Precipitation Type Research Articles

Toward the Development of an Impact-Based Decision Support Tool for Surface-Transportation Hazards. Part I: Tying Weather Variables to Road Hazards and Quantifying Impacts

Abstract Development of an impact-based decision support forecasting tool for surface-transportation hazards requires consideration for what impacts the product is intended to capture and how to scale forecast information to impacts to then categorize impact severity. In this first part of the series, we discuss the motivation and intent of such a product, in addition to outlining the approach we take to leverage existing and new research to develop the product. Traffic disruptions (e.g., crashes, increased travel times, roadway restrictions, or closures) are the intended impacts, where impact severity levels are intended to scale to reflect the increasing severity of adverse driving conditions that can correlate with a need for enhanced mitigation efforts by motorists and/or transportation agencies (e.g., slowing down, avoiding travel, and imposing roadway restrictions or closures). Previous research on how weather and road conditions impact transportation and novel research herein to create a metric for crash impact based on precipitation type and local hour of the day are both intended to help scale weather forecasts to impacts. Impact severity classifications can ultimately be determined through consideration of any thresholds used by transportation agencies, in conjunction with the scaling metrics. Significance Statement Weather can profoundly impact surface transportation and motorist safety. Because of this and because there are no explicit tools available to forecasters to identify and communicate potential impacts to surface transportation, there is a desire for the development of such a forecast product. However, doing so requires careful consideration for what impacts are intended to be included, how weather corresponds to impacts, and how thresholds for impact severity should be defined. In this first part of the paper series, we outline each of these aspects and present novel research and approaches for the development of an impact-based forecast product specifically tailored to surface-transportation hazards. The product is ultimately intended to improve motorist safety and mobility on roads.

Phylogenetic Effect on Tree Radial Growth Depends on Drought and Tree Sizes

AbstractTree radial growth is one of the most direct measures of tree performance and is also sensitive to climate. Growth performance is the consequence of the interplay between ecological and evolutionary processes. However, the effect of the evolutionary relatedness among species (i.e., phylogeny) on tree radial growth, especially under stressful conditions, remains largely unknown. Furthermore, there is still no ecological evidence for the influence of phylogeny on tree growth across different tree attributes (i.e., tree diameter variation and tree canopy height) and topographic habitat types. We used Blomberg's K to quantify the tree growth phylogenetic signal (TGPS) using two long‐term dendrometer data sets: one a continuous census of 225 tree species at 3‐month intervals in a tropical forest in southwest China from 2009 to 2017; the other, 12 tree species measured at 6‐month intervals in a temperate forest in Washington State, USA from 2013 to 2019. We found that TGPS values were higher in the temperate forest than in the tropical forest. Precipitation, tree diameter, canopy strata, and habitat types all influenced TGPS values. TGPS values were significantly (p < 0.05) and negatively related to precipitation in Xishuangbanna, and the three of four tree diameter classes in the temperate forest, respectively. Stressful growing conditions arose from either based on low precipitation or among large‐diameter trees competing with each other in the upper canopy led to phylogenetic conservatism in trees' radial growth performance. We conclude that phylogeny is pivotal to understanding the growth response differences among species and their responses to climate variability.

Toward the Development of an Impact-Based Decision Support Tool for Surface-Transportation Hazards. Part II: An Hourly Winter Storm Severity Index

Abstract In line with the continued focus of the National Weather Service (NWS) to provide impact-based decision support services (IDSS) and effectively communicate potential impacts, a new IDSS forecasting tool for surface-transportation hazards is in development at the Weather Prediction Center: the hourly winter storm severity index (WSSI-H). This second part of the series outlines the current algorithms and thresholds for the components of the WSSI-H, which has been developed in line with the approach and considerations discussed in Part I of this series. These components—snow amount, ice accumulation, snow rate, liquid rate, and blowing and drifting snow—each address a specific hazard for motorists. The inclusion of metrics related to driving conditions for untreated road surfaces and time-of-day factoring for active precipitation types helps directly tie forecasted weather conditions to transportation impacts. Impact severity level thresholds are approximately in line with thresholds used by transportation agencies when considering various mitigation strategies (e.g., imposing speed restrictions or closing roadways). Whereas the product is not meant to forecast specific impacts (e.g., road closure or pileup), impact severity levels are designed to scale with increasingly poor travel conditions, which can prompt various mitigation efforts from motorists or transportation agencies to maintain safety. WSSI-H outputs for three winter events are discussed in depth to highlight the potential utility of the product. Overall, the WSSI-H is intended to provide high-resolution situational awareness of potential surface-transportation-related impacts and aid in enhanced collaborations between NWS forecasters and stakeholders like transportation agencies to improve motorist safety. Significance Statement A new impact-based forecast product designed to aid in situational awareness of potential impacts from surface-transportation-related hazards is in development. In this second part of the series, we outline the algorithms and thresholds for the various components of the product, where each component addresses a unique hazard. Product outputs for three winter events are presented to highlight the potential utility of the product in an operational forecast setting. Ultimately, enhanced collaboration between forecasters and transportation agencies alongside guidance from this product will bolster consistent messaging to motorists and improve safety and mobility on roads.

Phosphorus addition stimulates overall carbon acquisition enzymes but suppresses overall phosphorus acquisition enzymes: A global meta-analysis

Of the total land worldwide, 43 % is phosphorus (P)-constrained, which is significantly greater than the proportion of nitrogen-constrained land (18 %). However, there are some uncertainties regarding the responses of enzyme activities to P addition on a global scale. We collected data from 99 publications and performed a meta-analysis to assess the responses of 11 extracellular enzymes, including carbon, nitrogen, and phosphorus acquisition enzymes, and oxidases. P addition significantly increased the activities of β-1, 4-glucosidase, sucrase, cellobiohydrolase, and alkaline phosphatase, while lowering the activities of acid phosphatase and phosphodiesterase. The responses of enzyme activities to P addition differed considerably across the three ecosystems (forest, grassland, and cropland). P addition significantly decreased the activities of acid phosphatase, phosphodiesterase, and P-acquisition enzymes in forests, but increased the activities of leucine aminopeptidase, carbon acquisition enzymes, and nitrogen acquisition enzymes in grasslands. Sucrase, β-1,4-glucosidase, N-acetyl-β-glucosaminidase, alkaline phosphatase, and carbon acquisition enzymes were significantly stimulated in croplands. In addition, all P addition rates significantly increased the activity of alkaline phosphatase, a P-acquisition enzyme, in croplands. Ca(H2PO4)2 had a greater effect on enzyme activity than other fertilizer types, possibly because Ca2+ can improve the soil structure and enhance microbial metabolic activities. Furthermore, structural equation models revealed that mean annual precipitation and ecosystem type had significant impacts on the response of P-acquisition enzymes, but no factor could directly influence the response of carbon-acquisition enzymes. Our investigation of enzyme activities in response to P addition complements the biogeochemical model and helps forecast soil nutrient dynamics. We propose that rather than focusing on a single factor, P fertilizer addition programs should take into account the effects of mean annual precipitation, ecosystem type, and nutrient interactions, which could also reduce P pollution.

Summer Convective Precipitation Changes Over the Great Lakes Region Under a Warming Scenario

AbstractTo understand future summer precipitation changes over the Great Lakes Region (GLR), we performed an ensemble of regional climate simulations through the Pseudo‐Global Warming (PGW) approach. We found that different types of convective precipitation respond differently to the PGW signal. Isolated deep convection (IDC), usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), usually concentrated upwind of the GLR, shift to the downwind region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to increase across almost the entire studied domain, creating a potential environment more favorable for stronger convection systems and less favorable for weaker ones. Meanwhile, changes in the lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, highlighting the significance of these thermodynamic factors in controlling precipitation over the domain. Our results indicate that the decrease in LCL and LCF in areas with increased convective precipitation is mainly due to increased atmospheric moisture. In response to the prescribed warming perturbation, MCSs occur more frequently downwind, while localized IDCs exhibit more intense rain rates, longer durations, and larger rainfall area.

Precipitation and cloud Parameters's characteristics of stratus in summer in Ningxia, eastern of northwest China

Stratus is the main artificial seeding target for weather modification in Ningxia. Meteorological satellites can detect macro and microcosmic physical parameters of large-scale stratus. Researching precipitation and cloud parameter characteristics of stratus can provide scientific and technological support for understanding the development and evolution of stratus to identify seeding conditions and effects. Eight typical stratus precipitation events of the summers of 2016–2021 of Ningxia were selected, using the nine point average method, that matched characteristic cloud parameters retrieved by FY-2G satellite with precipitation classification data of 25 national meteorological observation stations in Ningxia. These stratus precipitation characteristics were correlated with cloud parameters. The results indicate that precipitation decreased rapidly from the southeast to the northwest of Ningxia. In the synoptic background of precipitation, the cloud top height, super-cooled layer thickness, cloud optical thickness, cloud particle effective radius, and cloud liquid water content were all larger than those in the synoptic background of no precipitation. The spatial distribution feature manifests as gradually increased from southeast to northwest. The cloud top temperature and cloud blackbody temperature were smaller than those in the synoptic background of no precipitation. The cloud top temperature was near the cloud “seeding temperature window”, and the depth of the super-cooled layer was thick. This was in line with the “Seeder-Feeder” structure characteristic of cold stratus.

Effect of Temperature and Frequency on the Viscoelastic Behavior of Commercial 6082 (Al–Mg–Si) Alloy

<div>The viscoelastic response of pure Al and commercial 6082 and 6082-T6 (Al–Mg–Si) alloys is measured with dynamic–mechanical analyzer as a function of temperature (ranging from 35 to 425°C) and loading frequency (ranging from 0.01 to 100 Hz). The measured data (the storage modulus, loss modulus, and mechanical damping) are compared to available transmission electron microscopy and differential scanning calorimetry data, to ascertain whether unexplained variations of the viscoelastic behavior of the alloys can be correlated to phase transformations. The results suggest that some of these variations may be controlled by the formation and dissolution of metastable phases, such as Guinier–Preston (GP) zones and phases β″, β′, and B′. Indeed, GP zones and phase β″ have been reported to control other mechanical properties. However, due to the high complexity of the aging path of Al–Mg–Si alloys, with formation and dissolution reactions of many precipitate types overlapping along wide temperature intervals, further research is necessary to establish unequivocally the contribution of each individual phase transformation to the overall viscoelastic behavior. Finally, an internal friction peak related to grain boundary sliding is significantly smaller in the alloys compared to pure Al, probably because the precipitates pin the grain boundaries.</div>

Evolution of Physical and Chemical Characteristics of Atmospheric Precipitation and Its Significant Impacts on the Environment in Beijing

Atmospheric precipitation samples were collected in 2018, 2019, and 2021 in Beijing to study the concentrations and changes of the main metal elements and water-soluble ions； the wet deposition fluxes of heavy metals, water-soluble ions, dissolved inorganic nitrogen, and sulfur in the atmospheric precipitation and their impacts on the ecological environment； and the scavenging mechanisms of the typical precipitation to atmospheric pollutants during the study period. The results showed that the precipitation in Beijing during the study period was mostly neutral or alkaline, and the frequency of acid rain occurrence was very low, only accounting for 3.06%. The total concentrations of major metal elements in 2018, 2019, and 2021 were （4 787.46 ±4 704.31）, （7 663.07 ±8 395.05）, and （2 629.13 ±2 369.51） μg·L-1, respectively. The total equivalent concentrations of ions in 2018, 2019, and 2021 were （851.68 ±649.16）, （973.98 ±850.94）, and （644.31 ±531.16） μeq·L-1, respectively. The interannual changes in major metal elements and ions followed the order of 2019 > 2018 > 2021. The seasonal average total concentrations of major metal elements in spring, summer, autumn, and winter were （9 624.25 ±7 327.92）, （4 088.67 ±5 710.14）, （3 357.68 ±3 995.64）, and （6 203.19 ±3 857.43） μg·L-1, respectively, and the seasonal average total equivalent concentrations of ions in spring, summer, autumn, and winter were （1 014.71 ±512.21）, （729.83 ±589.90）, （724.35 ±681.40）, and （1 014.03 ±359.67） μeq·L-1, respectively, all presenting the order of spring > winter > summer > autumn. NO3- and SO42- were the main acid-causing ions in precipitation, whereas NH4+ and Ca2+ were the main acid-neutralizing ions. The wet deposition fluxes of the heavy metal Cd were very low [（0.05 ±0.01） mg·（m2·a）-1], only accounting for （0.13 ±0.04）% of the total wet deposition fluxes of main metal elements； however, its soil safety years were 291 years, significantly lower than those of other heavy metals, displaying that its ecological risk was relatively the highest. The total wet precipitation flux of water-soluble ions NH4+, Ca2+, NO3-, and SO42- accounted for （85.72 ±2.18）% of the wet precipitation flux of total ions, suggesting that their comprehensive impact on the ecological environment might have been higher. DIN wet deposition flux was mainly characterized by NH4+-N, which had a positive impact on the ecological environment in summer. SO42--S wet deposition flux was higher in summer, so its positive impact on the ecological environment was also greater. The scavenging effects of atmospheric precipitations to pollutants from the air were impacted by various factors, and the synergism effects of these factors could directly influence the scavenging mechanisms of precipitation to pollutants.

Aerosol impacts on summer precipitation forecast over the North China Plain by using Thompson aerosol aware scheme in WRF: Process analysis and response sensitivity to aerosol concentrations during a Heavy Rainfall Event in Beijing

Aerosol-Cloud-Interactions (ACIs) are possibly important factors affecting precipitation while are usually not considered in numerical weather prediction systems (NWP) due to the complexities and uncertainties involved by considering aerosol information. This research focused on the use of the Thompson aerosol-aware scheme in WRF (Weather Research and Forecasting model). This paper summarized the process analysis and response sensitivity to aerosol concentrations during a heavy rainfall event in Beijing. The July 16, 2018 rainfall event -a typical precipitation case involving both warm and cold-phase clouds was thoroughly analyzed, including cloud fraction, downward shortwave radiation, water vapor consumption, cloud microphysical processes, net latent heat etc., which verified that the aerosol-cloud interaction paths were accurately and adequately considered in Thompson aerosol-ware scheme. By tracking key parameter changes, it is confirmed that the CCN/IN activation and relative roles in changing precipitation at different stages are reasonable in Thompson aerosol-aerosol scheme. According to the rainfall characteristics, the precipitation was divided into two phases. And the difference in the aerosol effect on precipitation in the two precipitation phases is mainly due to the complexity of cold rain process and hypothesis. Sensitivity simulations also revealed that the current concentrations of background aerosol in Beijing are actually high enough and further ten-times of aerosol concentration increase didn't bring significant additional precipitation response.

Climate sensitivity of natural hazards processes in mountain regions: A fuzzy logic approach

Natural hazard processes, as an inherent component of mountain environments, react sensitively to global warming. The main drivers of these changes are alterations in the amount, intensity or type of precipitation, glacier melting, or thawing of permafrost ice. The hazard responses can involve a change in hazard intensity or frequency (increasing or decreasing), a shift in their location or, a shift from one type of hazard to another. As climate change impacts vary in space and time, this variability must be considered when planning measures to protect populations and infrastructure from hazardous processes. To support this, we developed a method for assessing the climate sensitivity of small individual rock releases and larger rockfall processes. The method is based on a fuzzy logic approach and uses highly resolved climate scenario data, allowing application on a regional or even larger scale.The application in a study area of 700 km2 in the central Valais (Switzerland) shows that the impacts of climate change on natural hazard processes can vary quite substantially across small spatial scales. Generally, an increase in rockfall frequency and magnitude is simulated under future warming scenarios, especially at higher altitudes. However, at lower elevations and on south-exposed slopes, a decrease in freeze-thaw cycles leads to a decrease in material availability. This knowledge is essential in discussions of how climate change should be considered in hazard and disaster management.

Assessment of spatial cyclone surge susceptibility through GIS-based AHP multi-criteria analysis and frequency ratio: a case study from the Bangladesh coast

Tropical cyclones, including surge inundation, are a common event in the coastal regions of Bangladesh. The surge washes out the area within a very short period and remains in flooded condition for several days. Spatial analysis to understand the surge susceptibility level can assist the cyclone management system. Surge susceptibility analysis could be one of the most essential parts of disaster risk reduction through which cyclone vulnerability can be minimized. A Geographic Information Systems-based analytical hierarchy process (AHP) multi-criteria analysis and bivariate frequency ratio (FR) techniques were conducted to understand the surge susceptibility level of a cyclone-prone area on the Bangladesh coast. A total of 10 criteria were considered influential to surge flooding, i.e. Topographic Wetness Index, elevation, wind velocity, slope, distance from sea and rivers, drainage density, Land Use and Land Cover, Normalized Difference Vegetation Index, precipitation, and soil types. The final surge susceptibility maps were categorized into five classes, i.e. very low, low, moderate, high, and very high. Conferring to these susceptibility classes, policymakers can make decisions for future land use management and disaster risk reduction activities. According to this research, AHP showed better precision (Receiver Operating Characteristic) than FR for surge susceptibility prediction on the Bangladesh coast.

Assessment of relationship between sea surface temperature (SST) changes and precipitation types in Nigeria from 2000 to 2022

This study investigated the circulation patterns associated with rainfall variations across Nigeria’s different climatic zones (2000–2022). Data was acquired from MERRA2, gridded ERSST5 provided by the NOAA, and observation data records obtained from the Climatic Research Unit (CRU). Principal Component Analysis (PCA) was employed to compare different precipitation types, while the Multinomial Logistic Regression Model was employed to examine the influence of SSTa on precipitation presenting regression coefficients with a significance level set at p < 0.05. Five distint standard precipitation index (SPI) classes: very dry, dry, normal, wet and very wet were categorised using prcipitation data. Analysis was done in R-studio and involved data preparation, model training, and evaluation, with emphasis on interpreting the coefficients to discern the impact of SST anomalies on precipitation for each specified level. The results show that TOP, AVP, LSP, and CNP varied: spatially, the northern region received low moisture budget from the Atlantic Ocean while the temporal distribution of precipitation across different climatic zones indicate high variability in precipitation across these zones. The mean SSTa in the WAf region were predominantly positive (0.5 and 1). The lowest (highest) global SST values were prevalent during the DJF (JJA) season(s) whereas, the monthly distribution of SSTa for the WAf region reveal neutral (2000–2016) and El Niño (2016–2022) episodes. The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.

Winter Storm Severity Index in Alaska: Understanding the Usefulness for Impact-Based Winter Weather Severity Forecast Information

Abstract There is growing interest in impact-based decision support services to address complex decision-making, especially for winter storm forecasting. Understanding users’ needs for winter storm forecast information is necessary to make such impact-based winter forecasts relevant and useful to the diverse regions affected. A mixed-method social science research study investigated extending the winter storm severity index (WSSI) [operational for the contiguous United States (CONUS)] to Alaska, with consideration of the distinct needs of Alaskan stakeholders and the Alaskan climate. Data availability differences suggest the need for an Alaska-specific WSSI, calling for user feedback to inform the direction of product modifications. Focus groups and surveys in six regions of Alaska provided information on how the WSSI components, definitions, and categorization of impacts could align with stakeholder expectations and led to recommendations for the Weather Prediction Center to consider in developing the WSSI Alaska product. Overall, wind (strength and direction) and precipitation are key components to include. Air travel is a critical concern requiring wind and visibility information, while road travel is less emphasized (contrasting with CONUS needs). Special Weather Statements and Winter Storm Warnings are highly valued, and storm trajectory and transition (between precipitation types) information are the important contexts for decision-makers. Alaska is accustomed to and prepared for winter impacts but being able to understand how components (wind, snow, and ice) contribute to overall impact enhances the ability to respond and mitigate damage effectively. The WSSI adapted for Alaska can help address regional forecast needs, particularly valuable as the climate changes and typical winter conditions become more variable. Significance Statement Impact-based support services can assist decision-makers in prioritizing preparedness and mitigation actions related to winter storm events. The winter storm severity index adapted for specific considerations in Alaska (such as including wind and visibility components) can extend winter weather impact-based forecasting’s utility. Additionally, lessons learned from the process of adapting a national product to specific regional needs may inform best practices for gathering stakeholder input and feedback.

Top-Down Phenomenon Observed in the Outer Rainbands of Typhoon Maysak (2020): Insights from the Comparative Analysis of Cloud and Precipitation Microphysics with a Typical Precipitation Event in Northeast China

Abstract Cloud and precipitation microphysics in tropical cyclones (TCs) moving toward Northeast China may exhibit significant distinctions compared with the typical precipitation of this region. In this study, observations from ground-based particle size velocity (Parsivel) disdrometers in Liaoning Province, China, and cloud property data from the Himawari geostationary satellite were utilized to analyze the raindrop size distribution (DSD) characteristics and cloud vertical evolution associated with the outer rainbands of Typhoon Maysak (2020). A comparative analysis was conducted with a typical precipitation event in Northeast China induced by a cold vortex (cold-core low). Our findings reveal distinctive DSD characteristics related to the TC, where medium-sized raindrops dominate, with a smaller diameter but higher concentration in the TC case compared to the typical cold-vortex-induced precipitation case in Northeast China. Convective precipitation falls between maritime-like and continental-like patterns, leaning more toward continental convection. This varies significantly with TCs in Southeast China but is similar to that observed in coastal-front-like rainbands, suggesting extratropical influence. A detailed analysis of the vertical profile of cloud droplets shows a unique “top-down” phenomenon during the extratropical transition process of the TC, where the development of lower-level clouds follows that of upper-level clouds, inconsistent with previous studies and the case for comparison. Further investigation indicates the significant role of the intrusion of dry and cold air from upper levels and the presence of high humidity in low levels in driving this phenomenon. Our results will provide novel insights into cloud and precipitation microphysics associated with TCs in midlatitude regions.

Soil organic carbon fractions and storage potential in Finnish arable soils

AbstractUnderstanding the factors affecting the total amount and distribution of soil organic carbon (OC) across different functional carbon pools is important to better define the future management of soil OC stocks. The interactions between soil management practices, local physicochemical soil properties and climate are essential for determining the OC content of the soil. Nevertheless, how these factors affect the total amount of OC and its distribution across carbon pools, i.e., more labile particulate (POC) and more stable mineral‐associated (MAOC) organic carbon, is only partly known. In this study, we assessed topsoil (0–20 cm) samples from 93 arable farms in the southern half of Finland to determine the total amount of OC, and its distribution in MAOC and POC, along with relevant soil properties (amount of clay and silt, aluminium and iron oxides and pH), climate (precipitation and temperature) and fertilization (mineral versus organic). The fertilization did not affect the total soil carbon content (12–58 g OC kg−1 soil). The share of OC in the MAOC fraction (on average 86% of total OC) was relatively stable across the large range of OC contents and clay contents (2%–68%). We assessed the highest feasible MAOC of the soils with boundary line analyses and their OC saturation state with Hassink's equation (Hassink, 1997). Only soils with the lowest clay content (&lt;10% clay) were assumed to be carbon‐saturated, suggesting that most of the studied soils have a capacity to accrue more MAOC. Simple linear regression showed that clay, aluminium and iron oxides explained 9%, 21% and 22% of the variation in MAOC, respectively. Multiple regression analyses including the amount of clay, clay+silt, aluminium and iron oxides, pH, type of fertilization, precipitation and temperature as explanatory variables explained 33%–53% of the variation in OC and MAOC. In all soils, aluminium oxides were important explanatory variable for MAOC, whereas Fe oxides were significant only in soils with higher clay content (&gt;30%). In soils with a low clay content (&lt;30%), pH had added value in explaining MAOC. Altogether, it seems that various climatic, edaphic and soil management‐related factors are context‐dependently controlling OC and that soil textural information alone is not necessarily an adequate predictor to assess the MAOC saturation state of the soil.

Effect of Pre-Deformation on Precipitation in Al–Zn–Mg–Cu Alloy

AbstractIn this work, strengthening effects and evolution of precipitates in a pre-deformed Al–Zn–Mg–Cu alloy during ageing were investigated using Vickers hardness measurements, tensile tests, and high angle annular dark field scanning transmission electron microscopy (HAADF-STEM). It was found that all cold rolled conditions had higher mechanical strength than the non-deformed condition for all ageing times and that this effect increases at higher deformation ratios. It was also found that the non-deformed condition has a higher age hardening response than that of the cold rolled conditions. A homogeneous precipitate distribution was observed in the non-deformed condition, while the cold rolled conditions contained non-uniformly distributed precipitates due to the introduced dislocations. This led to larger precipitate sizes and a reduction in the precipitate number densities in the pre-deformed conditions. HAADF-STEM analysis revealed differences in the fraction of different precipitate types between the non-deformed and the cold rolled conditions. η', η2, and disordered η phase were observed in the non-deformed condition, while η', η2 and the newly identified Y phase were observed in the cold rolled conditions. The disordered η phase contained structural units of the η1 phase and was associated with reducing the lattice misfit between this phase and the Al matrix. Formation of the Y phase was related to an accelerated nucleation rate in the regions of high dislocation density. Graphical abstract

Improved mechanical behavior of friction stir drilled 6082 aluminum alloy via T6 treatment

6082 Al-alloy underwent a friction stir drilling (FSD) processing. Subsequently, a two-stage post-heat treatment (PHT) procedure, i.e., solution treatment at 550 °C for 2 h, followed by artificial aging at 175 °C for 18 h, was implemented to significantly enhance microstructure and mechanical performance of the alloy. The microstructure was characterized by optical, laser, scanning electron and electron backscattered diffraction microscopes, while the mechanical behavior was assessed by a micro-indentation hardness tester, employing the indentation hardness (HIT) technique. Corrosion behavior of FSD as well as PHT specimens was investigated through electrochemical techniques.The microstructure of the base metal (BM) manifested an α-Al matrix with an average grain size of approximately 50 μm. FSD resulted in the creation of stirring zone (SZ) and thermo-mechanical affected zone (TMAZ), with respective widths of 400 ± 50 and 950 ± 100 μm. The SZ exhibited a very fine structure with an average grain size of 0.5 μm, thereby displaying increased hardness. The PHT microstructure displayed the formation of fine βʹ and βʺ second phase precipitate types, whereas the HIT hardness of the PHT α-aluminum matrix in the SZ, was lower than TMAZ and BM, due to reductions of βʹ in the SZ compared to TMAZ and BM. Moreover, the corrosion rate of the SZ decreased after the heat-treatment cycle, attributed to the recovery of strain energy induced during friction drilling and the increased solubility of solute atoms within the α-Al matrix.

Outdoor Radon Dose Rate in Canada's Arctic amid Climate Change.

Decades of radiation monitoring data were analyzed to estimate outdoor Radon Dose Rates (RnDRs) and evaluate climate change impacts in Canada's Arctic Regions (Resolute and Yellowknife). This study shows that the RnDR involves dynamic sources and complex environmental factors and processes. Its seasonality and long-term trends are significantly impacted by temperatures and soil-and-above water contents. From 2005 to 2022, Yellowknife's RnDR increased by +0.35 ± 0.06 nGy/h per decade, with the fastest increases occurring in cold months (October to March). The rise is largely attributable to water condition changes over time in these months, which also caused enhanced soil gas emissions and likely higher indoor radon concentrations. In Resolute, the RnDR increased between 2013 and 2022 at +0.62 ± 0.19 nGy/h (or 16% relatively) per decade in summer months, with a positive temperature relationship of +0.12 nGy/h per °C. This work also demonstrates the relevance of local climate and terrain features (e.g., typical active layer depth, precipitation amount/pattern, and ground vegetation cover) in researching climate change implications. Such research can also benefit from using supporting monitoring data, which prove effective and scientifically significant. From the perspective of external exposure to outdoor radon, the observed climate change effects pose a low health risk.

Microstructure and strengthening mechanism of TIG welded joint of AZ31 alloy based on FSP technique

Magnesium alloys, renowned for their outstanding properties, present promising applications within the realm of advanced manufacturing. Addressing the challenges of coarse grains and inferior properties in the fusion welding of magnesium alloys, a novel strengthening approach for fusion-welded joints is proposed in this study. This method employs fine, uniform, and dense grains as the matrix, with particle-reinforced structures serving as the strengthening backbone. By utilizing powder feeding in conjunction with fusion welding and friction stir processing, ideal microstructures were successfully fabricated, and the mechanisms influencing grain morphology and joint properties were explored. Following the strengthening treatment, the grain size of the magnesium alloy molten weld was reduced from 193.5 μm to 15.9 μm, resulting in a grain refinement efficacy of 91.8 %. Concurrently, the tensile strength was augmented by 70.2 MPa, and the elongation experienced a 136 % enhancement. The grain morphology, eutectic phase structure, texture strength, precipitated phase type and dislocation distribution at each processing stage of the welded joint were observed. Research shows that nano-enhanced particles adhere to the eutectic structure of grain boundaries, effectively inhibiting the diffusion of solute elements and significantly reducing the dendrite growth rate. It is the main mechanism by which reinforced particles lead to grain refinement. Discontinuous recrystallization during FSP treatment leads to grain refinement, work hardening and enhanced pinning of particles at grain boundaries, which are the main reasons for the strength improvement.

A general comprehensive evaluation method for cross-scale precipitation forecasts

Abstract. With the development of refined numerical forecasts, problems such as score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecasts and the increasing subjective risk arising from the scale setting of the neighborhood spatial verification method have become increasingly prominent. To address these issues, a general comprehensive evaluation method (GCEM) is developed for cross-scale precipitation forecasts by directly analyzing the proximity of precipitation forecasts and observations in this study. In addition to the core indicator of the precipitation accuracy score (PAS), the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases, and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and does not delimit the area of influence; it constitutes a fair scoring formula with objective performance and can be suitable for evaluating rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and threat score (TS) are conducted for two typical precipitation weather processes. The results show that relative to the TS, the PAS better aligns with subjective expectations, indicating that the PAS is more reasonable than the TS. In the case of an extreme-precipitation event in Henan, China, two high-resolution models were evaluated using the PAS, TS, and fraction skill score (FSS), verifying the evaluation ability of PAS scoring for predicting extreme-precipitation events. In addition, other indices of the GCEM are utilized to analyze the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecasting ability for different weather processes. These indices not only provide overall scores similar to those of the TS for individual cases but also support two-dimensional score distribution plots which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods.