All-sky Imager Research Articles

Improved GALEX UV Photometry for 700,000 SDSS Galaxies

The Galaxy Evolution Explorer (GALEX) satellite performed the first and only large-area UV survey, which in tandem with the Sloan Digital Sky Survey (SDSS) has facilitated modeling of the spectral energy distributions of low-redshift galaxies and the determination of various galaxy properties, in particular the star formation rate. However, the relatively crude angular resolution of GALEX (5″) made its images susceptible to blending of sources, resulting in potentially biased far-UV and near-UV (NUV) pipeline photometry. To remedy this issue and take advantage of model-fit photometry, we use the EMphot software to obtain forced GALEX photometry for ∼700,000 SDSS galaxies at z < 0.3. Positional priors of target galaxies and potentially contaminating neighbors were taken from SDSS. New photometry is based on the best-fitting of three model profiles: optical-like, exponential, and flat. New photometry mitigates blending present in the original pipeline catalogs, which affected 16% of galaxies at a level of >0.2 mag and 2% at a level of >1 mag. Pipeline NUV magnitudes are severely affected (≳1 mag) when the neighbor is brighter than the target galaxy and within 10″, or when the neighbor is fainter and within ∼3″ of the target. New photometry fixes edge-of-detector bias, which affected pipeline photometry by up to 0.1 mag in NUV. We present catalogs with new photometry for GALEX observations of different depths, corresponding to the all-sky imaging survey (AIS), medium imaging survey, and deep imaging survey. Catalogs feature combined magnitudes for multiple detections of the same galaxy in a survey.

Ultra-short-term forecasting of global horizontal irradiance (GHI) integrating all-sky images and historical sequences

Accurate minute solar forecasts play an increasingly crucial role in achieving optimal intra-day power grid dispatch. However, continuous changes in cloud distribution and coverage pose a challenge to solar forecasting. This study presents a convolutional neural network-long short-term memory (CNN-LSTM) model to predict the future 10-min global horizontal irradiance (GHI) integrating all-sky image (ASI) and GHI sequences as input. The CNN is used to extract the sky features from ASI and a fully connected layer is used to extract historical GHI information. The resulting temporary information outputs are then merged and forwarded to the LSTM for forecasting the GHI values for the next 10 min. Compared to CNN solar radiation forecasting models, incorporating GHI into the forecasting process leads to an improvement of 18% in the accuracy of forecasting GHI values for the next 10 min. This improvement can be attributed to the inclusion of historical GHI sequences and regression via LSTM. The historical GHI contains valuable meteorological information such as aerosol optical thickness. In addition, the sensitivity analysis shows that the 1-lagged input length of the GHI and ASI sequence yields the most accurate forecasts. The advantages of CNN-LSTM facilitate power system stability and economic operation. Codes of the CNN-LSTM model in the public domain are available online on the GitHub repository https://github.com/zoey0919/CNN-LSTM-for-GHI-forecasting.

Design and Development of an Ultraviolet All-Sky Imaging System.

All-sky cameras capture a panoramic view of the full sky from horizon to horizon to generate a wide-angle image of the observable sky. State-of-the-art all-sky imagers are limited to imaging in the visible and infrared spectrum and cannot image in the UV spectrum. This article describes the development of an all-sky imaging system capable of capturing 130° wide-angle sky images from horizon to horizon in the UV-AB spectrum. The design of the UV all-sky imaging system is based on low-cost, accessible, and scalable components to develop multiple images that can be deployed over a wider geographical area. The spectral response of the camera system has been validated in the UV spectrum (280-420 nm) using a monochromatic UV beam with an average power output of 22 nW. UV all-sky imaging systems complement existing infrared and visible all-sky cameras. They have wide applications in astronomy, meteorology, atmospheric science, vulcanology, meteors and auroral monitoring, and the defence sector.

Aerosol Optical Properties and Type Retrieval via Machine Learning and an All-Sky Imager

This study investigates the applicability of using the sky information from an all-sky imager (ASI) to retrieve aerosol optical properties and type. Sky information from the ASI, in terms of Red-Green-Blue (RGB) channels and sun saturation area, are imported into a supervised machine learning algorithm for estimating five different aerosol optical properties related to aerosol burden (aerosol optical depth, AOD at 440, 500 and 675 nm) and size (Ångström Exponent at 440–675 nm, and Fine Mode Fraction at 500 nm). The retrieved aerosol optical properties are compared against reference measurements from the AERONET station, showing adequate agreement (R: 0.89–0.95). The AOD errors increased for higher AOD values, whereas for AE and FMF, the biases increased for coarse particles. Regarding aerosol type classification, the retrieved properties can capture 77.5% of the total aerosol type cases, with excellent results for dust identification (&gt;95% of the cases). The results of this work promote ASI as a valuable tool for aerosol optical properties and type retrieval.

Nightside High‐Latitude Phase and Amplitude Scintillation During a Substorm Using 1‐Second Scintillation Indices

AbstractWe examined evolution of Global Positioning System (GPS) scintillation during a substorm in the nightside high latitude ionosphere, using 1‐s phase and amplitude scintillation indices from the Canadian High Arctic Ionospheric Network (CHAIN) network. The traditional 1‐min scintillation indices showed that the phase scintillation was dominant, while the amplitude scintillation was weak. However, the 1‐s amplitude scintillation occurred more often in association with major auroral structures (polar cap arc, growth phase arc, onset arc, poleward expanding arc, poleward boundary intensification, and diffuse aurora) that were detected by the THEMIS all‐sky imagers (ASIs). The 1‐min index missed much of the amplitude fluctuations because they only lasted ∼10 s near a local peak or at the gradients of the auroral structures. The 1‐s phase scintillation was concurrent with the amplitude scintillation but was much weaker than the 1‐min phase scintillation. The frequency spectral analysis showed that the spectral power above ∼1 Hz was diffractive and below ∼1 Hz was refractive. We suggest that the amplitude scintillation in the high‐latitude ionosphere is much more common than previously considered, and that a short time window of the order of 1 s should be used to detect the scintillation. The 1‐min phase scintillation index is largely influenced by refractive effects due to total electron content (TEC) variations, and the spectral power below ∼1 Hz should be removed to identify diffractive scintillation.

A Ground‐Based Instrument Suite for Integrated High‐Time Resolution Measurements of Pulsating Aurora With Arase

AbstractA specialized ground‐based system has been developed for simultaneous observations of pulsating aurora (PsA) and related magnetospheric phenomena with the Arase satellite. The instrument suite is composed of (a) six 100 Hz sampling high‐speed all‐sky imagers (ASIs), (b) two 10 Hz sampling monochromatic ASIs observing 427.8 and 844.6 nm auroral emissions, (c) a 20 Hz sampling fluxgate magnetometer. The 100 Hz ASIs were deployed in four stations in Scandinavia and two stations in Alaska, which have been used for capturing the main pulsations and quasi 3 Hz internal modulations of PsA at the same time. The 10 Hz sampling monochromatic ASIs have been operative in Tromsø, Norway with the 20 Hz sampling magnetometer. Combination of these multiple instruments with the European Incoherent SCATter (EISCAT) radar enables us to detect the low‐altitude ionization due to energetic electron precipitation during PsA and further to reveal the ionospheric electrodynamics behind PsA. Since the launch of the Arase satellite, the data from these instruments have been examined in comparison with the wave and particle data from the satellite in the magnetosphere. In the future, the system can be utilized not only for studies of PsA but also for other classes of aurora in close collaboration with the planned EISCAT_3D project.

Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data

Abstract. This work introduces a model for all-sky-image-based cloud and direct irradiance nowcasting (MACIN), which predicts direct normal irradiance (DNI) for solar energy applications based on hemispheric sky images from two all-sky imagers (ASIs). With a synthetic setup based on simulated cloud scenes, the model and its components are validated in depth. We train a convolutional neural network on real ASI images to identify clouds. Cloud masks are generated for the synthetic ASI images with this network. Cloud height and motion are derived using sparse matching. In contrast to other studies, all derived cloud information, from both ASIs and multiple time steps, is combined into an optimal model state using techniques from data assimilation. This state is advected to predict future cloud positions and compute DNI for lead times of up to 20 min. For the cloud masks derived from the ASI images, we found a pixel accuracy of 94.66 % compared to the references available in the synthetic setup. The relative error of derived cloud-base heights is 4 % and cloud motion error is in the range of ±0.1ms-1. For the DNI nowcasts, we found an improvement over persistence for lead times larger than 1 min. Using the synthetic setup, we computed a DNI reference for a point and also an area of 500 m×500 m. Errors for area nowcasts as required, e.g., for photovoltaic plants, are smaller compared with errors for point nowcasts. Overall, the novel ASI nowcasting model and its components proved to work within the synthetic setup.

Spectral and RGB analysis of the light climate andits ecological impacts using an all-sky camerasystem in the Arctic.

The ArcLight observatory provides an hourly continuous time series of all-sky images providing light climate data (intensity, spectral composition, and photoperiod) from the Arctic (Svalbard at 79°N). Until recently, no complete annual time series of light climate relevant for biological processes has been provided from the high Arctic because of insufficient sensitivity of commercial light sensors during the Polar Night. The ArcLight set up is unique, as it provides both all-sky images and the corresponding integrated spectral irradiance in the visible part of the solar electromagnetic spectrum (E P A R ). Here we present a further development providing hourly diel-annual dynamics from 2020 of the irradiance partitioned into the red, green, and blue parts of the solar spectrum and illustrate their relation to weather conditions, and sun and moon trajectories. We show that there is variation between the RGB proportions of irradiance throughout the year, with the blue part of the spectrum showing the greatest variation, which is dependent on weather conditions (i.e.,cloud cover). We further provide an example of the biological impact of these spectral variations in the light climate using in vivo Chl a-specific absorption coefficients of diatoms (mean of six low light acclimated northern-Arctic bloom-forming species) to model total algal light absorption (AQ t o t a l ) and the corresponding fraction of quanta used by Photosystem II (AQPSII) (O 2 production) in RGB bands and the potential impacts on the photoreceptor response, suggesting periods where repair and maintenance functions dominate activity in the absence of appreciable levels of red or green light. The method used here can be applied to light climate data and spectral response data worldwide to give localized ecological models of AQ.

Design of all-sky airglow imaging spectrometers in the middle and upper atmosphere

In order to detect the distribution of gravity waves in the middle and upper atmosphere, an all-sky airglow imaging spectrometer is designed to measure the airglow. It has the detection advantages of ultrawide field of view (FOV), large relative aperture and high signal-to-noise ratio (SNR). It can obtain the spectral images of OH (715–850 nm / 880–930 nm) and OI (630 nm) in the height range of 87–250 km. The whole design method of telecentric objective splicing relay zoom group is used to effectively suppress the spectral drift less than 0.2 nm, which meets the requirements of narrow bandwidth filters. The field experiments in northwest China show that the all-sky airglow imaging spectrometer can continuously acquire airglow spectral images with high SNR in both OH channel and OI channel without focusing in the temperature range of 0–45 ℃, and the images obtained in OH channel have obvious gravity wave phenomenon after star point removal and geometric correction.

Intra-hour PV power forecasting based on sky imagery

This paper introduces an upgraded version of the PV2-state model [Paulescu et al. Renew Energy 195 (2022) 322] for intra-hour photovoltaic (PV) power forecasting. The model incorporates real-time adjustments to the estimated clear-sky PV power or the transmittance of clouds, considering the Sun coverage by clouds. A physics-based approach for processing cloud field information from an all-sky imager is proposed to intra-hour forecast SSN, a binary quantifier stating whether the Sun is shining (SSN = 1) or not (SSN = 0). The model performance with the new procedure is investigated from three perspectives: forecast accuracy, forecast precision and the response to the variability in the state-of-the-sky. The study was conducted with high-quality 1-min data collected from a micro-PV plant, on a sample of days with scattered clouds. PV2-state demonstrates notable performance particularly under challenging conditions, where models typically struggle to perform well. In terms of skill score, the overall model performance ranges between 10 and 20%, and under very high variability conditions even exceeding four times the purely statistical forecast. For the operationally relevant 15-min horizon, PV2-state exhibits a noteworthy precision, with two-thirds of forecasts falling within a 10% tolerance interval. Even under severe conditions roughly one third falls in this 10% interval.

Imaging the Milky Way with Millihertz Gravitational Waves

Modern astronomers enjoy access to all-sky images across a wide range of the electromagnetic spectrum from long-wavelength radio to high-energy gamma rays. The most prominent feature in many of these images is our own Galaxy, with different features revealed in each wave band. Gravitational waves (GWs) have recently been added to the astronomers’ toolkit as a nonelectromagnetic messenger. To date, all identified GW sources have been extra-Galactic and transient. However, the Milky Way hosts a population of ultracompact binaries (UCBs), which radiate persistent GWs in the milliHertz band that is not observable with today’s terrestrial gravitational-wave detectors. Space-based detectors such as the Laser Interferometer Space Antenna will measure this population and provide a census of their location, masses, and orbital properties. In this work, we will show how this data can be used to form a false-color image of the Galaxy that represents the intensity and frequency of the gravitational waves produced by the UCB population. Such images can be used to study the morphology of the Galaxy, identify interesting multimessenger sources through cross-matching, and for educational and outreach purposes.

Intra-hour photovoltaic forecasting through a time-varying Markov switching model

This work presents a Markov switching model with a time-varying transition matrix to forecast intra-hour photovoltaic (PV) power output, aiming at providing forecasting flexibility. First, the proposed methodology captures images of the sky employing a self-made, low-cost all-sky imager. Second, the goal is to limit exposure problems in those images via the exposure fusion technique. Third, the proposed algorithm identifies groups of pixels forming clouds through a super paramagnetic clustering algorithm. Finally, we model the problem with a homogeneous Poisson process and forecast the cloud location and the shadowed area on a PV plant for the coming minutes. The shadowed area together with meteorological data are the inputs to this model. In the case study, our approach shows better performance than the persistence method, in particular for changing cloud conditions.

A case study on multiple self-interactions of MSTID bands: New insights

In this study, we report a special event of nighttime southwestward propagating medium scale traveling ionospheric disturbances (MSTIDs) observed in O(1D) 630.0 nm airglow images from an all-sky imager at Hanle (32.7°N, 78.9°E; Mlat. ∼ 24.1°N), Leh Ladakh, India on a geomagnetically quiet (Ap = 7) night of 15 September 2018. The time sequence of airglow images unveiled two dynamic interactions between multiple dark bands of MSTID. Following the first interaction, one of the interacting bands decayed possibly due to the entrance of plasma from the ambient higher plasma density region. Shortly after this interaction, the other interacting dark band was involved in the second interaction with a third dark band which resulted in the co-alignment of the two interacting bands. Following this co-alignment, one of the bands started rotating prominently that led to further separation of these two co-aligned bands. These changes in the MSTID phase fronts (bands) are explained based on the development of the polarization electric fields arising out of the interactions. This investigation combines the all-sky 630.0 nm airglow imaging observations with TEC maps constructed, for the first time over the Indian sector, from 67 Global Navigation Satellite System (GNSS) measurements to capture the MSTID over this region. The investigation reveals a few important features of self-interactions of MSTID bands over the geomagnetic low-mid latitude transition region which is important to assess their impact over low latitudes.

Equatorward Moving Auroral Arcs Associated with Impulse-Excited Field Line Resonance

The theory of equatorward moving east-west elongated auroral arcs associated with field line resonance (FLR) has been proposed for decades. However, confirming this theory requires in-situ observations of FLR within the magnetosphere and simultaneous all-sky imager observations of equatorward moving auroral arcs near satellite footpoints. In this study, we present the first observations of multiple equatorward moving auroral arcs related to impulse-excited FLR, using datasets from the WIND, Geotail satellites, and an all-sky imager at China’s Zhongshan Station (ZHS) in Antarctica. In the presented event, the ultra-low-frequency waves associated with solar wind dynamic pressure pulse was mainly toroidal mode, which is consistent with the theory that the toroidal mode waves usually related with external source. The all-sky imager located in Zhongshan station recorded several equatorward moving auroral arcs, followed by reverse propagating ones. The latitudinal width of the equatorward moving auroral arcs was on the order of 25 km and had an average equatorward propagation of ~0.37 km/s, which is very similar to the value from previous work. To better illustrate the observed evolution of auroral arcs related with the FLRs we proposed a simple model to evaluate the FACs induced by the FLRs in different latitudes. The latitudinal distribution evolution of FACs agrees well with the ground-based optical observations.

Poleward-Moving Black Aurora Associated with Impulse-Excited Field-Line Resonances in the Dawnside Sector: THEMIS and Ground Observations

The black aurora is a distinct phenomenon characterized by spatially well-defined regions where the diffuse auroral luminosity decreases notably. Typically, black auroras present as arcs moving at lower velocities, patches with higher moving speeds, and arc segments. However, the mechanism behind black auroras remains unclear. In this paper, we present a novel observation of a poleward-moving black auroral arc associated with impulse-excited field-line resonances in the dawnside sector from the multi-spacecraft THEMIS (Time History of Events and Macroscale Interactions during Substorms) mission, equivalent ionospheric currents, and a conjugated all-sky imager. The field-line resonance velocities exhibit periodic vorticity, which correspond to periodic poleward-moving bands of enhanced FACs. Based on the relatively large reduction in luminosity, we conclude that the poleward-moving black auroral arc was most likely caused by downward FACs associated with field-line resonances.

Aurora Classification in All-Sky Images via CNN–Transformer

An aurora is a unique geophysical phenomenon with polar characteristics that can be directly observed with the naked eye. It is the most concentrated manifestation of solar–terrestrial physical processes (especially magnetospheric–ionospheric interactions) in polar regions and is also the best window for studying solar storms. Due to the rich morphological information in aurora images, people are paying more and more attention to studying aurora phenomena from the perspective of images. Recently, some machine learning and deep learning methods have been applied to this field and have achieved preliminary results. However, due to the limitations of these learning models, they still need to meet the requirements for the classification and prediction of auroral images regarding recognition accuracy. In order to solve this problem, this study introduces a convolutional neural network transformer solution based on vision transformers. Comparative experiments show that the proposed method can effectively improve the accuracy of aurora image classification, and its performance has exceeded that of state-of-the-art deep learning methods. The experimental results show that the algorithm presented in this study is an effective instrument for classifying auroral images and can provide practical assistance for related research.

Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques

Accurate solar radiation nowcasting models are critical for the integration of the increasing solar energy in power systems. This work explored the benefits obtained by the blending of four all-sky-imagers (ASI)-based models, two satellite-images-based models and a data-driven model. Two blending approaches (general and horizon) and two blending models (linear and random forest (RF)) were evaluated. The relative contribution of the different forecasting models in the blended-models-derived benefits was also explored. The study was conducted in Southern Spain; blending models provide one-minute resolution 90 min-ahead GHI and DNI forecasts. The results show that the general approach and the RF blending model present higher performance and provide enhanced forecasts. The improvement in rRMSE values obtained by model blending was up to 30% for GHI (40% for DNI), depending on the forecasting horizon. The greatest improvement was found at lead times between 15 and 30 min, and was negligible beyond 50 min. The results also show that blending models using only the data-driven model and the two satellite-images-based models (one using high resolution images and the other using low resolution images) perform similarly to blending models that used the ASI-based forecasts. Therefore, it was concluded that suitable model blending might prevent the use of expensive (and highly demanding, in terms of maintenance) ASI-based systems for point nowcasting.

Development of a Machine Learning Forecast Model for Global Horizontal Irradiation Adapted to Tibet Based on Visible All-Sky Imaging

The Qinghai-Tibet Plateau is rich in renewable solar energy resources. Under the background of China’s “dual-carbon” strategy, it is of great significance to develop a global horizontal irradiation (GHI) prediction model suitable for Tibet. In the radiation balance budget process of the Earth-atmosphere system, clouds, aerosols, air molecules, water vapor, ozone, CO2 and other components have a direct influence on the solar radiation flux received at the surface. For the descending solar shortwave radiation flux in Tibet, the attenuation effect of clouds is the key variable of the first order. Previous studies have shown that using Artificial intelligence (AI) models to build GHI prediction models is an advanced and effective research method. However, regional localization optimization of model parameters is required according to radiation characteristics in different regions. This study established a set of AI prediction models suitable for Tibet based on ground-based solar shortwave radiation flux observation and cloud cover observation data of whole sky imaging in the Yangbajing area, with the key parameters sensitively tested and optimized. The results show that using the cloud cover as a model input variable can significantly improve the prediction accuracy, and the RMSE of the prediction accuracy is reduced by more than 20% when the forecast horizon is 1 h compared with a model without the cloud cover input. This conclusion is applicable to a scenario with a forecast horizon of less than 4 h. In addition, when the forecast horizon is 1 h, the RMSE of the random forest and long short-term memory models with a 10-min step decreases by 46.1% and 55.8%, respectively, compared with a 1-h step. These conclusions provide a reference for studying GHI prediction models based on ground-based cloud images and machine learning.

Unusual simultaneous manifestation of three non-interacting mid-latitude ionospheric plasma structures

An unusual event of three characteristically different plasma structures on a geomagnetically quiet night (Ap = 4) of 08 July 2018 has been investigated in this paper using an all-sky imager installed at Hanle, Ladakh (32.7°N, 78.9°E; Mlat. ∼ 24.1°N), India. These structures include a freshly generated electrified medium scale traveling ionospheric disturbances (EMSTID), ambiguous plasma depletions, and a northward propagating non-electrified MSTID. One of the most fascinating aspects of this event was the lack of mutual interaction between the three structures, even though they existed simultaneously and propagated in different directions. They individually underwent evolution, distortion, and dissipation separately. One of the structures was an EMSTID, which got generated within the imager’s field-of-view (FOV) and evolved with time. As time progressed, different strip-like structures travelled southwestward, merged with each other to form the EMSTID. The second structure was plasma depletions which appeared in the southeastern part of the FOV. They eventually merged into a single band, which propagated nearly westward. The merged band evolved with time, extended further northward, and dissipated later. Along with these, a very rare non-electrified MSTID structure with east–west aligned fronts was observed which propagated northward. Its fronts underwent distortion, became curved and dissipated. In this study, we have explored the role of electrodynamics behind the observed unique features of the three plasma structures.

How catching the interstellar wind in the inner solar system led the way on a road to interdisciplinary research between heliophysics and astrophysics

Combined in situ observations of the interstellar wind through the solar system and of its pickup ions (PUIs), implanted after ionization in the solar wind, explain, in comparison with interstellar absorption lines of nearby stars, that the Sun is in an interaction region of the two nearest interstellar clouds. This new finding disrupts the long-held understanding that we are inside the local interstellar cloud (LIC). We discuss how space physics evolved toward such interdisciplinary studies between heliophysics and astrophysics. In 1984, the discovery of interstellar He+ PUIs exposed the very local interstellar medium to in situ diagnostics at 1AU. These PUIs provide the interstellar gas composition and form a stepping stone for the acceleration of ions, especially into anomalous cosmic rays. Using the Sun as a gravitational spectrograph, direct imaging of the neutral interstellar wind, first for He and then for H, O, and Ne, provides the interstellar gas velocity vector and temperature at the heliopause. Combining the interstellar gas flow vectors, those of secondary neutral He and O, and the interstellar magnetic field direction deduced from the interstellar H deflection and termination shock anisotropy seen by the Voyagers provides synergistically the heliosphere’s shape, its interaction with the interstellar medium, and constrains our radiation environment. This ISMF organizes the bright Ribbon seen in all-sky images of energetic neutral atoms with the potential to provide its precision determination. The elemental and isotopic composition from PUI and neutral gas observations constrains the galactic evolution and Big Bang cosmology, opening additional interdisciplinary opportunities.