TOOCAN dataset - Deep Convective Systems from SAM Radiative-Convective Equilibrium Simulations

This dataset contains the catalog of deep convective systems (DCSs) identified and tracked using the TOOCAN algorithm, applied to long-duration cloud-resolving simulations performed with the System for Atmospheric Modeling (SAM v6.11.2). The simulations follow the RCEMIP protocol for radiative-convective equilibrium (RCE) with prescribed sea surface temperatures of 300 K and 305 K. The SAM simulations were conducted on a 6144 × 384 km domain with 3 km horizontal resolution and variable vertical resolution, using the Rapid Radiative Transfer Model, SAM1MOM microphysics, and a TKE subgrid scheme. After a 100-day integration, the last 25 days were analyzed to exclude spin-up effects. TOOCAN was adapted from its original satellite-based framework to simulated brightness temperature (BT) fields. Outgoing longwave radiation (OLR) from SAM was converted into equivalent BT using coefficients derived via RTTOV forward radiative transfer simulations. The algorithm applies spatiotemporal segmentation to identify cold cloud systems, growing convective “seeds” from a 190 K threshold outward to 235 K. A domain-wrapping strategy ensures continuity across periodic model boundaries, with duplicate detections merged during post-processing.
The TOOCAN-SAM/RCE dataset consists of two types of files:
Regional segmented images with a 0.04° spatial resolution and a 30-minute temporal frequency (in NETCDF).
Regional and monthly tracking files (in ASCII or NETCDF), documenting the integrated morphological parameters of DCSs (e.g., lifetime duration, distance of propagation) and the evolution of DCS parameters throughout their life cycles.

References:

-Fiolleau, T. and R. Roca, 2013: An Algorithm for the Detection and Tracking of Tropical Mesoscale Convective Systems Using Infrared Images From Geostationary Satellite, IEEE Trans. Geosci. Remote Sens., vol. 51, no. 7, pp. 4302–4315. doi: 10.1109/TGRS.2012.2227762