TOOCAN-SAM/DYAMOND dataset

TOOCAN is a cloud tracking algorithm, described in Fiolleau and Roca (2013), designed to detect and track Deep Convective Systems (DCSs) using geostationary infrared observations. In this instance, the TOOCAN algorithm has been adapted and applied to the equivalent brightness temperatures of the SAM/DYAMOND simulations (Stevens et al.) to monitor the entire tropical belt within the 40°S-40°N latitudinal band over the period from 1 August to 10 September 2016.
The TOOCAN-SAM/DYAMOND 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

-Stevens, B., Satoh, M., Auger, L. et al. DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Prog Earth Planet Sci 6, 61 (2019). https://doi.org/10.1186/s40645-019-0304-z