The intensity of typhoons affecting the Korean Peninsula has been rapidly increasing, resulting in significant damage. Notably, this intensification correlates with the rise in Sea Surface Temperature (SST) in the western Pacific Ocean and surroundin...
In the Asia–Pacific, where rice is an essential crop for food security and economic activity, tropical cyclones and consecutive floods can cause substantial damage to rice fields. Humanitarian organizations have developed impact-based forecasti...
The Southeast Mediterranean (SEM) is characterized by increased vulnerability to river/stream flooding. However, impact-oriented, operational fluvial flood forecasting is far away from maturity in the region. The current paper presents the first atte...
The importance of impact-based forecasting services, which can support decision-making, is being emphasized to reduce the damage of meteorological disasters, centered around the World Meteorological Organization. The Korea Meteorological Administrati...
A wind profiler radar detects fine spatiotemporal resolution dynamical information, enabling the capture of meso- and micro-scale systems. Experience gained from observing system experiments (OSEs) studies confirms that reasonable profiler assimilati...
This invited review outlines a selection of recent technical and communication advances, in certain areas of climate and weather science that could improve the capability and utility of drought early warning systems in Australia. First, a selection o...
Climate change has significantly increased multi-hazard disasters caused by typhoons, exposing the limitations of conventional forecasting systems that often neglect regional socio-economic vulnerabilities. This study develops and validates the Typho...
Drought is one of the most complex natural hazards, characterized by its slow onset, persistent nature, diverse sectoral impacts (e.g., agriculture, water resources, ecosystems), and dependence on meteorological, hydrological, and socioeconomic facto...
This study estimates the impact of dust aerosols on surface solar radiation and solar energy in Egypt based on Earth Observation (EO) related techniques. For this purpose, we exploited the synergy of monthly mean and daily post processed satellite re...
The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs) and distribution system operato...
In response to the challenges faced by traditional short-term electricity load forecasting models during holiday load predictions, a novel approach based on multifactor analysis and the Backpropagation–Gated Recurrent Unit (BP-GRU) model is pro...
A Long Short Term Memory (LSTM) based sales model has been developed to forecast the global sales of hotel business of Travel Boutique Online Holidays (TBO Holidays). The LSTM model is a multivariate model; input to the model includes several indepen...
Government Purchasing Price (Harga Pembelian Pemerintah, HPP) is a policy established to maintain stable Harvested Dry Paddy (Gabah Kering Panen, GKP) prices at the farm-gate level and to protect farmers from declining incomes due to price drops duri...
The floods triggered by the 29 October 2024 cut-off low in Valencia (Spain) expose a persistent challenge in disaster risk reduction: extensive meteorological and territorial data do not automatically become timely, trusted or actionable public guida...
In recent years Local Energy Markets (LEM) have emerged as an innovative and versatile energy trade solution. They bring benefits when renewable energy sources are used and are more flexible for consumers. There are, however, security concerns that p...
Floods have recently become a major hazard in West Africa (WA) in terms of both their magnitude and frequency. They affect livelihoods, infrastructure and production systems, hence impacting on Sustainable Development (SD). Early Warning Systems (EWS...
We describe enhancements to an operational forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The syste...
Accurate energy consumption forecasting is essential for efficient power grid management, yet existing deep learning models struggle with the multi-scale nature of energy consumption patterns. Contemporary approaches like LSTM and GRU networks proces...
Forecasting hydropower plant power production is a great challenge in the context of maintaining power system stability, reliability and efficiency, especially in an age with variable renewable energy sources when demand for electricity is steadily r...
Maintenance scheduling in large run-of-river hydropower plants requires balancing maintenance urgency, asset condition, hydrological opportunity, and operational constraints. This study proposes an integrated decision-support framework for the Santo...
Radar reflectivity assimilation is often used to initialize hydrometeors, to which Numerical Weather Prediction (NWP) is highly sensitive. To better initialize hydrometeors, this study further developed the background error covariance (BEC) with vert...
The CyFFORS (Cyprus Flood Forecasting System) project aims at increasing flood risk awareness and promoting preparedness against flooding by developing and validating a pilot flood forecasting system targeted over three river/stream basins in the Lar...
28 August 2025
This study assesses the impact of heatwaves on hospital admissions in the Matam region of Senegal by combining climatic indices with machine learning methods. Using daily maximum temperature (TMAX) and heat index (HI), heatwave events were identified...
Climate change threatens Tetraclinis articulata, a Mediterranean plant endangered by habitat loss, logging, and aridification. This study used the MaxEnt model to analyze factors affecting its distribution under current and future climate scenarios (...
Data assimilation generally assumes that observation-minus-background (OMB) departures follow an unbiased Gaussian distribution. Therefore, bias correction (BC) is essential for the effective assimilation of satellite radiances. This study applies fo...
The effective forecast and warning of pluvial flooding in real time is one of the key elements and remaining challenges of an integrated urban flood risk management. This paper presents a new methodology for integrating risk-based solutions and 2D hy...
This article examines the influence of specific time series attributes on the efficacy of fuel demand forecasting. By utilising autoregressive models and Markov chains, the research aims to determine the impact of these attributes on the effectivenes...
In previous studies, radar reflectivity is often directly assimilated using reflectivity operators based on a single-moment (SM) microphysics scheme, though the forecast model uses a double-moment (DM) microphysics scheme. With the fixed number conce...
In this study, the temperature and relative humidity profiles retrieved from five ground-based microwave radiometers in Beijing were assimilated into the rapid-refresh multi-scale analysis and prediction system-short term (RMAPS-ST). The precipitatio...
There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation...
Global navigation satellite system (GNSS) signals are affected by refraction when traveling through the troposphere, which result in tropospheric delay. Generally, the tropospheric delay is estimated as an unknown parameter in GNSS data processing. W...
Due to the deteriorating ecological environment in recent years, many countries have introduced relevant policies to support the development of clean energy. This paper focuses on wind power generation as the subject for examining green R&D diffu...
An integrated early warning system (EWS) for compound coastal and fluvial flooding is developed for Pyrgos, Western Greece, where low-lying geomorphology and past storm events highlight the need for rapid, impact-based forecasting. The methodology co...
The advancement of Numerical Weather Prediction (NWP) is pivotal for enhancing high-impact weather forecasting and warning systems. However, due to the high spatial and temporal inhomogeneity, the moisture field is difficult to describe by initial co...
The Tensift River Basin, part of the Mediterranean region, faces significant agricultural losses due to increasing drought frequency and severity, impacting up to 15% of the national GDP. The increasing climate crisis demands our immediate attention...
Flooding is the most frequent natural hazard that accompanies hardships for millions of civilians and substantial economic losses. In Sri Lanka, fluvial floods cause the highest damage to lives and properties. Ratnapura, which is in the Kalu River Ba...
The primary goal of this study is to introduce the initial phase of developing an impact-based forecasting system for extreme heatwaves, utilizing a novel multivariate index which, at this early stage, already employs a combination of a statistical a...
Introduction: Early warning systems reduce losses when risk knowledge, forecasting, communication, and response planning operate as an end-to-end chain, yet Gulf Coast warning practice often treats hazard dynamics, ecosystem change, and social vulner...
Effective weather forecast information helps smallholder farmers improve their adaptation to climate uncertainties and crop productivity. The main objective of this study was to assess the impact of weather forecast adoption on crop productivity. We...
The growth in volatile renewable energy (RE) generation is accompanied by an increasing network load and an increasing demand for storage units. Household storage systems and micro power plants, in particular, represent an uncertainty factor for dist...
Today, variable flow pattern, which uses static rule curves, is considered one of the challenges of reservoir operation. One way to overcome this problem is to develop forecast-based rule curves. However, managers must have an estimate of the influen...
Wind energy and wind power forecast errors have a direct impact on operational decision problems involved in the integration of this form of energy into the electricity system. As the relationship between wind and the generated power is highly nonlin...
This paper applies a two-tier model based on fuel hedging (model 1) and the testing of the impact of commodity risk on airline capacity forecasting, which is based on a system dynamics framework (model 2). Model 1 provides a comprehensive examination...
To improve the landfalling tropical cyclone (TC) forecasting, the pseudo inner-core observations derived from the optimal-member forecast (OPT) and its probability-matched mean (OPTPM) of a mesoscale ensemble prediction system, namely TREPS, were ass...
COVID-19 has imposed tremendously complex impacts on the container throughput of ports, which poses big challenges for traditional forecasting methods. This paper proposes a novel decomposition–ensemble forecasting method to forecast container...
Surface ozone is one of six air pollutants designated as harmful by National Ambient Air Quality Standards because it can adversely impact human health and the environment. Thus, ozone forecasting is a critical task that can help people avoid dangero...
Accurate forecasting of meteorological parameters is essential for the reliable operation and performance optimization of photovoltaic (PV) power plants. Among these parameters, ambient temperature and global horizontal irradiance (GHI) have the most...
This study examines the impacts of assimilating ocean-surface winds derived from the NASA Cyclone Global Navigation Satellite System (CYGNSS) on improving the short-range numerical simulations and forecasts of landfalling hurricanes using the NCEP op...
Prescribed burning (PB) is practiced throughout the USA, most extensively in the southeast, for the purpose of maintaining and improving the ecosystem and reducing wildfire risk. However, PB emissions contribute significantly to trace gas and particu...
Previous research provides conflicting results regarding how R&D expenditures impact market value. Given that financial analysts are the primary intermediaries between companies and investors, our study focused on the impact of R&D-related un...
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