Verif: A Weather-Prediction Verification Tool for Effective Product Development

Abstract

Abstract Verif is an open-source tool for verifying weather predictions against a ground truth. It is suitable for a range of applications and designed for iterative product development involving fine-tuning of algorithms, comparing methods, and addressing scientific issues with the product. The tool generates verification plots based on user-supplied input files containing predictions and observations for multiple point-locations, forecast lead times, and forecast initialization times. It supports over 90 verification metrics and diagrams and can evaluate deterministic and probabilistic predictions. An extensive set of command-line flags control how the input data are aggregated, filtered, stratified, and visualized. The broad range of metrics and data manipulation options allows the user to gain insight from both summary scores and detailed time series of individual weather events. Verif is suitable for many applications, including assessing numerical weather prediction models, climate models, reanalyses, machine learning models, and even the fidelity of emerging observational sources. The tool has matured through long-term development at the Norwegian Meteorological Institute and the University of British Columbia. Verif comes with an extensive wiki page and example input files covering a wide range of prediction applications, allowing students and researchers interested in verification to get hands-on experience with real-life datasets. This article describes the functionality of Verif version 1.3 and shows how the tool can be used for effective product development.