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

Jaffrés, Jasmine B.D., and Gray, Jessie L. (2023) Chasing rainfall: estimating event precipitation along tracks of tropical cyclones via reanalysis data and in-situ gauges. Environmental Modelling and Software, 167. 105773.

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Abstract

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.

Item ID: 80318
Item Type: Article (Research - C1)
ISSN: 1873-6726
Keywords: Event tracking, Rainfall accumulation, Reanalysis, Station data, Toolbox, Tropical cyclones
Copyright Information: © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
Date Deposited: 14 Sep 2023 03:24
FoR Codes: 37 EARTH SCIENCES > 3701 Atmospheric sciences > 370101 Adverse weather events @ 50%
49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490399 Numerical and computational mathematics not elsewhere classified @ 30%
46 INFORMATION AND COMPUTING SCIENCES > 4601 Applied computing > 460106 Spatial data and applications @ 20%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1801 Air quality, atmosphere and weather > 180104 Weather @ 50%
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220401 Application software packages @ 50%
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