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Special Issue "Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification"

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

Deadline for manuscript submissions: 31 January 2024 | Viewed by 4188

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Special Issue Editors

Dr. Mrinal K. Biswas

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Guest Editor

National Center for Atmospheric Research, Boulder, CO 80305, USA
Interests: Tropical cyclones, verification, testing and evaluation, physical parameterization

Dr. Jun A. Zhang

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Guest Editor

Hurricane Research Division, NOAA's Atlantic Oceanographic and Meteorological Laboratory 4301 Rickenbacker Causeway, Miami, FL 33149, USA
Interests: air-sea interaction; turbulence; boundary layer; tropical cyclones

Dr. Bin Liu

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Guest Editor

Lynker at NOAA/NWS/NCEP/EMC, College Park, MD 20740, USA
Interests: tropical cyclone data assimilation and forecast system development and operational transition; atmosphere-wave-ocean interaction and coupling; marine meteorology; surface wave dynamics and modeling; regional climate downscaling

Special Issue Information

Dear Colleagues,

Improved tropical cyclone (TC) predictions have come a long way during the past two decades. The advancement of high-performance computing, physical parameterizations, and data assimilation (DA) techniques has contributed significantly to the understanding of physical processes and led to improvements in TC prediction. Recent cyclones Harvey (2017), Irma (2017), Hato (2017), Debbie (2017), Michael (2018), Kong-rey (2018), Goni (2020), Amphan (2020), and Tauktae (2021), among others, have wreaked havoc, causing fatalities and property damage. Accurate forecasts of these extreme events underscore the need for better understanding of physical processes, especially for rapid intensification. The official forecasts rely on numerical weather prediction (NWP) models as well as statistical models (including single or multimodal ensembles). The success of a TC forecast entails prediction of the large-scale as well as storm-scale environment, hence requiring rigorous testing, evaluation, diagnostic studies, and tuning of the forecast models based on field experiments.

In this Special Issue, authors are invited to submit original and review articles to advance the understanding and prediction of TCs, including field experiments, DA, and their impacts on TC prediction, advances in physical parameterizations, advancement of statistical models, and verification and validation of TC products against observations.

Dr. Mrinal K. Biswas
Dr. Jun Zhang
Dr. Bin Liu
Guest Editors

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

tropical cyclones
intensity
verification
physical parameterization
data assimilation
modeling
field experiments

Published Papers (5 papers)

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Research

18 pages, 5821 KiB

Open AccessArticle

Examining the Predictability of Tropical Cyclogenesis over the East Sea of Vietnam through the Ensemble-Based Data Assimilation System

and

Atmosphere 2023, 14(11), 1671; https://doi.org/10.3390/atmos14111671 - 10 Nov 2023

Viewed by 397

Abstract

In this study, we conducted experiments to assess the forecasting capabilities for tropical cyclone (TC) genesis over the east sea of Vietnam using the ensemble-based data assimilation system (EPS-DA) by WRF-LETKF. These experiments covered forecast lead times of up to 5 days and spanned a period from 2012 to 2019, involving a total of 45 TC formation events. The evaluation involved forecast probability assessments and positional and timing error analysis. Results indicated that successful forecasting depends on the lead time and initial condition quality. For TC formation from an embryo vortex to tropical depression intensity, the EPS-DA system demonstrated improved accuracy as the forecast cycle approached the actual formation time. TC centers converged towards observed locations, highlighting the potential of assimilation up to 5 days before formation. We examined statistical variations in dynamic and thermodynamic variables relevant to TC processes, offering an objective system assessment. Our study emphasized that early warnings of TC development appear linked to formation-time environmental conditions, particularly strong vorticity and enhanced moisture processes. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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9 pages, 3080 KiB

Open AccessCommunication

Investigating the Characteristics of Tropical Cyclone Size in the Western North Pacific from 1981 to 2009

Qing Cao

Xiaoqin Lu

and

Guomin Chen

Atmosphere 2023, 14(9), 1468; https://doi.org/10.3390/atmos14091468 - 21 Sep 2023

Viewed by 504

Abstract

Tropical cyclone (TC) size is an important parameter for estimating TC risks, such as precipitation distribution, gale-force wind damage, and storm surge. This paper uses the TC size dataset compiled by the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA) to investigate the interannual, monthly variation in TC size, and the relationships between TC size and intensity in the WNP basin from 1981 to 2009. The results show that the annual mean TC size oscillated within the range of 175–210 km from 1981 to 2002, then decreased following 2003. For the monthly average TC size, there are two peaks in September and October. The TC size, overall, becomes larger with increasing intensity; the samples with an unusually large size are mainly concentrated near a 40 m s⁻¹ intensity. After the TC intensity exceeds 40 m s⁻¹, the number of unusually large size samples gradually decreases. About 60% of the TCs reach their maximum size after reaching the peak intensity, and the average lag time is 8.3 h. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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18 pages, 5623 KiB

Open AccessArticle

Diagnosing Hurricane Barry Track Errors and Evaluating Physics Scalability in the UFS Short-Range Weather Application

Nicholas D. Lybarger

Kathryn M. Newman

and

Evan A. Kalina

Atmosphere 2023, 14(9), 1457; https://doi.org/10.3390/atmos14091457 - 19 Sep 2023

Viewed by 457

Abstract

To assess the performance and scalability of the Unified Forecast System (UFS) Short-Range Weather (SRW) application, case studies are chosen to cover a wide variety of forecast applications. Here, model forecasts of Hurricane Barry (July 2019) are examined and analyzed. Several versions of the Global Forecast System (GFS) and Rapid Refresh Forecast System (RRFS) physics suites are run in the UFS-SRW at grid spacings of 25 km, 13 km, and 3 km. All model configurations produce significant track errors of up to 350 km at landfall. The track errors are investigated, and several commonalities are seen between model configurations. A westerly bias in the environmental steering flow surrounding the tropical cyclone (TC) is seen across forecasts, and this bias is coincident with a warm sea surface temperature (SST) bias and overactive convection on the eastern side of the forecasted TC. Positive feedback between the surface winds, latent heating, moisture, convection, and TC intensification is initiated by this SST bias. The asymmetric divergent flow induced by the excess convection results in all model TC tracks being diverted to the east as compared to the track derived from reanalysis. The large differences between runs using the same physics packages at different grid spacing suggest a deficiency in the scalability of these packages with respect to hurricane forecasting in vertical wind shear. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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16 pages, 5823 KiB

Open AccessArticle

Influence of Dynamic and Thermal Effects of Asian Topography on Tropical Cyclone Activity as Simulated in a Global Climate Model

Jinxiao Li

Atmosphere 2023, 14(5), 905; https://doi.org/10.3390/atmos14050905 - 22 May 2023

Viewed by 832

Abstract

Asian topography plays a significant role in regional and global weather and climate change. Based on the dataset of climate system model named CAS FGOALS-f3 participated in Global monsoons Model Inter-comparison (GMMIP), the MIP endorsement of Coupled Model Intercomparison Project Phase 6 (CMIP6), the role of Asian topography to the formation and movement of tropical cyclones (TCs) are discussed in this study. This study provides the first comparative analysis of the dynamic and thermal effects of Asian topography on the regional and global activity of TCs. The results indicate that the Asian topography promotes the generation and development of TCs, especially in the Northwest Pacific (WNP). The contribution of the Asian topography to the number of TCs reached about 50% in WNP. It is worth noting that there are still positive biases of TC track density in the experiment named “AMIP-NS”, which means the thermal effect of Asian topography is also essential for TC formation and development in WNP, which has not received much attention before. Besides, the possible reasons for the modulation of TC activity are given from two aspects: (1) The existence of Asian topography has changed the large-scale factors related to TC activities such as warm core, sea-level pressure, genesis potential index (GPI), which are beneficial to the generation and movement of TC. (2) Asian topography promotes the spread of Madden–Julian oscillation (MJO), which is also beneficial to the generation and movement of TC. It is worthwhile to investigate further the mechanisms by which Asian topography affects the activity of TCs. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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17 pages, 4252 KiB

Open AccessArticle

Evaluation of Western North Pacific Typhoon Track Forecasts in Global and Regional Models during the 2021 Typhoon Season

and

Atmosphere 2023, 14(3), 499; https://doi.org/10.3390/atmos14030499 - 04 Mar 2023

Viewed by 1234

Abstract

The track forecasts of tropical cyclones (TC) in the western North Pacific (WNP) basin during 2021 typhoon season with five global models and four regional models are evaluated here. The results show that the average direct position errors (DPEs) of the global and regional models are approximately 80, 150, 200, 300, and 400 km at 24 h, 48 h, 72 h, 96 h, and 120 h lead-times, respectively. The European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) achieved the best track forecast performance at each lead among the five global models. Among the four regional models, The China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) attained the smallest DPEs within a 72 h lead, while The Hurricane Weather Research and Forecasting (HWRF) achieved the best track forecast performance at 96 h and 120 h leads. Most of the models produced an obvious westward systematic bias on track forecast from a 24 h to a 120 h lead. Further correlation and cluster analyses indicate that initial TC intensity and size and environmental steering flow can be regarded as good predictors for TC DPEs. TCs with a stronger initial intensity, a bigger initial size, and a larger environmental steering flow in general attain a smaller DPE, and the improvements may go up to 36% at short lead-time. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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