from high values in core urban areas to low values in rural areas, with an overall root mean squared error of 0.11. The LISI-based approach is recommended for fractional ISA estimation in a large area.

The problem of the acceleration of electrons of the outer radiation belt and magnetospheric substorms

Predicting of the location of the maximum in high-energy electron fluxes filling a new radiation belt is an endeavor being carried out by physicists studying the magnetosphere. We analyzed the data from the Defense Meteorological Satellite Program (DMSP) satellites and ground-based magnetometers obtained during geomagnetic storm on 8–9 October 2012. The minimum value of the disturbance storm time (Dst) was −111 nT, and the maximum in high-energy electron fluxes that appeared during the recovery phase was observed at L = 4 Re. At the same time, we analyzed the motion of the auroral oval toward lower latitudes and related substorm activity using the data of the low-orbiting DMSP satellites and the IMAGE magnetic meridian network. It was found from the DMSP satellites’ measurements that the maximum of the energy density of precipitating ions, the maximum of the plasma pressure, and the most equatorial part of the westward auroral electrojet are all located at the 60° geomagnetic latitude. This value corresponds to L = 4 Re, i.e., it coincides with the location of the maximum in high-energy electron fluxes. This L-value also agrees with the predictions of the Tverskaya relation between the minimum in Dst variation and the location of the maximum of the energetic electron fluxes, filling a new radiation belt. The obtained results show that the location of this maximum could be predicted solely from the data of the auroral particle precipitations and/or ground-based magnetic observations.

Low‐altitude satellite measurements of pulsating auroral electrons

AbstractWe present observations from the Defense Meteorological Satellite Program and Reimei satellites, where common‐volume high‐resolution ground‐based auroral imaging data are available. These satellite overpasses of ground‐based all‐sky imagers reveal the specific features of the electron populations responsible for different types of pulsating aurora modulations. The energies causing the pulsating aurora mostly range from 3 keV to 20 keV but can at times extend up to 30 keV. The secondary, low‐energy electrons (&lt;1 keV) are diminished from the precipitating distribution when there are strong temporal variations in auroral intensity. There are often persistent spatial structures present inside regions of pulsating aurora, and in these regions there are secondary electrons in the precipitating populations. The reduction of secondary electrons is consistent with the strongly temporally varying pulsating aurora being associated with field‐aligned currents and hence parallel potential drops of up to 1 kV.

Improving Arctic sea ice edge forecasts by assimilating high horizontal resolution sea ice concentration data into the US Navy's ice forecast systems

Abstract. This study presents the improvement in ice edge error within the US Navy's operational sea ice forecast systems gained by assimilating high horizontal resolution satellite-derived ice concentration products. Since the late 1980's, the ice forecast systems have assimilated near real-time sea ice concentration derived from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI and then SSMIS). The resolution of the satellite-derived product was approximately the same as the previous operational ice forecast system (25 km). As the sea ice forecast model resolution increased over time, the need for higher horizontal resolution observational data grew. In 2013, a new Navy sea ice forecast system (Arctic Cap Nowcast/Forecast System – ACNFS) went into operations with a horizontal resolution of ~ 3.5 km at the North Pole. A method of blending ice concentration observations from the Advanced Microwave Scanning Radiometer (AMSR2) along with a sea ice mask produced by the National Ice Center (NIC) has been developed, resulting in an ice concentration product with very high spatial resolution. In this study, ACNFS was initialized with this newly developed high resolution blended ice concentration product. The daily ice edge locations from model hindcast simulations were compared against independent observed ice edge locations. ACNFS initialized using the high resolution blended ice concentration data product decreased predicted ice edge location error compared to the operational system that only assimilated SSMIS data. A second evaluation assimilating the new blended sea ice concentration product into the pre-operational Navy Global Ocean Forecast System 3.1 also showed a substantial improvement in ice edge location over a system using the SSMIS sea ice concentration product alone. This paper describes the technique used to create the blended sea ice concentration product and the significant improvements in ice edge forecasting in both of the Navy's sea ice forecasting systems.

An improved method of night-time light saturation reduction based on EVI

Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) night-time light (NTL) data have been widely applied to studies on anthropogenic activities and their interactions with the environment. Due to limitations of the OLS sensor, DMSP NTL data suffer from a saturation problem in central urban areas, which further affects studies based on nocturnal lights. Recently, the vegetation-adjusted NTL urban index (VANUI) has been developed based on the inverse correlation of vegetation and urban surfaces. Despite its simple implementation and ability to effectively increase variations in NTL data, VANUI does not perform well in certain rapidly growing cities. In this study, we propose a new index, denoted enhanced vegetation index (EVI)-adjusted NTL index (EANTLI), that was developed by reforming the VANUI algorithm and utilizing the EVI. Comparisons with radiance-calibrated NTL (RCNTL) and the new Visible Infrared Imager Radiometer Suite (VIIRS) data for 15 cities worldwide show that EANTLI reduces saturation in urban cores and mitigates the blooming effect in suburban areas. EANTLI’s similarity to RCNTL and VIIRS is consistently higher than VANUI’s similarity to RCNTL and VIIRS in both spatial distribution and latitudinal transects. EANTLI also yields better results in the estimation of electric power consumption of 166 Chinese prefecture-level cities. In conclusion, EANTLI can effectively reduce NTL saturation in urban centres, thus presenting great potential for wide-range applications.

Mapping US Urban Extents from MODIS Data Using One-Class Classification Method

Urban areas are one of the most important components of human society. Their extents have been continuously growing during the last few decades. Accurate and timely measurements of the extents of urban areas can help in analyzing population densities and urban sprawls and in studying environmental issues related to urbanization. Urban extents detected from remotely sensed data are usually a by-product of land use classification results, and their interpretation requires a full understanding of land cover types. In this study, for the first time, we mapped urban extents in the continental United States using a novel one-class classification method, i.e., positive and unlabeled learning (PUL), with multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) night stable light data were used to calibrate the urban extents obtained from the one-class classification scheme. Our results demonstrated the effectiveness of the use of the PUL algorithm in mapping large-scale urban areas from coarse remote-sensing images, for the first time. The total accuracy of mapped urban areas was 92.9% and the kappa coefficient was 0.85. The use of DMSP-OLS night stable light data can significantly reduce false detection rates from bare land and cropland far from cities. Compared with traditional supervised classification methods, the one-class classification scheme can greatly reduce the effort involved in collecting training datasets, without losing predictive accuracy.

A dynamic model for population mapping: a methodology integrating a Monte Carlo simulation with vegetation-adjusted night-time light images

Population is attracting increasing attention as a driver of resource overexploitation, environmental degradation, loss of biodiversity, and other environmental challenges. Timely and accurately updating maps of population distribution are thus urgently needed. Images of night-time lights from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) have been used for years in population mapping as an alternative to human settlement distribution. The capacity of night-time light images for gridding populations, however, is compromised by the dual effects of saturation and overglow. Static models of the human settlement index (HSI), elevation-adjusted human settlement index (EAHSI), and vegetation-adjusted night-time light urban index (VANUI) have been developed to counteract these negative effects by using constant coefficients. The static models, however, retain disadvantages due to the negative effects of the high variation of socio-economic backgrounds in different study areas. In this study, we integrate Monte Carlo simulation with the above three static indices and propose the dynamic model VANUI Supported by Monte Carlo Simulation (VANUIMCS) for mapping the population of Liaoning Province, China. We assess the accuracy of the simulation using data for 60 counties and 1251 townships. The VANUIMCS improve the accuracy of population mapping, with the mean percentage errors of 19.43% at the county level and 43.19% at the township level.