Can fourier neural operators replicate the intrinsic predictability of spatiotemporal chaos?: for the Kuramoto-Sivashinsky system

The use of deep learning in global weather forecasting has shown significant promise in improving both forecasting accuracy and speed. Traditional numerical weather prediction models have gradually improved forecasting skills but at the cost of increased computational complexity. In contrast, new deep learning models, trained directly on...

Novel machine learning methods for short-term solar PV forecasting: Satellite image and PV generation based forecast framework for the German energy market

With the growing global drive to act up on climate change, the adoption of renewable energy sources such as solar photovoltaic (PV) is continuously increasing. This crucial shift poses many economic and environmental benefits, however the variability in solar PV generation may also threaten the stability of our power grid and energy supply. The...

An automated approach to estimate car- bon monoxide emissions from steel plants by utilizing TROPOMI satellite measure- ments

Since the 13th of October 2017, the Tropospheric Monitoring Instrument (TROPOMI) aboard ESA’s Sentinel 5-Precursor (S5-P) satellite enables daily global measurements of carbon monoxide (CO) total column con- centrations at an unprecedented spatial resolution of 7×5.6 km. TROPOMI has the ability to detect distinct pollution plumes, arising from...

Extreme convective gusts in a future warmer climate assessed through a convection permitting model

Severe wind gusts associated with mid-latitude convective storms contribute to an increasing amount of natural hazard related losses in Europe. Modifications of the atmosphere associated with anthropogenic climate change are projected to increase the frequency of favorable conditions for convective storms, and it is absolutely critical to...

Characterizing coastal wind speed gradients using Scanning LiDAR data and mesoscale modeling

This research attempts to investigate the coastal flow structure horizontally. The flow cases with different flow directions, including perpendicular and parallel to the shoreline directions, are selected by analyzing the New Europe Wind Atlas (NEWA) reanalysis data. After the cases are determined, high-resolution Weather Research and...

Estimation of Turbulence Intensity from Cup Anemometer-Based Mean Wind Speed Data via Fractal Interpolation

In the well-known process of the turbine design, turbulence intensity (TI) plays a vital role in prediction of the power output and loads on the turbine's structure. TI is believed to be an important statistical parameter of the wind speed that can be extracted from the signals recorded by the dedicated sensors in the wind energy area. Despite...

Mesoscale Modelling of Waterspouts: An Offshore Wind Energy Perspective

Wind energy is becoming an important renewable energy source. An increased number of offshore wind farms are constructed due to the relatively higher wind speeds. Besides, compared with the land, the ocean areas offer more empty space for the installation of wind turbines. In recent years, several governments in Europe have the plan to expand...

Addressing the Grid size Sensitivity Issue in Large eddy Simulations of Stable Boundary Layers

In current study, several fundamental and inherent problems in original Deardorff subgrid model are identified under stably stratified condition. It is found that the mixing length parameterization in this subgrid model is at the root of a long trouble problem of grid size sensitivity in large-eddy simulation (LES). A new formulation of mixing...