tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

• Main Authors: M. Heikenfeld, P. J. Marinescu, M. Christensen, D. Watson-Parris, F. Senf, S. C. van den Heever, P. Stier
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-10-01
• Series: Geoscientific Model Development
• Online Access: https://www.geosci-model-dev.net/12/4551/2019/gmd-12-4551-2019.pdf

<p>We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as <code>Iris</code> cubes or <code>xarray</code> arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.</p>