Intercomparison of four algorithms for detecting tropical cyclones using ERA5

Abstract. The assessment of tropical cyclone (TC) statistics requires the direct, objective, and automatic detection tracking TCs in reanalyses model simulations. Research groups have independently developed numerous algorithms during recent decades order to answer that need. Today, there is a large number trackers aim detect positions gridded datasets. questions we ask here are following: does choice tracker impact climatology obtained? And, if it does, how should deal with this issue? This paper compares four very different formulations detail. We assess their performances by ERA5 reanalysis comparing outcome IBTrACS observations database. find typical rates around 80 %. At same time, false alarm (FARs) greatly vary across can sometimes exceed genuine cyclones detected. Based on finding many these alarms (FAs) extra-tropical (ETCs), adapt two existing filtering methods common all trackers. Both post-treatments dramatically FARs, which range from 9 % 36 our final catalogs TC tracks. then show traditional metrics be sensitive particular tracker, particularly true for frequencies durations. By contrast, identify robust negative bias intensities, result already noted previous studies. conclude advising against using as possible averaging results. A more efficient approach would involve selecting one or few well-known complementary properties.