3,351 Results Found

The water vapor-related microphysical processes (WVRMPs) in cloud microphysics schemes are crucial to the formation and dissipation of clouds, which have a significant impact on the quantitative precipitation forecasting of numerical weather predicti...

Satellite precipitation estimates are crucial for managing climate-related risks such as droughts and floods. However, these datasets often contain systematic errors due to the observation methods used. The accuracy of these estimates can be enhanced...

Hydrogeological disasters occur frequently. Proposing an effective prediction method for hydrology data can play a guiding role in disaster prevention; however, due to the complexity and instability of hydrological data, this is difficult. This paper...

Climatic variability is one of the fundamental aspects of the climate. Our scope of knowledge of this variability is limited by unavailable long-term high-resolution spatial data. Climatic simulations indicate that warmer climate increases extreme pr...

Precipitation forecasts provided by high-resolution NWP models have a degree of realism that is very appealing to most users of meteorological data. However, it is a challenge to demonstrate whether or not such forecasts contain more skillful informa...

Reanalysis data is widely used to develop predictor-predictand models, which are further used to downscale coarse gridded general circulation models (GCM) data at a local scale. However, large variability in the downscaled product using different GCM...

Climate forecasting is essential for energy production, agricultural activities, transportation, and civil defense sectors, serving as a foundation for decision-making and risk management. This study addresses the challenge of accurately predicting e...

Accurate detection of antibiotics in biological samples is essential for clinical diagnoses and therapeutic drug monitoring. This research examines how proteins and other substances in blood plasma affect the detection of the antibiotic ceftriaxone u...

Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6...

This study evaluates the feasibility of nitrogen recovery from wastewater via electrochemical methods as an alternative nutrient source for agricultural applications. Ammonium nitrogen (NH4+-N) and phosphate (PO43−-P) contamination poses signif...

This study assessed the precipitation recycling and moisture sources in the Colombian Pacific region between 1980–2017, based on the monitoring of moisture in the atmosphere through the Eulerian Water Accounting Model-2 layer (WAM2 layer) and t...

Nanosizing is an approach to improve the dissolution rate of poorly soluble drugs. The first aim of this work was to develop nanosuspension of cilostazol with liquid antisolvent precipitation (LASP) and its combination with ultrasound. Second, to sys...

The development of processing techniques for the extraction of rare earth elements and critical minerals (REE/CM) from acid mine drainage precipitates (AMDp) has attracted increased interest in recent years. Processes under development often utilize...

Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high temporal and spatial resolutions as opposed to sparse observations from rain gauges. Radar-based QPE’s have been widely used in many hydrological and met...

The lack of high spatial resolution precipitation data, which are crucial for the modeling and managing of hydrological systems, has triggered many attempts at spatial downscaling. The essence of downscaling lies in extracting extra information from...

Global Navigation Satellite System (GNSS) meteorology has emerged as a valuable tool for atmospheric monitoring, providing high-resolution, near-real-time data that can significantly improve precipitation nowcasting. This study aims to enhance short-...

Very short-term (0~3 h) radar-based quantitative precipitation forecasting (QPF), also known as nowcasting, plays an essential role in flash flood warning, water resource management, and other hydrological applications. A novel nowcasting method comb...

Calcium phosphate nanoparticles (CaP NPs) are an efficient class of nanomaterials mainly used for biomedical applications but also very promising in other sectors such as cosmetics, catalysis, water remediation, and agriculture. Unfortunately, as in...

In this study, the viability of three metaheuristic regression techniques, CatBoost (CB), random forest (RF) and extreme gradient tree boosting (XGBoost, XGB), is investigated for the prediction of monthly streamflow considering satellite precipitati...

The development of high-precision, long-term, hourly-scale precipitation data is essential for understanding extreme precipitation events. Reanalysis systems are particularly promising for this type of research due to their long-term observations and...

Precipitation extremes driven by the El Niño–Southern Oscillation (ENSO) are one of the critical ways in which the ENSO impacts the global climate, specifically in the tropical Pacific, where they have the potential to cause extreme weat...

Spatially explicit precipitation data is often responsible for the prediction accuracy of hydrological and ecological models. Several statistical downscaling approaches have been developed to map precipitation at a high spatial resolution, which are...

The Dobrogea region, located in southeastern Romania, experiences a semi-arid climate. This study provides a deep analysis of monthly precipitation series from 46 meteorological stations spanning 1965–2005, exploring mean and variance character...

Because of local climate, a phenomenon called huaico occurs in the coastal regions of Peru, configured by an alluvial flow of surface runoff caused by precipitation and accompanied by the transport of solid particles. A total of 24% of the huaicos re...

In this study, we investigate the sources of moisture (and moisture for precipitation) over the Danube River Basin (DRB) by means of a Lagrangian approach using the FLEXPART V9.0 particle dispersion model together with ERA-Interim reanalysis data to...

This study describes a framework that provides qualitative weather information on winter precipitation types using a data-driven approach. The framework incorporates the data retrieved from weather radars and the numerical weather prediction (NWP) mo...

Obtaining accurate near-real-time precipitation data and merging multiple precipitation estimates require sufficient in-situ rain gauge networks. The triple collocation (TC) approach is a novel error assessment method that does not require rain gauge...

Accurate drought identification is important for both scientists and decision-makers to be able to make informative decisions. In this study, parametric and non-parametric approaches for analyzing meteorological drought are compared, aiming at simpli...

Precipitation nowcasting is one of the main tasks of weather forecasting that aims to predict rainfall events accurately, even in low-rainfall regions. It has been observed that few studies have been devoted to predicting future radar echo images in...

Quantitative precipitation prediction is essential for managing water-related disasters, including floods, landslides, tsunamis, and droughts. Recent advances in data-driven approaches using deep learning techniques provide improved precipitation now...

This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptr...

Zinc oxide (ZnO) possesses exceptional potential to be utilized in water and wastewater treatment applications, either as a photocatalyst or in membrane incorporation. In the present study, ZnO nanoparticles were synthesized using the precipitation m...

The scarcity of groundwater and precipitation stations has limited accurate assessments of basin-scale groundwater systems. This study proposes a workflow that integrates satellite and on-site observations to improve the spatial and temporal resoluti...

The mean annual water balance is essential for evaluating water availability in a catchment and planning water resources. Climate change alters this balance by affecting precipitation, evapotranspiration, and overall water availability. This study an...

Tropical-like cyclones (TLCs) are hybrid low-pressure systems formed over the Mediterranean Sea, showing the characteristics of tropical and extratropical cyclones. The literature review revealed that several studies have focused on determining the p...

A simple approach was used to create Fe3O4-methylcellulose (MC) nanocomposites, which were then analyzed using XRD, FTIR, and FE-SEM to determine their structure. The effective factors for enhancing the ratio of magnetite NPs in the samples were inve...

Land degradation is one of the world’s most serious environmental issues. Human activities play an important role in it. Therefore, human-induced land degradation monitoring is of crucial scientific significance in revealing the evolution of la...

In the present work, a wavelet-based multiscale deep learning approach is developed to forecast precipitation using the lagged monthly rainfall, local climate variables, and global teleconnections such as IOD, PDO, NAO, and Nino 3.4 as predictors. Th...

Cost-efficient single-polarized X-band radars are a feasible alternative due to their high sensitivity and resolution, which makes them well suited for complex precipitation patterns. The first horizontal scanning weather radar in Peru was installed...

High-resolution real-time satellite-based precipitation estimation datasets can play a more essential role in flood forecasting and risk analysis of infrastructures. This is particularly true for extended deserts or mountainous areas with sparse rain...

One of the most challenging tasks in studying precipitation is quantifying how the complexities of individual components contribute to the overall system complexity. To address this, we employed information measures based on Kolmogorov complexity (KC...

Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitati...

Quantifying future changes in extreme events and associated flooding is challenging yet fundamental for stormwater managers. Along the U.S. Atlantic Coast, Eastern North Carolina (ENC) is frequently exposed to catastrophic floods from extreme rainfal...

In the open literature, there are numerous studies on the normal and extreme (flood and drought) behavior of wet and dry periods based on the understanding of the standard precipitation index (SPI), which provides a series of categorizations by consi...

This study developed a Reliability–Resiliency–Vulnerability (R–R–V) approach that aggregates the frequency, duration, and severity of droughts estimated using the Standardized Precipitation Evapotranspiration Index (SPEI). This approach was used to a...

Sustainable forest management requires accurate biometric tools to estimate forest site quality. This is particularly relevant for prescribing adequate silvicultural treatments of forest management planning. The aim of this research was to incorporat...

The Min River is the largest river in Fujian Province in southeastern China. The construction of a series of dams along the upper reaches of the Min River, especially the Shuikou Dam, which started filling in 1993, modified the flow processes at the...

The increasing global requirement for clean and safe drinking water has necessitated the development of efficient methods for the elimination of organic contaminants, especially dyes, from wastewater. This study reports the synthesis of magnesium oxi...

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serv...

The spread of many infectious diseases by vectors is a globally severe issue. Climate change and the increase of vector resistance are the primary sources of rising mosquito populations. Therefore, advanced approaches are needed to prevent the disper...