Search Results (80)

“After this I will return, and I will rebuild the dwelling of David, which has fallen; from its ruins I will rebuild it, and I will set it up” (Acts 15:16 NRSV). This verse, quoting Amos 9:11, is part of James’ speech to the Jerusalem “council” considering the issue of Gentile believers and their relationship to the Law. In some Pentecostal circles, especially those influenced by the “Latter Rain” revival of 1948, this verse has taken on a different force based on the Greek skēnē, literally a tent or traditionally “tabernacle.” This teaching is based on the “tabernacle of David” as described in 1 Chron. 16:1–6 and other places and likely the venue in which some of the original psalms were performed. Their argument is that this is part of a model for experiencing the dynamic presence of God in worship and the restoration of the NT church. It forms a theological basis or rationale for contemporary praise and worship with the use of musical instruments, lifted hands, dance, clapping, etc., following the Psalms. However, this interpretation of “David’s fallen tent” seems to fail interpretive tests such as context, authorial intention and audience understanding. This article discusses the interpretive challenges raised by Acts 15:16, how skilled interpreters have understood the “tent of David,” and some weaknesses in these readings. The argument of “Latter Rain” authors on the “Tabernacle of David” is explained and evaluated in the light of some other contemporary research and hermeneutical principles associated with typology. The Latter Rain position is found to have considerable strengths but overreaches in some key points especially by making structure too central. Full article

This study evaluated the Snowmelt-Runoff Model (SRM) and the Génie Rural à X Paramètres Journalier (GRxJ) model family, analyzing the latter both independently and in combination with the CemaNeige snow module. SRM and GRxJ represent snowmelt-runoff and rainfall-runoff hydrological models, respectively. Accurate streamflow estimation in snow- and rain-dominated basins is crucial for water resource management, especially in the Andes where climate variability and glacier retreat threaten long-term water availability. The analysis was conducted in two Chilean watershed basins with contrasting regimes: the snow-dominated Aconcagua and the mixed rain–snow Duqueco basins. Daily data (2012–2020) of precipitation, temperature, evapotranspiration, snow cover (MODIS), and streamflow were used. Models were calibrated and validated with optimization algorithms and evaluated using $NSE$, $RMSE$, $R^2$, $PBIAS$, $KGE$, $MAE$, $logNSE$ and $APFB$. The results show that SRM effectively reproduces variability and, in the case of the rain–snow regime basin, extreme events, with $NSE$ ranging from $0.70$ to $0.78$ (Aconcagua) and $0.93$ to $0.94$ (Duqueco). Model selection should take into account the dominant hydrological processes. In this study, SRM showed the best performance in both analyzed catchments, although with limitations in reproducing extreme streamflow events. In contrast, the GRxJ models did not adequately capture the hydrological dynamics of the snow-dominated Aconcagua catchment. However, their performance improved considerably when applied to the mixed regime of the Duqueco River. These findings highlight the importance of adapting modeling strategies to local hydrological conditions and limited data availability, offering practical guidance for water management and climate change adaptation in Andean catchments. Full article

There are various mechanisms through which water droplets can be present in compressor flows, e.g., rain ingestion in aeroengines or overspray fogging used in heavy-duty gas turbines to boost power output. For the latter, droplet evaporation within the compressor leads to a cooling of the flow as well as to a shift in the fluid properties, which is beneficial to the overall process. However, due to their inertia, the majority of droplets are deposited in the first stages of a multistage compressor. While this phenomenon is generally considered in CFD computations of droplet-laden flows, the subsequent re-entrainment of collected water, the formation of new droplets, and the impact on the overall evaporation are mostly neglected because of the additional computational effort required, especially with regard to the modeling of films formed by the deposited water. The work presented here shows an approach that allows for the integration of the process of droplet deposition and re-entrainment based on relatively simple correlations and experimental observations from the literature. Thus, the two-phase flow in multistage compressors can be modelled and analyzed very efficiently. In this paper, the models and assumptions used are described first, then the results of a study performed based on a generic multistage compressor are presented, whereby the various models are integrated step by step to allow an assessment of their impact on the droplet evaporation throughout the compressor and overall performance. It can be shown that evaporation becomes largely independent of droplet size when deposition on both rotor and stator and subsequent re-entrainment of collected water is considered. In addition, open issues with regard to the future improvement of models and correlations of two-phase flow phenomena are highlighted based on the results of the current investigation. Full article

Among the species used for syrup production, sugar maple (Acer saccharum Marsh.) is preferred by producers, while red maple (Acer rubrum L.) is considered less productive in terms of sap yield and sugar content. This study aims to measure the volume and physicochemical characteristics of the sap produced from two red maples and two sugar maples during the 2023 sugar season in a commercial sugarbush in Laterrière (QC, Canada). Sap exudation was measured continuously with the gravity method using automatic rain gauges. Sap production was discontinuous and heterogeneous, reaching 2.6 L during the most productive day. No significant difference was found in the daily production between species, but we observed a difference in the cumulative sap production (7 L in red maple vs. 13.5 L in sugar maple) due to a longer period of sap exudation in the latter. Despite daily variations in pH, Brix values, sucrose concentration, osmolality, and conductivity, no differences in physicochemical characteristics were detected between species. Full article

We propose a semi-empirical method—based on a filtered Markov process—to convert 10 min rain rate time series into 1 min time series, i.e., quasi-instantaneous rainfall—the latter to be used as input to the synthetic storm technique, which is a very reliable tool for calculating rain attenuation time series in satellite communication systems or for estimating runoff, erosion, pollutant transport, and other applications in hydrology. To develop the method, we used a very large data bank of 1 min rain rate time series collected in several sites with different climatic conditions. The experimental and simulated 1 min rain rate time series agree very well. Afterward, we used them to simulate rain attenuation time series at 20.7 GHz, in 35.5° slant paths to geostationary satellites. The two simulated annual rain attenuation probability distributions show very small differences. We conclude that the rain rate conversion method is very reliable. Full article

Precipitation is a fundamental component of the hydrologic cycle and is an extremely important variable in meteorological, climatological, and hydrological studies. Reliable climate information including accurate precipitation data is essential for identifying precipitation trends and variability as well as applying hydrologic models for purposes such as estimating (surface) water availability and predicting flooding. In this study, I compared precipitation rates from five reanalysis datasets and one analysis dataset—the European Centre for Medium-Range Weather Forecasts Reanalysis Version 5 (ERA-5), the Japanese 55-Year Reanalysis (JRA-55), the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis 1 (NCEP/NCAR R1), the NCEP/Department of Energy Reanalysis 2 (NCEP/DOE R2), and the NCEP/Climate Forecast System Version 2 (NCEP/CFSv2)—with the merged satellite and rain gauge dataset from the Global Precipitation Climatology Project in Version 2.3 (GPCPv2.3). The latter was taken as a reference due to its global availability including the oceans. Monthly mean precipitation rates of the most recent five-year period from 2019 to 2023 were chosen for this comparison, which included calculating differences, percentage errors, Spearman correlation coefficients, and root mean square errors (RMSEs). ERA-5 showed the highest agreement with the reference dataset with the lowest mean and maximum percentage errors, the highest mean correlation, and the smallest mean RMSE. The highest mean and maximum percentage errors as well as the lowest correlations were observed between NCEP/NCAR R1 and GPCPv2.3. NCEP/DOE R2 showed significantly higher precipitation rates than the reference dataset (only JRA-55 precipitation rates were higher), the second lowest correlations, and the highest mean RMSE. Full article

Reliable streamflow forecasting is crucial for several tasks related to water-resource management, including planning reservoir operations, power generation via Hydroelectric Power Plants (HPPs), and flood mitigation, thus resulting in relevant social implications. The present study is focused on the application of Automated Machine-Learning (AutoML) models to forecast daily streamflow in the area of the upper Teles Pires River basin, located in the region of the Amazon biomes. The latter area is characterized by extensive water-resource utilization, mostly for power generation through HPPs, and it has a limited hydrological data-monitoring network. Five different AutoML models were employed to forecast the streamflow daily, i.e., auto-sklearn, Tree-based Pipeline Optimization Tool (TPOT), H2O AutoML, AutoKeras, and MLBox. The AutoML input features were set as the time-lagged streamflow and average rainfall data sourced from four rain gauge stations and one streamflow gauge station. To overcome the lack of training data, in addition to the previous features, products estimated via remote sensing were leveraged as training data, including PERSIANN, PERSIANN-CCS, PERSIANN-CDR, and PDIR-Now. The selected AutoML models proved their effectiveness in forecasting the streamflow in the considered basin. In particular, the reliability of streamflow predictions was high both in the case when training data came from rain and streamflow gauge stations and when training data were collected by the four previously mentioned estimated remote-sensing products. Moreover, the selected AutoML models showed promising results in forecasting the streamflow up to a three-day horizon, relying on the two available kinds of input features. As a final result, the present research underscores the potential of employing AutoML models for reliable streamflow forecasting, which can significantly advance water-resource planning and management within the studied geographical area. Full article

The quantity of the main pollutants present in the atmosphere (particulate matter, ozone, sulfur dioxide, nitrogen dioxide) and meteorological events (rain) can cause permanent or catastrophic damage to plant growth. This study was conducted for the environmental assessment of the Italian territory, in the cities of Palermo, Bari, Ferrara, Padua, and Venice, which respectively represent southern, central, and northern Italy, in order to have a territory global environmental view. The aim of this research is to analyze the relationship between air pollution (PM10, O₃, NO₂, SO₂) and crops (durum and common wheat, corn) as a basis for the subsequent definition of an agronomic model. Later, meteorological events were also added to the analysis, to have a complete overview for the evaluation, since meteorological events contribute to the pollutants’ behavior and favor the deposition of the latter on the vegetation, increasing the negative and toxic effect on crops. The analyses showed that pollutants have a significant effect on crops and in particular ozone appears to be the most influential parameter. Full article

The present study, carried out in Gujarat (India) between 2005 and 2021, aims to prepare dew and rain maps of Gujarat over a long period (17 years, from 2005 to 2021) in order to evaluate the evolution of the potential for dew and rain in the state. The ratio of dew to precipitation is also determined, which is an important metric that quantifies the contribution of dew to the overall water resources. Global warming leads, in general, to a reduction in precipitation and non-rainfall water contributions such as dew. The study shows, however, a rare increase in the rainfall and dew condensation, with the latter related to an increase in relative humidity and a decrease in wind amplitudes. Rain primarily occurs during the monsoon months, while dew forms during the dry season. Although dew alone cannot resolve water scarcity, it nonetheless may provide an exigent and unignorable contribution to the water balance in time to come. According to the site, the dew–rain ratios, which are also, in general, well correlated with dew yields, can represent between 4.6% (Ahmedabad) and 37.2% (Jamnagar). The positive trend, observed since 2015–2017, is expected to continue into the future. Full article

The COVID-19 pandemic produced substantial and sudden changes in the reality of everyday life and in the collective construction of meaning. Questions arose: how should events occurring within an empty reality be broadcast? And, even before that, what structure is needed to make these events transmissible and interpretable, coping with the fact that they happen within a framework of lack of relationships and absolute silence? By analysing the worldwide live recording broadcast on 27 March 2020, commonly known as “the pope alone in Saint Peter’s Square during the pandemic”, this paper identifies a series of communicative solutions adopted by television. These range from making visible what should be hidden, to variously filling the emptiness by modifying the spatial colocation of the event, to an even more extreme solution, in which the emptiness remains as it is, and a rare semantic case occurs in which the sign coincides with its meaning. The latter is what I label the “pope of the rain” solution. Full article

Corn (Zea mays L.) is an important cereal for food sovereignty, extensively planted due to its adaptation to various agroecological conditions. Climatic conditions and pests can affect its production. Concerning the latter, natural enemies could be considered in biological control programs. The objective of this study was to estimate the influence of the presence of insects, damage to plants and cobs, and their incidence on corn yield in two planting seasons. During the rainy (February to May) and dry seasons (Jun to October) of the year 2023, in Calceta, Lodana, and Quevedo, three important corn-growing areas on the Ecuadorian coast, corn plots of 1126 m² were planted. The diversity of phytophagous and natural enemies was estimated. Damage to young plants and cobs was observed, and corn yield was determined. Of the 9073 insects observed, 44.2% and 55.8% constituted phytophagous and natural enemies, respectively. A moderate diversity (Shannon-H Index = 2.474–2.629 and Margalef Index = 2.734–3.110) of insects associated with corn was determined. Yield (range: 6.9 to 15.3 t) was negatively correlated with rainfall and cob damage (p < 0.05). Although precipitation is necessary for planting in rainy season, frequent and intense rains could be affect corn yield. Full article

In light of recent extreme weather events, it is imperative to explore innovative methodologies for promptly and accurately measuring various meteorological parameters. The high spatial and temporal variability in precipitation often surpasses the resolution capabilities of traditional rain gauge measurements and satellite estimation algorithms. Therefore, exploring alternative methods to capture this variability is crucial. Research on the correlation between signal attenuation and precipitation could offer valuable insights into these alternative approaches. This study investigates (a) the feasibility of the classification of precipitation rate using signal power measurements in cellular terminals and (b) the impact of atmospheric humidity as well as other meteorological parameters on the signal. Specifically, signal power data were collected remotely through a specialized Android application designed for this research. During the time of analysis, the power data were processed alongside meteorological parameters obtained from the meteorological station of the Physics Department at the University of Ioannina gathered over one semester. Having in mind the radio refractivity of the air as a fascinating concept affecting the way radio waves travel through the atmosphere, the processed results revealed a correlation with signal attenuation, while a correlation between the latter and absolute humidity was also observed. Moreover, a precipitation rate classification was attained with an overall accuracy exceeding 88%. Full article

Marine eutrophication is a pervasive and growing threat to global sustainability. Thereby, nutrient discharges to the marine environment should be reduced to a minimum. When fertilizers are loaded to the vessels in ports, a significant amount of nutrients are released into the sea, but so far these actions have received little attention. Here, we employed the Boosted Regression Trees modeling (BRT) to define the relationships between fertilizer loading, the loading area, rain intensity, nutrient discharge, and the marine environment, and then used the established relationships to predict the daily nutrient discharge due to fertilizer loading. The studied subject was a port in the Gulf of Finland, where significant amounts of both nitrogen and phosphorus are loaded to vessels. BRT models accounted for a significant proportion of the variability of nutrient discharge. As expected, the nutrient discharge increased with the number of fertilizers loaded and the intensity of rain. On the other hand, with the increasing loading area, the total nitrogen discharge increased, but the total phosphorus discharge decreased. The latter result may be due to the different characteristics of the loading areas of different terminals. The model predicted that at the studied port, the total nitrogen and phosphorus discharge to the marine environment due to fertilizer loading was 272,906 and 196 kg per year, respectively. Importantly, the developed model can be used to predict the nutrient loads for different future scenarios in order to propose the best mitigation methods for nutrient discharges to the sea. Full article

Space probes are always obstructed by floating objects in the atmosphere (clouds, haze, rain, etc.) during imaging, resulting in the loss of a significant amount of detailed information in remote sensing images and severely reducing the quality of the remote sensing images. To address the problem of detailed information loss in remote sensing images, we propose an end-to-end detail enhancement network to directly remove haze in remote sensing images, restore detailed information of the image, and improve the quality of the image. In order to enhance the detailed information of the image, we designed a multi-scale detail enhancement unit and a stepped attention detail enhancement unit, respectively. The former extracts multi-scale information from images, integrates global and local information, and constrains the haze to enhance the image details. The latter uses the attention mechanism to adaptively process the uneven haze distribution in remote sensing images from three dimensions: deep, middle and shallow. It focuses on effective information such as haze and high frequency to further enhance the detailed information of the image. In addition, we embed the designed parallel normalization module in the network to further improve the dehazing performance and robustness of the network. Experimental results on the SateHaze1k and HRSD datasets demonstrate that our method effectively handles remote sensing images obscured by various levels of haze, restores the detailed information of the images, and outperforms the current state-of-the-art haze removal methods. Full article

Toxic and harmful algal blooms (HABs) are a global problem affecting human health, marine ecosystems, and coastal economies, the latter through their impact on aquaculture, fisheries, and tourism. As our knowledge and the techniques to study HABs advance, so do international monitoring efforts, which have led to a large increase in the total number of reported cases. However, in addition to increased detections, environmental factors associated with global change, mainly high nutrient levels and warming temperatures, are responsible for the increased occurrence, persistence, and geographical expansion of HABs. The Chilean Patagonian fjords provide an “open-air laboratory” for the study of climate change, including its impact on the blooms of several toxic microalgal species, which, in recent years, have undergone increases in their geographical range as well as their virulence and recurrence (the species Alexandrium catenella, Pseudochattonella verruculosa, and Heterosigma akashiwo, and others of the genera Dinophysis and Pseudo-nitzschia). Here, we review the evolution of HABs in the Chilean Patagonian fjords, with a focus on the established connections between key features of HABs (expansion, recurrence, and persistence) and their interaction with current and predicted global climate-change-related factors. We conclude that large-scale climatic anomalies such as the lack of rain and heat waves, events intensified by climate change, promote the massive proliferation of these species by creating ideal conditions for their growth and persistence, as they affect water-column stratification, nutrient inputs, and reproductive rates. Full article