Precipitation Analysis Research Articles

The Role of Precipitation in Sustainable Water Management: Insights from Atmospheric Science

Water scarcity is a growing challenge in many regions around the world, including Nigeria, where precipitation patterns have a significant impact on water availability for human and ecological systems. This research paper explores the role of precipitation in sustainable water management, drawing insights from atmospheric science research. In particular, we conduct a trend analysis of precipitation in key areas of Nigeria using the new Innovative Trend Analysis (ITA) method. ITA is a powerful statistical method that allows for the detection of trends and periodicities in time series data, even in the presence of non-linear trends and data uncertainties. Our analysis aims to provide a better understanding of how precipitation has changed over time in Nigeria and what implications these changes have for water management strategies and practices. The potential for atmospheric science research to inform future water policy and planning decisions are also discussed. The examination of precipitation trends using the ITA approach revealed a range of patterns, from reducing or trendless scatter points in the southern vegetation zones to increasing precipitation trends in the savannah regions; this emphasizes the need for context-specific water management strategies. Regions experiencing declining precipitation may necessitate adaptive measures to address potential water scarcity, while those with increasing trends require strategies to mitigate potential flooding risks. By combining meteorological data with reviewed insights from other disciplines such as hydrology, ecology, and economics, we can work towards a more sustainable and equitable management of water resources in Nigeria and even beyond.

Spatial and Temporal Trend Analysis of Precipitation and Temperature Data in Malwa Region of Kshipra River Basin, India

Spatial and Temporal Trend Analysis of Precipitation and Temperature Data in Malwa Region of Kshipra River Basin, India

Parametric and Non-parametric Analysis of Annual Precipitation for Amaravati: A Spatial and Temporal Analysis

Parametric and Non-parametric Analysis of Annual Precipitation for Amaravati: A Spatial and Temporal Analysis

Investigating North Sea Precipitation Variability: Implications for Offshore Wind Energy Siting and Condition Assessments

Rain-driven wind turbine blade erosion, particularly in offshore locations, has been observed as early as within 5 to 7 years of turbine operation, which is below the lifetime expectancy design age of 20 to 25 year. Due to the harsh atmospheric conditions offshore, the preservation of wind turbine blade integrity has become a fundamental necessity. To address this challenge, we compare precipitation maps from two distinct sources (satellite data and a reanalysis product) over 12 years in the region of the North Sea, and we pursue insights into local weather patterns through temporal analysis. This integrated approach enhances the understanding of offshore conditions by focusing on precipitation and wind speed data analysis in time and space. This enables more efficient wind farm planning, operation and maintenance, as well as wind farm siting via informed decisions that account for the risk of rain-driven blade erosion and allow for mitigation measures.

Microstructural analysis of cold-drawn medium-carbon low-alloy martensite: effect of deformation and tempering temperature

Microstructure of cold-drawn (≈ 0.9 effective deformation) medium-carbon steel containing Cr and Mo, was investigated in samples tempered at 923 K (tempering at high temperature [HTT]) and 723 K (tempering at intermediate temperature [ITT]) using transmission electron microscopy, X-ray diffraction and microhardness. The study revealed distinct features in lath martensite. HTT samples showed reduced dislocation density and larger precipitates compared to ITT samples. After cold drawing, ITT samples exhibited lamellar dislocation cells and cell blocks, while HTT specimens primarily showed cell block structures. Analysis of precipitates revealed changes in orientation after drawing, as well as alterations in both inter- and intragranular precipitate density. ITT samples also displayed higher post-tempering hardness. This analysis provides quantitative insights into the microstructural evolution and mechanical behaviour after tempering and cold-drawing, which can help optimise processes for achieving ultrafine-grained structures.

Correlative Electron Microscopy Analysis of Precipitates in a V–Nb–Mo Micro-alloyed Steel

Correlative Electron Microscopy Analysis of Precipitates in a V–Nb–Mo Micro-alloyed Steel

Evaluation of five gridded precipitation products for estimating precipitation and drought over Yobe, Nigeria

ABSTRACT Ground observations are often considered as the most reliable and precise source of precipitation data. However, long-term precipitation data from ground observations are lacking in many parts of the world. Gridded precipitation products (GPPs) therefore have emerged as crucial alternatives to ground observations, but it is essential to assess their capability to accurately replicate precipitation patterns. This study aims to evaluate the performance of five GPPs, NASA POWER, TerraClimate, Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS), GPCC, and Climate Research Unit (CRU), in capturing precipitation and drought patterns from 1981 to 2021 in Yobe, Nigeria. The results indicate that GPCC had good performance at both monthly and annual scales, with high correlation coefficients and low error values. However, it tends to underestimate precipitation amounts in certain areas. Other products also exhibit satisfactory performance with moderate correlations with ground observations. Drought analysis indicates that GPCC outperforms other products in standardised precipitation index-6 calculations, while NASA POWER demonstrates inconsistencies with ground observations, particularly during the early 1980s and mid-2000s. In conclusion, GPCC is the most preferable GPP for precipitation and drought analysis in the Yobe State in Nigeria.

A new look at genetic variability in pomegranate: Landscape genetics and structural equation modeling (SEM)

Pomegranate (Punica granatum L.) is an important horticultural plant in Iran and has been a food source since ancient times. Despite several genetic diversity studies conducted on these taxa, there are no reports on the landscape genetics of these important plants in Iran, nor is there any information on the effects of environmental, spatial, and climatic variables on the genetic structure of pomegranate. Therefore, this study used genetics, structural equation modeling (SEM), and species distribution modeling (SDM) approaches to explore the above-mentioned objectives. We used both cytogenetic and molecular analyses (SSR and SCoT markers) of several pomegranate samples along with environmental, spatial, and climatic variables. The redundancy analysis (RDA) analysis showed a significant positive association between terminal chiasmata with the longitudinal distribution of the pomegranate accession, while total chiasma number and interstitial chiasmata have an association with the altitude. The spatial PCA analysis indicated the role played by both global and local spatial variables in the cytogenetic variability like the univalent and terminal chiasmata formation. The Mantel test indicates that the cytogenetic difference in pomegranate plants is not related to their geographical distance, while the Moran I test result shows that geographical regions with similar spatial conditions affect the cytogenetic structuring of pomegranate plants in a similar way. SEM methods showed a strong negative association between bivalent formation and the environmental variables, while they showed both positive and negative associations between some of the environmental variables and different kinds of chiasmata. The sPCA analysis of molecular data showed a significant global, and local, spatial structuring of the molecular data and the genetic cline formation within the pomegranate accessions studied. Similarly, the spatial PCA analysis of climate variables, precipitation, and temperature revealed a significant structuring of genetic diversity and the formation of genetic clines by these factors. RDA analysis identified some of the loci that are significantly associated with temperature and precipitation. Therefore, both geographical/ or spatial variables and climate factors contribute to the genetic structure of the pomegranate accessions studied. SEM models based on genetic data revealed a positive association between environmental and climate variables with genetic diversity parameters and SSR-SCoT molecular loci studied. Climate change is unlikely to hurt pomegranate growing areas due to the high genetic diversity of pomegranate plants and the diverse genetic lineages present in the country.

A Detailed Examination of Türkiye's Projected Precipitation and Growth Season Trends under Climate Change Condition

This study presents a comprehensive analysis of Türkiye's changing precipitation patterns and growing season dynamics in the context of global warming, utilizing the Coupled Model Intercomparison Project Phase 5 (CMIP5) and various Representative Concentration Pathway (RCP) scenarios. In light of global warming, this study provides a thorough analysis of Türkiye's evolving precipitation patterns and growing season dynamics using multiple RCP scenarios and CMIP5. The research aims to fill a crucial gap in climate research by combining historical data and future projections to assess Türkiye's precipitation path under different greenhouse gas emission scenarios. The study employs linear regression for trend analysis and uses data from the Climate Change Knowledge Portal (CCKP), with a focus on precipitation data from 1986 to 2100. According to various RCP scenarios, this study’s findings show a considerable variation in precipitation trends over the 21st century. The RCP 8.5 scenario predicts a significant decrease in precipitation, which would present difficulties for the management of water resources and agricultural productivity. In contrast, the least severe RCP 2.6 pathway shows a fairly stable pattern of precipitation. Complex seasonal hydrological responses to climate change are revealed by monthly precipitation analysis; RCP8.5 predicts an increase in the frequency of periods of drought and heavy precipitation events. The impact of these changes in precipitation on Türkiye's agricultural growing seasons was further investigated in this study. In high-emission scenarios, there was an initial tendency towards longer growing seasons, which were subsequently followed by shorter ones. This suggests that although global warming might initially result in an extended growing season, it might ultimately cause a reduction in it, particularly in situations where mitigation efforts are minimal. The need for adaptable strategies that can respond to long-term climate trends as well as seasonal variability was highlighted by this research. It draws attention to the fact that to mitigate the effects of climate variability, informed policy decisions and integrated resource management are essential. The results highlight the need for quick action to lower the risks associated with water and highlight the potential advantages of intensive mitigation efforts in stabilizing and extending growing seasons.

Aluminum Removal from Rare Earth Chloride Solution through Regulated Hydrolysis via Electrochemical Method

Due to the coexistence of Al3+ and RE3+ and their similar properties, the separation of aluminum from rare earths is difficult. In this study, selective precipitation was used to separate aluminum from rare earth chloride solution via electrochemical regulated hydrolysis. By controlling the current density and electrolytic time, the rate of hydroxyl ion production was regulated, and the selective separation of rare earth and aluminum was realized according to the different precipitation sequences. By altering the temperature, current density, pH value, and other parameters, the separation performance of aluminum from rare earth in mixed rare earth chloride systems was systematically investigated. The removal rate of aluminum reached 88.35%, and the loss rate of rare earth was only 5.99% under optimized conditions. Compared with traditional neutralization hydrolysis, the new process showed higher efficiency and lower rare earth loss rate. Furthermore, a kinetic analysis of aluminum precipitation revealed that the reaction adhered to pseudo-first order kinetics. Additionally, the precipitate obtained via separation and filtration was amorphous alumina hydroxide with a small amount of rare earth attached. No reagent was consumed for the new process, which was more efficient and cleaner, providing a new idea for removing aluminum impurities from rare earth solutions.

Nonstationary frequency analysis of extreme precipitation: Embracing trends in observations

Knowledge of the recurrence intervals of precipitation extremes is vital for infrastructure design, risk assessment, and insurance planning. However, trends and shifts in rainfall patterns globally pose challenges to the application of extreme value analysis (EVA) which relies critically on the assumption of stationarity. In this paper, we explore: (1) the suitability of nonstationary (NS) models in the presence of statistically significant trends, and (2) their potential in modeling out-of-sample data to improve frequency analysis of extreme precipitation. We analyze the benefits of using a nonstationary Generalized Extreme Value (GEV) model for annual extreme precipitation records from Southern Brazil. The location of the GEV distribution is allowed to change with time. The unknown GEV model parameters are estimated using Bayesian techniques coupled with Markov chain Monte Carlo simulation. Next, we use GAME sampling to compute the evidence (and their ratios, the so-called Bayes factors) for stationary and nonstationary models of annual maximum precipitation. Our results show that the presence of a statistically significant trend in annual maximum precipitation alone does not justify the use of a NS model. The location parameter of the GEV distribution must also be well defined, otherwise, stationary models of annual maximum precipitation receive more support by the data. These findings reiterate the importance of accounting for GEV model parameters and predictive uncertainty in frequency analysis and hypothesis testing of annual maximum precipitation data records. Furthermore, a meaningful EVA demands detailed knowledge about the origin and persistence of observed changes.

Assessing the effects of climate and land-use change on flood recurrence in Kokcha River, Afghanistan

ABSTRACT This study critically assesses the combined effects of climate and land-use change on flood recurrence in the Kokcha River, Afghanistan, spanning the period from 2010 to 2021 and projecting forward to 2088–2099. Through the application of a bias-corrected model, we achieved high accuracy in temperature and precipitation simulations, with notable NSE values of 0.9 and 0.69, and R2 values of 0.92 and 0.78, respectively. Future streamflow simulations under different scenarios highlight climate change as the major driver influencing flood recurrence in the Kokcha River, contributing to 101.1% of the total variation, while land-use change has a minimal contribution of −1.1%. Our analysis of precipitation, average temperature, and streamflow data reveals significant patterns and changes, with future projections indicating a gradual decline in precipitation levels, mean temperature, and streamflow. Flood frequency analysis for return periods of 10, 50, 100, 200, and 500 years, considering different scenarios, underscores the likelihood of floods of varying magnitudes. Notably, the highest streamflow spikes under both scenarios highlight the impact of futuristic air temperature and precipitation on flood recurrence. The study advocates prioritizing climate change adaptation and resilient land-use strategies to ensure sustainable water resource management, emphasizing the mitigation of potential flood risks.

Refinement of Microstructure and Enhancement of Wear Resistance of Ni–Cr Cast Iron by NbC

This article investigates the influence of niobium addition on the microstructure and properties of Ni–Cr cast iron. In situ observations and analysis of phase precipitation during solidification are conducted through a high‐temperature laser scanning confocal microscope and Thermo‐Calc software. The refining mechanism of the microstructure and the enhancement of wear resistance by NbC are explored. The results indicate that with an increase in Nb content, the precipitation temperature of NbC particles gradually rises. When the niobium content exceeds 0.2%, NbC becomes the first precipitated phase during the solidification of the liquid phase. NbC particles can serve as heterogeneous nucleus for austenite, refining the grain structure of Ni–Cr cast iron. The existence of NbC particles within the grain impedes the elongation of martensite and bainite bundles while providing additional nucleation sites to accelerate the phase transformation. The grain refinement and the obstructive influence of NbC particles collectively induce a more disordered bainitic structure. Moreover, the exceptional hardness of NbC particles effectively safeguards the matrix from abrasion, consequently enhancing the wear resistance of Ni–Cr cast iron.

Analysis of Average Daily Temperature and Precipitation on the Territory of Belarus Using Quantile Regression

Analysis of Average Daily Temperature and Precipitation on the Territory of Belarus Using Quantile Regression

Improving the recovery for dissolved eDNA state: A comparative analysis of isopropanol precipitation, magnetic bead extraction, and centrifugal dialysis

AbstractEnvironmental DNA consists of multiple states including but not limited to membrane‐bound, adsorbed, and dissolved states. Because of their chemical and physical properties, each of these states may have different degradation and transport potential. Essential to the study of eDNA states is being able to isolate them from an environmental sample. Here, we focus on improving the DNA recovery of the dissolved state of eDNA from water. We compared three recovery methods, namely isopropanol precipitation, magnetic bead extraction, and centrifugal dialysis. We evaluated the effectiveness of these methods based on the measured DNA recovery of two different species' DNA of different sizes. DNA recovery was assessed with qPCR. We also checked for the effect of inhibitor removal, and lastly, we estimated the cost of reagents and consumables (not labor). The DNA recovery varied among extraction methods, with isopropanol precipitation yielding the highest recovery (52.47 ± 19.69%), followed by centrifugal dialysis (12.58 ± 7.15%) and magnetic bead extraction (9.92 ± 3.89%). However, isopropanol precipitation's efficacy was influenced by humic acid concentration in the water matrix. The presence of humic acids significantly affected isopropanol precipitation, with higher humic acid concentrations leading to increased DNA recovery. This suggests that humic acids act as co‐precipitators during isopropanol precipitation. We observed that longer DNA fragments (chicken) had lower recovery compared to shorter fragments (salmon) across all extraction methods. Magnetic bead extraction effectively removed inhibitors, while centrifugal dialysis and isopropanol extraction required an additional inhibitor removal step. Isopropanol, magnetic bead extraction, and centrifugal dialysis methods have estimated costs of 7.74, 8.53, and 23.62 USD in 2023 respectively. Overall, isopropanol precipitation was the least expensive and most effective with the highest measured recoveries, but it was dependent on humic acid concentration in the environmental sample.

Validation and comparative analysis of sodium sulphite precipitation (SSP) method for fibrinogen measurement: A practical approach for dysfibrinogenemia diagnosis

Validation and comparative analysis of sodium sulphite precipitation (SSP) method for fibrinogen measurement: A practical approach for dysfibrinogenemia diagnosis

Assessment of precipitation and near-surface temperature simulation by CMIP6 models in South America

This study evaluated the performance of 50 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the statistical features of precipitation and air temperature in five subdomains of South America during the historical period (1995–2014). Monthly precipitation and temperature simulations were validated with data from the Climate Prediction Center Merged Analysis of Precipitation, the Global Precipitation Climatology Project, and the ERA5 reanalysis. The models’ performance was evaluated using a ranking analysis with statistical metrics such as mean, standard deviation, Pearson’s spatial correlation, annual cycle amplitude, and linear trend. The analyses considered the representation of precipitation and air temperature separately for each subdomain, the representation for all five regions together, and the joint representation of precipitation and air temperature for all five subdomains. In the Brazilian Amazon, the best-performing models were EC-Earth3-Veg, INM-CM4-8, and INMCM5-0 (precipitation), and IPSL-CM6A-LR, MPI-ESM2-0, and IITM-ESM (temperature). In the La Plata Basin, KACE-1-0-G, ACCESS-CM2, and IPSL-CM6A-LR (precipitation), and GFDL-ESM4, TaiESM1, and EC-Earth3-Veg (temperature) yielded the best simulations. In Northeast Brazil, SAM0-UNICON, CESM2, and MCM-UA-1-0 (precipitation), BCC-CSM2-MR, KACE-1-0-G, and CESM2 (temperature) showed the best results. In Argentine Patagonia, the GCMs ACCESS-CM2, ACCESS-ESM1-5 and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) outperformed. Finally, for Southeast Brazil, the models ACCESS-CM2, ACCESS-ESM1-5, and EC-Earth3-Veg-LR (precipitation), and CAMS-CSM1-0, CMCC-CM2-HR4, and GFDL-ESM4 (temperature) yielded the best simulations. The joint evaluation of the regions and variables indicated that the best models are CESM2, TaiESM1, CMCC-CM2-HR4, FIO-ESM-2-0, and MRI-ESM2-0.

Application of Mann Kendal Sen's Slope Estimator in Trend Analysis of Historical And Future Precipitation and Temperature in the Kilombero River Basin

This study examines historical (1981-2020) and future (2020-2070) trends in rainfall and temperature in the Kilombero Basin using the Mann-Kendall method with Sen's slope estimator. Data were obtained from the Tanzania Meteorological Agency and from simulated historical and future climate data sourced from the Coupled Model Intercomparison Project 6 (CMIP6). The CMIP6 datasets were downscaled and bias-corrected using the CMhyd tool. The basin exhibited a bimodal rainfall pattern with an average of 1400 mm, peaking around April. The CMIP6 models successfully simulated monthly rainfall, Tmax, and Tmin at most stations. No definitive trends in rainfall were observed, but Tmax and Tmin showed significant increases under both SSP2-4.5 and SSP5-8.5 scenarios. More warming is predicted under SSP5-8.5 by the mid-21st century, raising Tmax and Tmin at all stations. This rise in temperature could potentially increase evapotranspiration demand, negatively impacting freshwater availability. The average annual rainfall showed a slightly increasing trend post-2000, from 1403.96mm/year (1981-1999) to 1433.38mm/year (2000-2020), an increase of 2.05%. Sen's slope analysis, however, revealed varying trends across stations, with most showing a decreasing trend. Notably, only Ulanga Met Station showed a significant increasing trend with a slope value of 14.70 and a p-value below 0.05. The study concluded that both temperature and precipitation in the Kilombero Basin are on the rise.

Climate change impacts on precipitation and water resources in Northwestern China

A statistical analysis is conducted on the hourly precipitation at 105 national meteorological stations in the Xinjiang region of China from 2011 to 2020. The purpose of this analysis is to determine the total quantity of precipitation during the warm and cold seasons, as well as the precipitation frequency at each station. The results of the analysis indicate that there is a more pronounced inter-annual variation in precipitation during the warm and cold seasons in Xinjiang, where the total amount of precipitation during the warm season is significantly higher than that during the cold season, with the warm season experiencing at least twice as much precipitation. In terms of the inter-annual incremental amount of precipitation, both the warm and cold seasons exhibit a trend of increasing and then decreasing over the years. However, the curvature change is more prominent in the cold season compared to the warm season, suggesting that the inter-annual variation in precipitation during the warm season remains relatively stable. The spatial distribution characteristics of the total precipitation in Xinjiang indicate that warm-season precipitation is more scattered, while cold-season precipitation is mainly concentrated in the northern region of the territory. This pattern holds true at low, medium, medium–high, and high altitudes. The cumulative precipitation during the warm season is always higher than that in the cold season, and this difference becomes more prominent with increasing altitude. This indicates that warm-season precipitation in Xinjiang is closely related to its complex topographic structure, particularly the convective weather generated by topographic clouds. On the other hand, precipitation in the cold season is mainly concentrated in the low- and medium-altitude stations, and there is not much correlation between precipitation and altitude. Precipitation is mainly affected by the mesoscale and the direct influence of large-scale weather systems. Analysis of precipitation in extreme moments reveals that during the warm season, extreme precipitation events occur mainly from the evening to early morning (19:00–03:00 the next day), accounting for 75.24% of the 105 stations. In contrast, during the cold season, extreme precipitation events occur between 03:00 and 18:00, corresponding to 74.29% of the stations. The relationship between precipitation and altitude differs in the warm and cold seasons. In the warm season, there is a linear relationship between precipitation and altitude, with a slope of 0.72 and a correlation coefficient of 0.52, indicating that precipitation increases with increasing altitude. However, in the cold season, the linear relationship between precipitation and altitude is very inconspicuous, with a slope of −0.05 and a correlation coefficient of −0.05, suggesting that there is no significant relationship between precipitation and altitude during this season. These findings provide valuable insights into the changing patterns of precipitation gradients at different altitudes and seasons in Xinjiang. This information can be used for the site selection of smokestack operations in high-altitude areas and for ground and air weather modification operations in low-altitude areas. Additionally, these data contribute to the understanding of precipitation patterns in Xinjiang, further improving the effectiveness of weather modification efforts and increasing the utilization of airborne water resources.

The tale of upper and lower bainite: A computational analysis of concurrent C-diffusion and precipitation

Carbon partitioning in bainite is a central mechanism controlling this transformation. Depending on whether C atoms form precipitates in the ferrite platelets or remain dissolved in a solid solution, the resulting microstructure is denoted as either lower or upper bainite. In the present analysis, a simulation study is conducted with long-range diffusion of C and simultaneous precipitation of carbides. The computational analysis suggests that carbides always form within the ferritic subunits before carbon redistribution into the surrounding austenite commences, independent of temperature. Since these carbides can rapidly dissolve again at higher bainite transformation temperatures, they are commonly not experimentally observed in upper bainite. At lower temperatures, carbide re-dissolution takes significantly more time, and carbides are, therefore, commonly identified, with the corresponding microstructure denoted as lower-bainite. Since carbides shall always form in the ferrite platelets, a classification of upper and lower bainite based on the existence of carbides should be reconsidered.