Multi-year Data Research Articles

Probabilistic Techno-Economic Design of Isolated Microgrid

Isolated microgrid (MG) proved its potential to electrify the remote community through the cheaper and greener renewable energy alternatives with higher reliability than the weak grid. The goal of universal electricity access and the climate change mitigation paves the way for many public/private owned microgrids in remote areas. Having in mind various uncertainties associated with the design parameters of the MG (e.g., temperature, irradiation, load), this paper presents a probabilistic approach for optimal sizing and techno-economic assessment of the PV-based MG. The potential environmental impact of the isolated MG is taken into account by considering both, the PV/Battery, and more conventional PV/Battery/Diesel Generator configuration. The effectiveness of multi-year data over the single year data in the probabilistic approach is demonstrated. The probabilistic techno-economic analysis of different configurations facilitates informed decision making regarding the configuration and size of MG components while meeting the reliability of supply and environmental constraints. The feasibility and affordability of the configurations are demonstrated through the distribution of net present cost, levelized cost of energy and the unmet load percentage.

Tree Ring Width Responses of Pinus densiflora and Robinia pseudoacacia to Climate Variation in the Mount Tai Area of Northern China

To effectively combat climate change and put plans in place to enhance the health and quality of forests, research on the connections between long-term climate change and tree ring width is essential. Here, Pinus densiflora Siebold & Zucc. and Robinia pseudoacacia L. in the Mount Tai area were studied. Specifically, their tree ring width characteristics were investigated according to the principles of dendrochronology, based on the analysis of multiyear climate data (1972–2022). The results showed that (1) the variation in tree ring width of Pinus densiflora Siebold & Zucc. generally decreased. Its basal area increment sequence presented a “growth-decline” change process. The trend for Robinia pseudoacacia L. was stability at first and then a reduction. Its basal area increment sequence presented a “growth-stabilization” change process. (2) The standard chronologies of both tree species contained more environmental information than the residual chronologies, rendering the former more appropriate for analysis. (3) The tree ring width of Pinus densiflora Siebold & Zucc. was positively correlated with the mean maximum temperature in February, March, and July, the mean temperature in May, and the mean precipitation in December of the previous year and June of the current year. The tree ring width of Robinia pseudoacacia L. was positively correlated with the mean and maximum temperatures in October of the previous year, the mean maximum temperature in May of the current year, and the mean temperature in July of the current year. This variable was positively correlated with the mean precipitation in November of the previous year and July of the current year but negatively correlated with the mean minimum temperature in November of the previous year and the mean temperature in December of the current year. (4) During 1987–1988, 1994–1995, 2005–2006, and 2018–2019, the tree ring width was restricted by rising temperatures and low precipitation, with variations in tree ring width observed in various hydrological periods. (5) The moisture index, followed by the warmth index, precipitation and temperature, was the primary climate factor determining the tree ring width in both tree species.

Migratory swans individually adjust their autumn migration and winter range to a warming climate.

In response to climate warming, migratory animals can alter their migration so that different events in the annual cycle are better aligned in space and time with suitable environmental conditions. Although such responses have been studied extensively during spring migration and the breeding season, much less is known about the influence of temperature on movements throughout autumn migration and how those movements result in a winter range and shifts therein. We use multi-year GPS tracking data to quantify how daily autumn movement and annual winter distance from the breeding grounds are related to temperature in the Western Palearctic Bewick's swan, a long-lived migratory waterbird whose winter range has shifted more than 350 km closer to the breeding grounds since 1970 due to individuals increasingly 'short-stopping' their autumn migration. We show that the migratory movement of swans is driven by lower temperatures throughout the autumn season, with individuals during late autumn moving only substantially when temperatures drop below freezing. As a result, there is large flexibility in their annual winter distance as a response to winter temperature. On average, individuals overwinter 118 km closer to the breeding grounds per 1°C increase in mean December-January temperature. Given the observed temperature increase in the Bewick's swan winter range during the last decades, our results imply that the observed range shift is for a substantial part driven by individual responses to a warming climate. We thus present an example of individual flexibility towards climatic conditions driving the range shift of a migratory species. Our study adds to the understanding of the processes that shape autumn migration decisions, winter ranges and shifts therein, which is crucial to be able to predict how climate change may impact these processes in the future.

Multi-year belowground data of minirhizotron facilities in Selhausen

The production of crops secure the human food supply, but climate change is bringing new challenges. Dynamic plant growth and corresponding environmental data are required to uncover phenotypic crop responses to the changing environment. There are many datasets on above-ground organs of crops, but roots and the surrounding soil are rarely the subject of longer term studies. Here, we present what we believe to be the first comprehensive collection of root and soil data, obtained at two minirhizotron facilities located close together that have the same local climate but differ in soil type. Both facilities have 7m-long horizontal tubes at several depths that were used for crosshole ground-penetrating radar and minirhizotron camera systems. Soil sensors provide observations at a high temporal and spatial resolution. The ongoing measurements cover five years of maize and wheat trials, including drought stress treatments and crop mixtures. We make the processed data available for use in investigating the processes within the soil–plant continuum and the root images to develop and compare image analysis methods.

Assessing Northern Gulf of Mexico Sperm Whale’s (Physeter macrocephalus) time budget using passive acoustic monitoring

A time budget empirically measures species-specific behavior regarding the time periods spent engaging in a certain behavior. Sperm whales emit phonations categorized as either foraging or socializing, making it straightforward when creating their time budget based on acoustic observations alone. Understanding regional time budgets can help assessing habitat uses, prey availability, as well as identifying short and long-term trends across the population. Furthermore, sperm whales exhibit both high sexual dimorphism as well as sexually regulated group structures. Individualized multi-pulse echolocation click structure allows total body length as well as sex to be estimated. Apart from a case study conducted by McDonald et al., 2017, a long-term time budgets for sperm whales have not been investigated in the Northern Gulf of Mexico (NGoM). The analysis of multi-year archival acoustic data from the NGoM using a sperm whale click detector as well as CABLE software [Beslin et al., JASA (2018)] is presented to infer sperm whale’s time budget and group structures. [Data acquisition for this research was made possible in part by grants from The Gulf of Mexico Research Initiative and BOEM.]

Whales, wind, and whale watching—Uncovering the secret soundscape of Geographe Bay

Quantifying the acoustic soundscape of an area is an important precursor to understanding the significance of that area from an environmental perspective, as well as providing useful environmental context to inform environmental management. Underwater soundscapes provide important contextual information about the use of that habitat by marine fauna species as well as some of the anthropogenic stressors that may be present. Multi-year acoustic data collected from an underwater acoustic recorder near Cape Naturalist in Geographe Bay was used to characterize the underwater soundscape and complete an initial assessment of cetacean presence. Ambient noise conditions within the Bay were characterized, providing an interim baseline of the ambient noise conditions within the Bay, identifying the biological and anthropogenic contributors to the soundscape. This characterization provided a better understanding of species presence within the Bay and general trends in occurrence, and has also been used to investigate the scale and extent of existing anthropogenic pressures. The information from the monitoring program has been applied to better understand the value of the Geographe Bay area to different species, while at the same time setting a benchmark for ongoing monitoring efforts and providing inputs into detection range modeling to assist in enhancing program design.

Empirical analysis of the prevalence of HVAC faults in commercial buildings

Commercial building HVAC systems experience many sensing, mechanical, and control-related faults that increase energy consumption and impact occupant comfort. Fault detection & diagnostics (FDD) software has been demonstrated to identify and help diagnose these types of faults. Several studies have demonstrated FDD energy savings potential, but there is limited empirical data characterizing the quantity and type of faults reported by FDD tools. This paper presents results of an FDD fault reporting study, employing multi-year monitoring data for over 60,000 pieces of HVAC equipment, covering over 90 fault types, and using new metrics that we developed to characterize fault prevalence. Study results offer an unprecedented accounting of the quantity of faults reported, the most commonly occurring faults, and fault persistence. We find that 21 air handling unit (AHU) faults were reported on 20% or more AHUs in our dataset, and 18 AHU faults persisted for more than 20% of the time period covered by the data. On any given day, 40% of AHUs and 30% of air terminal units saw a reported fault of some kind. Based on in-depth analysis of these results we provide recommendations for building operators, FDD software developers, and researchers to enable more efficient commercial building operation.

Численное моделирование распространения пассивных примесей в Белом море

It is hardly possible to make experiments on transport of potentially dangerous tracers in a sea. Therefore numerical simulation is successfully used to assess the risks and consequences of various events like oil spills, flux of toxicants with river runoff after industrial accidents or phytoplankton in case of harmful algae bloom. As the White Sea is a transport hub and a strategically important location for extraction of natural resources, so it is important to know the most likely scenarios of pollutants behavior. The JASMINE numerical model, based on the FEMAO (Finite-Element Model of the Arctic Ocean) simulates evolution of sea state, including three-dimensional currents, temperature and salinity, and sea ice, and is able to calculate tracer advection, so giving answers to a number of questions related to how pollution evolves in the White Sea. We describe numerical experiments to study advection of floating tracers in the White Sea when the initial distribution is delta-like and located in the mouths of main rivers. Also, we calculate the time of almost complete removal of an initially homogeneous concentration of a passive tracer. Spatial resolution is 3 km, vertical grid is 5 m down to the depth level of 150 m (10 m for depths more than 150 m). The time step is 360 s. NOAA/NCEP atmospheric reanalysis is used for atmospheric forcing. Five main rivers are taken into account with the monthly-mean runoff taken from the multi-year observation data. We have estimated the time needed to remove most of the matter from the sea; it depends on morphometric characteristics of the bays and is the highest for the Onezhskiy bay. Matter exchange between the bays is low, only Dvinskiy-Onezhskiy-Mezenskiy transport is present, as we would expect from the geostrophic current pattern.

Studying insulin needs in Type 1 Diabetes by analysing the OpenAPS Data Commons

Introduction & BackgroundType 1 Diabetes (T1D) is a chronic condition where the body produces too little insulin, a hormone required to regulate blood glucose (BG). Finding the correct insulin dose and time remains a complex and as yet unsolved control task. Many factors such as food, exercise, stress, menstrual cycle, etc. change how much insulin is required. Most of these factors remain unobserved and/or underexplored. The NHS national diabetes audit shows that in 2020-21 only 9.8% of people with T1D had a NICE recommended glycated haemoglobin (HbA1c) test result of 48 mmol/mol or less to avoid complications due to diabetes.
 Objectives & ApproachOur research aims to improve the understanding of underexplored factors that drive changes in insulin needs of people with T1D. We use unsupervised time series pattern detection methods such as time series k-means, heatmaps and matrix profile to identify underexplored patterns. These are times when insulin on board (IOB) does not rise with more carbohydrates on board (COB) and times when BG does not fall with more IOB and/or rise with more COB as expected. In the future, we aim to use causal feature selection methods to exclude COB as a causal driver for these patterns and identify other factors as causal drivers.
 Relevance to Digital FootprintsWe use a digital footprints dataset of n=187 people who use an open-source automated insulin delivery system and have donated their data via the OpenAPS Data Commons and the OpenHumans.org platform. The data has been collected in real-life conditions and contains system logs, BG sensor data and various user-entered annotations. The richness of the data provides a unique opportunity to study what happens in real-life conditions but also poses challenges for many methods. These include inconsistencies between users, irregular sampling between devices and missing data.
 ResultsOur pattern detection methods can successfully identify underexplored patterns in insulin needs that are not directly driven by COB. These include months that require more/less insulin without eating more/less carbohydrates and times of day when blood glucose does not rise with more COB and/or fall with more IOB.
 Conclusions & ImplicationsWhile our current methods can identify underexplored patterns in insulin needs, the principal pattern identified remains the well-known pattern of the main meal COB spikes. This is not surprising given the frequency and impact of this pattern. We are working on methods that can identify both frequent and less frequent patterns as well as patterns arising from the irregularity of the sampling. Digital footprints datasets like the OpenAPS Data Commons are promising to help increase understanding of complex conditions such as T1D. More of this type of multi-year data is needed. Especially data that includes multiple different sensor readings to help identify causal drivers behind underexplored patterns of insulin needs. And we need pattern-finding methods that deal well with missing and irregularly sampled data.

Comparison of the Performance of Solar Panels Designed in Three Different Ways under the Same Conditions

Renewable energy sources such as solar energy have great potential to alleviate some of the negative environmental problems, including climate change, caused by intensive fossil fuel use. Solar energy will play an important part in future energy systems because of its rapid installation technology and lowering costs. In order to use solar radiation intensity in a wide range in the most efficient way, the plants must either be at an optimum angle in the area where they are installed or they should be designed with moving systems. In this study, performance and efficiency comparisons of solar tracking systems and fixed-designed systems based on real-field conditions have been made. In this way, price performance ratios can be determined clearly and it will be easier to decide on the types of power plants to be built. While solar tracking systems move according to the most efficient position that they can get from the sun through radiation sensors, they are designed with elements such as PLCs using multi-year solar data that operate with an open loop and based on meteorological data. In this study, three different power plant types designed as 1-axis, 2-axis, and fixed angle were controlled as open loop with PLC software and production differences between power plants were evaluated for 1 year. According to this research we have done, it has been concluded that 2-axis tracking systems produce approximately 32% more energy annually than a fixed-angle system, with an annual efficiency rate of 23% higher than a 1-axis system.

How do bankruptcy risk estimations change in time? Empirical evidence from listed US companies

The study analyzes how bankruptcy risk estimations of listed US companies changed in the period January 2006 to May 2023. Based on multi-year data series of bankruptcy risk estimations, the study shows the dynamics of bankruptcy risk estimations and, therefore, helps interpret the outcome of bankruptcy prediction models and evaluate the recent financial distress that a notable number of listed US companies exhibits. Furthermore, the study analyzes the pre-bankruptcy patterns of listed US companies that filed for bankruptcy in 2023.

Do Bats Avoid the Urban Core in the Breeding Season? A Case Study from Temperate Latitudes

Seasonal utilization of urban areas by bats remains inadequately explored. This study aimed to comprehensively survey the species composition and population dynamics of bats during both the breeding season (May–July) and autumn migration season (August–September) within a large urban area, specifically Kharkiv city, Ukraine. We conducted multiyear data collection from 2014 to 2016, employing a combination of acoustic recordings, mist-netting, and registration of opportunistically found bats. The results revealed the identification of seven bat species using all methods (Eptesicus serotinus, Nyctalus noctula, N. leisleri, Pipistrellus pygmaeus, P. kuhlii, P. nathusii, and Vespertilio murinus), with notable differences in species composition between the studied periods. During the migration season, N. noctula was a numerically predominant species, while P. kuhlii and E. serotinus were the most abundant during the breeding season. The urban core bat population during the breeding season primarily consisted of males and solitary reproductive females, mainly represented by P. kuhlii and E. serotinus. Acoustic recording data indicated that N. noctula actively avoided the urban core during the breeding season, but was more common on the city periphery. In contrast, during the migration season, the city experienced a significant surge in bat abundance, both in general and specifically among noctule bats, with their numbers increasing tenfold compared to the breeding season. Moreover, a considerable number of young individuals were observed during the migration season. These findings provide evidence that bats tend to avoid the urban core in large cities at temperate latitudes during the breeding season but actively utilize urban areas during autumn migration. Understanding the seasonal preferences and movements of bats in urban environments is crucial for effective conservation and management strategies.

Spatial differentiation of carbon emissions from energy consumption based on machine learning algorithm: A case study during 2015–2020 in Shaanxi, China

Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables. In this study, we propose a machine learning algorithm for carbon emissions, a Bayesian optimized XGboost regression model, using multi-year energy carbon emission data and nighttime lights (NTL) remote sensing data from Shaanxi Province, China. Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models, with an R2 of 0.906 and RMSE of 5.687. We observe an annual increase in carbon emissions, with high-emission counties primarily concentrated in northern and central Shaanxi Province, displaying a shift from discrete, sporadic points to contiguous, extended spatial distribution. Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns, with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering. Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissions more accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment. This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.

A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements

Abstract. We present a global multiyear height-resolved data set of aerosol-type-specific cloud condensation nuclei concentrations (nCCN) estimated from the spaceborne lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. For estimating nCCN, we apply the recently introduced Optical Modelling of the CALIPSO Aerosol Microphysics (OMCAM) algorithm to the CALIPSO Level 2 Aerosol Profile product. The estimated nCCN are then gridded into a uniform latitude–longitude grid of 2∘×5∘, a vertical grid of resolution 60 m from the surface to an altitude of 8 km, and a temporal resolution of 1 month. The data span a total of 186 months, from June 2006 to December 2021. In addition, we provide a 3D aerosol-type-specific climatology of nCCN produced using the complete time series. We further highlight some potential applications of the data set in the context of aerosol–cloud interactions. The complete data set can be accessed at https://doi.org/10.1594/PANGAEA.956215 (Choudhury and Tesche, 2023).

Changes in the Carpathian fauna of Malachiinae beetles (Coleoptera, Melyridae) in the context of temperature increase

Over last century in Europe a tendency of change in species ranges has occurred for insects of different taxonomic groups. We analyzed the changes that have taken place in the distribution of some soft-winged beetles (Malachiinae, Melyridae) species in the Carpathian region. The obtained data are based on a study of museum beetles’ collections and the authors’ collected materials. Data comparison relating to species distribution shows that the Carpathian fauna during the second half of the 20th century increased by 12 species. Some species have significantly changed their ranges. Species of Southern European and Mediterranean (Anthomalachius strangulatus, Clanoptilus spinipennis), Central-East European (Apalochrus femoralis, Clanoptilus falcifer) origin spread to the East Carpathian region. And vice versa, some species (e.g. Malachius scutellaris) from Central European and the Carpathian regions have spread beyond their borders of ranges to the East and North. Malachiinae species are anthophilic insects. Their life cycles, flight period, and distribution depend on the phenology of host plants. Acceleration of phenophases of the host plants and intensification of the metamorphosis processes due to increase in air temperature has caused an earlier appearance of soft-winged beetles in recent years and contributed to expansion of the ranges of some species of them. In our opinion, expansion of the species ranges and penetration of new beetle species into the Carpathian region from surrounding areas are related to the climate changes, in particular to warming. This thesis is confirmed by multiyear air temperature data of the Transcarpathian Centre of Hydrometeorology. On a background of increase in regional air temperature by about 0.8 °C an average air temperature in foothills of Ukrainian Carpathians has increased by 1.7 °C during last 50–60 years.

Identifying the impacts of warming anomalies in the Arctic region and the Tibetan Plateau on PM2.5 pollution and regional transport over China

Arctic region (AR) and Tibetan plateau (TP) are the most sensitive regions to climate change and have synchronously experienced accelerated warming over recent decades. Based on the multi-year observational data of PM2.5 and meteorology, we investigated the modulation of AR and TP's anomalous warming on the variations of PM2.5 pollution and regional transport over central and eastern China (CEC), including major PM2.5 pollution regions in northern China (NC), the Yangtze river delta (YRD), central China (CC), and southern China (SC). Results show that the thermal effects of TP and AR modulated PM2.5 pollution in different ways respectively with prominently influencing the interannual changes of PM2.5 concentrations and heavy PM2.5 pollution occurrences. The impacts of anomalous warming in TP and AR on PM2.5 pollution consistently enhanced regional PM2.5 transport from NC to YRD and SC, while the warming anomalies over AR and TP respectively enhanced and inhibited the southward transport of PM2.5 from NC. In association with the synergistic impact of warming anomalies in AR and TP, the regional PM2.5 transport over CEC presented the inverse patterns of the northward anomalies between NC and CC and the southward anomalies from the eastern part of NC, YRD to SC, forming the regional distribution with negative PM2.5 anomalies in NC and CC and positive PM2.5 anomalies in YRD and SC. Our results highlight the effect of warming anomalies in AR and TP on the PM2.5 pollution over China with the implication of source–receptor relationship of regional transport of air pollutants.

ВЫДЕЛЕНИЕ АМПЕЛОЭКОТОПОВ ДЛЯ ЭФФЕКТИВНОГО ВЫРАЩИВАНИЯ ВИНОГРАДА В СЕВАСТОПОЛЬСКОМ РЕГИОНЕ

The article presents the research results on the degree of favorability of agro-ecological conditions of Sevastopol for grapevine cultivation. The analysis according to the available multi-year data of weather stations of the Crimean peninsula is given. The following climatic indices characterizing vegetation period and grape ripening period were calculated: sum of temperatures above 20°C, ratio of sum of temperatures above 20 °C to sum of temperatures above 10 °C, Huglin and Winkler indices, average temperature of vegetation period, Selyaninov hydrothermal coefficient, sum of precipitation per year and vegetation period. Besides, the main agro-ecological factors limiting the possibility and efficiency of grapevine cultivation were considered: average of absolute minima of air temperature and sum of active temperatures above 10 °С. A digital complex map of the spatial distribution of these indices on the analyzed territory was constructed by means of geoinformation modeling. The distribution of Sevastopol territories that are not suitable for vineyards establishment was analyzed: with unfavorable soil conditions, with a height of more than 600 m above sea level, with a slope of over 20 degrees, as well as lands of forest and reserve funds. As a result of a comprehensive analysis of agro-ecological conditions in the territory of Sevastopol 9 ampeloecotopes were identified. According to the results of the comparison of agro-ecological conditions of the selected ampeloecotopes with the requirements of grapevine varieties to growing conditions, taking into account the dependence of the quality indicators of viticulture and winemaking products on agro-ecological factors, recommendations for agroecological optimization of the varietal composition and terroir specialization of the viticulture and winemaking industry in the territory of the city of federal significance − Sevastopol were developed.

Spatial distribution of atmospheric black carbon in the Eurasian sector of the Arctic Ocean from 28 marine expeditions (2007–2022)

Outflows of absorbing aerosol (black carbon) from continental regions of midlatitudes affect appreciably the climate and ecological state of the Arctic Ocean. We present a statistical generalization of the absorbing substance concentrations was measured in the equivalent of black carbon (eBC) in the atmosphere of the Eurasian sector of the Arctic Ocean (from the Greenland to Chukchi Seas), which is based on the largest amount of in-situ measurements in 28 marine expeditions. Our research results show a common regularity for all investigated regions of the Arctic Ocean with eBC decreasing with latitude rising (increasing distance from continent). The average decreasing gradient of the eBC concentrations per 1° latitude is 3.2 ng/m3 over the Barents Sea and 1.3 ng/m3 over the Kara Sea. The atmosphere of the Barents Sea stands out in the largest black carbon content: the average and modal eBC values are 56 and 15 ng/m3 respectively. Relative to the maximum over the Barents Sea, the eBC concentrations decrease to 20 ng/m3, in both the western (the Greenland Sea) and eastern directions (the East Siberian and Chukchi Seas). More than a factor of two decrease in the eBC concentrations from the Barents sea to Far East seas indicates that the total contribution of outflows of absorbing aerosol from Asian part is smaller than from the north of Europe. Episodic outflows of the strongest pollution (more than 150 ng/m3) are noted to have a significant effect on the statistical characteristics of black carbon. These situations are observed most often in the atmosphere of the Barents and Kara Seas. Under the influence of these anomalies, the average eBC concentrations increase by a factor of 1.5, and the coefficients of variations by a factor of 1.7–2.4. The maps of the average spatial distribution of the eBC concentrations, measured in marine expeditions, qualitatively agree with multiyear data from model calculations (MERRA-2 reanalysis). The main difference is the higher model eBC values in the southern part of the Laptev Sea and the East Siberian Sea. A comparison of the two data types in these regions, matched to be coincident in time and collocated in space, confirmed that the model eBC concentrations overestimate measurements by 5.68 ng/m3 on the average. Of two reasons for this difference, more probable (as the authors think) is that the model calculations overestimate the outflows of absorbing aerosol to the eastern sector of the Arctic Ocean.

Zwicky Transient Facility and Globular Clusters: The gr-band Period–Luminosity Relations for Mira Variables at Maximum Light and their Applications to Local Galaxies

Based on 14 Miras located in seven globular clusters, we derived the first gr-band period–luminosity (PL) at maximum light for the large-amplitude Mira variables using the multiyear light-curve data collected from the Zwicky Transient Facility (ZTF). Since Miras are red variables, we applied a color-term correction to subsets of ZTF light curves, and found that such corrections do not have a large impact on period determinations. We applied our derived PL relations to the known extragalactic Miras in five local galaxies (Sextans, Leo I, Leo II, NGC 6822 and IC 1613), and determined their Mira-based distances. We demonstrated that our PL relations can be applied to short-period (≲300 days) Miras, including those in the two most distant galaxies (NGC 6822 and IC 1613) in our sample even when only a portion of the light curves around maximum light have detections. We have also shown that the long-period extragalactic Miras do not follow the PL relations extrapolated to longer periods. Hence, our derived PL relations are only applicable to the short-period Miras, which will be discovered in abundance in local galaxies within the era of Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

A comparison of FORMOSAT-3/COSMIC radio occultation and ionosonde measurements in sporadic E detection over mid- and low-latitude regions

The investigation of sporadic E or Es layers typically relies on ground-based or satellite data. This study compares the Es layers recorded in ionograms with those detected using GNSS L1 signal-to-noise ratio data from FORMOSAT-3/COSMIC radio occultation at mid and low latitudes. GPS radio occultation measurements of Es layers, during an 11-year time span of 2007–2017, within a 2° latitude × 5° longitude grid around each ionosonde site are compared to the Es recordings of the ionosonde. By comparing multi-year radio occultation data with recordings from six ionosonde stations at mid and low latitudes, it was discovered that at least 20% of the Es layer detection results between each ionosonde and its crossing GPS radio occultation measurements did not agree. The results show that the agreement between the two methods in Es detection is highly dependent on the season and local time. This study suggests that Es layer recordings from ground-based ionosonde observations have the best agreement with the Es layers detected by radio occultation data during daytime and local summers. The difference in the Es detection mechanisms between the two methods can explain the inconsistency between Es events measured by these two methods. The detection of Es layers in ionograms relies on the high plasma concentration in the E region, whereas signal scintillations caused by a large vertical gradient of the plasma density in the E region are considered a sign of Es occurrence in satellite techniques.