Tropical Cyclone Structure Research Articles

Examining tropical cyclone thermodynamic structure with TROPICS observations

Abstract This study examines the three-dimensional thermodynamic structure of a rapidly intensifying tropical cyclone (TC) through the utilization of synthetic retrievals based off of the specifications of NASA’s Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission. Proxy TROPICS vertical profiles of temperature and water vapor mixing ratio generated from the Hurricane Nature Run (HNR1; Nolan et al. 2013) are utilized to analyze the TC structure over a 10-day period that includes the HNR1 TC’s rapid intensification (RI) from a tropical storm to a major hurricane. Analyses are performed to assess how accurately TROPICS may be able to determine thermodynamic profiles both within the storm and in the environment by validating against the HNR1 model data. It is found that the TROPICS retrievals compare favorably with the HNR1 data at most heights and times with errors consistently less than the proposed mission requirements (2 K for temperature; 25% for humidity). In addition, the retrievals show the ability to qualitatively track extensive dry air that is present in the vicinity of the TC. Although a substantial dry bias is present within the storm region of the TC (between 0 – 200 km from the surface center) in the 350–550 mb layer in the TROPICS retrievals, this bias is reduced when the retrievals associated with precipitating grid points are removed from the analyses. However, despite this filtering, a significant bias remains, which suggests that the TROPICS retrievals will likely lose accuracy in regions of stronger scattering.

Changes in the Deep Convective Structures of Tropical Cyclones Associated With the Diurnal Pulse

AbstractThis study uses satellite passive microwave (PMW) and spaceborne precipitation radar (PR) observations to investigate changes in the cloud and precipitation structures of tropical cyclones (TCs) experiencing diurnal pulses (DPs). A total of 4677 PMW and 3074 PR snapshots are matched with DP and non‐DP events of TCs objectively identified from infrared satellite images. The PMW observations suggest that compared to non‐DP events, the inner‐core (0–100 km) cold clouds containing both ice and liquid particles become more frequent and widespread when DP occurs. The greatest DP‐associated enhancement of cold clouds occurs in the downshear left quadrant of weak TCs (tropical storms) and in the upshear region of moderate‐to‐strong (≥ CAT 1) hurricanes, respectively. Also, the inner‐core cold clouds of DP events still maintain a relatively symmetric distribution under high‐shear (>10 ms−1) environments compared to non‐DP counterparts. The inner‐core warm cloud, dominated by liquid hydrometeors, increases in regions right of the shear but decreases left of the shear during DP events. Similarly, PR echo‐top height statistics show significant increases of moderate‐to‐deep convection in the TC inner region (0–300 km) on DP events especially for weak TCs. Particularly, the upshear‐right quadrant has the greatest increase in moderate‐to‐deep convection during DP events. These changes lead to a deeper and more symmetric convective structure of TCs' inner region with the occurrence of DPs.

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

The urban effects on the planetary boundary layer wind structures of Typhoon Lekima (2019)

The urban effects on the planetary boundary layer (PBL) wind structures of landfalling tropical cyclones (TCs) have rarely been explored. In this study, numerical simulations for Typhoon Lekima (2019), with and without multilayer building effect parameterization (BEP) and urban land cover, were executed to investigate the urban effects on TC PBL wind structures. Validations against observations demonstrate that the simulation incorporating BEP and urban surface replicates the track, intensity and 10-m wind field of Lekima better. Based on the comparison between the simulations with and without urban land cover, urban effects were analyzed, and the possible mechanisms were examined from the perspective of turbulent transport. Results show that urban surfaces have a deceleration effect on TC wind fields overall. This deceleration effect is most pronounced near the surface and decreases with height under 1 km above ground level. Urban surfaces reduce tangential winds and radial inflow in the near-surface layer, leading to a slight decrease in TC intensity. This is primarily attributed to the enhanced downward transfer of tangential momentum and upward transfer of radial momentum within the PBL, which results in larger magnitudes of negative tangential wind tendencies and positive radial wind tendencies induced by the divergence of subgrid-scale (SGS) momentum fluxes. Additionally, stronger tangential winds and radial outflow above the elevated PBL height correspond well to the increased tangential and radial wind tendencies in nearby areas. The analysis illustrates that turbulent transport provides insights into how urban surfaces affect the PBL wind structures of TCs.

Improved tropical cyclone boundary layer model and its application in floating offshore wind turbine structural response analysis

The accurate simulation of tropical cyclone (TC) wind fields is essential for analyzing structural responses, given the potential severe damage to infrastructure caused by TCs. An improved TC boundary layer mean wind field model is proposed, building upon the Kepert model, by introducing a two-dimensional pressure field that varies with height and radius, a surface turbulent diffusivity influenced by wind speed at the lower boundary, and a surface roughness length affected by waves and spray. The accuracy of the improved model is validated through comparisons with TC observational data. Comparative analysis indicates that the Kepert model overestimates the tangential wind speed component. The two-dimensional pressure field employed in the improved model more accurately simulates the central pressure difference within the TC boundary layer. Furthermore, the incorporation of a surface turbulent diffusivity and sea surface roughness length that better reflects physical phenomena further enhances the accuracy of the improved wind field model. The structural responses of a floating offshore wind turbine (FOWT) situated in the TC eyewall region under emergency shutdown conditions are computed using both wind field models separately. The results indicate that blade tip displacement, tower top displacement, platform translation, and rotation responses (pitch and yaw) are overestimated by the Kepert model. In conclusion, the improved model accurately represents the TC structure, offering precise wind field data for assessing FOWT structural responses in TC conditions.

Evaluation of Hurricane Analysis and Forecast System (HAFS) Error Statistics Stratified by Internal Structure and Environmental Metrics

Abstract This study quantifies tropical cyclone (TC) error statistics from the Hurricane Analysis and Forecast System (HAFS) across different environmental conditions (e.g., vertical wind shear) and inner core structural metrics. A particular focus is the evolution of poorly understood aspects of internal TC structure, including vortex tilt, and their impact on forecast errors. Although previous studies have demonstrated that vortex tilt, vertical wind shear, and precipitation processes impact TC intensity and track, this is the first known study to stratify these cooperative interactions to gain insights on their relationships with forecast errors. A three-year retrospective sample of forecasts in the North Atlantic basin from two HAFS configurations (-A and -B) demonstrates that TCs with larger tilt magnitudes have larger forecast track errors on average than smaller tilt TCs. Smaller tilt magnitudes have larger absolute intensity errors in short range forecasts, whereas larger tilt magnitudes tend to have larger negative intensity biases at medium range. TCs with a tilted vortex are shown to have both left of shear (maximizing DSL) and left of tilt oriented positional track biases. Furthermore, those cases with greater downshear biases tend to have more convection and larger positive intensity biases, highlighting the importance of the interplay between inner core characteristics and forecast errors.

The role of diabatic heating/cooling in outer rainbands in the secondary eyewall formation and evolution in a numerically simulated tropical cyclone

In this study, the role of diabatic heating/cooling in outer rainbands (ORBs) in the formation and evolution of the secondary eyewall of a numerically simulated tropical cyclone (TC) is investigated. This is done through a series of sensitivity experiments under idealized conditions using a high-resolution cloud-resolving atmospheric model. The results show that artificially increasing diabatic heating in rainbands enhances convective activities in ORBs and leads to an earlier secondary eyewall formation (SEF), and later the faster weakening and earlier dissipation of the primary eyewall. Reducing diabatic heating in ORBs weakens the rainbands and delays the SEF but prolongs the duration of the double eyewall structure if the SEF occurs. Reducing diabatic cooling in ORBs enhances convective activity in rainbands but has little effect on convection in the primary eyewall prior to the SEF. However, it results in a widened eyewall structure and a stronger TC after the eyewall replacement. Increasing diabatic cooling in ORBs largely suppresses convection in rainbands and prohibits the SEF. These results demonstrate that diabatic heating/cooling in ORBs plays important roles in the SEF and evolution. Since diabatic heating/cooling in rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the critical importance of large-scale environmental moist condition to the formation and evolution of secondary eyewall in TCs. In addition, it is also found that when the area-averaged diabatic heating rate in ORBs becomes similar in magnitude to that in the primary eyewall, the secondary eyewall forms. Plain language summaryPrevious studies have demonstrated the importance of diabatic heating/cooling in outer rainbands to the structure and intensity changes of tropical cyclones (TCs) with a single eyewall. It is unclear whether and how diabatic heating/cooling in outer rainbands may affect the formation and evolution of the secondary eyewall in TCs. These issues have been addressed based on a series of sensitivity experiments under idealized conditions using a high-resolution atmospheric model. Results show that diabatic heating in outer rainbands is favorable for the secondary eyewall formation (SEF). Increasing diabatic heating in outer eyewall can lead to faster weakening and thus earlier dissipation of the primary eyewall. Diabatic cooling in outer rainbands suppresses convection in outer rainbands and prohibits the SEF. Since diabatic heating/cooling in outer rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the importance of the large-scale environmental moist condition to the SEF of TCs. We also found that when the area-averaged diabatic heating rate in outer rainbands becomes similar in magnitude to that in the primary eyewall, the secondary eyewall would form, which can be considered as a measure of the SEF in TCs. Key points1.Increasing diabatic heating in outer rainbands leads to earlier SEF, and faster weakening and earlier dissipation of the primary eyewall.2.Increasing diabatic cooling in outer rainbands suppresses convective activity in outer rainbands and is unfavorable for the SEF.3.When the area-averaged diabatic heating rate in outer rainbands and the eyewall become similar in magnitude, the secondary eyewall forms.

Tropical Cyclone Ocean Winds and Structure Parameters Retrieved from Cross-Polarized SAR Measurements

Tropical Cyclone Ocean Winds and Structure Parameters Retrieved from Cross-Polarized SAR Measurements

The impact of coupling a dynamic ocean in the Hurricane Analysis and Forecast System

Coupling a three-dimensional ocean circulation model to an atmospheric model can significantly improve forecasting of tropical cyclones (TCs). This is particularly true of forecasts for TC intensity (maximum sustained surface wind and minimum central pressure), but also for structure (e.g., surface wind-field sizes). This study seeks to explore the physical mechanisms by which a dynamic ocean influences TC evolution, using an operational TC model. The authors evaluated impacts of ocean-coupling on TC intensity and structure forecasts from NOAA’s Hurricane Analysis and Forecast System v1.0 B (HFSB), which became operational at the NOAA National Weather Service in 2023. The study compared existing HFSB coupled simulations with simulations using an identical model configuration in which the dynamic ocean coupling was replaced by a simple diurnally varying sea surface temperature model. The authors analyzed TCs of interest from the 2020–2022 Atlantic hurricane seasons, selecting forecast cycles with small coupled track-forecast errors for detailed analysis. The results show the link between the dynamic, coupled ocean response to TCs and coincident TC structural changes directly related to changing intensity and surface wind-field size. These results show the importance of coupling in forecasting slower-moving TCs and those with larger surface wind fields. However, there are unexpected instances where coupling impacts the near-TC atmospheric environment (e.g., mid-level moisture intrusion), ultimately affecting intensity forecasts. These results suggest that, even for more rapidly moving and smaller TCs, the influence of the ocean response to the wind field in the near-TC atmospheric environment is important for TC forecasting. The authors also examined cases where coupling degrades forecast performance. Statistical comparisons of coupled versus uncoupled HFSB further show an interesting tendency: high biases in peak surface winds for the uncoupled forecasts contrast with corresponding low biases, contrary to expectations, in coupled forecasts; the coupled forecasts also show a significant negative bias in the radii of 34 kt winds relative to National Hurricane Center best track estimates. By contrast, coupled forecasts show very small bias in minimum central pressure compared with a strong negative bias in uncoupled. Possible explanations for these discrepancies are discussed. The ultimate goal of this work will be to enable better evaluation and forecast improvement of TC models in future work.

Quality Control of Geostationary Lightning Mapper Observations for Tropical Cyclone Applications

Abstract The Geostationary Lightning Mapper (GLM) has been providing unprecedented observations of total lightning since becoming operational in 2017. The potential for GLM observations to be used for forecasting and analyzing tropical cyclone (TC) structure and intensity has been complicated by inconsistencies in the GLM data from a number of artifacts. The algorithm that processes raw GLM data has improved with time; however, the need for a consistent long-term dataset has motivated the development of quality control (QC) techniques to help remove clear artifacts such as blooming events, spurious false lightning, ‘bar’ effects, and sun glint. Simple QC methods are applied that include scaled maximum energy thresholds and minima in the variance of lightning group area and group energy. QC and anomaly detection methods based on machine learning (ML) are also explored. Each QC method is successfully able to remove artifacts in the GLM observations while maintaining the fidelity of the GLM observations within TCs. As the GLM processing algorithm has improved with time, the amount of QC flagged lightning within 100 km of Atlantic TCs is reduced, from 70% during 2017, to 10% in 2018, to 2% during 2021. These QC methods are relevant to the design of ML-based forecasting techniques which could pick up on artifacts rather than the signal of interest in TCs if QC wasn’t applied beforehand.

Thermodynamic Pathways of Vertical Wind Shear Impacting Tropical Cyclone Intensity Change: Energetics and Lagrangian Analysis

Abstract This study analyzes the variations in the thermodynamic cycle and energy of a tropical cyclone (TC) under the influence of vertical wind shear (VWS), exploring the possible thermodynamic pathways through which VWS affects TC intensity. The maximum energy harnessed by the TC diminishes alongside a decrease in storm intensity in the presence of VWS. In the sheared TC, the ascending branch of the thermodynamic cycles of TC shifts toward lower entropy, which is related to the reduction in entropy in the eyewall and/or the increase in entropy and enhanced upward motion outside the eyewall. Moreover, the descending leg shifts toward higher entropy due to the increase in entropy and weakening of downward motion in both the ambient environment and the upper troposphere. These changes in the ascending and descending branches could reduce the work done by the heat engine cycle, with the former playing a primary role in the presence of VWS. Given that the ascending branch is influenced by the eyewall and the rainbands outside the eyewall under VWS, the thermodynamic pathways could be categorized into inner ventilation and outer ventilation based on the location of their roles. The pathways associated with inner ventilation primarily reduce the entropy in the eyewall. In addition to the conventional low- and midlevel ventilation, the inner ventilation also encompasses new pathways entering the midlevel eyewall after descending from the upper level and ascending from the boundary layer. Conversely, the pathways of outer ventilation are related to the increase in the entropy outside the eyewall. These include the ascent of high-entropy air to the middle and upper troposphere related to the inner and outer rainbands, the outward advection of high-entropy air from the eyewall in the midlevel and upper level, and air warming by the descending draft from the upper- to midlevel troposphere. These insights contribute to a nuanced understanding of the sophisticated interactions within TCs and their response to VWS. Significance Statement Vertical wind shear (VWS) is known to modify the thermodynamic structure of tropical cyclones (TCs), thereby affecting their development. The incorporation of multiple thermodynamic mechanisms amplifies the complexity of related studies and predictions. Within the context of a unified heat engine framework, this study aims to paint a relatively comprehensive picture of the key thermodynamic pathways through which VWS impacts the intensity of TCs. Contrary to previous studies, we emphasize the increase in entropy and the intensified upward motion outside the eyewall, which play pivotal roles in diminishing the intensity of TCs in the presence of VWS. Gaining an understanding of these critical mechanisms and structural changes offers insights and guidance that can enhance the prediction of sheared TCs.

Comparison of tropical cyclone structures over different ocean basins revealed in COSMIC-2 radio occultation observations

Utilizing three-years COSMIC-2 radio occultation (RO) bending angle (BA) observations from 1 October 2019 to 31 December 2022, composite structures of BA anomalies α−α¯env/α¯env in vertical and radial directions are generated for hurricanes, tropical storms and tropical depressions over the ocean basins of North Atlantic, West Pacific, East Pacific, South Pacific, North Indian, and South Indian. The magnitude and altitude of the maximum BA anomaly within hurricanes, tropical storms and tropical depressions are about (6 km, 14%), (5 km, 11%) and (3.5 km, 9%), respectively. The vertical and radial extents of BA anomaly exceeding 6% are (6 km, 450 km) and (7 km, 500 km) over North Atlantic and West Pacific oceans, respectively. The warm core of hurricane over East Pacific ocean displays the widest radial extent (650 km), while that over North India ocean has the deepest vertical extent (8.5 km). As expected, the BA anomalies of tropical storms and tropical depressions are weaker in magnitude and smaller in size than those of hurricanes. An exception is found for the maximum BA anomaly of hurricanes over South Pacific ocean is not located near hurricane centers but at the 175-km radial distance. Accordingly, the mean altitudes of the atmospheric boundary layer estimated from COSMIC-2 BA observations increase from the 175-km radial distances to both sides for hurricanes over South Pacific ocean, while those over the other five ocean basins increase from eye centers outward.

Are Forecasts of the Tropical Cyclone Radius of Maximum Wind Skillful?

AbstractThe radius of maximum wind (RMW) defines the location of the maximum winds in a tropical cyclone and is critical to understanding intensity change as well as hazard impacts. A comparison between the Hurricane Analysis and Forecast System (HAFS) models and two statistical models based off the National Hurricane Center official forecast is conducted relative to a new baseline climatology to better understand whether models have skill in forecasting the RMW of North Atlantic tropical cyclones. On average, the HAFS models are less skillful than the climatology and persistence baseline and two statistically derived RMW estimates. The performance of the HAFS models is dependent on intensity with better skill for stronger tropical cyclones compared to weaker tropical cyclones. To further improve guidance of tropical cyclone hazards, more work needs to be done to improve forecasts of tropical cyclone structure.

Escalating tropical cyclone precipitation extremes and landslide hazards in South China under global warming

Tropical cyclones (TCs) are expected to produce more intense precipitation under global warming. However, substantial uncertainties exist in the projection of coarse-resolution global climate models. Here, we use deep learning to aid targeted cloud-resolving simulations of extreme TCs. Contrary to the Clausius-Clapeyron (CC) scaling, which indicates a 7% moisture increase per K warming, our simulations reveal more complex responses of TC rainfall. TCs will not intensify via strengthened updrafts but through the expansion of deep convective cores with suppression of shallow cumulus and congestus. Consequently, while localized hourly rainfall may adhere to the CC scaling, precipitation accumulation over city-sized areas could surge by 18%K-1. This super-CC intensification due to changing TC structure has profound implications for floods and landslides. Estimations using Hong Kong’s slope data confirm this concern and suggest an up to 215% increase in landslide risks with 4-K warming, highlighting amplified threats from compound disasters under climate change.

A flexible tropical cyclone vortex initialization technique for GFDL SHiELD

Tropical cyclone (TC) intensity forecasting poses challenges due to complex dynamical processes and data inadequacies during model initialization. This paper describes efforts to improve TC intensity prediction in the Geophysical Fluid Dynamics Laboratory (GFDL) System for High-resolution prediction on Earth-to-Local Domains (SHiELD) model by implementing a Vortex Initialization (VI) technique. The GFDL SHiELD model, relying on the Global Forecast System (GFS) analysis for initialization, faces deficiencies in initial TC structure and intensity. The VI method involves adjusting the TC vortex inherited from the GFS analysis and merging it back into the environment at the observed location, enhancing the analyzed representation of storm structure. We made modifications to the VI package implemented in the operational Hurricane Analysis and Forecast System, including handling initial condition data, reducing input domain size, and improving storm intensity enhancement. Experiments using the T-SHiELD configuration demonstrate that using VI significantly improves the representation of initial TC intensity and size, enhancing TC predictions, particularly in storm intensity and outer wind forecasts within the first 48 h.

Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parametrization in the Weather Research and Forecasting model

Abstract. Mesoscale modeling can be used to analyze key parameters for wind turbine load assessment in a large variety of tropical cyclones. However, the modeled wind structure of tropical cyclones is known to be sensitive to the boundary layer scheme. We analyze modeled wind speed, shear, and wind veer across a wind turbine rotor plane in the eyewall and outer cyclone. We further assess the sensitivity of wind speed, shear, and veer to the boundary layer parametrization. Three model realizations of Typhoon Megi are analyzed over the open ocean using three frequently used boundary layer schemes in the Weather Research and Forecasting (WRF) model. All three typhoon simulations reasonably reproduce the cyclone track and structure. The boundary layer parametrization causes up to 15 % differences in median wind speed at hub height between the simulations. The simulated wind speed variability also depends on the boundary layer scheme. The modeled median wind shear is smaller than or equal to 0.11 used in the current IEC (International Electrotechnical Commission) standard regardless of the boundary layer scheme for the eyewall and outer cyclone region. However, up to 43.6 % of the simulated wind profiles in the eyewall region exceed 0.11. While the surface inflow angle is sensitive to the boundary layer scheme, wind veer in the lowest 400 m of the atmospheric boundary layer is less affected by the boundary layer scheme. Simulated median wind veer reaches values up to 1.7×10-2° m−1 (1.2×10-2° m−1) in the eyewall region (outer cyclone region) and is relatively small compared to moderate-wind-speed regimes. On average, simulated wind speed shear and wind veer are highest in the eyewall region. Yet strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads due to rapid changes in the wind profile at the turbine location.

Sensitivity of HAFS-B Tropical Cyclone Forecasts to Planetary Boundary Layer and Microphysics Parameterizations

Abstract Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and three sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the days 3–4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-kt (1 kt ≈ 0.51 m s−1) wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results. Significance Statement A new hurricane model, the Hurricane Analysis and Forecast System (HAFS), is being introduced for operational prediction during the 2023 hurricane season. One of the most important parts of any forecast model are the “physics parameterizations,” or approximations of physical processes that govern things like turbulence, cloud formation, etc. In this study, we tested these approximations in one configuration of HAFS, HAFS-B. Specifically, we looked at two different versions of the microphysics (modeling the growth of water and ice in clouds) and boundary layer physics (the approximations for turbulence in the lowest level of the atmosphere). We found that both of these sets of model physics had important effects on the forecasts from HAFS. The microphysics had notable impacts on the track forecasts, and also changed the vertical depth of the model hurricanes. The boundary layer physics, including some of our changes based on observed hurricanes and turbulence-resolving models, helped the model better predict rapid intensification (periods where the wind speed increases quickly). Work is ongoing to improve the model physics for better forecasts of rapid intensification and overall storm structure, including storm size. The study also shows the combination of both PBL and microphysics modifications overall leads to the best results and thus was used as one of the two first operational implementations of HAFS.

The Role of the Peak Radius of Maximum Wind Contraction Rate Preceding the Peak Intensification Rate on Tropical Cyclone Lifetime Maximum Intensity

AbstractThe prevalence of the maximum radius of maximum wind (RMW) contraction rate for the tropical cyclone (TC) before the maximum TC intensification rate has been observed in several previous studies. However, it remains unclear whether and how the maximum RMW contraction rate preceding the maximum TC intensification rate affects the TC lifetime maximum intensity (LMI). In this study, tropical cyclones are grouped into three types depending on whether the peak RMW contraction rate precedes, occurs simultaneously with, or lags the time of the peak intensification rate in the North Atlantic and western North Pacific. Results indicate that when the maximum RMW contraction rate occurs before the maximum intensification rate, TCs are more likely to gain a greater LMI. TCs with the time of maximum RMW contraction rate preceding the time of the maximum intensification rate are more likely to achieve a small RMW and intermediate intensity after the maximum RMW contraction rate period, which is conducive to higher intensification rates. An intermediate initial intensity and higher maximum intensification rate both lead to a greater LMI. Environmental factors are also examined but are found to have little impact on the LMI for the three types of TCs. This work suggests that TCs with a higher LMI are often characterized by a notable maximum rate of RMW contraction before the peak intensification rate and helps to a better understanding of TC structure and intensity changes.

Implementation and evaluation of a spectral cumulus parametrization for simulating tropical cyclones in JMA‐GSM

AbstractA spectral cumulus parametrization (spectral scheme) developed using a cloud‐resolving model simulation was implemented in Global Spectral Model of the Japan Meteorological Agency (JMA‐GSM, GSM hereafter). The performance of the spectral scheme in terms of mean state, variability, and tropical cyclone (TC) properties was evaluated using atmosphere‐only model experiments by comparing results of the original convection scheme (based on Arakawa–Schubert scheme, AS scheme) and the spectral scheme. Parameter tunings were first conducted for the spectral scheme, through which the climatological errors of the cloud cover in the Southern Ocean and temperature were greatly improved. The spectral scheme showed comparable climatological errors to the AS scheme in the increased resolutions. The spectral scheme greatly improved tropical variability, that is, response to El Niño/Southern Oscillation and Madden–Julian Oscillation. Analyses on TC statistical data revealed that the spectral scheme improved TC properties in terms of genesis frequency, intensity, and the response of TC to tropical variability. Specifically, significant improvements were seen in the Northern Hemisphere. Further analyses on the TC structure revealed that higher TC intensity was sustained for longer times by the spectral scheme than by the AS scheme. The reason for this is that the spectral scheme better simulates convective heating by considering coexistence of different cloud types with parametrized vertically varying entrainment rates, especially from low to mid‐altitudes. The convective heating leads to a sharper vertical‐radial circulation in the TC structure, causing stronger incoming moisture flux toward the TC centre, and resulting in a stronger TC intensity. Consequently, the spectral scheme can simulate a comparable mean state, better variability, and better TC properties compared with the original scheme by simulating a more detailed convective structure. Therefore, it has a potential to increase the TC forecast skill for operational GSM.

Short-Term Intensity Prediction of Tropical Cyclones Based on Multi-Source Data Fusion with Adaptive Weight Learning

Tropical cyclones (TCs) can cause significant economic damage and loss of life in coastal areas. Therefore, TC prediction has become a crucial topic in current research. In recent years, TC track prediction has progressed considerably, and intensity prediction remains a challenge due to the complex mechanism of TC structure. In this study, we propose a model for short-term intensity prediction based on adaptive weight learning (AWL-Net) for the evolution of the TC’s structure as well as intensity changes, exploring the multidimensional fusion of features including TC morphology, structure, and scale. Furthermore, in addition to using satellite imageries, we construct a dataset that can more comprehensively explore the degree of TC cloud organization and structure evolution. Considering the information difference between multi-source data, a multi-branch structure is constructed and adaptive weight learning (AWL) is designed. In addition, according to the three-dimensional dynamic features of TC, 3D Convolutional Gated Recurrent (3D ConvGRU) is used to achieve feature enhancement, and then 3D Convolutional Neural Network (CNN) is used to capture and learn TC temporal and spatial features. Experiments on a sample of northwest Pacific TCs and official agency TC intensity prediction records are used to validate the effectiveness of our proposed model, and the results show that our model is able to focus well on the spatial and temporal features associated with TC intensity changes, with a root mean square error (RMSE) of 10.62 kt for the TC 24 h intensity forecast.