Precipitation Rate Research Articles

Groundwater quality evaluation of the weathering mantle in crystalline basement aquifer system, southern Brazil.

Groundwater is the main source of water for more than 2 billion people worldwide. In southern Brazil, the Crystalline Basement Aquifer System is composed of strategic groundwater reservoirs. Groundwater is mostly taken from shallow wells, and it is often used without any treatment, which poses a risk to public health. The present study aims to evaluate shallow groundwater quality and the geochemistry of shallow and deep groundwater located in the municipality of Canguçu, southern Brazil. The physicochemical and microbiological parameters of groundwater samples collected from shallow wells were monitored and analyzed using ANOVA variance analysis and water quality index (CCME WQI) approaches. Also, the results were compared with secondary data from deep wells. The monitored shallow wells had thermotolerant coliforms, Escherichia coli, pH, potassium, manganese, iron, and nitrate in disagreement with the guidelines of the World Health Organization. Moreover, variance analysis showed that the parameters temperature, dissolved oxygen, pH, chloride, and magnesium were the most influenced by seasonal variations. According to the CCME WQI, most samples had good quality (60%), 28% had fair quality, and 12% had poor quality. In addition, the field campaigns with higher precipitation rates also presented fair quality. Therefore, most of the shallow groundwater quality is affected by surface pollutants from the urban area, aggravated in rainy periods. Whereas deep groundwater is influenced by geochemistry mechanisms. The results revealed the risk of water consumption for public health and the urgent need for better maintenance of these wells and water treatment implementation.

Rainfall Sensitivity to Microphysics and Planetary Boundary Layer Parameterizations in Convection-Permitting Simulations over Northwestern South America

Convection-permitting modeling allows us to understand mechanisms that influence rainfall in specific regions. However, microphysics parameterization (MP) and planetary boundary layer (PBL) schemes remain an important source of uncertainty, affecting rainfall intensity, occurrence, duration, and propagation. Here, we study the sensitivity of rainfall to three MP [Weather Research and Forecasting (WRF) Single-Moment 6-class (WSM6), Thompson, and Morrison] and two PBL [the Yonsei University (YSU) and Mellor–Yamada Nakanishi Niino (MYNN)] schemes with a convection-permitting resolution (4 km) over northwestern South America (NWSA). Simulations were performed by using the WRF model and the results were evaluated against soundings, rain gauges, and satellite data, considering the spatio-temporal variability of rainfall over diverse regions prone to deep convection in NWSA. MP and PBL schemes largely influenced simulated rainfall, with better results for the less computationally expensive WSM6 MP and YSU PBL schemes. Regarding rain gauges and satellite estimates, simulations with Morrison MP overestimated rainfall, especially westward of the Andes, whereas the MYNN PBL underestimated precipitation in the Amazon–Savannas flatlands. We found that the uncertainty in the rainfall representation is highly dependent on the region, with a higher influence of MP in the Colombian Pacific and PBL in the Amazon–Savannas flatlands. When analyzing rainfall-related processes, the selection of both MP and PBL parameterizations exerted a large influence on the simulated lower tropospheric moisture flux and moisture convergence. PBL schemes significantly influenced the downward shortwave radiation, with MYNN simulating a greater amount of low clouds, which decreased the radiation income. Furthermore, latent heat fluxes were greater for YSU, favoring moist convection and rainfall. MP schemes had a marked impact on vertical velocity. Specifically, Morrison MP showed stronger convection and higher precipitation rates, which is associated with a greater latent heat release due to solid-phase hydrometeor formation. This study provides insights into assessing physical parameterizations in numerical models and suggests key processes for rainfall representation in NWSA.

Effects of grain size and seawater salinity on magnesium hydroxide dissolution and secondary calcium carbonate precipitation kinetics: implications for ocean alkalinity enhancement

Abstract. Understanding the impacts that mineral grain size and seawater salinity have on magnesium hydroxide (Mg(OH)2) dissolution and secondary calcium carbonate (CaCO3) precipitation is critical for the success of ocean alkalinity enhancement. We tested Mg(OH)2 dissolution kinetics in seawater using three Mg(OH)2 grain sizes (<63, 63–180 and >180 µm) at three salinities (∼36, ∼28 and ∼20). While Mg(OH)2 dissolution occurred more quickly the smaller the grain size, salinity did not significantly impact measured rates. Our results also demonstrate that grain size can impact secondary CaCO3 precipitation, suggesting that an optimum grain size exists for ocean alkalinity enhancement (OAE) using solid Mg(OH)2. Of the three grain sizes tested, the medium grain size (63–180 µm) was optimal in terms of delaying secondary CaCO3 precipitation. We hypothesise that in the lowest-grain-size experiments, the higher surface area provided numerous CaCO3 precipitation nuclei, while the slower dissolution of bigger grain sizes maintained a higher alkalinity and pH at the surface of particles, increasing CaCO3 precipitation rates and making them observable much more quickly than for the intermediate grain size. Salinity also played a role in CaCO3 precipitation, where the decrease in magnesium (Mg) allowed secondary precipitation to occur more quickly, similar in effect size to another known inhibitor, i.e. dissolved organic carbon (DOC). In summary, our results suggest that OAE efficiency as influenced by CaCO3 precipitation depends not only on seawater composition but also on the physical properties of the alkaline feedstock used.

Blue carbon assessment in Avicennia marina sediments and vegetation along the Red Sea Coast of Egypt: Improving methods and insights

Mangrove forests play a crucial role in the coastal environment. A plethora of research is focusing on mangroves’ role in climate mitigation through sequestering and storing CO2. This study aims to assess the organic carbon (OC) stocks and carbon sequestration rate (CSR) of the largest stands of mangroves in the Red Sea Coast of Egypt, to evaluate their significance in climate mitigation strategies. Intensive sampling was conducted in mangrove stands of Safaga, Qulaan, and Hamata to investigate OC and sediment properties along depth intervals to 1 m deep. Additionally, OC stored in the above- and below-ground biomass was estimated using Landsat 9 OLI/TIRS satellite images. TOC content (∼0.50%) and stocks in the sediments (54.49 ± 31.71–86.00 ± 29.00 MgC/ha) were very low compared to the global average for mangrove stands, and comparable to the mangrove forest in the Middle East region. This can be attributed to the desert and semi-desert conditions, limited riverine input, and low precipitation rates. Moreover, the above-ground biomass, estimated from Normalized Difference Vegetation Index, exhibited extremely low OC storage. Therefore, the sediment acted as the main pool of organic carbon in these mangrove ecosystems. The research findings revealed that mangrove stands in Egypt exhibit low CSR, ranging from 11.94 to 18.02 g C m−2 year−1. Additionally, the study determined that the stable nature of mangrove stands in Egypt makes their annual CO2 emissions negligible. Despite local studies suggesting otherwise, it is highly unlikely that mangroves in Egypt contribute to the climate mitigation related to CO2 sequestration. Therefore, it is important to implement restoration plans to ensure the preservation of other ecological services provided by mangroves along the Red Sea Coast.

Characterizing Mesoscale Cellular Convection in Marine Cold Air Outbreaks With a Machine Learning Approach

AbstractDuring marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment.

Biosilica-coated carbonic anhydrase displayed on Escherichia coli: A novel design approach for efficient and stable biocatalyst for CO2 sequestration

A robust and stable carbonic anhydrase (CA) system is indispensable for effectively sequestering carbon dioxide to mitigate climate change. While microbial surface display technology has been employed to construct an economically promising cell-displayed CO2-capturing biocatalyst, the displayed CA enzymes were prone to inactivation due to their low stability in harsh conditions. Herein, drawing inspiration from biomineralized diatom frustules, we artificially introduced biosilica shell materials to the CA macromolecules displayed on Escherichia coli surfaces. Specifically, we displayed a fusion of CA and the diatom-derived silica-forming Sil3K peptide (CA-Sil3K) on the E. coli surface using the membrane anchor protein Lpp-OmpA linker. The displayed CA-Sil3K (dCA-Sil3K) fusion protein underwent a biosilicification reaction under mild conditions, resulting in nanoscale self-encapsulation of the displayed enzyme in biosilica. The biosilicified dCA-Sil3K (BS-dCA-Sil3K) exhibited improved thermal, pH, and protease stability and retained 63 % of its initial activity after ten reuses. Additionally, the BS-dCA-Sil3K biocatalyst significantly accelerated the CaCO3 precipitation rate, reducing the time required for the onset of CaCO3 formation by 92 % compared to an uncatalyzed reaction. Sedimentation of BS-dCA-Sil3K on a membrane filter demonstrated a reliable CO2 hydration application with superior long-term stability under desiccation conditions. This study may open new avenues for the nanoscale-encapsulation of enzymes with biosilica, offering effective strategies to provide efficient, stable, and economic cell-displayed biocatalysts for practical applications.

A Machine Learning Method to Retrieve Global Rainfall and Snowfall Rates From the Passive Microwave Observations of FY‐3E

AbstractPassive microwave radiometers onboard satellites rely on the received upwelling radiation to retrieve precipitation, which is a mixed signal from the surface, atmosphere and precipitation hydrometeors. Liquid precipitation droplets increase the upwelling radiation from the surface at lower frequencies, while ice particles cause a decrease in upwelling radiation at higher frequencies. The task of the retrieval algorithm is to identify the precipitation phase and to isolate the signal of precipitation from that of the surface. This study develops a machine learning method to retrieve rainfall and snowfall rates based on observations from the Microwave Hydrometer Sounder and Microwave Temperature Sounder onboard FY‐3E. Self‐organized mapping (SOM) is selected to classify the precipitation and underlying surface types, and an artificial neural network (ANN) is subsequently used to relate the brightness temperature to the precipitation rate for the clusters derived from the SOM. The half‐hour product of the Integrated Multi‐Satellite Retrieval for Global Precipitation Measurement (IMERG) is used to train the ANN. To address the issue that number of heavy precipitation samples are not enough for training, the simulation of radiative transfer for TOVS is used as a supplement to heavy rain samples. The SOM‐ANN algorithm outperforms the IMERG and Goddard profiling algorithm (GPROF) retrieval products in both rainfall and snowfall retrieval. Compared with the hourly observations at ∼4,400 stations during a 2‐year period, the root mean square errors of SOM‐ANN proposed here are 1.06 and 0.34 mm/hr for the rainfall and snowfall rates, which are better than those of IMERG (1.23 and 0.42 mm/hr) and GPROF (1.22 and 0.44 mm/hr).

Contrasting extremely warm and long-lasting cold air anomalies in the North Atlantic sector of the Arctic during the HALO-(𝒜 𝒞)3 campaign

Abstract. How air masses transform during meridional transport into and out of the Arctic is not well represented by numerical models. The airborne field campaign HALO-(𝒜𝒞)3 applied the High Altitude and Long-range Research Aircraft (HALO) within the framework of the collaborative research project on Arctic amplification (𝒜𝒞)3 to address this question by providing a comprehensive observational basis. The campaign took place from 7 March to 12 April 2022 in the North Atlantic sector of the Arctic, a main gateway of atmospheric transport into and out of the Arctic. Here, we investigate to which degree the meteorological and sea ice conditions during the campaign align with the long-term climatology (1979–2022). For this purpose, we use the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5), satellite data, and measurements at Ny-Ålesund, including atmospheric soundings. The observations and reanalysis data revealed two distinct periods with different weather conditions during HALO-(𝒜𝒞)3: the campaign started with a warm period (11–20 March 2022) where strong southerly winds prevailed that caused poleward transport of warm and moist air masses, so-called moist and warm air intrusions (WAIs). Two WAI events were identified as atmospheric rivers (ARs), which are narrow bands of strong moisture transport. These warm and moist air masses caused the highest measured 2 m temperatures (5.5 °C) and daily precipitation rates (42 mm d−1) at Ny-Ålesund for March since the beginning of the record (1993). Over the sea ice northwest of Svalbard, ERA5 indicated record-breaking rainfall. After the passage of a strong cyclone on 21 March 2022, a cold period followed. Northerly winds advected cold air into the Fram Strait, causing marine cold air outbreaks (MCAOs) until the end of the campaign. This second phase included one of the longest MCAO events found in the ERA5 record (19 d). On average, the entire campaign period was warmer than the climatological mean due to the strong influence of the ARs. In the Fram Strait, the sea ice concentration was well within the climatological variability over the entire campaign duration. However, during the warm period, a large polynya opened northeast of Svalbard, untypical for this season. Compared to previous airborne field campaigns focusing on the evolution of (mixed-phase) clouds, a larger variety of MCAO conditions was observed during HALO-(𝒜𝒞)3. In summary, air mass transport into and out of the Arctic was more pronounced than usual, providing exciting prospects for studying air mass transformation using HALO-(𝒜𝒞)3.

Phase-Field Simulation of Precipitation and Grain Boundary Segregation in Fe-Cr-Al Alloys under Irradiation.

A phase-field model for the precipitation of Fe-Cr-Al alloy is established incorporating grain boundary (GB) effects and irradiation-accelerated diffusion. The radiation source and grain boundary effect are incorporated to broaden the applicability of the Fe-Cr-Al precipitated phase-field model. The model is firstly employed to simulate the precipitation of the Cr-rich α' phase in a single-crystal alloy. The precipitation rate and the size distribution of the precipitated phase were analyzed. Subsequently, the model is utilized to simulate segregation at GBs in a double-crystal system, analyzing the enrichment of Cr and depletion of Al near these boundaries. The simulation results are consistent with experimental observations reported in the references. Finally, the model is applied to simulate the precipitation in a polycrystalline Fe-Cr-Al system. The simulated results revealed that the presence of GBs induces the formation of localized regions with enhanced Cr and Al content as well as depleted zones adjacent to these boundaries. GBs also diminish both the quantity and precipitation rate of the formed phase within the grains.

Added value of EURO-CORDEX downscaling over the complex orography region of the Pyrenees

This study presents an assessment of the added value of downscaling utilizing Regional Climate Models (RCMs) compared to Global Climate Models (GCMs) in the high mountain region of the Pyrenees, characterized by complex topography. The EURO-CORDEX ensemble was investigated, employing a gridded high-resolution observational database as a reference. A recently proposed method is applied to quantify the performance gains or losses associated with dynamic downscaling. Our analysis focuses on calculating the added value by exploring the extremes of the Probability Density Function (PDF), spatial distribution patterns, and its relationship with elevation. Overall, our findings reveal significant improvements in the representation and general characterization of precipitation, minimum temperature, and maximum temperature in the Pyrenean region. Furthermore, RCMs demonstrate enhanced performance in capturing maximum precipitation events; however, they struggle to represent low precipitation rates, particularly in the Mediterranean area of the mountain range. Regarding temperature extremes, dynamical downscaling exhibits improvements in capturing maximum events. Nevertheless, deficiencies are observed in the RCMs’ representation of minimum temperature events for both minimum and maximum temperature variables, as well as in representing near-freezing temperatures.

High-performance photocatalytic hydrogen evolution in a Zn0.5Cd0.5S/MoS2 p–n heterojunction

With respect to solid-solution photocatalysts for water splitting, researchers have focused on improving the loading and stability of catalysts, which have been major concerns and research interests. Herein, the fabrication of Zn0.5Cd0.5S/MoS2 nanocomposites involved a two-step method that encompassed hydrothermal synthesis and physical mixing. Experimental results confirmed that the Zn0.5Cd0.5S/MoS2 nanocomposites exhibited outstanding photocatalytic performance. In particular, they exhibited a notable hydrogen precipitation rate of 19.41 mmol/(g*h). The hydrogen production performance of Zn0.5Cd0.5S/MoS2 was approximately nine times greater than that of pure Zn0.5Cd0.5S, indicating a considerable increase. The observed enhancement in photocatalytic efficiency can be attributed to the formation of a p–n heterojunction between Zn0.5Cd0.5S and MoS2. This particular junction helped in separating and migrating photoinduced charge carriers, ultimately improving the photocatalytic performance. Furthermore, the addition of excess thiourea in MoS2 preparation produced Mo–O defects and increased the layer spacing of the involved material, improving the electron transfer and visible-light utilization of the material. The inhibition of carrier recombination was beneficial for synthesizing efficient and long-lasting photocatalysts.

The Role of Cold Pools in Modulating Convective Organization During the MJO

AbstractIn this study, we investigate the role of cold pools in modulating convective organization throughout the Madden‐Julian Oscillation (MJO) life cycle using a modeling approach that combines Eulerian and Lagrangian techniques. First, we conduct a simulation using the soundings and forcing of the DYNAMO/AMIE campaign. The simulation shows a lag of several days between the precipitation rate peak time associated with MJO and the highest convective organization time. Second, to analyze the role of cold pools, we consider a series of 2‐day simulations conducted at different stages of the MJO. The simulation results suggest that cold pools are larger and last longer during the mature stages of the MJO, possibly because of decreased environmental surface latent heat fluxes and stronger downdrafts. These lead to the formation of moist rings at the leading edges of cold pools, facilitating the formation of more convective cores and increasing the degree of convective organization.

Mechanistic Study on the Influence of Wax on Hydrate Formation Process.

To manage the interactions between wax and hydrate formation, a comprehensive understanding of the system's thermodynamics and flow characteristics is essential. Wax and hydrates coexist under low-temperature and high-pressure conditions, mutually influencing each other both thermodynamically and kinetically. This study focused on two main aspects: how wax affects the rate of hydrate formation in the oil-water system and how hydrate formation influences the thermodynamics of wax crystal precipitation. The presence of wax decreased the rate of hydrate formation, especially at higher wax contents. In systems with high wax content, over 70% of wax precipitated before hydrate formation, leading to less precipitation within the hydrate formation temperature range. With low water content, there were more nucleation sites for wax crystals in the oil phase, resulting in a greater difference in precipitation rates among different wax contents. For water content greater than 10%, the differences in precipitation rates were less significant, indicating a diminished effect of water content on wax crystal precipitation rates. Hydrates' hydrophilic nature had a limited impact on wax crystal nucleation and growth. Generally, wax crystals precipitate before hydrate formation, necessitating control measures for wax deposition during production processes.

Analysis of the Relationship between Extreme Precipitation Pattern and Maximum Runoff in Hongze County From the Perspective of Urban Underlying Surface Production and Confluence

Based on the hourly precipitation data and evaporation data of the meteorological in Hongze County from 1959 to 2020, we studied the relationship between extreme precipitation and annual runoff control rate from the perspective of the underlying surface of the Hongze County watershed. We conducted a literature review and statistical analysis using SPSS in this study. From 1959 to 2020, precipitation in the Hongze region varied greatly annually, with the maximum and minimum annual precipitation of 1473.8 and 349.6 mm. The precipitation fluctuated but increased, and the extreme precipitation was concentrated in July to August. The annual average evapotranspiration from 1959 to 2020 was 1165.8 mm with an inter-annual fluctuation and decrease due to the urbanization process. The process affected the local evapotranspiration condition. More evaporation was observed from May to August than from December to January with a difference of 50 mm. The evaporation data coincided with seasonal variation in Hongze County. In determining the control rate of annual total runoff, we considered the inter-annual and annual differences in precipitation. The natural runoff condition and economic cost before urbanization were explored, too. The greater the rain intensity, the earlier the runoff generation time, the shorter the confluence time, and the greater the possibility of floods. In short-duration extreme precipitation, it is necessary to pay attention to its middle period, while for long-duration extreme precipitation, it is necessary to focus on its late period.

Controls on Li partitioning and isotopic fractionation in inorganic calcite

The δ7Li of marine carbonates has been interpreted as an archive of the evolution of seawater δ7Li, and therefore continental weathering, through geological time. However, little is known about the incorporation of Li into calcium carbonate minerals and, consequently, the controls on Li partitioning (DLi) and isotopic fractionation (Δ7Lisolid-fluid) associated with Li incorporation. Crucially, we lack a fundamental understanding of how Li partitioning and Δ7Lisolid-fluid change in response to the chemical and physical conditions of crystal formation. Here, we present DLi and Δ7Lisolid-fluid data from a series of inorganic calcite precipitation experiments where temperature, and solution pH and dissolved inorganic carbon (DIC) were independently varied. We find DLi values in the range 0.8–1.5 × 10−3, which show no relationship with temperature, a strong positive correlation with pH, and a weak positive correlation with DIC. At face value, these patterns are inconsistent with the results of previous precipitation studies. However, the correlations with pH and DIC are consistent with a strong precipitation rate control on DLi that aligns well with previous data, with a likely secondary influence from the incorporation of Li-HCO30 ion pairs from solution. We find Δ7Lisolid-fluid values in the range −6 to −2 ‰, which show no relationship with temperature or pH, and a weak positive correlation with DIC and crystal precipitation rate. These results do not agree with previously published data. Considered alongside previously published data, we observe no consistent relationship between Δ7Lisolid-fluid and any reported physical or chemical experimental parameter, highlighting the need for substantial further work to determine whether systematic controls on Li isotopic fractionation exist in carbonate minerals, and whether they may be environmentally significant.

Evaluating the Sediment Yield and Environmental Impact in Mining Expansion Scenarios in Sta. Cruz – Candelaria, Zambales

The study addressed the environmental concerns arising from industrial activities, such as mining, by focusing on the Candelaria-Santa Cruz region. Nickel mining in the region has raised issues related to water quality and sedimentation patterns. Employing the Modified Universal Soil Loss Equation (MUSLE) model, sediment yield computations were conducted, with consideration on factors like bare soil coverage, slope characteristics, and precipitation rates. The results emphasize the need for sustainable land management practices to mitigate adverse effects. The research covers a 10,000-ha area, simulating overburden removal scenarios ranging from 100 ha to 5,847.78 ha, and assesses sediment yield implications under different precipitation rates. The study also determines optimal relative growth rates and plant cover densities for progressive rehabilitation, highlighting the potential for effective erosion control. The findings underscore the significant impact of mining on sediment yield and water quality, prompting the call for comprehensive monitoring, calibration, and validation of the MUSLE model to guide informed decision-making and promote sustainable practices in the region. This research highlights the crucial role of integrated approaches in understanding and mitigating the consequences of resource exploitation on the environment and local communities.

A Climatology of Convective Precipitation over Europe

Abstract The annual, seasonal, and diurnal spatiotemporal heavy convective precipitation patterns over a pan-European domain are analyzed in this study using a combination of datasets, including the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) precipitation rate product, E-OBS ground-based precipitation gauge data, European climatological gauge-adjusted radar precipitation dataset (EURADCLIM), Operational Programme for the Exchange of Weather Radar Information (OPERA) ground-based radar-derived precipitation rates, and fifth major global reanalysis produced by ECMWF (ERA5) total and convective precipitation products. Arrival Time Difference Network (ATDnet) lightning data are used in conjunction with IMERG and EURADCLIM precipitation rates, with an imposed threshold of 10 mm h−1 to classify precipitation as convective. Annually, the largest convective precipitation accumulations are over the European seas and coastlines. In summer, convective precipitation is more common over the European continent, though relatively large accumulations exist over the northern coastal waters and the southern seas, with a seasonal localized maximum over the northern Adriatic Sea. Activity shifts southward to the Mediterranean and its coastlines in autumn and winter, with maxima over the Ionian Sea, the eastern Adriatic Sea, and the adjacent coastline. Over the continent, 1%–10% of the total precipitation accumulated is classified as convective, increasing to 10%–40% over the surrounding seas. In contrast, 30%–50% of ERA5 precipitation accumulations over land is produced by the convective parameterization scheme and 40%–60% over the seas; however, only 1% of ERA5 convective precipitation accumulations are from rain rates exceeding 10 mm h−1. Regional analyses indicate that convective precipitation rates over the inland mountains follow diurnal heating, though little to no diurnal pattern exists in convective precipitation rates over the seas and coastal mountains.

A clean metallurgical process for vanadium precipitation from vanadium-rich solutions

Ammonium salt vanadium precipitation process has excellent performance in industrial production, but its shortcomings such as high cost and environmental impact are not conducive to sustainable development. In this paper, ethylenediamine was selected as the precipitant, and vanadate was precipitated from acidic simulated vanadium-rich solutions by the ammonium salt precipitation process. The high purity V2O5 product was obtained after calcination. Under optimal conditions, the precipitation rate of vanadium reached 94.8 %, and the purity of vanadium was as high as 99.1 %. The vanadium precipitation product was hexamethyl ammonium, and the vanadium product was V2O5. It can be derived by the differential method that the reaction order was n = 2.4, the reaction rate equation was CV-1.4=kt+a, and the apparent activation energy was 27.8097 kJ/mol, which can be classified as the diffusion-controlled reaction. This innovative process enables a savings of 5050 yuan per ton of V2O5. On this basis, a complete V2O5 production process with zero waste discharge was designed.

Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors

With current advances in automated driving, optical sensors like cameras and LiDARs are playing an increasingly important role in modern driver assistance systems. However, these sensors face challenges from adverse weather effects like fog and precipitation, which significantly degrade the sensor performance due to scattering effects in its optical path. Consequently, major efforts are being made to understand, model, and mitigate these effects. In this work, the reverse research question is investigated, demonstrating that these measurement effects can be exploited to predict occurring weather conditions by using state-of-the-art deep learning mechanisms. In order to do so, a variety of models have been developed and trained on a recorded multiseason dataset and benchmarked with respect to performance, model size, and required computational resources, showing that especially modern vision transformers achieve remarkable results in distinguishing up to 15 precipitation classes with an accuracy of 84.41% and predicting the corresponding precipitation rate with a mean absolute error of less than 0.47 mm/h, solely based on measurement noise. Therefore, this research may contribute to a cost-effective solution for characterizing precipitation with a commercial Flash LiDAR sensor, which can be implemented as a lightweight vehicle software feature to issue advanced driver warnings, adapt driving dynamics, or serve as a data quality measure for adaptive data preprocessing and fusion.

Carbonate chimneys at the highly productive point Dume methane seep: Fine-scale mineralogical, geochemical, and microbiological heterogeneity reflects dynamic and long-lived methane-metabolizing habitats.

Methane is a potent greenhouse gas that enters the marine system in large quantities at seafloor methane seeps. At a newly discovered seep site off the coast of Point Dume, CA, ~ meter-scale carbonate chimneys host microbial communities that exhibit the highest methane-oxidizing potential recorded to date. Here, we provide a detailed assessment of chimney geobiology through correlative mineralogical, geochemical, and microbiological studies of seven chimney samples in order to clarify the longevity and heterogeneity of these highly productive systems. U-Th dating indicated that a methane-driven carbonate precipitating system at Point Dume has existed for ~20 Kyr, while millimeter-scale variations in carbon and calcium isotopic values, elemental abundances, and carbonate polymorphs revealed changes in carbon source, precipitation rates, and diagenetic processes throughout the chimneys' lifespan. Microbial community analyses revealed diverse modern communities with prominent anaerobic methanotrophs, sulfate-reducing bacteria, and Anaerolineaceae; communities were more similar within a given chimney wall transect than in similar horizons of distinct structures. The chimneys represent long-lived repositories of methane-oxidizing communities and provide a window into how carbon can be transformed, sequestered, and altered over millennia at the Point Dume methane seep.