AutoNowP: An Approach Using Deep Autoencoders for Precipitation Nowcasting Based on Weather Radar Reflectivity Prediction

Detecting weather radar clutter using satellite-based nowcasting products

This contribution presents some initial results from investigations into detection of weather radar clutter by data fusion with satellite-based nowcasting products. Weather radar data from three C-band Doppler weather radars of the Danish Meteorological Institute has been extracted for cases of sea and land clutter caused by anomalous propagation as well as cases of clutter free data. In additi...

Doppler weather radar based nowcasting of cyclone Ogni

In this paper, we describe offline analysis of Indian Doppler Weather Radar (DWR) data from cyclone Ogni using a suite of radar algorithms as implemented on NEXRAD and the advanced algorithms developed jointly by the National Severe Storms Laboratory (NSSL) and the University of Oklahoma. We demonstrate the applicability of the various algorithms to Indian radar data, the improvement in the qua...

Weather Radar image Based Forecasting using Joint Series Prediction

A new approach to wind turbine power generation forecasting, using weather radar data based on Hidden Markov Model

The wind is one of the most important and affecting phenomena and is known as one of the significant clean resources of energy. Apart from other atmospheric parameters, the wind has complex behavior and intermittent characteristics. Local phenomena can be accompanied by the wind, which is strong, non-predicted, and damaging.  Weather radars are capable of detecting and displaying storm-related ...

Distributed Quantitative Precipitation Forecasting Using Information from Radar and Numerical Weather Prediction Models

The benefits of short-term (1–6 h), distributed quantitative precipitation forecasts (DQPFs) are well known. However, this area is acknowledged to be one of the most challenging in hydrometeorology. Previous studies suggest that the ‘‘state of the art’’ methods can be enhanced by exploiting relevant information from radar and numerical weather prediction (NWP) models, using process physics and ...