Representation of Tropical Cyclone Precipitation in Global Reanalysis Datasets

Every year, tropical cyclones impact communities around the world by producing rain and subsequent flooding that leads to property damage and injury. At individual locations, tropical cyclone precipitation can comprise a large percentage of annual precipitation in a given year. The accurate representation of this precipitation in datasets such as reanalyses is crucial for accurate forecasting and climate projections. This motivates a better understanding and quantification of the differences between reanalysis datasets for the purposes of forecasting and research.

Previous studies have investigated the spread of the representation of synoptic scale mid-latitude precipitation, as well as tropical cyclone lifetimes, tracks and intensities between global reanalysis datasets, but not tropical cyclone precipitation. Our study analyzes the representation of tropical cyclone precipitation in eight global reanalysis datasets by taking the official best track of tropical cyclones from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and assigning precipitation to each tropical cyclone for these reanalyses. Preliminary results quantifying the spread in tropical cyclone precipitation between the datasets are presented by considering various timescales and different regions of the world. The results are also compared to various observational precipitation datasets.