Examining the Historical Trends of Tropical Cyclone Frequency in the NOAA-20CRv3 Reanalysis

Despite improvements in tropical cyclone (TC) monitoring since the 1980s with geostationary weather satellites, the short duration of high-quality data limits our ability to discern long-term trends in TC activity. In this project, we analyze the TC-like storms in the NOAA-20CRv3 reanalysis dataset tracked using the algorithm TRACK (Hodges 1994). The NOAA-20CRv3 dataset spans from 1836 to 2015 and comprises 80 ensemble members. By assimilating only surface observations of sea-level pressure (SLP)-based reports, it is less affected by temporal inhomogeneities in the observational network, making it well-suited for studying long-term trends in TC activity. In our analysis, we found that the TC frequency trends in the NOAA-20CRv3 are particularly sensitive to the Lifetime Maximum Intensity (LMI) threshold considered when analyzing the trends in a subset of the storms detected. Because of this threshold dependence and the use of different datasets and tracking algorithms in previous studies (e.g. Chand et al. 2022), we will expand our analysis by comparing to trends across other reanalysis datasets. Additionally, we will examine the NOAA-20CRv3 environmental fields influencing TC frequency to better understand the reasons behind these trends.

References

Chand, S.S., et al. (2022). Declining tropical cyclone frequency under global warming. Nat. Clim. Chang. 12, 655–661, doi: 10.1038/s41558-022-01388-4.

Hodges, K.I. (1994). A general-method for tracking analysis and its application to meteorological data. Mon. Wea. Rev. 122, 2573–2586.