Search Results (26)

Surface albedo is a key variable influencing ground-reflected solar irradiance, which is a vital factor in boosting the energy gains of bifacial solar installations. Therefore, surface albedo is crucial towards estimating photovoltaic power generation of both bifacial and tilted solar installations. Varying across daylight hours, seasons, and locations, surface albedo is assumed to be constant across time by various models. The lack of granular temporal observations is a major challenge to the modeling of intra-day albedo variability. Though satellite observations of surface reflectance, useful for estimating surface albedo, provide wide spatial coverage, they too lack temporal granularity. Therefore, this paper considers a novel approach to temporal downscaling with imaging time series of satellite-sensed surface reflectance and limited high-temporal ground observations from surface radiation (SURFRAD) monitoring stations. Aimed at increasing information density for learning temporal patterns from an image series and using visual redundancy within such imagery for temporal downscaling, we introduce temporally shifted heatmaps as an advantageous approach over Gramian Angular Field (GAF)-based image time series. Further, we propose Multispectral-WaveMix, a derivative of the mixer-based computer vision architecture, as a high-performance model to harness image time series for surface albedo forecasting applications. Multispectral-WaveMix models intra-day variations in surface albedo on a 1 min scale. The framework combines satellite-sensed multispectral surface reflectance imagery at a 30 m scale from Landsat and Sentinel-2A and 2B satellites and granular ground observations from SURFRAD surface radiation monitoring sites as image time series for image-to-image translation between remote-sensed imagery and ground observations. The proposed model, with temporally shifted heatmaps and Multispectral-WaveMix, was benchmarked against predictions from models image-to-image MLP-Mix, MLP-Mix, and Standard MLP. Model predictions were also contrasted against ground observations from the monitoring sites and predictions from the National Solar Radiation Database (NSRDB). The Multispectral-WaveMix outperformed other models with a Cauchy loss of 0.00524, a signal-to-noise ratio (SNR) of 72.569, and a structural similarity index (SSIM) of 0.999, demonstrating the high potential of such modeling approaches for generating granular time series. Additional experiments were also conducted to explore the potential of the trained model as a domain-specific pre-trained alternative for the temporal modeling of unseen locations. As bifacial solar installations gain dominance to fulfill the increasing demand for renewables, our proposed framework provides a hybrid modeling approach to build models with ground observations and satellite imagery for intra-day surface albedo monitoring and hence for intra-day energy gain modeling and bifacial deployment planning. Full article

We review recent articles that focus on the main issues identified in high-frequency financial data analysis. The issues to be addressed include nonstationarity, low signal-to-noise ratios, asynchronous data, imbalanced data, and intraday seasonality. We focus on the research articles and survey papers published since 2020 on recent developments and new ideas that address the issues, while commonly used approaches in the literature are also reviewed. The methods for addressing the issues are mainly classified into two groups: data preprocessing methods and quantitative methods. The latter include various statistical, econometric, and machine learning methods. We also provide easy-to-read charts and tables to summarize all the surveyed methods and articles. Full article

A circadian clock (CC) has evolved in plants that synchronizes their growth and development with daily and seasonal cycles. A properly functioning circadian clock contributes to increasing plant growth, reproduction, and competitiveness. In plants, continuous light treatment has been a successful approach for obtaining novel knowledge about the circadian clock. The olive tree (Olea europaea L.) is one of the most important crops in the Mediterranean area, and, so far, limited information is available on its CC gene network. Here, we studied the behavior of circadian rhythm genes under LD (light/darkness) and LL (light/light) conditions, the relationships in this network, and the ability of the treatments to modulate gene expression in the photoprotective pigment and lipid biosynthesis pathways. One month of LL conditions increased olive growth performance, but LL exposure also caused reductions in vegetative growth and chlorophyll accumulation. A panel was designed for a study of the transcription expression levels of the genes involved in light perception, the CC, and secondary metabolite and fatty acid biosynthesis. Our results revealed that the levels of 78% of the transcripts exhibited intraday differences under LD conditions, and most of them retained this rhythmicity after exposure to one and two months of LL conditions. Furthermore, co-regulation within a complex network among genes of photoreceptors, anthocyanidins, and fatty acids biosynthesis was orchestrated by the transcription factor HY5. This research enriches our knowledge on olive trees grown under prolonged irradiation, which may be attractive for the scientific community involved in breeding programs for the improvement of this species. Full article

Randomness and intermittency of renewable energy generation are inevitable impediments to the stable electricity supply of isolated energy systems in remote rural areas. This paper unveils a novel framework, the electric–hydrogen hybrid energy storage system (EH-HESS), as a promising solution for efficiently meeting the demands of intra-day and seasonal peak shaving. A hierarchical time discretization model is applied to achieve unified operation of hydrogen and electric energy storage to simplify the model. Furthermore, an operation strategy considering the energy interaction between ESSs is introduced, while an optimization model of hydrogen storage working interval within the state transition limit is designed to improve the utilization of hydrogen storage. Numerical tests are conducted to validate the approach, demonstrating that the proposed energy storage structure and operation strategy can effectively improve the utilization of energy storage and ensure the energy supply of the system, which will provide a reference for the sustainable operation of renewable energy systems in the future. Full article

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability is substantial. In response, we have integrated wave energy with offshore photovoltaic and wind power generation and propose a day-ahead and intra-day multi-time-scale rolling optimization scheduling strategy for the complementary dispatch of these three energy sources. Using real meteorological data from this maritime area, we employed a CNN-LSTM neural network to predict the power generation and load demand of the area on both day-ahead 24 h and intra-day 1 h time scales, with the DDPG algorithm applied for refined electricity management through rolling optimization scheduling of the forecast data. Simulation results demonstrate that the proposed strategy effectively meets load demands through complementary scheduling of wave power, wind power, and photovoltaic power generation based on the climatic characteristics of the Bohai and Yellow Sea regions, reducing the negative impacts of the seasonality and intra-day uncertainty of these three energy sources on the grid. Additionally, compared to the day-ahead scheduling strategy alone, the day-ahead and intra-day rolling optimization scheduling strategy achieved a reduction in system costs by 16.1% and 22% for a typical winter day and a typical summer day, respectively. Full article

In the Yellow and Bohai Seas, the detailed characteristics of visibility are analyzed based on automatic hourly observation data of marine visibility between 2019 and 2021. The results show that the annual average visibility in the Yellow and Bohai Seas is 13.346 km. The average visibility at high latitudes is higher than that at low latitudes in the Yellow and Bohai Seas. The low visibility area is mainly distributed in the southwest of the Yellow Sea. There are obvious seasonal differences in visibility in the Yellow and Bohai Seas. Visibility is high from September to November, with maximum values in October. Visibility is lowest in July when the maximum visibility is low and the minimum visibility is high. The visibility in spring is overall relatively low, and the areas of low visibility appear in the southwest of the Yellow Sea. The visibility in autumn is overall relatively high, and the areas of high visibility occur in the northern part of the Bohai and Yellow Seas. The visibility has significant intraday variation. The visibility around sunset is significantly higher than that around sunrise. The hourly visibility is low between 4:00 and 9:00, with the lowest visibility most likely around 7:00. The hourly visibility is high between 16:00 and 21:00, with the highest visibility most likely around 18:00. Low visibility occurs frequently between November and April, most of all in March. Low visibility most often occurs between 4:00 and 7:00. Low visibility may occur at any time between November and April, and also in mornings between May and August. It occurs less often at other times. Full article

High-frequency observations of surface current field data over large areas and long time series are imperative for comprehending sea-air interaction and ocean dynamics. Nonetheless, neither in situ observations nor polar-orbiting satellites can fulfill the requirements necessary for such observations. In recent years, geostationary satellite data with ultra-high temporal resolution have been increasingly utilized for the computation of surface flow fields. In this paper, the surface flow field in the East China Sea is estimated using maximum cross-correlation, which is the most widely used flow field computation algorithm, based on the total suspended solids (TSS) data acquired from the Geostationary Ocean Color Imager satellite. The inversion results were compared with the modeled tidal current data and the measured tidal elevation data for verification. The results of the verification demonstrated that the mean deviation of the long semiaxis of the tidal ellipse of the inverted M₂ tide is 0.0335 m/s, the mean deviation of the short semiaxis is 0.0276 m/s, and the mean deviation of the tilt angle is 6.89°. Moreover, the spatially averaged flow velocity corresponds with the observed pattern of tidal elevation changes, thus showcasing the field’s significant reliability. Afterward, we calculated the sea surface current fields in the East China Sea for the years 2013 to 2019 and created distribution maps for both climatology and seasonality. The resulting current charts provide an intuitive display of the spatial structure and seasonal variations in the East China Sea circulation. Lastly, we performed a diagnostic analysis on the surface TSS variation mechanism in the frontal zone along the Zhejiang coast, utilizing inverted flow data collected on 3 August 2013, which had a high spatial coverage and complete time series. Our analysis revealed that the intraday variation in TSS in the local surface layer was primarily influenced by tide-induced vertical mixing. The research findings of this article not only provide valuable data support for the study of local ocean dynamics but also verify the reliability of short-period surface flow inversion of high-turbidity waters near the coast using geostationary satellites. Full article

Differential code bias (DCB) is one of the main errors involved in ionospheric total electron content (TEC) retrieval using a global navigation satellite system (GNSS). It is typically assumed to be constant over time. However, this assumption is not always valid because receiver DCBs have long been known to exhibit apparent intraday variations. In this paper, a combined method is introduced to estimate the epoch-wise receiver DCB, which is divided into two parts: the receiver DCB at the initial epoch and its change with respect to the initial value. In the study, this method was proved feasible by subsequent experiments and was applied to analyze the possible reason for the intraday receiver DCB characteristics of 200 International GNSS Service (IGS) stations in 2014 (high solar activity) and 2017 (low solar activity). The results show that the proportion of intraday receiver DCB stability less than 1 ns increased from 72.5% in 2014 to 87% in 2017, mainly owing to the replacement of the receiver hardware in stations. Meanwhile, the intraday receiver DCB estimates in summer generally exhibited more instability than those in other seasons. Although more than 90% of the stations maintained an intraday receiver DCB stability within 2 ns, substantial variations with a peak-to-peak range of 5.78 ns were detected for certain stations, yielding an impact of almost 13.84 TECU on the TEC estimates. Moreover, the intraday variability of the receiver DCBs is related to the receiver environment temperature. Their correlation coefficient (greater than 0.5 in our analyzed case) increases with the temperature. By contrast, the receiver firmware version does not exert a great impact on the intraday variation characteristics of the receiver DCB in this case. Full article

Background: Emerging evidence has integrated short-term exposure to PM₁ with children’s morbidity and mortality. Nevertheless, most available studies have been conducted on a daily scale, ignoring the exposure variations over the span of a day. Objective: The main intention of this study was to examine the association between pediatric emergency department visits (PEDVs) and intra-day exposures to PM₁ and PM_2.5. We also aimed to investigate whether a high PM₁/PM_2.5 ratio elevated the risk of PEDVs independent from PM_2.5 exposure within several hours. Methods: We collected hourly data on aerial PM₁ and PM_2.5 concentrations, all-cause PEDVs, and meteorological factors from two megacities (i.e., Guangzhou and Shenzhen) in southern China during 2015–2016. Time-stratified case-crossover design and conditional logistic regression analysis were used to assess the associations of PEDVs with exposures to PM₁ and PM_2.5 at different lag hours. The contribution of PM₁ to PM_2.5-associated risk was quantified by introducing PM₁/PM_2.5 ratio as an additional exposure indicator in the analysis adjusting for PM_2.5. Subgroup analyses were performed stratified by sex, age, and season. Results: During this study period, 97,508 and 101,639 children were included from Guangzhou and Shenzhen, respectively. PM₁ and PM_2.5 exposures within several hours were both remarkably related to an increased risk of PEDVs. Risks for PEDVs increased by 3.9% (95% confidence interval [CI]: 2.7–5.0%) in Guangzhou and 3.2% (95% CI: 1.9–4.4%) in Shenzhen for each interquartile range (Guangzhou: 21.4 μg/m³, Shenzhen: 15.9 μg/m³) increase in PM₁ at lag 0–3 h, respectively. A high PM₁/PM_2.5 ratio was substantially correlated with increased PEDVs, with an excess risk of 2.6% (95% CI: 1.2–4.0%) at lag 73–96 h in Guangzhou and 1.2% (95% CI: 0.4–2.0%) at lag 0–3 h in Shenzhen. Stratified analysis showed a clear seasonal pattern in PM-PEDVs relationships, with notably stronger risks in cold months (October to March of the following year) than in warm months (April to September). Conclusions: Exposures to ambient PM₁ and PM_2.5 within several hours were related to increased PEDVs. A high PM₁/PM_2.5 ratio may contribute an additional risk independent from the short-term impacts of PM_2.5. These findings highlighted the significance of reducing PM₁ in minimizing health risks due to PM_2.5 exposure in children. Full article

It is a widely known fact that the intraday seasonality of trading intervals for financial transactions such as stocks is short at the beginning of business hours and long in the middle of the day. In this paper, we extend the stochastic conditional duration (SCD) model to capture the pattern of intraday trading intervals and propose a new Markov chain Monte Carlo method to estimate this intraday seasonality simultaneously. To efficiently generate the Monte Carlo sample, we used a hybrid of the Gibbs/Metropolis–Hastings (MH) sampling scheme and also applied generalized Gibbs sampling. In addition to capturing this intraday seasonality, this paper also considers limit order book information. Three-day tick data for three stocks obtained from Nikkei NEEDS are used for estimation, and model selection is performed on smooth parameters, Weibull distribution and Gamma distribution. The typical intraday regularity of frequent trading immediately after the start of trading is confirmed, and the spread of the limit order book information is also found to affect the trading time interval. Full article

In recent years, the conversion of saline-alkali land to rice fields has become the most dominant land use change feature in western Jilin, leading to significant surface greening. Saline–alkali land and paddy fields have distinct surface biophysical properties; however, there is a lack of systematic assessment of the moderating effect of planting rice on saline–alkali land on regional climate by changing surface properties. In this paper, multiscale data on the surface temperature of saline–alkali land and paddy fields were obtained using 1 km MODIS product, 30 m Landsat 8 satellite imagery and centimeter-scale UAV imagery in Da’an City, western Jilin as the study area, and the various characteristics of the surface temperature of saline-alkali land and paddy fields in different months of the year and at different times of the day were analyzed. Furthermore, the effect of rice cultivation in saline–alkali land on the local surface temperature was assessed using a space-for-time approach. The results based on satellite observations including both MODIS and Landsat showed that the surface temperature of saline–alkali land was significantly higher than that of paddy fields during the crop growing season, especially in July and August. The high temporal resolution MODIS LST data also indicated the paddy fields cool the daytime surface temperature, while warming the nighttime surface temperature, which was in contrast for saline–alkali land during the growing season. High-resolution UAV observations in July confirmed that the cooling effect of paddy fields was most significant at the middle of day. From the biophysical perspective, the reclamation of saline–alkali land into paddy fields leads to an increase in leaf area index, followed by a significant increase in evapotranspiration. Meanwhile, rice cultivation in saline–alkali land reduces surface albedo and increases surface net radiation. The trade-off relationship between the two determines the seasonal difference in the surface temperature response of saline–alkali land for rice cultivation. At the same time, the daily cycle of crop evapotranspiration and the thermal insulation effect of paddy fields at night are the main reasons for the intraday difference in surface temperature between saline–alkali land and paddy field. Based on the multiscale assessment of the impact of rice cultivation in saline-alkali land on surface temperature, this study provides a scientific basis for predicting future regional climate change and comprehensively understanding the ecological and environmental benefits of saline–alkali land development. Full article

The paper presents the results of field measurements and numerical modeling of the influence of various factors on the formation of coherent structures in the confluence zone of the Sylva and Chusovaya rivers, which are dammed by the Kamskaya Hydroelectric Power Station (HPS). A characteristic feature of the measured parameters in the zone under study is that they experience both seasonal fluctuations and fluctuations of much higher frequency associated with intraday regulation of the HPS operation. These intraday fluctuations give rise to coherent structures with periodicity T~2–10 min, which manifest themselves in the fluctuations of the specific electrical conductivity of water. The flow velocity also experiences significant fluctuations with a sufficiently wide frequency spectrum, although the characteristic period of its fluctuations is less than the period of electrical conductivity fluctuations and is equal to ~1 min. In order to study the features of the formation of such structures, numerical simulation was carried out within the framework of the three-dimensional approach. Calculations were performed for a 300-meter-long stretch of the Chusovaya River, which is located downstream of the confluence of Chusovaya and Sylva rivers and is the site of the Chusovskoy water intake of Perm city. It was found that the intraday irregularity of HPS operation gives rise to the occurrence of vortex structures in this layer, leading to the temporal variation of concentration at a given point of space and the formation of the wave structure of the concentration field at different moments of time. Time period and spatial scale of such vortex structures depend on the ratio of velocities of water masses and difference in their mineralization and, accordingly, in densities. Moreover, the period of fluctuations is proportional to the ratio of flow velocities. These estimations are of fundamental importance for the implementation of stable selective intake of water with required consumer properties under conditions of intraday irregularity of hydroelectric power station operation. Full article

This study evaluated a potential transition of India’s power sector to 100% wind and solar energy sources. Applying a macro-energy IDEEA (Indian Zero Carbon Energy Pathways) model to 32 regions and 114 locations of potential installation of wind energy and 60 locations of solar energy, we evaluated a 100% renewable power system in India as a concept. We considered 153 scenarios with varying sets of generating and balancing technologies to evaluate each intermittent energy source separately and their complementarity. Our analysis confirms the potential technical feasibility and long-term reliability of a 100% renewable system for India, even with solar and wind energy only. Such a dual energy source system can potentially deliver fivefold the annual demand of 2019. The robust, reliable supply can be achieved in the long term, as verified by 41 years of weather data. The required expansion of energy storage and the grid will depend on the wind and solar energy structure and the types of generating technologies. Solar energy mostly requires intraday balancing that can be achieved through storage or demand-side flexibility. Wind energy is more seasonal and spatially scattered, and benefits from the long-distance grid expansion for balancing. The complementarity of the two resources on a spatial scale reduces requirements for energy storage. The demand-side flexibility is the key in developing low-cost supply with minimum curtailments. This can be potentially achieved with the proposed two-level electricity market where electricity prices reflect variability of the supply. A modelled experiment with price signals demonstrates how balancing capacity depends on the price levels of guaranteed and flexible types of loads, and therefore, can be defined by the market. Full article

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233–1.606), 1.470 (95% CI: 1.220–1.771) and 1.741 (95% CI: 1.157–2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384–1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change. Full article

The purpose of this work is to summarize a large amount of observational data about the secular decrease of Cas A flux in the radio range, as an indicator of physical processes both in the source itself and as a consequence of the influence of the propagation medium. This paper presents results of observations Cas A and Cyg A on radio telescopes of International Radio Astronomy Center (Latvia), and URAN-4 phased array antenna (Institute of Radio Astronomy NAS of Ukraine). According to URAN-4 observations, there were seasonal–diurnal changes in Cas A/Cyg A flux ratios due to the effects of solar activity on the ionosphere, and there may be no secular decrease in Cas A flux density, or a weak tendency to decrease it. The significant influence of the ionosphere makes it difficult to use Cyg A as a reference source in the decameter radio range. In the centimeter radio range, there were episodic intra-day variations at the level 8–10% of Cas A averaged flux. Additionally, in the period January–February 2021, Cas A flux was about 1.7 times that of Cyg A. Taking into account the observed complex type of secular decrease in Cas A flux against the background of changes in space weather variations, further observations of Cas A were planned at radio observatories in Latvia and Ukraine. Full article