Global tropical cyclone size and intensity reconstruction dataset for 1959–2022 based on IBTrACS and ERA5 data - Z. Xu; J. Guo; G. Zhang; Y. Ye; H. Zhao; H. Chen (Earth System Science Data)
Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. The International Best Track Archive for Climate Stewardship (IBTrACS) dataset provides widely used data to estimate TC climatology. However, it has low data coverage, lacking intensity and outer-size data for more than half of all recorded storms, and is therefore insufficient as a reference for researchers and decision makers. To fill this data gap, we reconstruct a long-term TC dataset by integrating IBTrACS and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data. This reconstructed dataset covers the period 1959–2022, with 3 h temporal resolution. Compared to the IBTrACS dataset, it contains approximately 3–4 times more data points per characteristic. We establish machine learning models to estimate the maximum sustained wind speed (Vmax) and radius of maximum wind (Rmax) in six basins for which TCs are generated, using ERA5-derived 10 m azimuthal mean azimuthal wind profiles as input, with Vmax and Rmax data from the IBTrACS dataset used as learning target data. Furthermore, we employ an empirical wind–pressure relationship and six wind profile models to estimate the minimum central pressure (Pmin) and outer size of the TCs, respectively. Overall, this high-resolution TC reconstruction dataset demonstrates global consistency with observations, exhibiting mean biases of <1 % for Vmax and 3 % for Rmax and Pmin in almost all basins. The dataset is publicly available from https://doi.org/10.5281/zenodo.13919874 (Xu et al., 2024) and substantially advances our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.