相关论文: A Radar-Based Hail Climatology of Australia
This study makes significant contributions to the understanding of hail climatology in Austria. First, it introduces a comprehensive database of hailstone sizes, constructed from three-dimensional radar data spanning 2009 to 2022 and…
Hail risk assessment is necessary to estimate and reduce damage to crops, orchards, and infrastructure. Also, it helps to estimate and reduce consequent losses for businesses and, particularly, insurance companies. But hail forecasting is…
This paper addresses the pattern of damage, and investigates its properties, of a theoretical hail storm which gathers in intensity before subsiding, and which travels linearly across the landscape at constant velocity. We start by assuming…
The weather phenomenon of frost poses great threats to agriculture. As recent frost prediction methods are based on on-site historical data and sensors, extra development and deployment time are required for data collection in any new site.…
Extreme rainfall is one of the major causes of natural hazards (for example flood, landslide, and debris flow) in the central Himalayan region, Nepal. The performance of strategies to manage these risks relies on the accuracy of…
In this paper we discuss and address the challenges of predicting extreme atmospheric events like intense rainfall, hail, and strong winds. These events can cause significant damage and have become more frequent due to climate change.…
Gridded estimated rainfall intensity values at very high spatial and temporal resolution levels are needed as main inputs for weather prediction models to obtain accurate precipitation forecasts, and to verify the performance of…
Differential reflectivity columns (ZDRC) have been shown to provide information about a storm's updraft intensity and size. The updraft's characteristics, in turn, influence a severe storm's propensity to produce hail and the size of said…
Weather radar echoes, correlated in both space and time, are the most important input data for short-term precipitation forecast. Motivated by real datasets, this paper is concerned with the spatio-temporal modeling of two-dimensional radar…
Cities are experiencing significant warming and more frequent climate extremes, raising risks for over 90% of Australians living in cities. Yet many of our tools for climate prediction and projection lack accurate representations of these…
This study examines the use of social media and news images to detect and measure hailstones, utilizing pre-trained multimodal large language models. The dataset for this study comprises 474 crowdsourced images of hailstones from documented…
Climate change is commonly associated with an overall increase in mean temperature in a defined past time period. Many studies consider temperature trends at the global scale, but the literature is lacking in in-depth analysis of the…
We propose an innovative meteorological radar, which uses reduced number of spatiotemporal samples without compromising the accuracy of target information. Our approach extends recent research on compressed sensing (CS) for radar remote…
To mitigate the risk posed by extreme rainfall events, we require statistical models that reliably capture extremes in continuous space with dependence. However, assuming a stationary dependence structure in such models is often erroneous,…
The calibration of weather radar for detecting meteorological phenomena has advanced rapidly, aiming to enhance accuracy. Utilizing an unmanned aerial vehicle (UAV) equipped with a suspended metal sphere introduces an efficient calibration…
The field of Detection and Attribution is rapidly moving beyond weather and climate, and towards incorporating hazards and their impacts on natural and human systems. Here, we review the comprehensive literature base relevant for the UK…
Modelling of precipitation and its extremes is important for urban and agriculture planning purposes. We present a method for producing spatial predictions and measures of uncertainty for spatio-temporal data that is heavy-tailed and…
Recent wildfires in Australia have led to considerable economic loss and property destruction, and there is increasing concern that climate change may exacerbate their intensity, duration, and frequency. Hazard quantification for extreme…
A Simultaneous Localization and Mapping (SLAM) system must be robust to support long-term mobile vehicle and robot applications. However, camera and LiDAR based SLAM systems can be fragile when facing challenging illumination or weather…
We present, motivate, and evaluate Radar Maxima, a calibrated area-based probabilistic forecast product for heavy precipitation. It is designed to overcome inherent limitations of point-based forecasts, which often yield low probabilities…