Tropical Cyclone Observations Research Articles

Large-eddy simulation of the rapidly intensifying tropical cyclone Soudelor (2015)

The lack of dense observations of tropical cyclones (TCs) far out at sea hinders mankind's understanding of their multiscale physics. Large-eddy simulation (LES) provides a potential surrogate considering its ability to reproduce the fine structures of a wide range of atmospheric flows including TC. In this study, an LES is carried out to reproduce the rapid intensification of TC Soudelor (2015). Comparisons with both observations and previous modeling studies indicate that the LES produces a reasonably accurate depiction of the TC structure, including the active rainbands, the remarkable secondary circulation and typical double warm cores. Notably, the LES captures exclusive features of the TC, such as the tornado-scale vortices (TSVs) reported in previous LES studies at much finer horizontal resolution. Local gust winds in these vortices are related to the unexpected minimum sea-level pressure, which may affect the determination of the TC intensity. To address this issue, a tractable correction algorithm is developed based on the systematic analysis of TSVs. This algorithm aims to help researchers better interpret the booming LESs of TC both at present and in the future.

Recent advancements in aircraft and in situ observations of tropical cyclones

Observations of tropical cyclones (TC) from aircraft and in situ platforms provide critical and unique information for analyzing and forecasting TC intensity, structure, track, and their associated hazards. This report, prepared for the tenth International Workshop on Tropical Cyclones (IWTC-10), discusses the data collected around the world in TCs over the past four years since the IWTC-9, improvements to observing techniques, new instruments designed to achieve sustained and targeted atmospheric and oceanic observations, and select research results related to these observations.In the Atlantic and Eastern and Central Pacific basins, changes to operational aircraft reconnaissance are discussed along with several of the research field campaigns that have taken place recently. The changes in the use and impact of these aircraft observations in numerical weather prediction models are also provided along with updates on some of the experimental aircraft instrumentation. Highlights from three field campaigns in the Western Pacific basin are also discussed. Examples of in-situ data collected within recent TCs such as Hurricane Ian (2022), also demonstrate that new, emerging technologies and observation strategies reviewed in this report, definitely have the potential to further improve ocean-atmosphere coupled intensity forecasts.

Scale Analysis of Infrared Water Vapor Brightness Temperatures for Tropical Cyclone All‐Sky Radiance Assimilation

AbstractWe analyzed the scale features of satellite infrared (IR) water vapor (WV) brightness temperature observations of tropical cyclones (TCs). This is to characterize the storm information at dominate scales in all‐sky radiance assimilation for TC numerical weather prediction. This paper presents the results from the study of Hurricane Patricia (2015). Our study shows that IR WV brightness temperatures have the ability to observe multiscale structures of TCs, ranging from a size of above 1,000 km that covers the entire storm and its surrounding areas to a scale resolving individual convective clouds embedded in the TC. The atmospheric moisture for TC development is mainly represented by large scales covering the storm and surrounding areas while the storm structures are characterized basically by all scales. The large‐scale moisture and small‐scale convection demonstrate strong correlation and are closely related to the TC development, suggesting the need for all‐sky radiance assimilation at multiple scales.

Rain-induced characteristics in C- and X-band synthetic aperture radar observations of tropical cyclones

ABSTRACT This work focused on the rain-induced characteristics of synthetic aperture radar (SAR) at the C- and X-bands. Six SAR images were collected in tropical cyclones: four C-band dual-polarized Sentinel-1 (S-1) images during the 2016 hurricane season and two vertical–vertical) polarized TerraSAR-X (TS-X) images of Hurricane Sandy (2012). Wind speeds were retrieved from the S-1 images at the vertical–horizontal polarization channel, and winds from the TS-X images were obtained from the Hurricane Research Division of the National Oceanic and Atmospheric Administration . Simultaneously, Tropical Rainfall Measuring Mission (TRMM) rain rates, current data from the HYbrid Coordinate Ocean Model and wave spectra simulated by the WAVEWATCH-III (WW3) model were collocated. The three-scale backscattering model was employed to simulate the normalized radar cross-section (NRCS)without considering the rain effect, yielding a 2.21-dB root mean square errorand 2.23-dB for S-1 and TS-X, respectively. The difference between model-simulated and observed NRCS was analysed using the TRMM rain rate. The results indicate a linear relationship of the difference at the X-band with the TRMM rain rate, while the difference at the C-band exhibited a ‘V’ relationship with the TRMM rain rate. It was also discovered that the difference at the X-band decreased with increasing wind speed, while the difference at the C-band increased with increasing wind speed.

Statistical Decomposition of the Recent Increase in the Intensity of Tropical Storms

In a recent paper, Kossin et al. showed that during the period from 1979 to 2017, there was a statistically significant increase in the ratio of category 3–5 to category 1–5 tropical storm fixes in the ADT-HURSAT satellite dataset of tropical cyclone observations. The sign of this increase is consistent with previously developed theory and modelling results for how tropical cyclones may change due to climate change. However, without further analysis, it is difficult to understand what the implications of this increase might be for present day tropical cyclone risk. It is also difficult to understand how tropical cyclone risk models might be adjusted to reflect this increase, since this ratio is not typically directly represented in such models. Our goal is therefore to understand the drivers for this increase in terms of changes in the numbers of fixes of different categories of storms in different basins, which are quantities that are more directly related to tropical cyclone risk and risk modelling. We use both heuristic and quantitative methods. We find that the increase in the ratio is mainly driven by a decrease in the denominator (the number of category 1–5 fixes) and to a small extent by a slight increase in the numerator (the number of category 3–5 fixes). The decrease in the denominator is mostly driven by a statistically significant reduction in the number of category 1 fixes outside the North Atlantic. The slight increase in the numerator is mostly driven by a statistically significant increase in the number of category 3–4 fixes in the North Atlantic. Based on these results, we discuss different ways in which the increase in the ratio could be represented in risk models.

A linear height-resolving wind field model for tropical cyclone boundary layer

The wind field model is one of the most important components for the tropical cyclone hazard assessment, thus the appropriate design of this element is extremely important. While solving the fully non-linear governing equations of the wind field was demonstrated to be quite challenging, the linear models showed great promise delivering a simple solution with good approximation to the wind field, and can be readily adopted for engineering applications. For instance it can be implemented in the Monte Carlo technique for rapid tropical-cyclone risk assessment. This study aims to develop a height-resolving, linear analytical model of the boundary layer winds in a moving tropical cyclone. The wind velocity is expressed as the summation of two components, namely gradient wind in the free atmosphere and frictional component near the ground surface. The gradient wind was derived straightforwardly, while the frictional component was obtained based on the scale analysis of the fully non-linear Navier-Stokes equations. The variation of wind field with respect to the angular coordinate was highlighted since its contribution to the surface wind speed and associated spatial distribution cannot be ignored in the first-order approximation. The results generated by the present model are consistent with tropical cyclone observations.

Assimilation of Tropical Cyclone Observations: Improving the Assimilation of TCVitals, Scatterometer Winds, and Dropwindsonde Observations

Abstract The standard statistical model of data assimilation assumes that the background and observation errors are normally distributed, and the first- and second-order statistical moments of the two distributions are known or can be accurately estimated. Because these assumptions are never satisfied completely in practice, data assimilation schemes must be robust to errors in the underlying statistical model. This paper tests simple approaches to improving the robustness of data assimilation in tropical cyclone (TC) regions. Analysis–forecast experiments are carried out with three types of data—Tropical Cyclone Vitals (TCVitals), DOTSTAR, and QuikSCAT—that are particularly relevant for TCs and with an ensemble-based data assimilation scheme that prepares a global analysis and a limited-area analysis in a TC basin simultaneously. The results of the experiments demonstrate that significant analysis and forecast improvements can be achieved for TCs that are category 1 and higher by improving the robustness of the data assimilation scheme.

Assimilation of High-Resolution Tropical Cyclone Observations with an Ensemble Kalman Filter Using HEDAS: Evaluation of 2008–11 HWRF Forecasts

Abstract NOAA has been gathering high-resolution, flight-level dropwindsonde and airborne Doppler radar data in tropical cyclones for almost three decades; the U.S. Air Force routinely obtained the same type and quality of data, excepting Doppler radar, for most of that time. The data have been used for operational diagnosis and for research, and, starting in 2013, have been assimilated into operational regional tropical cyclone models. This study is an effort to quantify the impact of assimilating these data into a version of the operational Hurricane Weather Research and Forecasting model using an ensemble Kalman filter. A total of 83 cases during 2008–11 were investigated. The aircraft whose data were used in the study all provide high-density flight-level wind and thermodynamic observations as well as surface wind speed data. Forecasts initialized with these data assimilated are compared to those using the model standard initialization. Since only NOAA aircraft provide airborne Doppler radar data, these data are also tested to see their impact above the standard aircraft data. The aircraft data alone are shown to provide some statistically significant improvement to track and intensity forecasts during the critical watch and warning period before projected landfall (through 60 h), with the Doppler radar data providing some further improvement. This study shows the potential for improved forecasts with regular tropical cyclone aircraft reconnaissance and the assimilation of data obtained from them, especially airborne Doppler radar data, into the numerical guidance.

Simulation of the Global ENSO–Tropical Cyclone Teleconnection by a High-Resolution Coupled General Circulation Model

Abstract This study assesses the influence of the El Niño–Southern Oscillation (ENSO) on global tropical cyclone activity using a 150-yr-long integration with a high-resolution coupled atmosphere–ocean general circulation model [High-Resolution Global Environmental Model (HiGEM); with N144 resolution: ~90 km in the atmosphere and ~40 km in the ocean]. Tropical cyclone activity is compared to an atmosphere-only simulation using the atmospheric component of HiGEM (HiGAM). Observations of tropical cyclones in the International Best Track Archive for Climate Stewardship (IBTrACS) and tropical cyclones identified in the Interim ECMWF Re-Analysis (ERA-Interim) are used to validate the models. Composite anomalies of tropical cyclone activity in El Niño and La Niña years are used. HiGEM is able to capture the shift in tropical cyclone locations to ENSO in the Pacific and Indian Oceans. However, HiGEM does not capture the expected ENSO–tropical cyclone teleconnection in the North Atlantic. HiGAM shows more skill in simulating the global ENSO–tropical cyclone teleconnection; however, variability in the Pacific is overpronounced. HiGAM is able to capture the ENSO–tropical cyclone teleconnection in the North Atlantic more accurately than HiGEM. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity, is used to further understand the response of tropical cyclone activity to ENSO in the North Atlantic and western North Pacific. The vertical wind shear response over the Caribbean is not captured in HiGEM compared to HiGAM and ERA-Interim. Biases in the mean ascent at 500 hPa in HiGEM remain in HiGAM over the western North Pacific; however, a more realistic low-level vorticity in HiGAM results in a more accurate ENSO–tropical cyclone teleconnection.

The Evolution of Hurricane Humberto (2001)

Abstract In 2001, the National Oceanic and Atmospheric Administration and the National Aeronautical and Space Administration marshaled their resources to sample Hurricane Humberto for 3 successive days during the fourth Convection and Moisture Experiment (CAMEX-4). Humberto developed from a tropical storm into a category-2 hurricane despite the deep-layer vertical shear of the environmental horizontal wind (VWS) increasing markedly on the second and third days of sampling. As exhibited in earlier studies, the eyewall convection developed an azimuthal wavenumber-1 (n = 1) asymmetry as the VWS increased. Horizontal divergence and vertical stability within 100 km of the eye exhibited persistent relationships to the VWS vector. The warm core evolved in an unexpected way. The warm anomaly was initially located in the lower troposphere and built upward as the storm intensified. The maximum temperature anomaly remained in the lower troposphere on all 3 days while the development of the upper-tropospheric warm anomaly appeared to be inhibited by the increasing VWS and the entrainment of dry environmental air into the core at midlevels. The warm core of this higher-latitude (33°N) storm displayed large differences when compared to most numerical simulations, wind-induced surface heat exchange theory, and observations of tropical cyclones in the deep tropics acquired nearly 50 years ago. The results were similar to some recent numerical simulations.

Cyclone Wind Field Asymmetries during Extratropical Transition in the Western North Pacific

AbstractRisk-assessment systems for wind hazards (e.g., hurricanes or typhoons) often rely on simple parametric wind field formulations. They are built using extensive observations of tropical cyclones and make assumptions about wind field asymmetry. In this framework, maximum winds are always simulated to the right of the cyclone, but analysis of the Climate Forecast System Reanalysis database for the western North Pacific Ocean suggests that wind fields from cyclones undergoing extratropical transition around Japan often present features that cannot be adequately simulated under these assumptions. These “left-hand-side contribution” (LHSC) wind fields exhibit strong winds on both sides of the moving cyclone with the maximum magnitude often located to the left. Classification of cyclones in terms of their most frequent patterns reveals that 67% of cases that make a transition around Japan are dominantly LHSC. They are more likely in autumn and have more intense maximum winds. The results from this study show the need for a new approach to the modeling of transitioning wind fields in the context of risk-assessment systems.

Tropical Cyclone Data Impact Studies: Influence of Model Bias and Synthetic Observations

AbstractThe impacts of assimilating dropwindsonde data and enhanced atmospheric motion vectors (AMVs) on tropical cyclone track forecasts are examined using the Navy global data assimilation and forecasting systems. Enhanced AMVs have the largest impact on eastern Pacific storms, while dropwindsonde data have the largest impact on Atlantic storms. Results in the western Pacific are mixed. Two western Pacific storms, Nuri and Jangmi, are examined in detail. For Nuri, dropwindsonde data and enhanced AMVs are at least as likely to degrade as to improve forecasts. For Jangmi, additional data improve track forecasts in most cases. An erroneous weakening of the forecasted subtropical high appears to contribute to the track errors for Nuri and Jangmi. Assimilation of enhanced AMVs systematically increases the analyzed heights in this region, counteracting this model bias. However, the impact of enhanced AMVs decreases rapidly as the model biases saturate at similar levels for experiments with and without the enhanced AMVs after the first few forecast days. Experiments are also conducted in which the errors assigned to synthetic tropical cyclone observations are increased. Moderate increases in the assigned errors improve track forecasts on average, but larger increases in the assigned errors produce mixed results. Both experiments allow for reductions in innovations and residuals when compared to dropwindsonde observations. These experiments suggest that a reformulation of the synthetic tropical cyclone observation scheme may lead to improved forecasts as more in situ and remote observations become available.

Joint Impact of Forecast Tendency and State Error Biases in Ensemble Kalman Filter Data Assimilation of Inner-Core Tropical Cyclone Observations

Abstract In this study the properties and causes of systematic errors in high-resolution data assimilation of inner-core tropical cyclone (TC) observations were investigated using the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS). Although a recent study by Aksoy et al. demonstrated overall good performance of HEDAS for 83 cases from 2008 to 2011 using airborne observations from research and operational aircraft, some systematic errors were identified in the analyses with respect to independent observation-based estimates. The axisymmetric primary circulation intensity was underestimated for hurricane cases and the secondary circulation was systematically weaker for all cases. The diagnostic analysis in this study shows that the underestimate of primary circulation was caused by the systematic spindown of the vortex core in the short-term forecasts during the cycling with observations. This tendency bias was associated with the systematic errors in the secondary circulation, temperature, and humidity. The biases were reoccurring in each cycle during the assimilation because of the inconsistency between the strength of primary and secondary circulation during the short-term forecasts, the impact of model error in planetary boundary layer dynamics, and the effect of forecast tendency bias on the background error correlations. Although limited to the current analysis the findings in this study point to a generic problem of mutual dependence of short-term forecast tendency and state estimate errors in the data assimilation of TC core observations. The results indicate that such coupling of errors in the assimilation would also lead to short-term intensity forecast bias after the assimilation for the same reasons.

Assimilation of High-Resolution Tropical Cyclone Observations with an Ensemble Kalman Filter Using NOAA/AOML/HRD’s HEDAS: Evaluation of the 2008–11 Vortex-Scale Analyses

AbstractThe Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) is developed to assimilate tropical cyclone inner-core observations for high-resolution vortex initialization. It is based on a serial implementation of the square root ensemble Kalman filter (EnKF). In this study, HWRF is used in an experimental configuration with horizontal grid spacing of 9 (3) km on the outer (inner) domain. HEDAS is applied to 83 cases from years 2008 to 2011. With the exception of two Hurricane Hilary (2011) cases in the eastern North Pacific basin, all cases are observed in the Atlantic basin. Observed storm intensity for these cases ranges from tropical depression to category-4 hurricane.Overall, it is found that high-resolution tropical cyclone observations, when assimilated with an advanced data assimilation technique such as the EnKF, result in analyses of the primary circulation that are realistic in terms of intensity, wavenumber-0 radial structure, as well as wavenumber-1 azimuthal structure. Representing the secondary circulation in the analyses is found to be more challenging with systematic errors in the magnitude and depth of the low-level radial inflow. This is believed to result from a model bias in the experimental HWRF caused by the overdiffusive nature of the planetary boundary layer parameterization utilized. Thermodynamic deviations from the observed structure are believed to be caused by both an imbalance between the number of the kinematic and thermodynamic observations in general and the suboptimal ensemble covariances between kinematic and thermodynamic fields. Future plans are discussed to address these challenges.

Storm-Relative Observations in Tropical Cyclone Data Assimilation with an Ensemble Kalman Filter

Abstract A storm-relative data assimilation method for tropical cyclones is introduced for the ensemble Kalman filter, using the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) developed at the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory at the National Oceanic and Atmospheric Administration. The method entails translating tropical cyclone observations to storm-relative coordinates and requires the assumption of simultaneity of all observations. The observations are then randomly redistributed to assimilation cycles to achieve a more homogeneous spatial distribution. A proof-of-concept study is carried out in an observing system simulation experiment in which airborne Doppler radar radial wind observations are simulated from a higher-resolution (4.5/1.5 km) version of the same model. The results here are compared to the earth-relative version of HEDAS. When storm-relative observations are assimilated using the original HEDAS configuration, improvements are observed in the kinematic representation of the tropical cyclone vortex in analyses. The use of the storm-relative observations with a more homogeneous spatial distribution also reveals that a reduction of the covariance localization horizontal length scale by ½ to ~120 km provides the greatest incremental improvements. Potential positive impact is also seen in the slower cycle-to-cycle error growth. Spatially smoother analyses are obtained in the horizontal, and the evolution of the azimuthally averaged wind structure during short-range forecasts demonstrates better consistency with the nature run.

Tropical Cyclone Activity Downscaled from NOAA‐CIRES Reanalysis, 1908–1958

A recently developed technique for deducing tropical cyclone activity from global reanalyses and climate models is applied to a reanalysis of the global atmosphere during the period 1908–1958. This reanalysis assimilates only sea surface temperature, sea ice, and surface pressure observations, which are relatively homogeneous over the period. The downscaling technique has been shown to produce results in good agreement with observations of tropical cyclones when driven by reanalyses over the period 1980–2006, a period when global tropical cyclone frequency was robustly observed. When applied to the 1908–1958 reanalysis, the derived global frequency of tropical cyclones shows no significant trend over the period, while the frequency of events in the southern hemisphere shows a statistically significant decline and that of the northern hemisphere shows a marginally significant increase. There are statistically significant increases in frequency over the period in the North Atlantic, eastern North Pacific, and northern Indian Oceans, while frequency declines in the western North Pacific. Power dissipation estimates from best‐track data are highly correlated with the power dissipation of downscaled events in the Atlantic, though the amplitude of the variability and trends of the downscaled power dissipation are smaller than those of the best‐track estimates by about a factor of two. A recently developed genesis index applied to the reanalysis data is highly correlated with downscaled event frequency on regional spatial scales, but is largely uncorrelated at the scale of the globe and even on the scale of large tropical cyclone‐producing regions such as the western North Pacific. Finally, while it is tempting to believe that specification of sea surface temperature is sufficient for capturing most aspects of the general state of the atmosphere relevant to tropical cyclones, we show, using simple arguments, that failure to account for changing radiative properties of the atmosphere can distort the response of tropical cyclone activity to changing distributions of sea surface temperature; moreover, models appear to systematically underestimate the response of near‐tropopause temperatures to changing surface temperature, and this too can affect the response of potential intensity.

CloudSat and A-Train Observations of Tropical Cyclones

The CloudSat 94-GHz Cloud Profiling Radar was designed to provide global information on the vertical structure of clouds. It was launched in April 2006, joining the A-Train of earth science satellites. Although primarily focused on clouds and climate, the CloudSat radar also provides a unique view of the vertical structure of clouds in tropical cyclones. The authors use data from CloudSat and other A-Train satellite constellation missions to examine tropical cyclone cloud properties. They consider several case studies and then examine cloud statistics based on seventeen tropical cyclone overpasses. In addition to the new qualitative view of cloud structure provided by CloudSat, the CloudSat and other ATrain products also contain quantitative estimates of cloud properties. Although the accuracy of these products in tropical cyclones is not validated by direct comparison, the authors do find reasonable agreement with previous in situ measurements.

Observations of Tropical Cyclones With the SSMIS

Passive microwave (PMW) radiometric observations of tropical cyclones (TCs) from the special sensor microwave imager/sounder (SSMIS) continue the legacy monitoring capabilities initiated with the special sensor microwave/imager (SSM/I) that began in 1987. The SSMIS has the following several important differences that should be factored into applications when compared to SSM/I data: 1) channel changes from 85 to 91 GHz result in a 2-8-K brightness temperature depression for many TC inner core scenes; 2) the inclusion of bore-sighted 150-GHz data can help in detecting rapidly growing convective cells that are frequently obscured by upper level clouds in visible and infrared data and are often associated with rapid intensification; and 3) the sensor swath increases by 300 km and permits enhanced spatial and temporal coverage of global TCs. All three attributes can be incorporated to maintain and/or enhance the satellite analyst's ability to monitor critical TC structure via these PMW observations.

Observations of tropical cyclone structure from WindSat

Passive microwave (PMW) radiometric observations of clouds from multichannel imaging sensors onboard low Earth-orbiting environmental satellites are now a vital operational dataset. The first operational passive microwave sensor was the Special Sensor Microwave/Imager onboard the Defense Meteorological Satellite Program satellites, which has been gathering hydrological data records since 1987, and continued with the Tropical Rainfall Measuring Mission (TRMM) and the Advanced Microwave Scanning Radiometer onboard Aqua. These sensors view the underlying scene with an Earth incidence angle near 53/spl deg/ and with a variable azimuthal angle, depending upon the orbit direction and scan position. The WindSat sensor onboard the Coriolis satellite, launched in January 2003, is a five-channel polarimetric PMW radiometer designed to optimize ocean surface wind vector retrievals. While it does not have 85-GHz channels, an added feature is its unique fore-aft viewing capability across a portion of its fore scan swath. This provides a view of the underlying scene from two separate azimuthal directions, which provides added information on the three-dimensional (3-D) structure of clouds and their evolution. In this paper, we compare WindSat and TRMM Precipiation Radar observations of tropical cyclones (TCs) with Monte Carlo radiative transfer simulations performed on idealized 3-D convective cloud structures. The TC 3-D structure and possible tilt in the convective cloud structure are inferred from the difference between the 37-GHz equivalent blackbody brightness temperatures (T/sub B/) from the corresponding fore and aft view observations. The information gained from this analysis is important since asymmetries in the cloud vertical and horizontal structure may be an indication of upper level wind shear, which plays a major role in influencing changes of the TC intensity.

Estimating vertical velocity and radial flow from Doppler radar observations of tropical cyclones

AbstractThe mesoscale vorticity method (MVM) is used in conjunction with the ground‐based velocity track display (GBVTD) to derive the inner‐core vertical velocity from Doppler radar observations of tropical cyclone (TC) Danny (1997). MVM derives the vertical velocity from vorticity variations in space and in time based on the mesoscale vorticity equation. The use of MVM and GBVTD allows us to derive good correlations among the eye‐wall maximum wind, bow‐shaped updraught and echo east of the eye‐wall in Danny. Furthermore, we demonstrate the dynamically consistent radial flow can be derived from the vertical velocity obtained from MVM using the wind decomposition technique that solves the Poisson equations over a limited‐area domain. With the wind decomposition, we combine the rotational wind which is obtained from Doppler radar wind observations and the divergent wind which is inferred dynamically from the rotational wind to form the balanced horizontal wind in TC inner cores, where rotational wind dominates the divergent wind. In this study, we show a realistic horizontal and vertical structure of the vertical velocity and the induced radial flow in Danny's inner core. In the horizontal, the main eye‐wall updraught draws in significant surrounding air, converging at the strongest echo where the maximum updraught is located. In the vertical, the main updraught tilts vertically outwards, corresponding very well with the outward‐tilting eye‐wall. The maximum updraught is located at the inner edge of the eye‐wall clouds, while downward motions are found at the outer edge. This study demonstrates that the mesoscale vorticity method can use high‐temporal‐resolution data observed by Doppler radars to derive realistic vertical velocity and the radial flow of TCs. The vorticity temporal variations crucial to the accuracy of the vorticity method have to be derived from a high‐temporal‐frequency observing system such as state‐of‐the‐art Doppler radars. Copyright © 2006 Royal Meteorological Society