Abstract. The assessment of tropical cyclone (TC) statistics requires the direct, objective, and automatic detection and tracking of TCs in reanalyses and model simulations. Research groups have independently developed numerous algorithms during recent decades in order to answer that need. Today, there is a large number of trackers that aim to detect the positions of TCs in gridded datasets. The questions we ask here are the following: does the choice of tracker impact the climatology obtained? And, if it does, how should we deal with this issue? This paper compares four trackers with very different formulations in detail. We assess their performances by tracking TCs in the ERA5 reanalysis and by comparing the outcome to the IBTrACS observations database. We find typical detection rates of the trackers around 80 %. At the same time, false alarm rates (FARs) greatly vary across the four trackers and can sometimes exceed the number of genuine cyclones detected. Based on the finding that many of these false alarms (FAs) are extra-tropical cyclones (ETCs), we adapt two existing filtering methods common to all trackers. Both post-treatments dramatically impact FARs, which range from 9 % to 36 % in our final catalogs of TC tracks. We then show that different traditional metrics can be very sensitive to the particular choice of tracker, which is particularly true for the TC frequencies and their durations. By contrast, all trackers identify a robust negative bias in ERA5 TC intensities, a result already noted in previous studies. We conclude by advising against using as many trackers as possible and averaging the results. A more efficient approach would involve selecting one or a few trackers with well-known and complementary properties.
Abstract. The assessment of Tropical Cyclones (TC) statistics requires the direct, objective, and automatic detection and tracking of TCs in reanalyses and model simulations. Research groups have independently developed numerous algorithms during recent decades in order to answer that need. Today, there is a large number of algorithms, often referred to as trackers, that aim to detect the positions of tropical cyclones in gridded datasets. This paper compares four trackers with very different formulations in detail. We assess their performances by tracking tropical cyclones in the ERA5 reanalysis and by comparing the outcome to the IBTrACS observations database. The first section of the paper finds typical detection rates of the trackers ranging from 75 to 85 %. At the same time, false alarm rates (FAR) greatly vary across the four trackers and can sometimes exceed the number of detected genuine cyclones. Based on the finding that many of these false alarms are extra-tropical cyclones, we adapt two existing filtering methods common to all trackers. Both post-treatments dramatically impact FARs, which range from 9 to 36 % in our final catalogs of tropical cyclones tracks. We then show that different traditional metrics can be very sensitive to the particular choice of the tracker, which is particularly true for the TC frequencies and their durations. By contrast, all trackers identify a robust negative bias in ERA5 tropical cyclones intensities, a result already noted in previous studies. We conclude by advising against using as many trackers as possible and averaging the results. A more efficient approach would involve selecting one or a few trackers with well-known properties.
<p>The direct detection &#8212; or tracking &#8212; of tropical cyclones (TC) in gridded datasets outputs from reanalyses or model simulations is required to assess TC statistics. This issue has been tackled independently by many modeling centers or research groups; hence there is little homogeneity in the existing methods. The trackers &#8211; i.e., the algorithms used to perform that tracking -- generally fall into one of two categories: physics-based or dynamics-based. Physics-based trackers use sea-level pressure as their primary tracking variable, with additional warm-core and intensity criteria, whereas dynamics-based trackers use kinematic variables such as vorticity.</p><p>We compared four trackers taken from both categories and that we deem very different from one another in terms of their formulation: UZ (sometimes called TempestExtremes, Ullrich et al. 2021), OWZ (Tory et al. 2013), TRACK (Hodges et al. 2017) and CNRM (Chauvin et al. 2016). We assessed their performances by tracking TCs in ERA5 and comparing the outcome to the IBTrACS database &#8211; a collection of TC observations from several meteorological centers worldwide.</p><p>We find typical detection rates ranging from 70 to 80% and False Alarm (FA) rates ranging from 20 to 50% depending on the trackers. Based on the finding that a large proportion of these FAs are extra-tropical cyclones, we adapted an existing filtering method that relies on the relative positions of the detected tracks and the upper troposphere subtropical jet. When applied identically to the four trackers, it reduces FA rates to figures ranging from 9 to 30% while leaving detection rates unchanged.</p><p>Even though we were able to find most of the observed TCs in ERA5, we find, in agreement with several results in the recent literature, that their intensity is largely underestimated. However, and perhaps counterintuitively, there is no simple attenuation relationship between observed and reanalyzed TCs: for example, the strongest observed TCs are found in ERA5 with intensities covering almost the entire TC intensity scale.</p><p>We conclude by providing guidelines applicable when faced with the question of which tracker(s) to use depending on the research question. In particular, we show that using several trackers is not necessarily relevant for optimizing detection skills but combining them can be helpful to gain insight into different aspects of TCs in the same dataset.</p><p>Finally, we used the expertise gained above to track TCs in a set of HighResMIP simulations performed with the IPSL-CM7A model at different resolutions. In agreement with recent results, we find that the ability to simulate TCs improves significantly with resolution. Even though the intensity of simulated TCs remains too weak on average, the global statistics approach observations for simulations at a few tens of kilometers of horizontal resolution.</p>
<p>The ERA5 dataset from the ECMWF is the first global reanalysis product to reach a horizontal resolution of 0.28125&#176; (31km), a resolution that is thought to allow for a realistic representation of small-scale atmospheric features such as tropical cyclones.<br>Using the CNRM Tropical Cyclone Tracking Scheme carefully calibrated for ERA5 and a track pairing algorithm that uses the International Best Track dataset (IBTrACS) as reference, we investigate how well tropical cyclones (TC) are represented in ERA5.</p><p>First we show that the majority of IBTrACS systems are found by the ERA5 tracking, but that performances in terms of probability of detection and false alarm rate varies from one geographical basin to the other. Moreover, by comparing the intensities between tracked TCs from ERA5 and their observational counterparts, we show that TCs in the reanalysis are rather weak considering the spatial resolution &#8211; both in terms of maximum wind speed and pressure minimum. By looking at mean wind speed life cycles in several geographic basins we also show that TCs de-escalate too quickly after reaching their peak intensity. Finally, using a compositing technique we look at the internal structure of TCs and and that despite the weak intensity, they present expected features regarding radial and tangential wind speed and upper-core temperature anomaly when sorted by Saffir-Simpson categories.</p>
The ERA5 dataset from the European Center for Medium-Range Weather Foreceasts is the first global reanalysis to reach a horizontal resolution of 31 km and thus provides a unique opportunity to look at tropical cyclones (TC), and in particular at the 3D fields associated with observed TCs. To that end, a specifically calibrated TC tracking scheme is applied on ERA5 along with a track pairing algorithm to match the detected tracks with the IBTrACS catalog in order to investigate how well TCs are represented in the reanalysis. After tuning of the tracking scheme and the application of a dynamic mid-latitude system filtering technique, it is shown that the majority of IBTrACS TCs are detected in ERA5 and that the amount of false alarms is kept reasonably low in most regions. By comparing detected tracks with their IBTrACS counterparts, it is found that TC intensity is still strongly underestimated in ERA5 but that the minimum sea-level pressure distribution is better represented than maximum wind speed. The comparison between the life cycles from both datasets highlights key differences between ERA5 and the best-track catalog, showing in particular that the delay with which TCs from ERA5 reach their peak intensity compared to IBTrACS increases significantly with real TC intensity increase. Finally, Assessing the representation of tropical cyclones in ERA5 with the CNRM tracker the internal structure of TCs in the reanalysis for each intensity class are analyzed and reveal distinct intensification patterns up to Category 3.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.