Tropical cyclones (TCs) have caused billions of dollars in damage and thousands of lives lost globally over the past fifty years. Mitigating this massive socioeconomic impact requires accurate forecasts of TC evolution. Substantial progress has been made in recent years in forecasting TC position. However, progress in forecasting TC intensity and structure has been more slowly incremental. Many challenges remain in forecasting intensity and structure changes, such as rapid intensification, eyewall replacement cycles, and impacts of complex vertical wind shear. It is imperative to advance our knowledge of intensity and structure changes on theoretical, observational, and numerical modeling grounds so that TC forecasts become more accurate in the future.The goal of this Research Topic was to collect the latest advances on theories, observations, numerical modeling, and forecasting of TC intensity and structure changes. These include intensity and structure changes resulting from environmental influences (such as ocean interactions, vertical wind shear, trough interactions, upper-level outflow, and dry/dusty air intrusions); internal influences (such as inner-core dynamic instabilities and mixing processes, eyewall replacement cycles, spiral rainband dynamics, and air-sea interactions); the mutual interaction of the internal and external processes; the role of physical processes associated with the boundary layer, clouds, and radiation; advances on quantifying intensification rate theories and intensification mechanisms; and new development of forecasting techniques for TC intensity and structure. Eighteen research articles were published in this Research Topic and a summary of these articles is provided below.First, we describe the theoretical studies. Schubert and Taft (2022) used a theoretical framework to examine rapid intensification (RI) through internal TC dynamical processes. In particular, they found that when the potential vorticity (PV) core evolves rapidly enough, inertiagravity waves were excited at the edges of the PV structure. If the PV core evolved slower, inertia-gravity wave activity was more negligible. (2022) used large-eddy simulations to show that tornado-scale vortices exist in the TC boundary 78 layer and were important contributors to extreme wind gusts there. They showed that in the eyewall 79 the peak gust factors associated with these vortices were near 1.8. This reenforced the importance of 80 considering gusts in addition to the maximum sustained wind and on further understanding the 81
Editorial28 August 2023
Editorial: Tropical cyclone intensity and structure changes: theories, observations, numerical modeling and forecasting
Satellite-based remote sensing technology plays a significant role in identifying tropical cyclones (TCs), and most of the current research focuses on intensity estimation. However, analyzing the wind structure of TCs, which is directly related to the danger they bring, remains a challenge. By adding prior knowledge of TCs into the model, we propose a physics incorporated network based on multi-task learning to estimate wind radii and the intensity, whose layers can automatically extract rotation-invariant features related to the TC core from multichannel satellite imageries. In addition, we build a more comprehensive dataset including global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to tackle the structure task. We compare our model with existing methods and it shows that our model gets better results in estimating 50-knot and 64-knot wind radii, and it achieves a 4.87 knot root-mean-squared error (RMSE) of intensity. By predicting probability density functions, our model quantifies the uncertainty of the result. The experimental results show that the incorporation of rotation equivariance into the layers can enhance TC structure estimation. By considering the feature importance of multi-source predictors, we find that our model pays attention to key predictors related to TC structure. Specifically, the tangential wind speed at 500 km from the TC center and the radius of the 5 knot wind both greatly reduce the error of the estimated parameters. Specifically, the tangential wind speed at 500 km from the TC center and the radius of the 5 knot wind both greatly reduce the error of the estimated parameters. Finally, two case studies show that the proposed model performs well most of the time during the TCs' rapid intensification. However, when TCs' system is not well organized, estimating the wind structure is challenging.
Super typhoon Lekima (2019) is the 5th strongest typhoon to make landfall in mainland China since 1949. After its landfall, typhoon Lekima moved northward along the coastline, resulting in an extreme rain event in Shandong Province that makes the largest precipitation within the available meteorological records. A WRF model simulation that well produces the track and intensity of typhoon Lekima and the spatio-temporal evolution of the rainfall is used to analyze the multi-scale characteristics of the extreme rain event. Different from the typhoon precipitation occurred at low latitudes, the extreme rain event occurred in midlatitudes were influenced by the interactions of midlatitude synoptic systems and typhoon circulation, especially with five mesoscale rainbands. The midlatitude synoptic systems, mainly including the upper-tropospheric jet, the Western North Pacific Subtropical High, the mid-latitude trough, the low-level jets and typhoon Krosa (2019), allow typhoon Lekima to maintain its intensity after landfall and provide favorable kinematic, thermodynamic and moisture conditions for the heavy rainfall in Shandong. Based on the evolution of the mesoscale rainbands, the extreme rain event can be divided into three stages. The first stage can be classified as a distant rainfall, which was affected by two convective rainbands associated with boundary layer processes. The second stage had the largest precipitation, featured the formation of a frontal zone in Shandong interacting with typhoon Lekima. The third stage had weakened rainfall and was directly influenced by the spiral rainband of typhoon Lekima.
ORIGINAL RESEARCH
12 January 2023
Hui Wang, 3 more and Jia Liang
5 Authors
- HW
Hui Wang
State Key Laboratory of Severe Weather, China
- YY
Yubin Yu
State Key Laboratory of Severe Weather, China
- HX
Hongxiong Xu
State Key Laboratory of Severe Weather, China
- DZ
Dajun Zhao
State Key Laboratory of Severe Weather, China
- JL
Jia Liang
State Key Laboratory of Severe Weather, China
The complex interactions between a tropical cyclone (TC) and the midlatitude upper-level trough or cutoff low (sometimes called cold-core vortex) can lead to unusual track, such as sudden turning motion, and intensity change of the TC, often leading to large forecast errors. In this study, the track and intensity changes of Typhoon Bavi (2020) under the influence of the upper-level trough and the detached cutoff low from its base are investigated based on numerical experiments using the advanced Weather Research and Forecasting (WRF) model. Bavi formed over the western North Pacific between the Taiwan and Okinawa Islands on 23 August 2020. Under the influence of an upper-level trough to the north, Bavi initially moved northeastward. As the trough propagated eastward, a cutoff low was detached from the base of the trough on the next day. The downward penetration of the upper-level cutoff low led to a sudden northwestward turning motion of Bavi when it intensified to a severe typhoon and then moved almost due north and made landfall over North Korea. These changes and processes are well captured in a control numerical experiment. In a sensitivity experiment with the mid-latitude upper-level trough removed in the initial conditions, the TC moved primarily north-northeastward after one day simulation without the sudden northwestward turning. This track change led to an earlier landfall of the storm over South Korea and thus an earlier weakening than in the control experiment, which is termed the indirect effect on the storm intensity due to the change in the TC track. The results also show that eddy angular momentum flux convergence associated with the upper-level trough contributed little to the simulated TC intensification while the environmental VWS is key to the intensity change of Bavi.
ORIGINAL RESEARCH
5 January 2023
Zhizhong Su, 3 more and Chenchen Ding
5 Authors
- ZS
Zhizhong Su
Xiamen Key Laboratory of Straits Meteorology, China
- YM
Yunqi Ma
CMA·Henan Key Laboratory of Agrometeorological Support and Applied Technique, China
- LJ
Li Jia
State Key Laboratory of Severe Weather, China
- FR
Fumin Ren
State Key Laboratory of Severe Weather, China
- CD
Chenchen Ding
Public Meteorological Service Center of CMA, China
2,009 views
4 citations
ORIGINAL RESEARCH
19 December 2022
Wayne H. Schubert, 1 more and Christopher J. Slocum
3 Authors
- WH
Wayne H. Schubert
Department of Atmospheric Science, United States
- RK
Richard K. Taft
Department of Atmospheric Science, United States
- CJ
Christopher J. Slocum
NOAA Center for Satellite Applications and Research, United States
2,870 views
1 citations
The accurate prediction of the weakening of landfalling tropical cyclones (TC) is of great importance to the disaster prevention but is still challenging. In this study, based on the 6-hourly TC best-track data and global reanalysis data, the relationship between the intensity change prior to landfall of TCs and the energy dissipation rate after landfall over mainland China is statistically analyzed, and the difference between East and South China is compared. Results show that TCs making landfall over East China often experienced pre-landfall weakening and usually corresponded to a rapid decay after landfall, while most TCs making landfall over South China intensified prior to landfall and weakened slowly after landfall. The key factors affecting both pre-landfall intensity change and post-landfall energy dissipation rate are quantitatively analyzed. It is found that the decreasing sea surface temperature (SST), increasing SST gradient, and increasing environmental vertical wind shear are the major factors favoring high pre-landfall weakening occurrence, leading to rapid TC weakening after landfall over East China. In South China, changes in the large-scale environmental factors are relatively small and contribute little to the post-landfall weakening rate.
ORIGINAL RESEARCH
8 November 2022
Wayne H. Schubertand Richard K. Taft
2 Authors
- WH
Wayne H. Schubert
Department of Atmospheric Science, United States
- RK
Richard K. Taft
Department of Atmospheric Science, United States
The problem of tropical cyclone rapid intensification is reduced to a potential
vorticity (PV) equation and a second order, inhomogeneous, partial differential
equation for the azimuthal wind. The latter equation has the form of a
Klein-Gordon equation, the right-hand side of which involves the radial
derivative of the evolving PV field. When the PV field evolves rapidly,
inertia-gravity waves are excited at the edges of the evolving PV structure.
In contrast, when the PV field evolves slowly, the second order time derivative
term in the Klein-Gordon equation is negligible, inertia-gravity waves are not
excited, and the equation reduces to an invertibility principle for the PV.
The above concepts are presented in the context of an axisymmetric shallow
water model, in both its linear and nonlinear forms. The nonlinear results
show a remarkable sensitivity of vortex intensification to the percentage of
mass that is diabatically removed from the region inside a given absolute
angular momentum surface.
As an artificial intelligence method, machine learning (ML) has been widely used in prediction models of high-dimensional datasets. This study proposes an ML method, the Gradient Boosted Regression Tree (GBRT), to predict the intensity changes of tropical cyclones (TCs) in the Western North Pacific at 12-, 24-, 36-, 48-, 60-, and 72-hour (hr) forecasting lead time and the model is optimized by the Bayesian Optimization algorithm. The model predictands are the TCs intensity changes at different forecasting lead times, obtained from the best track data of the Shanghai Typhoon Institute (STI) and the Joint Typhoon Warning Center (JTWC) from 2000 to 2019. The model predictors are the synoptic variables, climatological and persistent variables derived from the reanalysis data obtained from the National Centers for Environmental Prediction (NCEP), and the sea surface temperature (SST) data obtained from the National Oceanic and Atmospheric Administration (NOAA). The results show that the GBRT model can capture the TCs intensity changes well for the succeeding 12-hr, 24-hr, 36-hr, …, and 72-hr. Compared with the traditional multiple linear regression (MLR) model, the GBRT model has better performance in predicting TCs intensity changes. Compared with the MLR model, R2 of the GBRT model for TCs intensity forecast increases by an average of 8.47% and 4.45% for STI data and JTWC data. MAE (RMSE) drops by 26.24% (25.14%) and 10.51% (4.68%) for the two datasets, respectively. The potential future intensity change (POT), the intensity changes during the previous 12 hr (Dvmax), Initial storm maximum wind speed (Vmax), SST, and the Sea-Land ratio are the most significant predictors for the GBRT model in predicting TCs intensity change over the Western North Pacific.
ORIGINAL RESEARCH
19 May 2022
Haiyang Liuand Xiaodong Tang
The aerosol−cloud impacts of the Tongan volcanic eruptions on the nearby tropical cyclone (TC) Cody on 14~15 January 2022 are investigated by MODIS satellite and ERA5 reanalysis data. Both the precipitation and intensity of Cody were obviously enhanced after the main blast of Tongan volcanic eruption on January 15, although the sea surface temperature and vertical wind shear of environmental wind did not change much according to ERA5 data. The vision that a large amount of volcanic aerosol flowed from the Tongan eruption into the indraft of Cody was captured by the MODIS observations on January 15. The cloud top temperature dropped, and the cloud particle effective radius decreased in Cody from then on, which indicated the occurring of deep convection there. The analyzed results of ERA5 show that convection was strengthened in the periphery of Cody at the beginning of the volcanic eruption on 03:00 UTC January 15 and later in Cody’s inner core after the main blast on 06:00 UTC January 15. This could be because of the microphysical process of aerosol−cloud interaction, which inhibited stratiform precipitation, increased vertical velocity, and enhanced convective precipitation further. Since the deep convection in the inner core was conducive to the development of Cody, the total precipitation and intensity of Cody both increased after the main blast of the volcanic eruption. The result also suggests that major volcanic eruptions could increase the convective intensity and induce heavy precipitation in a nearby organized convective system (e.g., TC or mesoscale convective systems).
ORIGINAL RESEARCH
28 June 2022
Qingyuan Liu, 3 more and Na Wei
5 Authors
- QL
Qingyuan Liu
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, China
- LW
Liguang Wu
Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, China
- NQ
Nannan Qin
State Key Laboratory of Severe Weather, China
- JS
Jinjie Song
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, China
- NW
Na Wei
Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, China
3,552 views
2 citations
ORIGINAL RESEARCH
17 June 2022
2,598 views
3 citations