Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year 4.890
  • CiteScore value: 4.49 CiteScore 4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Volume 10, issue 3 | Copyright
Geosci. Model Dev., 10, 1069-1090, 2017
https://doi.org/10.5194/gmd-10-1069-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 07 Mar 2017

Methods for assessment of models | 07 Mar 2017

TempestExtremes: a framework for scale-insensitive pointwise feature tracking on unstructured grids

Paul A. Ullrich1 and Colin M. Zarzycki2 Paul A. Ullrich and Colin M. Zarzycki
  • 1Department of Land, Air and Water Resources, University of California, Davis, One Shields Ave., Davis, CA 95616, USA
  • 2National Center for Atmospheric Research, Boulder, CO, USA

Abstract. This paper describes a new open-source software framework for automated pointwise feature tracking that is applicable to a wide array of climate datasets using either structured or unstructured grids. Common climatological pointwise features include tropical cyclones, extratropical cyclones and tropical easterly waves. To enable support for a wide array of detection schemes, a suite of algorithmic kernels have been developed that capture the core functionality of algorithmic tracking routines throughout the literature. A review of efforts related to pointwise feature tracking from the past 3 decades is included. Selected results using both reanalysis datasets and unstructured grid simulations are provided.

Publications Copernicus
Download
Short summary
Automated pointwise feature tracking is used for objective identification and tracking of meteorological features, such as extratropical cyclones, tropical cyclones and tropical easterly waves, and has emerged as an important and desirable data-processing capability in climate science. In the interest of exploring tracking functionality, this paper introduces a framework for the development of robust tracking algorithms that is useful for intercomparison and optimization of tracking schemes.
Automated pointwise feature tracking is used for objective identification and tracking of...
Citation
Share