Clemente Lopez-Bravo has created two datasets – L1 and L2 – of satellite observations of cloud properties across Australia and the Maritime Continent as part of his PhD project with supervisors Claire Vincent, Yi Huang, and Todd Lane. The datasets, which have been released for the scientific community, are at a 2km spatial resolution at hourly intervals and cover five Austral summers in the period from November 2015 to March 2020. They have been derived from the Himawari-8 Advanced Himawari Imager (AHI) data and Community Satellite Processing Package for Geostationary Data, Geostationary Cloud Algorithm Testbed (CSPP-Geo Geocat, version 1.0.3).
The new collection of satellite data is the result of the integration of the high-resolution Himawari-8 AHI data, the CSPP-Geo Geocat, the ancillary data, the facilities of the National Computational Infrastructure (NCI) Australia, and several hours of data processing over the lockdown in 2020.
The L1 dataset offers full spectral resolution, and the L2 dataset provides a range of retrieved variables using the Advanced Baseline Imager Cloud Height Algorithm and Daytime and Night-time Cloud Optical and Microphysical Properties Algorithm.
Clemente and his supervisors have been using these datasets to investigate the diurnal cycle of rainfall in Sumatra to understand the morphology, lifecycle, and variability of the tropical mesoscale convective systems. They believe the datasets would be useful for research into processes across different scales such as convective storms, tropical cyclones, mid-latitude cyclones, tracking storms, estimate rainfall, the applicability of geostationary data on numerical weather prediction, and potential applications with other disciplines. They invite the community to use and explore the data, which is free and available on NCI Data Collection.
For further information, please, contact Clemente at firstname.lastname@example.org.