Fully Spectral Method for Radar-Based Precipitation Nowcasting

Nowcasting of Precipitation

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Short-term high-resolution precipitation forecasting has important implications for navigation, flood forecasting, and other hydrological and meteorological concerns. This article introduces a pixel-based algorithm for Short-term Quantitative Precipitation Forecasting (SQPF) using radar-based rainfall data. The proposed algorithm called PixelBased Nowcasting (PBN) tracks severe storms with a hi...

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...

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the in...