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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: closed (10 July 2024) | Viewed by 11630

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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 A. Zhang
Dr. Bin Liu
Guest Editors

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Keywords

tropical cyclones
intensity
verification
physical parameterization
data assimilation
modeling
field experiments

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Published Papers (10 papers)

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Research

17 pages, 22804 KiB

Open AccessArticle

The Diagnostic Analysis of the Thermodynamic Characteristics of Typhoon “Maysak” during Its Transformation Process

by Guanbo Zhou and Han Du

Atmosphere 2024, 15(9), 1058; https://doi.org/10.3390/atmos15091058 - 1 Sep 2024

Viewed by 465

Abstract

This study utilized high-resolution numerical simulation data from the WRF model to conduct a thermodynamic diagnosis of the process by which Typhoon “Maysak” transformed and merged with the Northeast Cold Vortex. The results indicated that the continuous intrusion of cold vortex air and the relative cold advection formed by the typhoon’s movement led to the demise of the typhoon’s warm core structure. The low-level low-pressure convergence and upper-level high-pressure divergence structure disappeared. After the transformation and merging with the Northeast Cold Vortex, the cyclone became cold throughout the entire layer, with a cold center appearing at low levels. During the process of the typhoon’s transformation and merging with the Northeast Cold Vortex, cold air accumulated near the low levels of the cyclone, causing the pseudo-adiabatic potential temperature lines to tilt and resulting in the slanted development of vertical vorticity in the mid-levels of the cyclone. After the typhoon transformed and merged with the Northeast Cold Vortex, the positive vertical vorticity advection at the bottom of the upper-level cold vortex trough promoted the cyclone’s development directly from the mid-levels to the upper levels, while the jet stream at the bottom of the cold vortex trough facilitated the maintenance of the positive vertical vorticity advection. Concurrently, the thermodynamic shear vorticity parameter could describe the typical vertical structure characteristics of the dynamic and thermodynamic fields above the rain area during the typhoon transformation process. In terms of temporal evolution trends, there was a certain correspondence with the development and movement of the ground rain area, and the perturbation thermodynamic divergence parameter had a good indicative effect on the area of heavy rainfall. Full article

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

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26 pages, 9488 KiB

Open AccessArticle

The Implementation of Cloud and Vertical Velocity Relocation/Cycling System in the Vortex Initialization of the HAFS

by JungHoon Shin, Zhan Zhang, Bin Liu, Yonghui Weng, Qingfu Liu, Avichal Mehra and Vijay Tallapragada

Atmosphere 2024, 15(8), 1006; https://doi.org/10.3390/atmos15081006 - 20 Aug 2024

Viewed by 317

Abstract

The first version operational Hurricane Analysis and Forecast System (HAFS) implemented the Vortex Initialization (VI) technique to optimize tropical cyclone structure and intensity, which was adopted from the Hurricane Weather Research and Forecasting system (HWRF) and does not initialize cloud hydrometeors and vertical velocity. This limitation in the VI caused the inconsistency issue between hurricane vortex and its cloud in the model initial condition. A new VI, which can relocate or cycle cloud hydrometeors and vertical velocity, has been developed to solve this issue. For the cold start, the VI simply relocates the cloud and vertical velocity fields of Global Forecasting System (GFS) analysis; for the warm start, the cloud and vertical velocity associated with a hurricane in the GFS analysis are replaced by the fields extracted from the 6 h HAFS forecast of a previous cycle. This new VI has been tested for the 2023 HAFS-A real-time experiment configuration, and another sensitivity experiment without relocating or cycling both cloud and vertical velocity is conducted to examine the effect of the new VI. A comparison of the results reveals that the new VI improves the intensity forecast and generates a very realistic initial cloud field in correct position. Validating the model initial conditions with observed radar data reveals that the new VI captures the secondary eyewall of major hurricanes and asymmetric convective structure of weak tropical storms. This improvement of the cloud field in the model initial condition through the new VI expects to provide a better background for further data assimilation. Additional sensitivity experiment that only relocates or cycles cloud hydrometeors without correcting the vertical velocity field results in poorer intensity forecasts, which highlights the importance of vertical velocity in the model initial condition. Full article

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

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24 pages, 14593 KiB

Open AccessArticle

The Effects of Upper-Ocean Sea Temperatures and Salinity on the Intensity Change of Tropical Cyclones over the Western North Pacific and the South China Sea: An Observational Study

by Pak-Wai Chan, Ching-Chi Lam, Tai-Wai Hui, Zhigang Gao, Hongli Fu, Chunjian Sun and Hui Su

Atmosphere 2024, 15(6), 674; https://doi.org/10.3390/atmos15060674 - 31 May 2024

Viewed by 666

Abstract

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory’s TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity’s impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. Full article

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

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22 pages, 12075 KiB

Open AccessArticle

Numerical Study of Effects of Warm Ocean Eddies on Tropical Cyclones Intensity in Northwest Pacific

by Ilkyeong Ma, Isaac Ginis and Sok Kuh Kang

Atmosphere 2024, 15(4), 445; https://doi.org/10.3390/atmos15040445 - 3 Apr 2024

Viewed by 942

Abstract

This study investigates the impact of warm core eddies (WCEs) on the ocean response and intensity of tropical cyclones (TCs) in the Northwest Pacific, focusing on three typhoons in 2018: Jebi, Trami, and Kong-rey. The research uses the Hurricane Weather Research and Forecast (HWRF) model coupled with the MPIPOM-TC ocean model. Idealized WCEs are embedded into the ocean model ahead of each TC. The impacts of WCEs are evaluated by comparing simulations with and without their presence. Uncoupled experiments with the fixed sea surface temperature (SST) serve as a reference for TC maximum potential intensity. To quantitatively assess the impact of WCEs on the SST, enthalpy fluxes, and TC intensity, a Maximum WCE Potential Index (MWPI) is introduced. Our findings indicate that for a WCE with a 200 km radius, the potential to reduce SST cooling ranges from 34 to 37%, while the potential to increase enthalpy fluxes varies between 25 and 39%. The influence of WCEs on TC intensity, as measured by minimum pressure, shows a larger variation from 27% to 48%, depending on the oceanic and atmospheric environmental conditions in each storm. Additional experiments reveal the sensitivity of the MWPI to WCE size, with TC Trami showing less sensitivity due to its slower translational speed. This study underscores the significant role of oceanic thermal conditions, particularly WCEs, in modulating TC intensity. Full article

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

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20 pages, 16515 KiB

Open AccessArticle

The Impact of High-Density Airborne Observations and Atmospheric Motion Vector Observation Assimilation on the Prediction of Rapid Intensification of Hurricane Matthew (2016)

by Xinyan Lyu and Xuguang Wang

Atmosphere 2024, 15(4), 395; https://doi.org/10.3390/atmos15040395 - 22 Mar 2024

Viewed by 751

Abstract

Tropical cyclone rapid intensification (RI) prediction still remains a big international challenge in numerical weather prediction. Hurricane Matthew (2016) underwent extreme and non-classic RI, intensifying from a Category 1 storm to a Category 5 hurricane within 24 h under a strong vertical shear environment. However, most models failed to capture this RI, and limited or no inner core, and outflow observations were assimilated in the NWS operational HWRF Model before the onset of RI for Matthew (2016). The goals of the study are to (1) explore the best way to assimilate the High-Density Observations (HDOB, including FL and SFMR) and AMV data; (2) study the impact of assimilating these observations on the analysis of both the inner-core and outflow structures; and (3) examine the impact of assimilating these data on the prediction of RI for Matthew. The main results are as follows: (1) With proper pre-processing of the HDOB observations and by using a 4DEnVar method, the inner-core structure analysis was improved. And the RI prediction is more consistent with the best track without spin-down for the first 24 h. Assimilating CIMMS AMV observations on top of the HDOB observations further improves both the track and intensity forecasts. Specifically, both the magnitude and timing of the peak intensity are further improved. (2) Diagnostics are conducted to understand how the assimilation of these different types of observations impacts RI prediction. Without assimilating HODB and AMV data, baseline experimentover-predict the intensification rate during the first 18 h, but under-predict RI after 18 h. However, the assimilation of FL and SFMR and CIMMS AMV correctly weakens the upper-level outflow and improves the shear-relative structure of the inner-core vortex, such as reducing the low-level moisture in the downshear left quadrant. The deep convection on the downshear side is weaker than baseline for the first 18 h but keeps enhancing, later moving cyclonically to the USL quadrant, and then causes more subsidence warming, maximizing in the USL quadrant and the maximum wind increases faster. Moreover, the rapid intensification rate is much more consistent with the best track and the forecast skill of RI is improved. Therefore, 4DEnVar assimilation with proper pre-processing of the high-density observations can indeed correct the shear-relative moisture and structural distributions of both the inner core and environment for TCs imbedded in the stronger shear, which is important for shear-TC RI prediction. Full article

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

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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

by Dao Nguyen-Quynh Hoa, Tran-Tan Tien, Nguyen-Y Nhu and Thi Lan Dao

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

Viewed by 1013

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

by Qing Cao, Xiaoqin Lu and Guomin Chen

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

Viewed by 1155

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

by 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 933

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

by Jinxiao Li

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

Viewed by 1454

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

by Guomin Chen, Tim Li, Mengqi Yang and Xiping Zhang

Atmosphere 2023, 14(3), 499; https://doi.org/10.3390/atmos14030499 - 4 Mar 2023

Cited by 2 | Viewed by 2417

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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