Chasing rainfall: estimating event precipitation along tracks of tropical cyclones via reanalysis data and in-situ gauges.

Tropical cyclones (TCs) are an important water source in many regions around the world, replenishing local dams, waterways and groundwater systems. Three diverse precipitation datasets were tested for dissimilarities in their rainfall characteristics via a new, freely available rainfall tracking toolbox for MATLAB and GNU Octave users: 1) the ERA5 global reanalysis, 2) the Global Historical Climatology Network (GHCN)-Daily station dataset and 3) the regional SILO (Scientific Information for Land Owners) database. Although SILO only covers Australia, its relatively high resolution (0.05°) provides advantages for studies in that region. To test the differences in precipitation datasets, six episodes (eight individual TC events) in all major basins affected by TCs have been selected. These include two instances in which consecutive TCs severely impacted the same region (TCs Idai and Kenneth in south-eastern Africa during March/April 2019 – and hurricanes Eta and Iota in Central America in November 2020). Precipitation for TC episodes was explored through event totals and the proportional contribution to water years within each dataset. Each precipitation dataset demonstrated its inherent advantages and drawbacks, highlighting the benefits of using more than one source to thoroughly evaluate an individual event. These attributes – coupled with the associated impacts of cyclonic events – reinforce the importance of developing tools that can aid in managing TC-related rainfall and flooding potential. [Display omitted] • rainfall_tracker : free toolbox for MATLAB and GNU Octave to extract rain properties. • Six tropical cyclone events from all major basins were assessed for inconsistencies. • Up to 63% of annual rainfall accumulation was attributed to one tropical cyclone. • The ERA5, GHCN-Daily and SILO precipitation datasets were statistically different. • Uncertainty in applicable precipitation period of station data may misalign tracks. [ABSTRACT FROM AUTHOR]