Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Three years of monitoring severe hailswaths across Canada using radar

View through CrossRef
One of the primary goals of the Northern Hail Project (NHP) is to generate the first detailed hail climatology for Canada. To do this, we are adopting several independent approaches. One of these is the use of the Maximum Expected Size of Hail (MESH) from radar data. Most of the 33 new S-band dual-polarization radars have been operational since early 2022. Using these radar data allowed us to identify hailstorms at high-spatial temporal resolution wherever we have radar data. In this research, we focused on manually identifying (and digitizing) severe hailswaths using the MESH data from 2022 through 2024.  A severe MESH hailswath is one that has a continuous 40 km long or greater track of 10 mm pixels, and must include at least 2 adjacent pixels of 30 mm or greater. A total of almost 2,000 severe hailswaths have been identified by radar to date. Although the regional year-to-year variability is significant, our analysis has identified the Canadian Prairies and far western Ontario as hot spots for long-lived, severe hailstorms. Some of the severe hailswaths in the dataset are impressive, extending over 500 km and lasting up to 6 hours. The widest hailswath in our MESH dataset is approximately 50 km across. Even though most of the MESH hailswaths in our database have occurred near or just to the north of the Canadian/U.S border, some hailswaths have occurred at the edge of our available radar network range, with the most northern MESH hailswath terminating at a latitude of 58.0 degrees north in Saskatchewan. Moving forward, we will continue to monitor severe hailswaths using a semi-automated algorithm that draws on machine vision and machine learning techniques and will be trained on the existing dataset. In 2022, we used the MESH product produced by the National Oceanic and Atmospheric Administration-Multi-Radar Multi-Sensor (NOAA-MRMS) and switched to the Environment and Climate Change Canada (ECCC) MESH product in 2023 and 2024. Although the products from the two groups are generally in good agreement, we noted that there are notable differences in the MESH values at times. Reasons for these discrepancies are being investigated using ground reference data collected by the NHP.
Title: Three years of monitoring severe hailswaths across Canada using radar
Description:
One of the primary goals of the Northern Hail Project (NHP) is to generate the first detailed hail climatology for Canada.
To do this, we are adopting several independent approaches.
One of these is the use of the Maximum Expected Size of Hail (MESH) from radar data.
Most of the 33 new S-band dual-polarization radars have been operational since early 2022.
Using these radar data allowed us to identify hailstorms at high-spatial temporal resolution wherever we have radar data.
In this research, we focused on manually identifying (and digitizing) severe hailswaths using the MESH data from 2022 through 2024.
  A severe MESH hailswath is one that has a continuous 40 km long or greater track of 10 mm pixels, and must include at least 2 adjacent pixels of 30 mm or greater.
A total of almost 2,000 severe hailswaths have been identified by radar to date.
Although the regional year-to-year variability is significant, our analysis has identified the Canadian Prairies and far western Ontario as hot spots for long-lived, severe hailstorms.
Some of the severe hailswaths in the dataset are impressive, extending over 500 km and lasting up to 6 hours.
The widest hailswath in our MESH dataset is approximately 50 km across.
Even though most of the MESH hailswaths in our database have occurred near or just to the north of the Canadian/U.
S border, some hailswaths have occurred at the edge of our available radar network range, with the most northern MESH hailswath terminating at a latitude of 58.
0 degrees north in Saskatchewan.
Moving forward, we will continue to monitor severe hailswaths using a semi-automated algorithm that draws on machine vision and machine learning techniques and will be trained on the existing dataset.
In 2022, we used the MESH product produced by the National Oceanic and Atmospheric Administration-Multi-Radar Multi-Sensor (NOAA-MRMS) and switched to the Environment and Climate Change Canada (ECCC) MESH product in 2023 and 2024.
Although the products from the two groups are generally in good agreement, we noted that there are notable differences in the MESH values at times.
Reasons for these discrepancies are being investigated using ground reference data collected by the NHP.

Related Results

The Firepond Long Range Imaging CO2 Laser Radar
The Firepond Long Range Imaging CO2 Laser Radar
The Massachusetts Institute of Technology Lincoln Laboratory has developed and tested the most advanced, high power, coherent CO2 laser radar ever built. The Firepond imaging laser...
Framework for generation of 3D weather radar data composite products
Framework for generation of 3D weather radar data composite products
Modern weather radar networks play an indispensable role in nowcasting and short-term weather forecasting. They provide high-resolution, volumetric data crucial for identifying con...
Waveform Selection For Multi-Band Multistatic Radar Networks
Waveform Selection For Multi-Band Multistatic Radar Networks
This study investigates the benefits of waveform selection by exploiting multiple illuminators of opportunity (IO) in hybrid radar systems consisting of multi-band receivers which ...
Waveform Selection For Multi-Band Multistatic Radar Networks
Waveform Selection For Multi-Band Multistatic Radar Networks
This study investigates the benefits of waveform selection by exploiting multiple illuminators of opportunity (IO) in hybrid radar systems consisting of multi-band receivers which ...
Prospects For The Canadian Petroleum Industry
Prospects For The Canadian Petroleum Industry
Introduction In contrast with the recession occurring in the U.S. oil and gas industry, and in contrast with the caution observed by investors in other parts of t...
New modeling method of millimeter-wave radar considering target radar echo intensity
New modeling method of millimeter-wave radar considering target radar echo intensity
Virtual test evaluation is an important development direction for automatic driving technology testing and evaluation. The millimeter-wave radar sensor model used in virtual test e...
Microstrip Rectangular Patch Array Antenna for Tsunami Radar
Microstrip Rectangular Patch Array Antenna for Tsunami Radar
Radar tsunami merupakan salah satu alat deteksi yang digunakan pada system peringatan awal tsunami. Radar tsunami yang umum digunakan adalah radar High frekuensi yang memiliki jara...
Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event
Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event
Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spati...

Back to Top