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

Abstract

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.

Extreme precipitation in the tropics is closely associated with long-lived convective systems

“…Designing long-lived systems dedicated cloud-resolving experiments, so far missing, would help in providing clarity on the thermodynamic, dynamical, and microphysical processes at play in extreme precipitation cases. The ready availability of tracking algorithms on model simulations 37 permits the use of the proposed duration metrics in model-based investigations.…”

The Role of Mesoscale Convective Systems in Precipitation in the Tibetan Plateau Region

“…The tracking procedure consists of three main steps: (a) cloud feature detection using IR brightness temperatures, (b) linking of cloud features over time, and (c) applying additional criteria based on co‐locations with precipitation. Using the python package tobac (Heikenfeld et al., 2019), cloud features were identified in each time step in the regridded field of IR brightness temperatures (T b ). The tracking library allows for smoothing the input field using a Gaussian filter.…”

“…However, this does not significantly affect the results, since most MCSs in the study region occur during the summer season (see Section 3.2). It should also be noted that, the merging and splitting of MCSs does not have any explicit treatment in the algorithm, but results in the survival of the MCS with the most similar travel direction (Heikenfeld et al., 2019). This way, we can identify long‐lived MCSs that grow upscale when multiple cells merge into one larger MCS.…”

“…Potential features within a restricted radius around the predicted location were then identified and the closest feature was connected with the trajectory, if its location was within a realistic distance to the previous cloud feature. More details about this linking method can be found in Heikenfeld et al (2019). To be retained as a potential MCS, the minimum area of 50,000 km 2 has to persist for at least 3 hr (six time steps).…”

Analysis of the Thermodynamic Phase Transition of Tracked Convective Clouds Based on Geostationary Satellite Observations

“…Walker et al (2012) studies the initiation of convection over the United States with 804 cases. Heikenfeld et al (2019) developed a flexible method based on the synergy of model simulations and observations and on the maximum vertical velocity, which is promising to track deep convective clouds. In most of the previous studies, the number of tracked clouds is less than 100, which limits the significance of statistical analysis.…”