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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-105
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-105
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: methods for assessment of models 24 May 2019

Submitted as: methods for assessment of models | 24 May 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

tobac v1.0: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Max Heikenfeld1, Peter J. Marinescu2, Matthew Christensen1, Duncan Watson-Parris1, Fabian Senf3, Susan C. van den Heever2, and Philip Stier1 Max Heikenfeld et al.
  • 1Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
  • 2Department of Atmospheric Sciences, Colorado State University, Fort Collins, USA
  • 3Leibniz Institute for Tropospheric Research, Leipzig, Germany

Abstract. 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 iris cubes or xarray 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. tobac 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.

Max Heikenfeld et al.
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Max Heikenfeld et al.
Data sets

tobac example datasets M. Heikenfeld https://doi.org/10.5281/zenodo.3195910

Max Heikenfeld et al.
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Short summary
We present tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing clouds in different types of datasets. It provides a flexible new way to include the evolution of individual clouds in a wide range of analyses. It is developed as a community project to provide a common basis for the inclusion of existing tracking algorithms and the development of new analyses that involve tracking of clouds and other features in geoscientific research.
We present tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for...
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