Australian Unified Radar Archive

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Fischer 2024

Overshooting Tops Climatology for 2005-2022

Hail climatology derived from overshooting tops. Generated from MTSAT and Himawari satellite datasets by Jannick Fischer at KIT (Germany) for the period 2005-2022
Methodology papers:

Bedka, K. M., Allen, J. T., Punge, H. J., Kunz, M., & Simanovic, D. (2018). A long-term overshooting convective cloud-top detection database over Australia derived from MTSAT Japanese Advanced Meteorological Imager Observations. Journal of Applied Meteorology and Climatology, 57(4), 937–951. https://doi.org/10.1175/JAMC-D-17-0056.1
Khlopenkov, K. V., Bedka, K. M., Cooney, J. W., & Itterly, K. (2021). Recent Advances in Detection of Overshooting Cloud Tops From Longwave Infrared Satellite Imagery. Journal of Geophysical Research: Atmospheres, 126(14), 1–25. https://doi.org/10.1029/2020JD034359
Punge, H. J., Bedka, K. M., Kunz, M., Bang, S. D., & Itterly, K. F. (2023). Characteristics of hail hazard in South Africa based on satellite detection of convective storms. Natural Hazards and Earth System Sciences Discussions, (November), 1–32.

Raupach et al. 2023

Climatology of and trends on hail-prone days over Australia from 1979-2021

Hail-prone day climatology is calculated using the proxy of Raupach et al., 2023a (DOI: 10.1175/MWR-D-22-0127.1) applied to ERA5 pressure-level reanalysis data (DOI: 10.24381/cds.bd0915c6) at gridded 0.25 degree resolution for 1979-2021 (daily) and March 1979-May 2022 (seasonally). A day was considered hail-prone if a hail-prone atmosphere was detected at 03, 06, or 09 UTC. Trends in hail-prone days are calculated as in Raupach et al., 2023b (DOI: 10.1038/s41612-023-00454-8).The climatology shows the mean annual hail-prone days per grid point over 1979-2021, while seasonal climatologies are over March 1979-May 2022. The trends information shows changes in annual hail-prone days over the same period.NB: The seasonal climatology values differ slightly from those in Supp. Figure 3 in Raupach et al 2023, owing to an improved calculation of the climatology. The differences for each season are less than hail-prone 0.5 days. For details of the change see https://github.com/traupach/era5_hail_climatology/blob/main/analysis/climatology_for_zenodo.ipynbThese data are licensed with a Creative Commons Attribution 4.0 International license (CC-BY-4.0, https://creativecommons.org/licenses/by/4.0/legalcode). These results contain modified Copernicus Climate Change Service information 2022. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.Journal Article: Raupach, T.H., Soderholm, J.S., Warren, R.A. et al. Changes in hail hazard across Australia: 1979–2021. npj Clim Atmos Sci 6, 143 (2023). https://doi.org/10.1038/s41612-023-00454-8Data repository: https://zenodo.org/records/10851299Acknowledgements: This research was undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government.

Warren 2024

Brook et al. 2023

A national radar-based hail climatology of Australia on a 1 degree grid. Nationally uniform hail frequencies calculated by interpolating the available radar data.

Journal Article: Brook, J. P., J. S. Soderholm, A. Protat, H. McGowan, and R. A. Warren, 2024: A Radar-Based Hail Climatology of Australia. Mon. Wea. Rev., 152, 607–628, https://doi.org/10.1175/MWR-D-23-0130.1.

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