Diverse Explorations of Rainfall Nowcasting with TrajGRU: Mitigating Smoothness and Fading Out Challenges for Longer Lead Times

Machine learning models offer promising potential in precipitation nowcasting. However, a common issue faced by many of these models is the tendency to produce blurry precipitation nowcasts, which are unrealistic. Previous research on the deep learning model - TrajGRU (Shi et al., 2017) indicated that data imbalance in radar images and the...

Nowcasting heavy precipitation in the Netherlands: a deep learning approach

Accurate short-term forecasts, also known as nowcasts, of heavy precipitation are desirable for creating early warning systems for extreme weather and its consequences, e.g. urban flooding. In this research, we explore the use of machine learning for short-term prediction of heavy summer rainfall showers in the Netherlands. We explore the use of...

Weather Targets Doppler Processing in Phased Array Radar with Fast Azimuthal Scanning: Phased Array Weather Radar

There is an increasing demand for a highly accurate weather system on the runway for early detection and warning of severe weather phenomena. Due to the high performances of a phased array radar system in terms of time-resolution and elevation-resolution, an already existing fast-rotating phased array radar, 60 RPM, is studied to find the...

A X-Band Patch Antenna Array With Low Cross-Polarization: For Weather Radar Applications

Meaningful dual-polarized radar estimations suitable for radar meteorology require a cross-polarization discrimination (XPD) and isolation (XPI) in excess of 30 dB to reach a differential reflectivity accuracy lower than 0.1 dB. A planar dual-polarized patch antenna array featuring low cross-polarization is proposed to meet these requirements...

Perceptual losses in precipitation nowcasting: Exploring limits and potential

Accurate short term rain predictions are important for flood early warning systems, emergency services, energy management and other services that that make weather dependent decisions. Recently introduced machine learning models suffer from blurry and unrealistic predictions at longer lead times, causing poor performance on the rarer heavy...

Consolidating Gauge, Weather Radar and GPM DPR Level 2A Observations of High-intensity Rainfall Events in the Netherlands

The Dual-Frequency Precipitation Radar on board the Global Precipitation Measurement (GPM) mission core satellite has been providing precipitation products across the globe for over 6 years, thereby even supplying precipitation estimates for areas on Earth where surface-based precipitation measurements are not possible, like in remote regions,...

Tornado Detection using a Dual Polarimetric X-band Doppler Weather Radar in The Netherlands: A Case Study

Hazardous whirlwind and tornado events are uncommon in the Netherlands. Though, the phenomenon is more frequently spotted over the last years, where significant damage is reported. In the United States, literature studies suggest that due to the increase of the Earth's surface temperature tornadoes will become more frequent and intense. This...