Related papers: Predicting Lake Erie Wave Heights using XGBoost
This study proposes a novel machine learning (ML) methodology for the efficient and cost-effective prediction of high-fidelity three-dimensional velocity fields in the wake of utility-scale turbines. The model consists of an auto-encoder…
This study investigates the effectiveness and efficiency of two variants of the XGBoost regression model, the full-capacity and lightweight (tiny) versions, for predicting the concentrations of carbon monoxide (CO) and nitrogen dioxide…
Extreme precipitation wreaks havoc throughout the world, causing billions of dollars in damage and uprooting communities, ecosystems, and economies. Accurate extreme precipitation prediction allows more time for preparation and disaster…
Wind speed retrieval at sea surface is of primary importance for scientific and operational applications. Besides weather models, in-situ measurements and remote sensing technologies, especially satellite sensors, provide complementary…
Accurate production forecasts are essential to continue facilitating the integration of renewable energy sources into the power grid. This paper illustrates how to obtain probabilistic day-ahead forecasts of wind power generation via…
The unusually warm sea surface temperature events known as marine heatwaves (MHWs) have a profound impact on marine ecosystems. Accurate prediction of extreme MHWs has significant scientific and financial worth. However, existing methods…
Recent extreme tropical cyclones caused extensive damages to critical civil infrastructure globally. To better capture the unique hurricane wind characteristics, a large eddy simulation (LES) Hurricane Boundary Layer (HBL) model is…
Significant wave height forecasting is a key problem in ocean data analytics. This task affects several maritime operations, such as managing the passage of vessels or estimating the energy production from waves. In this work, we focus on…
Accurate prediction of main engine power is essential for vessel performance optimization, fuel efficiency, and compliance with emission regulations. Conventional machine learning approaches, such as Support Vector Machines, variants of…
Accurate and timely prediction of sea fog is very important for effectively managing maritime and coastal economic activities. Given the intricate nature and inherent variability of sea fog, traditional numerical and statistical forecasting…
Accurate information on waves and storm surges is essential to understand coastal hazards that are expected to increase in view of global warming and rising sea levels. Despite the recent advancement in development and application of…
We present a wall model for large-eddy simulation that incorporates surface-roughness effects and is applicable across low- and high-speed flows, for both transitional and fully rough conditions. The model, implemented using an artificial…
Because of the impact of extreme heat waves and heat domes on society and biodiversity, their study is a key challenge. We specifically study long-lasting extreme heat waves, which are among the most important for climate impacts. Physics…
Wind energy resource assessment typically requires numerical models, but such models are too computationally intensive to consider multi-year timescales. Increasingly, unsupervised machine learning techniques are used to identify a small…
Seawater intrusion into coastal aquifers poses a significant threat to groundwater resources, especially with rising sea levels due to climate change. Accurate modeling and uncertainty quantification of this process are crucial but are…
In large lakes, ice cover plays an important role in shipping and navigation, coastal erosion, regional weather and climate, and aquatic ecosystem function. In this study, a novel deep learning model for ice cover concentration prediction…
Wind power as a renewable source of energy, has numerous economic, environmental and social benefits. In order to enhance and control renewable wind power, it is vital to utilize models that predict wind speed with high accuracy. Due to…
Real-time video applications require dynamic bitrate adjustments based on network capacity, necessitating accurate bandwidth estimation (BWE). We introduce Ivy, a novel BWE method that leverages offline meta-learning to combat data drift…
A high-resolution wave climate projection for the northwestern Atlantic Ocean has been conducted to help assess possible regional impacts due to global climate change. The spectral wave model NOAA WAVEWATCH III is utilized with three…
Accurate prediction of crop yield before harvest is of great importance for crop logistics, market planning, and food distribution around the world. Yield prediction requires monitoring of phenological and climatic characteristics over…