Precipitation Time Research Articles

Advanced precipitation peak offsets middle growing-season drought in impacting grassland C sink.

Redistribution of precipitation across seasons is a widespread phenomenon affecting dryland ecosystems globally. However, the impacts of shifting seasonal precipitation patterns on carbon (C) cycling and sequestration in dryland ecosystems remain poorly understood. In this study, we conducted a 10-yr (2013-2022) field manipulative experiment that altered the timing of growing-season precipitation peaks in a semi-arid grassland. We found that the delayed precipitation peak suppressed plant growth and thus reduced gross ecosystem productivity, ecosystem respiration, and net ecosystem productivity due to middle growing-season water stress. Surprisingly, shifting more precipitation to the early growing season can advance plant development, increase the dominance of drought-tolerant forbs, and thus compensate for the negative impacts of middle growing-season water stress on ecosystem C cycling, leading to a neutral change in grassland C sink. Our findings indicate that greater precipitation and plant development in spring could act as a crucial mechanism, maintaining plant growth and stabilizing ecosystem C sink. This underscores the urgent need to incorporate precipitation seasonality into Earth system models, which is crucial for improving projections of terrestrial C cycling and sequestration under future climate change scenarios.

Statistical Analysis of Atmospheric Delay Gradient and Rainfall Prediction in a Tropical Region

In recent years, precipitable water vapor has emerged as a key atmospheric parameter in weather prediction research. However, relying on only one parameter does not always accurately predict rainfall, as other atmospheric parameters also contribute to initiating rain events. In our previous study, we explored a methodology for rainfall forecasting based on the atmospheric delay gradient at an individual station in the tropical region. Commonly referred to as the atmospheric gradient, it accounts for the delay in GNSS signals due to changes in horizontal refractivity while propagating through the troposphere to the ground station. This paper discusses the spatial and temporal correlation of the gradient with precipitation occurring over a region. We have investigated different features, such as gradient magnitude, gradient convergence, and the flux of the atmospheric gradient, to propose potential nowcasting criteria for precipitation in the tropical climatic zone. The atmospheric gradient in the surrounding region orients toward the area of precipitation as the rain event approaches. This gradient gradually alters its orientation and converges toward the region of rainfall at the time of precipitation, introducing the concept of gradient convergence. This phenomenon results in an inward gradient flux at the time of the downpour, which presents a potential parameter for rainfall prediction over an area. We also proposed investigating area sizes of 4° × 4° or 8° × 8°, depending on the gradient feature, to establish a forecasting methodology for rainfall. The weather front in the tropical region begins to initiate 12 h before the actual time of occurrence and advances toward the area where it will have an impact from a more distant location. This article presents a detailed investigation of various features of the atmospheric gradient and its potential to nowcast rainfall for a region, as well as proposes the lead time for long-term weather predictions. Furthermore, a deep neural network has been employed to predict rainfall events for the next 6 h over an area in the tropical region.

Impact‐Based Skill Evaluation of Seasonal Precipitation Forecasts

AbstractWe introduce an impact‐based framework to evaluate seasonal forecast model skill in capturing extreme weather and climate events over regions prone to natural disasters such as floods and wildfires. Forecasting hydroclimatic extremes holds significant importance in an era of increasing hazards such as wildfires, floods, and droughts. We evaluate the performance of five Copernicus Climate Change Service (C3S) seasonal forecast models (CMCC, DWD, ECCC, UK‐Met, and Météo‐France) in predicting extreme precipitation events from 1993 to 2016 using 14 indices reflecting timing and intensity (using absolute and locally defined thresholds) of precipitation at a seasonal timescale. Performance metrics, including Percent Bias, Kendall Tau Rank Correlation Score, and models' discrimination capacity, are used for skill evaluation. Our findings indicate that the performance of models varies markedly across regions and seasons. While models generally show good skill in the tropical regions, their skill in extra‐tropical regions is markedly lower. Elevated precipitation thresholds (i.e., higher intensity indices) correlate with heightened model biases, indicating deficiencies in modeling severe precipitation events. Our analysis using an impact‐based framework highlights the superior predictive capabilities of the UK‐Met and Météo‐France models in capturing the underlying processes that drive precipitation events, or lack thereof, across many regions and seasons. Other models exhibit strong performance in specific regions and/or seasons, but not globally. These results advance our understanding of an impact‐based framework in capturing a broad spectrum of extreme weather and climatic events, and inform strategic amalgamation of diverse models across different regions and seasons, thereby offering valuable insights for disaster management and risk analysis.

Numerical simulation of circulation characteristics of orographic precipitation in Qilian Mountains, Northeastern Tibetan Plateau

In order to clarify the synoptic meteorology and low-level circulation characteristics of orographic precipitation in northeastern Tibetan Plateau (referred as TP), numerical simulation of a precipitation case that happened in Qilian Mountains on August 12–13, 2019 was conducted using the Weather Research and Forecasting (WRF) model in this paper. The results show that WRF model can roughly capture the timing and location of the orographic precipitation. During the period, a weak trough and a weak ridge were found behind a large-scale trough at 500 hPa at the initial and continuation phases primarily due to the effect of complicated topography to provide a beneficial circulation background at high altitudes. The extinction of this circulation pattern and northwesterly after the large-scale trough leaded to the extinction of the precipitation.In lower levels, warm advection from the south and cold advection from the north met over the precipitation region, resulting to a dividing temperature line tilting northeast from surface to high-altitude, which was crucial for instability and humidity, although no significant converging wind field near the surface suffering from the complex topography. In addition, the low-level jet, downslope flow and heating role at the basin bottom were also found to play important roles in the precipitation. The above analysis indicates that the precipitation was a result under the combined influence of the westerly circulation and the plateau monsoon circulation.

Removal of Germanium from a Solution by a Magnetic Iron-Based Precipitant.

This study presents a method for the precipitation of germanium from a solution using magnetic iron-based precipitants and contrasts this method with the commonly employed neutralization-precipitation technique in industrial production, analyzing and comparing their reaction conditions and the properties of their precipitates. This study analyzes the influence of varying experimental conditions (reaction time, reaction temperature, iron:germanium molar ratio, Fe3+:Fe2+ molar ratio, and reaction pH) on the germanium precipitation efficiency. With a precipitation time of 30 min, a precipitation temperature of 30 °C, an iron:germanium molar ratio of 30:1, an Fe3+:Fe2+ molar ratio of 3:1, and a reaction pH of 5.0, the optimal germanium precipitation efficiency achieved was 99.5%. Furthermore, this study employed X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, transmission electron microscopy, and vibrating sample magnetometry to analyze the properties and composition of the precipitate, providing support for the conclusion regarding germanium precipitation using magnetic iron-based precipitants. Through theoretical analysis and instrumental testing, it was determined that the precipitation of germanium from a solution using magnetic iron-based precipitants significantly reduces the reaction time compared to those of neutralization-precipitation methods. Moreover, a magnetic iron-based precipitant substantially reduces the amount of precipitate, allows for magnetic separation of the precipitate, and effectively alleviates the problem of the presence of other valuable metals in the precipitate.

Investigating the Limitations of Multi‐Model Ensembling of Climate Model Outputs in Capturing Climate Extremes

ABSTRACTIn the context of climate change, the widespread practice of directly employing Multi‐Model Ensembles (MMEs) for projecting future climate extremes, without prior evaluation of MME performance in historical periods, remains underexplored. This research addresses this gap through a comprehensive analysis of ensemble means derived from CMIP6‐based models, including both simple and weighted averages of precipitation (SEMP and WEMP) and temperature (SEMT and WEMT) time series, as well as simple (SEME) and weighted (WEME) averages of extremes based on model‐by‐model analysis. The study evaluates the efficacy of MMEs in capturing mean annual values of ETCCDI indices over India for the period 1951–2014, utilising the IMD gridded data set as a reference. The results reveal that SEME and WEME consistently align closely with IMD data across various precipitation indices. At the same time, SEMP and WEMP consistently display underestimation biases ranging from 20% to 80% across all precipitation indices, except for CWD, where there is an overestimation bias. Moreover, SEMP and WEMP consistently underestimate CDD and overestimate CWD, indicating a systematic bias in these ensemble means, while WEME and SEME demonstrate satisfactory performance. SEMT and WEMT exhibit notable underestimation in temperature indices. In summary, adopting SEME and SEMT leads to a more robust assessment of precipitation and temperature extremes, respectively. These findings highlight the limitations of traditional MME methodologies in reproducing observed extreme precipitation events across various climatic zones in India, offering essential insights for refining climate models and improving the reliability of climate projections specific to the Indian subcontinent.

Coupled evolution of basin structure and fluids recorded by microfractures: A case study of deep-buried ordovician in the tarim basin

The fluid activity in the deep strata of sedimentary basins is commonly related to tectonic activity, and the cements filled in fractures are a good carrier for the tectonic-fluid coupling evolution. Compared to macrofractures, microfractures have characteristics of high frequency and easy identifiable periods. Abundant microfractures infilled by carbonate cements (MCCFs) developed in carbonates of the Ordovician Yingshan and Yijianfang formations in the platform basin area of the Tarim Basin. Based on the study of petrology, U-Pb dating, and geochemical characteristics, this study determined the stages of MCCFs and clarified the tectonic-fluid coupling evolution process recorded by MCCFs in the study area. The formation order of these MCCFs is D1, C1, C2, D2, C3, and C4. The precipitation times of MCCFs have a good correspondence with orogeny around the Tarim Basin and active times of strike-slip faults in the platform basin area. The six stages of MCCFs in the Ordovician Yingshan and Yijianfang formations in the SLU recorded the tectonic-fluid coupling evolution process of concentrated seawater in the late Middle Ordovician, meteoric water at late Ordovician, organic acids during the Silurian, Mg-rich hot brine at the end Devonian-early Carboniferous, and magmatic hydrothermal fluids during the Permian. This not only indicates a close connection between fluid activity and tectonic activity in sedimentary basins, but also confirms that the formation of MCCFs in carbonate formations is closely related to regional tectonic-fluid coupling activities. This study provides a good example for studying macro scale tectonic-fluid coupling activities in basins using microfractures.

Investigating a Century of Rainfall: The Impact of Elevation on Precipitation Changes (Northern Tuscany, Italy)

Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small areas, precipitation shows the coexistence of positive and negative trends. Local topography seems to be a strong driver of precipitation changes. Understanding precipitation changes and their relationship with local topography is crucial for society’s resilience. Taking advantage of a dense and long-lasting (1920–2019) meteorological monitoring network, we analyzed the precipitation changes over the last century in a sensitive and strategic area in the Mediterranean hotspot. The study area corresponds to northern Tuscany (Italy), where its topography comprises mountain ridges and coastal and river plains. Forty-eight rain gauges were selected with continuous annual precipitation time series. These were analyzed for trends and differences in mean annual precipitation between the stable period of 1921–1970 and the last 30-year 1990–2019. The relationship between precipitation changes and local topography was also examined. The results show the following highlights: (i) A general decrease in precipitation was found through the century, even if variability is marked. (ii) The mountain ridges show the largest decrease in mean annual precipitation. (iii) The precipitation change entity over the last century was not homogenous and was dependent on topography and geographical setting. (iv) A decrease in annual precipitation of up to 400 mm was found for the mountainous sites.

Effect of hot-wire method on microstructure and mechanical properties of wire arc additive repaired superalloy

This study shows that the hot wire is an effective way to reduce the amount of undesirable Laves phase during the repair of 718Plus components, which are detrimental to the mechanical properties. The complex relationship between microstructure and hotwire was studied in detail. Five damaged components were repaired by depositing the melted 718Plus wire onto the wrought substrate using directed energy deposition-arc (DED-arc). A finite element model was used to provide clues for the thermal process analysis. The hot-wire method enhanced the cooling rate of the molten pool and suppressed the remelting behaviour of secondary dendritic arms (SDA) in the reheated zone. The resultant microstructure contained refined dendrites with more obvious SDA, which allows the production of tiny reticular Nb-rich liquid spots between dendrites during final solidification stage. These spots beyond a threshold of Nb could cause eutectic reaction, leading to the morphologic transformation from long-stripped to granular Laves phase and a lower volume fraction. Moreover, the hot-wire method hindered the dynamic precipitation of γ' phase due to the shortened precipitation time, which was responsible for the inferior mechanical properties. The heat-treatment re-optimized the precipitation of γ' phase and further dissolved Laves phase to release more Nb for γ' phase, which leads to the improvement of strength about 10 %.

Model sensitivity in predicting extreme precipitation events in urban areas: A case study over Beijing

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21–22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets.Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.

Inertia of Ionospheric Conductance During Electron Precipitation Events

AbstractUsing the SuperThermal Electron Transport (STET) model coupled with the Super‐thermal Proton Electron Atomic Hydrogen—tRansport in the Ionosphere and Thermosphere (SPEAH‐RIT) codes, we demonstrate that temporal variability of ionospheric conductance is defined by several time scales: the temporal variations of the magnetospheric source, the start time of electron precipitation, and the termination of the corresponding source. In these cases, the time scales are defined by dissipation of energetic electrons and effective recombination processes. The results presented in this paper were applied in the regions of pulsating aurora and polar arcs, demonstrating the fact that ionospheric conductance requires some time to form and decay. These time delays constitute an effective “inertia” in the conductance calculation which is not accounted for in many global models which assume an instantaneous connection between precipitation and conductance. Ionospheric conductance inertia influences the temporal variation in ionospheric and magnetospheric electric fields, and as a result, impacts magnetosphere‐ionosphere (MI) dynamics on a global scale.

Underlying mechanisms for the effect of Nb micro-alloying on the elemental distribution and precipitation behavior in the X70 weld metal

Niobium (Nb) is a widely recognized micro-alloying element due to its low cost and substantial impact on steel properties. While the effect of Nb in processed steels has been well investigated, studies on its elemental distribution and precipitation behavior in weld metal remain scarce. This study focuses on the weld metal of specially designed Nb-rich X70 pipeline steel by scanning transmission electron microscopy (STEM) and energy-dispersive X-ray spectroscopy (EDS) characterization, complemented with thermodynamic and kinetics modeling analysis. In the majority of the weld, Nb was essentially uniformly distributed. This suggests that Nb primarily exists in the solid solution form in the weld metal, which is also supported by precipitation kinetics modeling results. This is primarily due to the short thermal history associated with the welding process, which leads to insufficient time for the uniform precipitation of Nb. Two instances of Nb precipitates were observed at the weld centerline and reinforcement region. The low partition coefficient of Nb results in an elevated local concentration along the weld centerline. However, precipitation kinetics calculations suggest that this enhancement alone is not adequate to induce precipitate formation. The occurrence of MnS and the prior formation of Ti precipitates may provide heterogeneous nucleation sites for Nb, facilitating the nucleation of Nb precipitates in the weld centerline and reinforcement region.

Germination responses to changing rainfall timing reveal potential climate vulnerability in a clade of wildflowers.

The seasonal timing of life history transitions is often critical to fitness, and many organisms rely upon environmental cues to match life cycle events with favorable conditions. In plants, the timing of seed germination is mediated by seasonal cues such as rainfall and temperature. Variation in cue responses among species can reflect evolutionary processes and adaptation to local climate and can affect vulnerability to changing conditions. Indeed, climate change is altering the timing of precipitation, and germination responses to such change can have consequences for individual fitness, population dynamics, and species distributions. Here, we assessed responses to the seasonal timing of germination-triggering rains for eleven species spanning the Streptanthus/Caulanthus clade (Brassicaceae). To do so, we experimentally manipulated the onset date of rainfall events, measured effects on germination fraction, and evaluated whether responses were constrained by evolutionary relationships across the phylogeny. We then explored the possible consequences of these responses to contemporary shifts in precipitation timing. Germination fractions decreased with later onset of rains and cooler temperatures for all but three Caulanthus species. Species' germination responses to the timing of rainfall and seasonal temperatures were phylogenetically constrained, with Caulanthus species appearing less responsive. Further, four species are likely already experiencing significant decreases in germination fractions with observed climate change, which has shifted the timing of rainfall towards the cooler, winter months in California. Overall, our findings emphasize the sensitivity of germination to seasonal conditions, underscore the importance of interacting environmental cues, and highlight vulnerability to shifting precipitation patterns with climate change, particularly in more northern, mesic species.

Spring precipitation amount and timing predict restoration success in a semi‐arid ecosystem

Spring precipitation amount and timing predict restoration success in a semi‐arid ecosystem

Study on the evolution of multistage and multiscale Ti-bearing precipitation and microstructure in ultrahigh-strength titanium microalloyed weathering steels

In this study, 900 MPa ultrahigh-strength weathering steels were successfully developed through thermomechanical controlled processing (TMCP). Advanced microstructure characterization, combined with precipitation thermodynamics and kinetics models, elucidated the evolution of Ti-bearing precipitation and microstructure. The results showed that coiling temperature (CT) significantly impacts phase fractions, grain boundary density, and misorientation angles, while both CT and finishing rolling temperature (FRT) influence grain sizes in acicular ferrite (AF) and granular bainite. The lower coiling temperature resulted in a higher dislocation density of the test steel, which provided more nucleation sites for AF and TiC, favoring a higher number of TiC particles and a higher proportion of AF. Above 1050 °C, the addition of nitrogen changed the shape of the precipitation kinetics curve, reduced the nucleation energy barrier of TiC, decreased the critical nucleation size, and improved the nucleation rate. Meanwhile, the addition of nitrogen accelerated the precipitation transformation of TiC, which promoted the formation of Ti(C, N). Furthermore, increasing the deformation stored energy (DSE) further accelerated the precipitation of Ti(C, N) and significantly increased the nucleation rate. The formation mechanism of large-size Ti(C, N) and the transformation mechanism of Ti(C, N) to TiC are revealed by precipitation thermodynamics and kinetics. The completion time of TiC precipitation on dislocations is shorter than that on grain boundaries, which results in the TiC on dislocations being prone to coarsening during prolonged coiling. These findings provide crucial insights for optimizing the industrial production of ultrahigh-strength titanium microalloyed weathering steels.

Generating hourly mean areal precipitation times series with an at-site weather generator in Switzerland

Generating hourly mean areal precipitation times series with an at-site weather generator in Switzerland

Optimization and modeling of process parameters for nutrient recovery from sewage wastewater

ABSTRACT Nitrogen (N) and phosphorus (P) contamination in wastewater pose significant environmental challenges. Recovering these elements as struvite not only mitigates environmental pollution but also aligns with sustainable development goals by recycling valuable resources. This research hypothesizes that optimized recovery methods can enhance the efficiency and effectiveness of struvite crystallization, addressing existing challenges in conventional techniques. To achieve optimal removal and recovery of N and P from sewage, a response surface model was employed. This model allowed for the identification of optimal process conditions and the elucidation of interactions among various components. Key variables impacting struvite recovery were identified using the Plackett–Burman design, while the central composite design was used for further optimization. The study determined the optimized parameters for phosphate recovery to be an Mg:P ratio of 1:2, pH of 10.5, additive concentration of 350 ppm, and a precipitation time of 30 min. Thermogravimetric analysis indicated that the residual amounts were below 50%. Additionally, the size and surface morphology of the final product were influenced by the process parameters, particularly the Mg:P ratio and pH. An inexpensive, quick, and efficient method to recover struvite fertilizer with a minimum demand of time and chemicals is established toward SDG 2 and 6.

Deep Neural Networks for Predicting the Settlement of Earth Dams Based on the InSAR Outputs

Earth dams play a crucial role in water resource management, necessitating effective maintenance to ensure prolonged functionality and safety. Monitoring these dams traditionally involves methods such as surveying and instrumentation. However, challenges arise from equipment malfunctions and absences, especially in dams affected by environmental changes. In response to these challenges, the cost-effective and adaptable nature of Interferometric Synthetic Aperture Radar (InSAR) has made it a preferred choice for monitoring. Despite their advantages, traditional numerical models like finite element methods have limitations in predicting deformation comprehensively, particularly due to intricate, non-linear correlations involving material type and environmental conditions. To overcome these limitations, this research employs deep learning techniques, specifically Long Short-Term Memory (LSTM) network, to capture intricate relationships and accurately predict dam behavior. Time series data from InSAR, representing settlement, are decomposed into trend and seasonal components using Artificial Neural Networks (ANN) for trend prediction. Furthermore, an LSTM network is utilized to handle the complexity of the seasonal component and its correlation with environmental factors. This network incorporates settlement, precipitation, temperature, and reservoir water level time series as inputs, thereby enhancing prediction accuracy. The research outcome presents a robust solution that holds the promise of increased accuracy and efficiency in predicting, monitoring, and serving as an early warning system for earth dam deformations over time. Such advancements are crucial for ensuring the safety and integrity of critical infrastructure in the face of evolving environmental conditions.

Responses of plant biomass allocation to changed precipitation timing in a semi-arid steppe

Responses of plant biomass allocation to changed precipitation timing in a semi-arid steppe

Rainfall Trend Analysis in Mysuru and Bengaluru Districts of Karnataka, India

Climate change is one of the most pressing challenges facing humanity today, with temperature, precipitation, and runoff being key indicators closely linked to its impact. Understanding the spatial variability and temporal trends of rainfall is crucial for effective water resource management and agriculture. This study focuses on analyzing rainfall data from the Mysuru and Bengaluru districts, located in the Southern and Eastern dry zones of Karnataka, respectively. These regions play a pivotal role in the state's agricultural development and overall economic growth. We utilized daily precipitation records from two meteorological stations, spanning the period from 1983 to 2018, to analyze rainfall trends on monthly, seasonal, and annual scales. To assess these trends, we applied both parametric and non-parametric statistical methods, including the simple regression method, Mann-Kendall test, and Sen’s slope estimator. The Mann-Kendall test was used to detect significant trends in the precipitation time series, while Sen’s slope estimator quantified the magnitude of these trends. Bengaluru had higher average annual rainfall (928.81 mm) compared to Mysuru (681.65 mm), with excess rainfall in 2005 and a positive Pre-Monsoon trend (+3.543 mm/year), while Mysuru experienced maximum rainfall deficit in 2016 and a negative Monsoon trend (-3.238 mm/year). Neither district showed a significant trend in annual rainfall. The findings of this trend analysis are essential for informed water resource planning and management in the region.