公开英国降雨雷达数据集，用于短时预报模型训练与评估
A curated UK rain radar data set for training and benchmarking nowcasting models
- 构建1000条20步序列的英国雷达图像数据集
- 每条序列含40×40分辨率、15分钟间隔的降雨强度图
- 适合气象建模与深度学习研究者使用
本文介绍一个用于短时预报统计建模与机器学习方法的英国降雨雷达图像序列数据集。主数据集包含1000个随机采样的序列，每个序列长度为20步（每步15分钟），二维雷达强度场尺寸为40×40（空间分辨率为5公里）。通过基于阈值的截断剔除无雨时段后，采用空间分层抽样确保空间分布均匀性。每个雷达序列还附带大气与地理特征，包括日期、位置、平均海拔、平均风向风速及主导风暴类型。提供了用于解析二进制Nimrod雷达格式的新R函数，并通过案例研究训练和评估了一个简单的卷积神经网络，附带完整R代码。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。