Precipitation Time Research Articles

Trend analysis and change point detection in precipitation time series over the Eastern Province of Rwanda during 1981–2021

This study examines trends and change points in agroclimatic variables at 56 meteorological stations’ locations and region levels in Rwanda’s Eastern Province from 1981 to 2021. We used the Mann–Kendall and Regional Kendall tests, along with Sen’s Slope and Sequential Mann–Kendall Rank Statistic tests, to analyse six key agricultural indicators: seasonal rainfall totals, number of rainy days, rainfall intensity (light, moderate, heavy), onset and cessation dates, and season duration. In the March to May (MAM) season, 39 out of 56 stations recorded a decreasing rainfall trend, with significant trends observed at eight stations in the south. Conversely, 17 stations showed increasing trends, with only one in the north being significant. Regionally, the trend was a non-significant decrease. In the September to December (SOND) season, 31 stations (one significant) experienced decreasing rainfall trends. Among the 25 stations showing increasing trends, only one was significant. The regional trend indicates a non-significant increase. Onset days showed a decreasing trend at 41 stations (12 significant) in both MAM and SOND and a significant regional trend in SOND. Season duration increased at 43 stations in MAM (five significant) and 48 stations in SOND (six significant), with the regional trend being significant only in SOND. Heavy rainy days indicate a significantly regional decreasing trend in MAM. The change point of most stations with decreasing and increasing trends occurred between 2000–2020 and 1980–2000, respectively. These fluctuations have affected agricultural practices and led to crop failures, emphasizing the region’s need for better climate information services and adaptation strategies.

Increasing Soil Water Drought in Response to Altered Precipitation Timing Across the Western United States

Increasing Soil Water Drought in Response to Altered Precipitation Timing Across the Western United States

In vivo pharmacokinetic study and PBPK modeling: Comparison between 3D-printed nanocrystals and solid dispersions.

The solubility of drugs remains one of the most challenging aspects of formulation development. Several technologies exist to enhance the properties of poorly soluble drugs, with nanocrystal (NC) and solid dispersion (SD) technologies being among the most important. This work compared NCs and SDs under identical conditions using albendazole as a model drug and 3D printing technology as the delivery method. SDs were initially prepared and characterized, and then compared to the NCs system. Techniques such as TGA, DSC, XRD, FTIR, SEM, and Raman spectroscopy were employed to assess the solid-state properties and formulation homogeneity. Solubility and dissolution profiles were evaluated under simulated gastric and intestinal conditions. An in vivo pharmacokinetic study in dogs compared 3D-printed formulations (NC-3D and SD-3D) with a control group treated with the pure drug (ABZ-C) was carry out. A PBPK model was developed also in dogs to further analyse the results. While no statistically significant differences were observed in the in vitro dissolution profiles in 0.1 N HCl, differences emerged in precipitation time and solubility at intestinal pH (6.8). The pharmacokinetic study revealed improvements in the pharmacokinetic profile of both systems compared to the control, as expected. Between the NCs and the SD, the NC system demonstrated significantly superior pharmacokinetic parameters of interest. The PBPK model helped explain the differences observed in the in vivo study. The results suggest that nanocrystal technology is more effective at enhancing the in vivo performance of Class II drugs, at least when using albendazole as the model drug.

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.

A comparative analysis of rainfall data from IMERG early run and ground-based rain gauges on Bali Island

Abstract Ground-based precipitation measurements encounter challenges in various parts of Bali due to the limited number of gauge stations. Therefore, it is essential to identify dependable alternatives like satellite-derived precipitation data, which offer continuous precipitation time series with high spatial resolution. This study assessed the effectiveness of near real-time global satellite precipitation products, specifically the Integrated Multi-satellite Retrievals for Global Precipitation Measurement-Early Run (IMERG-E) compared to gauge data from 43 stations across Bali Province. To evaluate IMERG-E datasets, traditional point-to-pixel comparison techniques were employed, alongside statistical metrics including correlation coefficient (CC), mean absolute error (MAE), relative bias (RB), and Nash-Sutcliffe efficiency (NSE). The comparative analysis showed that the daily IMERG-E dataset performs moderately well, as evidenced by weak to moderate correlation and low MAE. IMERG-E showed evidence of underestimating rainfall, as indicated by the RB value. Conversely, IMERG-E demonstrates poor accuracy according to the NSE value. It is necessary to explore effective correction methods for IMERGE-E to establish it as a viable alternative data source.

Concordant Signal of Genetic Variation Across Marker Densities in the Desert Annual Chylismia brevipes Is Linked With Timing of Winter Precipitation.

Climate change coupled with large-scale surface disturbances necessitate active restoration strategies to promote resilient and genetically diverse native plant communities. However, scarcity of native plant materials hinders restoration efforts, leading practitioners to choose from potentially viable but nonlocal seed sources. Genome scans for genetic variation linked with selective environmental gradients have become a useful tool in such efforts, allowing rapid delineation of seed transfer zones along with predictions of genomic vulnerability to climate change. When properly applied, genome scans can reduce the risk of maladaptation due to mismatches between seed source and planting site. However, results are rarely replicated among complimentary data sources. Here, we compared RAD-seq datasets with 819 and 2699 SNPs (in 625 and 356 individuals, respectively) from the Mojave Desert winter annual Chylismia brevipes. Overall, we found that the datasets consistently characterized both neutral population structure and genetic-environmental associations. Ancestry analyses indicated consistent spatial genetic structuring into four regional populations. We also detected a marked signal of isolation by resistance (IBR), wherein spatial genetic structure was better explained by habitat resistance than by geographic distance. Potentially adaptive loci identified from genome scans were associated with the same environmental gradients-fall precipitation, winter minimum temperature, and precipitation timing-regardless of dataset. Paired with our finding that habitat resistance best explained genetic divergence, our results suggest that isolation of populations within environmentally similar habitats-and subsequent local adaption along gradients parallel to these habitats-drive genome-wide divergence in this species. Moreover, strong genetic associations with winter precipitation timing, along with forecasted shifts in precipitation regime due to midcentury climate change, could impact future population dynamics, habitat distribution, and genetic connectivity for C. brevipes populations within the Mojave Desert.

Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana

HighlightsTemperature and precipitation time series data from 1950 to 2020 were analyzed for the states of Haryana and Punjab.SARIMA models provided the most accurate temperature predictions for both states, though precipitation predictions in July were sometimes overestimated.SARIMA provided better results than machine learning-based models, with lower RMSE, AIC, and BIC values.Model forecasts can improve flood prediction, urban planning, and water resource management, benefiting scientists and decision-makers.

Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature

Abstract. Emulators of Earth system models (ESMs) are statistical models that approximate selected outputs of ESMs. Owing to their runtime efficiency, emulators are especially useful when large amounts of data are required, for example, for in-depth exploration of the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. This paper introduces an emulation framework that allows us to emulate gridded monthly mean precipitation fields using gridded monthly mean temperature fields as forcing. The emulator is designed as an extension of the Modular Earth System Model Emulator (MESMER) framework, and its core relies on the concepts of generalised linear models (GLMs). Precipitation at each (land) grid point and for each month is approximated as a multiplicative model with two factors. The first factor entails the temperature-driven precipitation response and is assumed to follow a gamma distribution with a logarithmic link function. The second factor is the residual variability in the precipitation field, which is assumed to be independent of temperature but may still possess spatial precipitation correlations. Therefore, the monthly residual field is decomposed into independent principal components and subsequently approximated and sampled using a kernel density estimation with a Gaussian kernel. The emulation framework is tested and validated using 24 ESMs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). For each ESM, we train on a single-ensemble member across scenarios and evaluate the emulator performance using simulations with historical and Shared Socioeconomic Pathways (SSP5-8.5) forcing. We show that the framework captures grid-point-specific precipitation characteristics, such as variability, trend, and temporal auto-correlations. In addition, we find that emulated spatial (cross-variable) characteristics are consistent with those of ESMs. The framework is also able to capture compound hot–dry and cold–wet extremes, although it systematically underestimates their occurrence probabilities. The emulation of spatially explicit coherent monthly temperature and precipitation time series is a major step towards a computationally efficient representation of impact-relevant variables of the climate system.

Development of Operando Spectroscopy Measurement Technique Under Electrochemical Reactions

ObjectiveTo improve the performance of lithium-ion batteries, a precise understanding of the reactions occurring at the single-particle into the active material is important, as it directly influences the redox processes at the electrode. Currently, single-particle electrochemical measurement methods (SPEMs: direct terminal contact method) using micro current collector have been reported as a method for understanding the electrochemical properties of active materials. However, most reports focus on electrical characteristics, such as constant current charge/discharge tests and AC impedance measurements1)2). On the other hand, for further characterization of single active material particles, it is expected that the structural changes associated with charge-discharge reactions can be elucidated through Operando spectroscopy. However, constructing an experimental system is difficult owing to their interference between the probe and incident radiation in the direct terminal contact methods. In this study, we have developed an Operando Raman spectroscopy technique (tweezers method), which enables spectroscopic measurement of single electrode active material particles while they perform electrochemical reactions. This method involves grasping particles with tweezers, allowing for examination of the reactions occurring at the active material/electrolyte interface during electrochemical processes.ExperimentIn this study, a micromanipulator, an electrochemical measuring device, and a Raman spectrometer were assembled in a dry box (dew point less than -76.0 degrees Celsius) as shown in Fig. 1, to conduct measurements. The structural changes in the electrolyte in the diffusion layer in the electrolyte, Operando Raman spectroscopic measurements were performed. Raman spectrometer consists of a laser wavelength of 532 cm-1, a grating of 2400 gr/mm, a measurement wavenumber range of 400 to 1600 cm-1, a laser diameter of φ 1 μm, and a resolution of 4.77 cm-1.Two types of Operando Raman measurement were conducted as shown in Fig.2. In both cases, 1.0 mol / kg EC-LiFSA was used as the electrolyte, anda Cu probe of φ 30 μm was used. First, the Raman spectroscopic measurement position was fixed, and potential scanning was performed to investigate the reaction of Li desolvation at the time of Li precipitation and the Li solvation reaction during the electrochemical reaction of Li. The experiment was conducted by fixing it at a position 3.77 μm away from the electrode surface. The conditions for cyclic voltammetry measurements were set at a scan rate of 0.1 mV/s, with the measured potential ranging from 3.2V to -0.1V. Second, the electrode potential was fixed at -25 mV, and the distance from the electrode surface was changed and measured every 25 μm to 175 μm from the surface of Cu probe.Result & DiscussionFig. 3 shows the Raman spectrum near the Cu electrode. The peaks in the Raman spectrum from 885 to 900cm-1 and 900 to 912 cm-1 were attributed to free EC and Li+-bound EC. Calculated each peak area ratios are shown in Fig.4. The rate remained constant from the initial condition to -50mV. However, the ratio of free EC increased in the -50mV to -100mV. The increase in this ratio is attributed to the desolvation of Li+ coordinated with EC accompanying the precipitation of Li. Furthermore, during the dissolution of Li, dissolved Li+ at the electrode surface rapidly coordinated with free EC, leading to a transient increase in Li+-bound EC and causing an increase in the ratio. Fig.5 shows the Raman spectra at various distances from the electrode surface under potentiostatic conditions. Up to 25 μm from the electrode surface, Li+-bound EC was locally predominated. The locally highly ratio of Li+-bound EC at the electrode surface is attributed to the reaction of precipitating Li from solvated Li+. Due to the localized increase in Li+-bound EC at the electrode surface, free EC were predominated from 25 μm to 100 μm away from the electrode surface. Moreover, a decrease in free EC was observed from 100 μm to 125 μm away from the electrode surface. The end of the diffusion layer is located at this distance. In this presentation, we will discuss about the end of the diffusion layer in detail and the differences between the diffusion layers of the plate electrode and microelectrode.1) K. Dokko et.al., J. Electrochem. Soc., 148 , A422-A426 (2001).2)T. Saito et.al., J. Phys. Chem. C, 124, 16758-16762 (2020).3) R. Furui et al., J. Phys. Chem. C, 127, 10748−10756 (2023). Figure 1

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.

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.

Tracing a Mantle Component in Both Paleo and Modern Fluids Along Seismogenic Faults of Southern Italy

AbstractAiming at understanding the source of the fluids that mineralizing within seismically active fault zones, we investigate the noble gas isotopes (i.e., helium (He), neon (Ne), and argon (Ar)) in the fluid inclusions (FIs) trapped in the calcite veins sampled along high‐angle fault zones of the Contursi hydrothermal basin, southern Italy. The latter basin lies in close vicinity of the MW = 6.9, 1980 Irpinia earthquake and exposes numerous fault scarps dissecting Mesozoic shallow‐water carbonates. The analyses of noble gases (He, Ne, Ar) are conducted to identify the origin of the volatiles circulating along the faults at the time of calcite precipitation. Then, outcomes of this discussions are compared with currently outgassing of deep‐sourced CO2 coupled to mantle‐derived He in that area, whose output is larger than those from some volcanic areas worldwide. The results indicate that He in FIs is dominated by a crustal radiogenic component (4He), and by an up to 20% of a mantle‐derived component (3He), with a highest isotopic signature of 1.38 Ra. This value is consistent with the highest percentage of mantle‐derived He associated to high‐flux CO2 gas emission in the investigated area (1.41 Ra). We propose that the variability of the He isotopic signature measured in primary FIs can result from early trapping of fluid inclusions or post trapping processes and seismic activity that modify the pristine He isotopic signature (i.e., derived from the crust and/or mantle) in groundwater along the faults during periods of background seismicity. Such investigations are fundamental to understand fluid migration in fault systems and the role of fluids in processes of earthquake nucleation.

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.

Application research of wind profile radar in short-term heavy rainfall forecast of typhoon in Fujian Province

Based on wind profile radar data, this paper aims at different typhoon processes landed and affected Fujian from 2011 to 2019, according to the nature of typhoon rainstorm, it can be classified into outer precipitation before typhoon landed, main body precipitation and precipitation at the rear of typhoon, the change of the characteristic quantities in approaching time of the occurrence of short-term heavy rainfall was analyzed, and the typhoon case in 2020 was back calculated. The results show that, the characteristics of low-level jet streams (maximum wind speed at low altitude, minimum height of jet streams, and low-level jet stream index), as well as the magnitude of vertical wind shear below 700 hPa, have important indicative significance for the occurrence of short-term heavy rainfall. (1) More than 80 % of short-term heavy rainfall occurred 3 h before the low-level jet stream already existed. The maximum wind speed below 2 km was basically close to a normal distribution, and the occurrence of heavy precipitation showed a bimodal pattern. The percentage of wind speed between 8 and 32 m/s was the highest, exceeding 85 %. The wind direction of the strong wind is mainly NE, SE, and SW. Classification analysis showed that the distribution characteristics of wind speed of the main precipitation were the same as before, but the wind direction SE was higher than NE. The wind speed of pre-landfall precipitation was basically skewed, and the occurrence time of heavy precipitation followed a normal distribution. The percentage of wind speed between 16 and 32 m/s was the highest, and the wind direction was the same as before classification. The maximum wind speed of precipitation in the rear was basically bimodal distribution, with a relatively even distribution, and the wind direction was mainly SE and SW. (2) In the 3 h before the occurrence of short-term heavy precipitation, there was an increase in the maximum wind speed value, a decrease in the minimum extension height, and an increase in the low-level jet stream index I. As short-term heavy rainfall approached, the intensity of the low-level jet stream remained high and its proportion increased. The minimum achievable extension height gradually decreased and remained stable at a low value. In the first 2 h of heavy rainfall, the wind speed reached its maximum, the extension height was the lowest, and the low-level jet stream index I was the highest. Classifying and discussing it, the precipitation in the rear was different, and the lowest height decreased to the lowest at the time of occurrence, at which point the I value reached its maximum. The characteristics of the other two categories were the same as before the classification. (3) The vertical wind shear from the ground to different isobaric surfaces gradually decreased with the increase of height. With the approach of short-term heavy rainfall, the vertical wind shear of each layer basically decreased gradually, after the beginning of heavy rainfall, which decreased to the minimum. The characteristics of main body precipitation were the same as before the classification. Pre-landfall precipitation, in addition to the gradual decrease of vertical wind shear from the ground to 925 hPa, both 850 hPa and 700 hPa increased first and then decreased, vertical wind shear decreased to the minimum after the beginning of heavy rainfall. Precipitation at rear of typhoon, vertical wind shear from ground to 700 hPa increased compared with that before the occurrence of heavy rainfall, while wind shear from ground to 925 hPa and 850 hPa showed the characteristics of decreasing when heavy rainfall occurred. (4)The median values of various physical quantities before the occurrence of typhoon short-term heavy rainfall were selected as the thresholds of short-term heavy rainfall will occur. The intensity of LLJ is about 21 m/s, the lowest height is about 0.65 km, the LLJ index I is about 36 × 10−3s−1. Vertical wind shear from the ground to 925 hPa, 850 hPa and 700 hPa are respectively about 15.9 × 10−3s−1, 11.2 × 10−3s−1 and 5.1 × 10−3s−1.

The Role of Atmospheric Rivers Moisture Origin in the Seasonality of Extreme Precipitation in the Eastern United States

Abstract Regional patterns of the seasonal weather and atmospheric moisture origins can impact the seasonal activities of extreme precipitation in the eastern United States (eUS). At many locations, tracks of atmospheric moisture can have different influence on timing of extreme precipitation based on the moisture origin source. In this study, we evaluate the contribution of atmospheric rivers (ARs) and their moisture origin sources to the distribution and seasonal effectivity of annual maximum precipitation (AMP) across the eUS during 1950–2021. Our results suggest that AR is a dominant mechanism of AMP in the eUS as it contributes to 75% (31 438 out of 41 976) of total AMP events recorded between 1950 and 2021. The seasonal analysis based on the circular density approach shows that spring, summer, and fall seasons display strong signals of seasonality of AMP-AR events. The spatial patterns of AMP associated with the four major moisture sources (the Pacific Ocean, the Atlantic Ocean, the combined source of the Caribbean Sea and the Gulf of Mexico, and the local source of moisture) reinforce the key role ARs play in transporting water vapor to the eUS from both oceanic and inland originated moisture. The results additionally highlight the importance of moisture subsources (major source subregions) in modulating the seasonality of extreme precipitation in the eUS.

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.

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.

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.