Articles | Volume 12, issue 11
https://doi.org/10.5194/gmd-12-4551-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4551-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
30 Oct 2019
Methods for assessment of models |
| 30 Oct 2019
| 30 Oct 2019
tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets
Max Heikenfeld
Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Peter J. Marinescu
Department of Atmospheric Sciences, Colorado State University, Fort Collins, USA
Matthew Christensen
Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Duncan Watson-Parris
Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Fabian Senf
Leibniz Institute for Tropospheric Research, Leipzig, Germany
Susan C. van den Heever
Department of Atmospheric Sciences, Colorado State University, Fort Collins, USA
Philip Stier
CORRESPONDING AUTHOR
Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
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31 citations as recorded by crossref.
- Intelligent Identification of Convective Cloud Cores and Surrounding Stratiform Clouds S. Wenting 10.1088/1755-1315/831/1/012030
- Characteristics of hail hazard in South Africa based on satellite detection of convective storms H. Punge et al. 10.5194/nhess-23-1549-2023
- The influence of boreal summer intraseasonal oscillations on precipitation extremes and their characteristics in Southeast Asia P. Xavier et al. 10.1038/s41612-024-00658-6
- An Analysis of the Complex and Compact Outflow Cavity Carved by HOPS 361-A in NGC 2071 IR N. Karnath et al. 10.3847/1538-4357/ad67dd
- Revisiting Lightning Activity and Parameterization Using Geostationary Satellite Observations X. Zhang et al. 10.3390/rs13193866
- Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments M. Oue et al. 10.5194/amt-15-4931-2022
- The impact of aerosols and model grid spacing on a supercell storm from Swabian MOSES 2021 C. Barthlott et al. 10.1002/qj.4687
- Development and Implementation of a Physics‐Based Convective Mixing Scheme in the Community Multiscale Air Quality Modeling Framework A. Pouyaei et al. 10.1029/2021MS002475
- A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations W. Jones et al. 10.5194/amt-16-1043-2023
- A Lagrangian perspective on the lifecycle and cloud radiative effect of deep convective clouds over Africa W. Jones et al. 10.5194/acp-24-5165-2024
- Lifecycle of updrafts and mass flux in isolated deep convection over the Amazon rainforest: insights from cell tracking S. Gupta et al. 10.5194/acp-24-4487-2024
- Direct Radiative Effects in Haboobs J. Bukowski & S. van den Heever 10.1029/2021JD034814
- Weather radar utility in hazard detection and response M. Benson et al. 10.5055/jem.0868
- The semi-diurnal cycle of deep convective systems over Eastern China and its surrounding seas in summer based on an automatic tracking algorithm W. Li et al. 10.1007/s00382-020-05474-1
- Object-based analysis of simulated thunderstorms in Switzerland: application and validation of automated thunderstorm tracking with simulation data T. Raupach et al. 10.5194/gmd-14-6495-2021
- PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis Z. Feng et al. 10.5194/gmd-16-2753-2023
- Impacts of Varying Concentrations of Cloud Condensation Nuclei on Deep Convective Cloud Updrafts—A Multimodel Assessment P. Marinescu et al. 10.1175/JAS-D-20-0200.1
- Mesoscale convective systems in the third pole region: Characteristics, mechanisms and impact on precipitation J. Kukulies et al. 10.3389/feart.2023.1143380
- Tracking Mesoscale Convective Systems in IMERG and Regional Variability of Their Properties in the Tropics M. Rajagopal et al. 10.1029/2023JD038563
- Life Cycle of Shallow Marine Cumulus Clouds From Geostationary Satellite Observations T. Seelig et al. 10.1029/2021JD035577
- Increasing frequency and precipitation intensity of convective storms in the Peruvian Central Andes: Projections from convection‐permitting regional climate simulations Y. Huang et al. 10.1002/qj.4820
- Deep convective cloud system size and structure across the global tropics and subtropics E. Wilcox et al. 10.5194/amt-16-5387-2023
- Spaceborne Observations of Lightning NO2 in the Arctic X. Zhang et al. 10.1021/acs.est.2c07988
- Characteristics of Deep Convective Systems and Initiation during Warm Seasons over China and Its Vicinity Y. Li et al. 10.3390/rs13214289
- tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena G. Sokolowsky et al. 10.5194/gmd-17-5309-2024
- A database of deep convective systems derived from the intercalibrated meteorological geostationary satellite fleet and the TOOCAN algorithm (2012–2020) T. Fiolleau & R. Roca 10.5194/essd-16-4021-2024
- Aerosol–cloud impacts on aerosol detrainment and rainout in shallow maritime tropical clouds G. Leung et al. 10.5194/acp-23-5263-2023
- Aerosol breezes drive cloud and precipitation increases G. Leung & S. van den Heever 10.1038/s41467-023-37722-3
- TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets K. Núñez Ocasio & Z. Moon 10.5194/gmd-17-6035-2024
- The Precipitation Characteristics of Mesoscale Convective Systems Over Europe N. Da Silva & J. Haerter 10.1029/2023JD039045
- TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets P. Ullrich et al. 10.5194/gmd-14-5023-2021
Latest update: 01 Nov 2024
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 clouds and other features in geoscientific research.
We present tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for...
