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Atmosphere
Special Issues
Tropical Cyclone Forecasting - Analysis and Methods
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Tropical Cyclone Forecasting - Analysis and Methods

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (30 October 2022) | Viewed by 5668

Special Issue Editor

Dr. Jiaxi Hu

E-Mail Website
Guest Editor
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 73019, USA
Interests: cloud microphysics; radar meteorology; severe weather forecast; numerical modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Accurate cyclone forecasts have great societal impacts when it comes to saving lives and minimizing economic loss. Over the years, forecast methods have moved from simple subjective deductions based on observations of specific parameters such as cloud types and motions, sea swells, and pressure, to more sophisticated techniques which use complex computer models of the atmosphere. Until recently, the prediction of track, winds, rainfall, storm surge, and threatened areas was incredibly difficult. Cyclone tracks are governed by weather conditions, wind pressure, sea surface temperature, air temperature, ocean currents, and Coriolis force, which means that it is a comprehensive and difficult task to take all these parameters into consideration and produce reliable forecasts. This Special Issue invites novel research from both the observation and modeling areas. In addition, machine-learning-based methods are also highly encouraged in this Special Issue. The editor encourages potential authors to use synergistic methods from both observation and models to explore new techniques for tropical cyclone forecasting.

Dr. Jiaxi Hu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cyclone forecasting
  • cyclone dynamics
  • cyclone cloud physics
  • modeling techniques
  • observation techniques
  • machine learning techniques

Published Papers (3 papers)

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Research

25 pages, 5025 KiB  
Article
Classification Analysis of Southwest Pacific Tropical Cyclone Intensity Changes Prior to Landfall
by Rupsa Bhowmick, Jill C. Trepanier and Alex M. Haberlie
Atmosphere 2023, 14(2), 253; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14020253 - 28 Jan 2023
Cited by 1 | Viewed by 1536
Abstract
This study evaluates the ability of a random forest classifier to identify tropical cyclone (TC) intensification or weakening prior to landfall over the western region of the Southwest Pacific Ocean (SWPO) basin. For both Australia mainland and SWPO island cases, when a TC [...] Read more.
This study evaluates the ability of a random forest classifier to identify tropical cyclone (TC) intensification or weakening prior to landfall over the western region of the Southwest Pacific Ocean (SWPO) basin. For both Australia mainland and SWPO island cases, when a TC first crosses land after spending ≥24 h over the ocean, the closest hour prior to the intersection is considered as the landfall hour. If the maximum wind speed (Vmax) at the landfall hour increased or remained the same from the 24-h mark prior to landfall, the TC is labeled as intensifying and if the Vmax at the landfall hour decreases, the TC is labeled as weakening. Geophysical and aerosol variables closest to the 24 h before landfall hour were collected for each sample. The random forest model with leave-one-out cross validation and the random oversampling example technique was identified as the best-performing classifier for both mainland and island cases. The model identified longitude, initial intensity, and sea skin temperature as the most important variables for the mainland and island landfall classification decisions. Incorrectly classified cases from the test data were analyzed by sorting the cases by their initial intensity hour, landfall hour, monthly distribution, and 24-h intensity changes. TC intensity changes near land strongly impact coastal preparations such as wind damage and flood damage mitigations; hence, this study will contribute to improve identifying and prioritizing prediction of important variables contributing to TC intensity change before landfall. Full article
(This article belongs to the Special Issue Tropical Cyclone Forecasting - Analysis and Methods)
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11 pages, 2468 KiB  
Article
Sensitivity of Typhoon Forecast to Prescribed Sea Surface Temperature Data
by Jinyoung Park, Woojin Cho, Dong-Hyun Cha, Seong-Hee Won and Jung-Rim Lee
Atmosphere 2023, 14(1), 72; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14010072 - 30 Dec 2022
Viewed by 1464
Abstract
This study investigates the impact of the sea surface temperature (SST) on the forecast of two typhoons, which consecutively hit South Korea in 2020. SST data were obtained from the Daily Optimum Interpolation Sea Surface Temperature (OISST) version 2 and HYbrid Coordinate Ocean [...] Read more.
This study investigates the impact of the sea surface temperature (SST) on the forecast of two typhoons, which consecutively hit South Korea in 2020. SST data were obtained from the Daily Optimum Interpolation Sea Surface Temperature (OISST) version 2 and HYbrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation (HYCOM/NCODA; GLBy0.08/expt_93.0). When verified using in situ observational data, the OISST data did not accurately estimate the changes in SST during each typhoon’s landfall period compared to the HYCOM data since it has a relatively low temporal resolution. To investigate the impact of these two SST data on typhoon forecasts, we conducted sensitivity experiments using the Weather Research and Forecasting (WRF) model. The results showed that simulated typhoon intensities were significantly improved in the simulations with HYCOM data (HY runs), while typhoon track forecast performances were similar in both runs. In addition, the forecast performances of the maximum wind speed at 10 m during the typhoon landfall period were improved in the HY runs. Therefore, this study showed that the overall typhoon intensity and forecast performances during the landfall period could be improved when the higher temporal-resolution SST data were prescribed in the model boundary conditions for a better representation of typhoon-induced SST changes. Full article
(This article belongs to the Special Issue Tropical Cyclone Forecasting - Analysis and Methods)
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16 pages, 4606 KiB  
Article
Trends of Tropical Cyclone Translation Speed over the Western North Pacific during 1980−2018
by Danyi Gong, Xiaodong Tang, Johnny C. L. Chan and Qiuyun Wang
Atmosphere 2022, 13(6), 896; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060896 - 01 Jun 2022
Cited by 2 | Viewed by 2251
Abstract
Tropical cyclone (TC) translation speed often affects the time of strong wind attacks and precipitation accumulation in the areas that TCs pass through. Therefore, the trend of TC translation speed has important implications for TC-related risks in the current and future climate. In [...] Read more.
Tropical cyclone (TC) translation speed often affects the time of strong wind attacks and precipitation accumulation in the areas that TCs pass through. Therefore, the trend of TC translation speed has important implications for TC-related risks in the current and future climate. In this paper, the trends of TC translation speed over the Western North Pacific (WNP) from 1980 to 2018 are analyzed, and TC lifetime maximum intensity (LMI) is proposed as a factor related to the interdecadal change of translation speed. During the periods with accurate data, 1980–1997 shows a decreasing trend in TC translation speed while an increasing trend was found in 1998–2018. The main lifetime period contributing to a TC translation speed change is before the occurrence of the LMI. The change in the trend is related to both the TC’s characteristics itself and the environmental factors. For the period 1998–2018, an increasing trend of TC intensity has a significant influence on the trend of translation speed. For the environmental factors, a trend of east wind enhancement at and above 500 hPa as the steering flow is found mostly correlated in the active TC region of the WNP with westward translation before reaching LMI, accompanied by a weakening trend of 200–850 hPa vertical wind shear, and an increasing trend of potential intensity. Full article
(This article belongs to the Special Issue Tropical Cyclone Forecasting - Analysis and Methods)
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