A curated UK rain radar data set for training and benchmarking nowcasting models
This paper documents a data set of UK rain radar image sequences for use in statistical modeling and machine learning methods for nowcasting. The main dataset contains 1,000 randomly sampled sequences of length 20 steps (15-minute increments) of 2D radar intensity fields of dimension 40x40 (at 5km spatial resolution). Spatially stratified sampling ensures spatial homogeneity despite removal of clear-sky cases by threshold-based truncation. For each radar sequence, additional atmospheric and geographic features are made available, including date, location, mean elevation, mean wind direction and speed and prevailing storm type. New R functions to extract data from the binary "Nimrod" radar data format are provided. A case study is presented to train and evaluate a simple convolutional neural network for radar nowcasting, including self-contained R code.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
OpenML Benchmarking Suites
Machine learning research depends on objectively interpretable, comparable, and reproducible algorithm benchmarks. We advocate the use of curated, comprehensive suites of machine learning tasks to standardize the setup, …
BenchmarkingBIG-bench Machine LearningGeneral ClassificationOpen Radar Initiative: Large Scale Dataset for Benchmarking of micro-Doppler Recognition Algorithms
In this paper, we discuss an "open radar initiative" aimed at promoting the sharing of radar datasets and a common framework for acquiring data. The framework is based on widely available and affordable short-range radar…
BenchmarkingBenchmarking Suite for Synthetic Aperture Radar Imagery Anomaly Detection (SARIAD) Algorithms
Anomaly detection is a key research challenge in computer vision and machine learning with applications in many fields from quality control to radar imaging. In radar imaging, specifically synthetic aperture radar (SAR),…
Anomaly DetectionBenchmarkingRadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts
Quality analysis of weather forecasts is an essential topic in meteorology. Although traditional score-based evaluation metrics can quantify certain forecast errors, they are still far from meteorological experts in term…
TRUE-Colon: Exposing a Consistent Transfer Asymmetry in Real-Time Polyp Detection
Computer-aided detection (CADe) systems for colonoscopy promise to reduce clinical miss rates, yet reliable real-world deployment remains elusive. This translational gap stems in part from a structural flaw in model deve…