Doppler Radar Wind Research Articles

A Comparison of HWRF Six-Hourly 4DEnVar and Hourly 3DEnVar Assimilation of Inner Core Tail Dopper Radar Observations for the Prediction of Hurricane Edouard (2014)

Six-hourly three-dimensional ensemble variational (3DEnVar) (6H-3DEnVar) data assimilation (DA) assumes constant background error covariance (BEC) during a six-hour DA window and is, therefore, unable to account for temporal evolution of the BEC. This study evaluates the one-hourly 3DEnVar (1H-3DEnVar) and six-hourly 4DEnVar (6H-4DEnVar) DA methods for the analyses and forecasts of hurricanes with rapidly evolving BEC. Both methods account for evolving BEC in a hybrid EnVar DA system. In order to compare these methods, experiments are conducted by assimilating inner core Tail Doppler Radar (TDR) wind for Hurricane Edouard (2014) and by running the Hurricane Weather Research and Forecasting (HWRF) model. In most metrics, 1H-3DEnVar and 6H-4DEnVar analyses and forecasts verify better than 6H-3DEnVar. 6H-4DEnVar produces better thermodynamic analyses than 1H-3DEnVar. Radar reflectivity shows that 1H-3DEnVar produces better structure forecasts. For the first 24–48 h of the intensity forecast, 6H-4DEnVar forecast performs better than 1H-3DEnVar verified against the best track. Degraded 1H-3DEnVar forecasts are found to be associated with background storm center location error as a result of underdispersive ensemble storm center spread. Removing location error in the background improves intensity forecasts of 1H-3DEnVar.

Assimilation of Doppler radar radial wind data in the GRAPES mesoscale model with observation error covariances tuning

AbstractThe accurate estimation of observation error statistics for high‐density remote‐sensing data is a fundamental step toward optimally utilizing such data, including radar data, for operational numerical weather prediction. Based on the high‐resolution (3 × 3 km) GRAPES model together with the three‐dimensional variational assimilation system (GRAPES_3DVAR) developed by the China Meteorological Administration, a set of assimilation processes for radar radial wind data is designed. First, a scheme is proposed to guarantee the quality of radar radial wind data by correcting the velocity ambiguity for the data. The observation error covariances of the radar data in the GRAPES_3DVAR assimilation system are re‐estimated by using a diagnostic method based on analysis residuals, showing that the re‐estimated radial wind observation error covariances increase with altitude. An optimal regularization parameter is selected by the L‐curve method to constrain the radar observations that were assimilated using inaccurate observation error covariances. Furthermore, to verify the assimilation effects of the refined radial velocity observation error covariances and the constrained observations by the regularization parameter on the analysis and forecasting, a numerical study is carried out on typhoonYunque, which occurred on 3 August 2018. The results show that the modified Doppler radar wind data assimilation using the re‐estimated radial velocity observation error covariances enhances the wind analysis field and the water vapour transport, and accordingly obtains better short‐term precipitation estimates. The radar wind data assimilation results of using the constrained observations also indicate an enhanced wind analysis field and water vapour transport, which leads to better short‐term precipitation estimates.

Systematic Evaluation of the Impact of Assimilating a Network of Ground-Based Remote Sensing Profilers for Forecasts of Nocturnal Convection Initiation during PECAN

AbstractNocturnal convection is often initiated by mechanisms that cannot be easily observed within the large gaps between rawinsondes or by conventional surface networks. To improve forecasts of such events, we evaluate the systematic impact of assimilating a collocated network of high-frequency, ground-based thermodynamic and kinematic profilers collected as part of the 2015 Plains Elevated Convection At Night (PECAN) experiment. For 13 nocturnal convection initiation (CI) events, we find small but consistent improvements when assimilating thermodynamic observations collected by Atmospheric Emitted Radiance Interferometers (AERIs). Through midlevel cooling and moistening, assimilating the AERIs increases the fractions skill score (FSS) for both nocturnal CI and precipitation forecasts. The AERIs also improve various contingency metrics for CI forecasts. Assimilating composite kinematic datasets collected by Doppler lidars and radar wind profilers (RWPs) results in slight degradations to the forecast quality, including decreases in the FSS and traditional contingency metrics. The impacts from assimilating thermodynamic and kinematic profilers often counteract each other, such that we find little impact on the detection of CI when both are assimilated. However, assimilating both datasets improves various properties of the CI events that are successfully detected (timing, distance, shape, etc.). We also find large variability in the impact of assimilating these remote sensing profilers, likely due to the number of observing sites and the strength of the synoptic forcing for each case. We hypothesize that the lack of flow-dependent methods to diagnose observation errors likely contributes to degradations in forecast skill for many cases, especially when assimilating kinematic profilers.

Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction

Abstract The impact of Doppler radar wind observations on forecasts from a developmental, high-resolution numerical weather prediction (NWP) system is assessed. The new 1.5-km limited-area model will be Australia’s first such operational NWP system to include data assimilation. During development, the assimilation of radar wind observations was trialed over a 2-month period to approve the initial inclusion of these observations. Three trials were run: the first with no radar data, the second with radial wind observations from precipitation echoes, and the third with radial winds from both precipitation and insect echoes. The forecasts were verified against surface observations from automatic weather stations, against rainfall accumulations using fractions skill scores, and against satellite cloud observations. These methods encompassed verification across a range of vertical levels. Additionally, a case study was examined more closely. Overall results showed little statistical difference in skill between the trials, and the net impact was neutral. While the new observations clearly affected the forecast, the objective and subjective analyses showed a neutral impact on the forecast overall. As a first step, this result is satisfactory for the operational implementation. In future, upgrades to the radar network will start to reduce the observation error, and further improvements to the data assimilation are planned, which may be expected to improve the impact.

Estimating Convection’s Moisture Sensitivity: An Observation–Model Synthesis Using AMIE-DYNAMO Field Data

AbstractWe seek to use ARM MJO Investigation Experiment (AMIE)-DYNAMO field campaign observations to significantly constrain height-resolved estimates of the parameterization-relevant, causal sensitivity of convective heating Q to water vapor q. In field data, Q profiles are detected via Doppler radar wind divergence D while balloon soundings give q. Univariate regressions of D on q summarize the information from a 10-layer time–pressure series from Gan Island (0°, 90°E) as a 10 × 10 matrix. Despite the right shape and units, this is not the desired causal quantity because observations reflect confounding effects of additional q-correlated casual mechanisms. We seek to use this matrix to adjudicate among candidate estimates of the desired causal quantity: Kuang’s matrix of the linear responses of a cyclic convection-permitting model (CCPM) at equilibrium. Transforming to more observation-comparable forms by accounting for observed autocorrelations, the comparisons are still poor, because (we hypothesize) larger-scale vertical velocity, forbidden by CCPM methodology, is another confounding cause that must be permitted to covary with q. By embedding and modified candidates in an idealized GCM, and treating its outputs as virtual field campaign data, we find that observations favor a factor of 2 (rather than 0 or 1) to small-domain ’s free-tropospheric causal q sensitivity of about 25% rain-rate increment over 3 subsequent hours per +1 g kg−1 q impulse in a 100-hPa layer. Doubling this sensitivity lies partway toward Kuang’s for a long domain that organizes convection into squall lines, a weak but sign-consistent hint of a detectable parameterization-relevant (causal) role for convective organization in nature. Caveats and implications for field campaign proposers are discussed.

Data assimilation impact of in situ and remote sensing meteorological observations on wind power forecasts during the first Wind Forecast Improvement Project (WFIP)

AbstractDuring the first Wind Forecast Improvement Project (WFIP), new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and wind profiles by networks of Doppler sodars and radar wind profilers. Previous data denial studies found a significant improvement of up to 6% root mean squared error (RMSE) reduction for short‐term wind power forecasts due to the assimilation of all of these observations into the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) forecast model using a 3D variational data assimilation scheme. As a follow‐on study, we now investigate the impacts of assimilating into the RAP model either the additional remote sensing observations (sodars and radar wind profilers) alone or assimilating the industry‐provided in situ observations (tall towers and nacelle anemometers) alone, in addition to routinely available standard meteorological data sets. The more numerous tall tower/nacelle observations provide a relatively large improvement through the first 3 to 4 hours of the forecasts, which diminishes to a negligible impact by forecast hour 6. In comparison, the sparser vertical profiling sodars/radars provide an initially smaller impact that decays at a much slower rate, with a positive impact present through the first 12 hours of the forecast. Large positive assimilation impacts for both sets of instruments are found during daytime hours, while small or even negative impacts are found during nighttime hours.

Monitoring wind effects of a landfall typhoon on a 600 m high skyscraper

This article presents the observations of the atmospheric boundary layer (ABL) and wind effects on a 600 m high skyscraper during a landfall typhoon. Wind structure and characteristics throughout the entire ABL are presented and discussed based on records from a Doppler radar wind profiler and near-ground measurements at several meteorological stations. Wind speed profiles with the feature of low-level jets and radial-distance and exposure dependences of gradient height are stressed. Afterwards, wind-induced pressures on building surfaces of the skyscraper are investigated with highlights on non-Gaussian probability distributions of negative pressures and vortex shedding occurred alternately at two sides of the building. The structural responses measured by both accelerometers and strain gauges are analyzed subsequently. Modal parameters of the skyscraper and their dependence on response amplitude are presented and discussed. This study aims to provide useful information for the wind-resistant design of skyscrapers in tropic cyclone-prone regions.

An Enhanced Optical Flow Technique for Radar Nowcasting of Precipitation and Winds

AbstractThe atmospheric state evolution is an inherently highly complex three-dimensional problem that numerical weather prediction (NWP) models attempt to solve. Although NWP models are being successfully employed for medium- and long-range forecast, their short-duration forecast (or nowcast) capabilities are still limited because of model initialization challenges. On the lower end of the complexity scale, nowcasting by extrapolation of two-dimensional weather radar images has long been the most effective tool for nowcasting precipitation. Attempts are being made to take advantage of both approaches by blending extrapolation and numerical model forecasts. In this work a different approach is presented, relying on the additional Doppler radar wind information and a simplified modeling of basic physical processes. Instead of mixing the outputs of different forecasts as in blended approaches, the idea behind this study is to combine extrapolation and precipitation modeling in a new technique with a higher level of complexity with respect to conventional nowcasting methods, although still much simpler than NWP models. As a preliminary step, the Variational Doppler Radar Analysis System (VDRAS) is used to provide an initial analysis exploiting all the available dual-polarization and Doppler radar observations. The rainwater and wind fields are then advected using an optical flow technique that is subject to simplified physical interactions. As a result precipitation and wind nowcasting are obtained and are successively validated up to a 1-h lead time, showing potential improvement upon standard extrapolation.

Winter Snow Level Rise in the Northern Sierra Nevada from 2008 to 2017

The partitioning of precipitation into frozen and liquid components influences snow-derived water resources and flood hazards in mountain environments. We used a 915-MHz Doppler radar wind profiler upstream of the northern Sierra Nevada to estimate the hourly elevation where snow melts to rain, or the snow level, during winter (December–February) precipitation events spanning water years (WY) 2008–2017. During this ten-year period, a Mann-Kendall test indicated a significant (p < 0.001) positive trend in snow level with a Thiel-Sen slope of 72 m year−1. We estimated total precipitation falling as snow (snow fraction) between WY1951 and 2017 using nine daily mid-elevation (1200–2000 m) climate stations and two hourly stations spanning WY2008–2017. The climate-station-based snow fraction estimates agreed well with snow-level radar values (R2 = 0.95, p < 0.01), indicating that snow fractions represent a reasonable method to estimate changes in frozen precipitation. Snow fraction significantly (p < 0.001) declined during WY2008–2017 at a rate of 0.035 (3.5%) year−1. Single-point correlations between detrended snow fraction and sea-surface temperatures (SST) suggested that positive SST anomalies along the California coast favor liquid phase precipitation during winter. Reanalysis-derived integrated moisture transported upstream of the northern Sierra Nevada was negatively correlated with snow fraction (R2 = 0.90, p < 0.01), with atmospheric rivers representing the likely circulation mechanism producing low-snow-fraction storms.

Observations of vertical wind profiles of tropical cyclones at coastal areas

Vertical wind profiles of tropical cyclones (TCs) below 5000m with marine and rugged exposures are investigated based on synchronized measurements from Doppler radar wind profilers and anemometers at three coastal meteorological stations in Hong Kong. The dependence of TCs׳ mean wind structure on storm-relative position, wind strength and exposure is discussed in the context of both case study and composite analysis. For onshore winds, it is found that the wind speed profiles follow the logarithmic-law below about 400m, and the mean wind veers logarithmically with height throughout the Ekman layer. Moreover, the roughness length scale reaches a maximum value and then decreases with increasing wind speed. As the exposure transforms from a marine type to rugged terrains, the mean wind structures vary markedly, featured by a stronger wind shear in a deepened boundary layer. The low-level jets of mean speed profiles are observed in the range of 330–1600m and tilt outward with height. The gust factor of surface wind and the maximum wind scaled by a layer mean wind speed vary with the storm-relative position as well. The obtained profiles also reveal the occasional existence of a secondary maximum wind near 3000–3500m that is accompanied with more turbulent surface wind.

A Multiscale Overview of the El Reno, Oklahoma, Tornadic Supercell of 31 May 2013

Abstract On 31 May 2013 a broad, intense, cyclonic tornado and a narrower, weaker companion anticyclonic tornado formed in a supercell in central Oklahoma. This paper discusses the synoptic- and mesoscale environment in which the parent storm formed, based on data from the operational network of surface stations, rawinsondes, and WSR-88D radars, and from the Oklahoma Mesonet, a Doppler radar wind profiler, Rapid Refresh (RAP) analyses, and photographs. It also documents the overall behavior of the tornadoes and their relationships to features in their parent supercell based on data from a nearby, rapid-scan, polarimetric, mobile Doppler radar. The supercell formed near the intersection of a cold front and a dryline in an environment of moderately strong vertical shear and high CAPE, at the southern end of a line of multicell convective storms. The tornado damage path was as wide as 4.2 km according to the NWS damage assessment and ground-relative Doppler velocities of at least 135 m s−1 were found at the theoretical beam height of <20 m AGL. The tornado debris signature in the copolar cross-correlation coefficient ρhv was as wide as ~4–5 km. After the strong tornado formed, at least one additional cyclonic tornado formed and rotated cyclonically around the main tornado; it was then absorbed by it and the main tornado broadened. Smaller subvortices, which rotated cyclonically around a common axis of rotation, were subsequently observed. The tornado then weakened but remained broad, while the anticyclonic tornado formed to the southeast along the rear-flank gust front.

Temporal Wind Pairs for Space Launch Vehicle Capability Assessment and Risk Mitigation

Space launch vehicles incorporate upper-level wind assessments to determine wind effects on the vehicle and for a commit-to-launch decision. These assessments make use of wind profiles measured hours before launch and may not represent the actual wind the vehicle will fly through. Uncertainty in the winds over the time period between the assessment and launch introduces uncertainty in assessment of vehicle controllability and structural integrity that must be accounted for to ensure launch safety. Temporal wind pairs are used in engineering development of allowances to mitigate uncertainty. Five sets of temporal wind pairs at various times (0.75, 1.5, 2, 3, and 4 h) at the United States Air Force Eastern Range and Western Range, as well as the National Aeronautics and Space Administration’s Wallops Flight Facility, are developed for use in upper-level wind assessments on vehicle performance. Historical databases are compiled from balloon-based and vertically pointing Doppler radar wind profiler systems. Various automated and manual quality control procedures are used to remove unacceptable profiles. Statistical analyses on the resultant wind pairs from each site are performed to determine if the observed extreme wind changes in the sample pairs are representative of extreme temporal wind change. Wind change samples in the Eastern Range and Western Range databases characterize extreme wind change. However, the small sample sizes in the Wallops Flight Facility databases yield low confidence that the sample population characterizes extreme wind change that could occur.

A Diabatic Lagrangian Technique for the Analysis of Convective Storms. Part I: Description and Validation via an Observing System Simulation Experiment

Abstract A diabatic Lagrangian analysis (DLA) technique for deriving potential temperature, water vapor and cloud water mixing ratios, and virtual buoyancy from three-dimensional time-dependent Doppler radar wind and reflectivity fields in storms is presented. The DLA method proceeds from heat and water substance conservation along discrete air trajectories via microphysical diabatic heating/cooling and simple damping and surface flux parameterizations in a parcel-following ground-relative reference frame to thermodynamic fields on a regular grid of trajectory endpoints at a common analysis time. Rain and graupel precipitation size distributions are parameterized from observed reflectivity at discrete Lagrangian points to simplify the cloud model–based microphysically driven heating and cooling rate calculations. The DLA approximates the precipitation size distributions from reflectivity assuming conventional inverse exponential size distributions and prescribed input intercept parameter values based on the output of a mature simulated storm. The DLA is demonstrated via an observing system simulation experiment (OSSE), and its analysis compares favorably with the known output buoyancy and water substance fields in the simulated storm case. The DLA-analyzed thermal–solenoidal horizontal vorticity tendency is of comparable magnitude to the corresponding modeled solenoidal vorticity tendency. A test application of the DLA to a radar-observed storm is presented in a companion paper (Part II).

The Effect of Topographic Variability on Initial Condition Sensitivity of Low-Level Wind Forecasts. Part II: Experiments Using Real Terrain and Observations

Abstract A study by Bieringer et al., which is Part I of this two-part study, demonstrated analytically using the shallow-water equations and numerically in controlled experiments that the presence of terrain can result in an enhancement of sensitivities to initial condition adjustments. The increased impact of adjustments to initial conditions corresponds with gradients in the flow field induced by the presence of the terrain obstacle. In cross-barrier flow situations the impact of the initial condition adjustments on the final forecast increases linearly as the height of the terrain obstacle increases. While this property associated with initial condition perturbations may be present in an analytic and controlled numerical environment, it is often difficult to realize these benefits in a more operationally realistic setting. This study extends the prior work to a situation with actual terrain, Doppler radar wind observations over the terrain, and observations from a surface mesonet for model verification. The results indicate that the downstream surface wind forecast was improved more when the initial conditions adjusted through the assimilation of Doppler radar data originated from areas with terrain gradients than from regions where the terrain was relatively flat. This result is consistent with the findings presented in Part I and suggests that when varying terrain elevation is present upstream of a target forecast area, a greater benefit (in terms of forecast accuracy) can be made by targeting additional observations in the regions containing variable terrain than regions where the terrain is relatively flat.

Quality Control Algorithms for the Kennedy Space Center 50-MHz Doppler Radar Wind Profiler Winds Database

Abstract This paper presents the process used by the Marshall Space Flight Center Natural Environments Branch (EV44) to quality control (QC) data from the Kennedy Space Center’s 50-MHz Doppler radar wind profiler (DRWP) for use in vehicle wind loads and steering commands. The database has been built to mitigate limitations of using the currently archived databases from weather balloons. The DRWP database contains wind measurements from approximately 2.7- to 18.6-km altitude at roughly 5-min intervals for the August 1997–December 2009 period of record, and the extensive QC process was designed to remove spurious data from various forms of atmospheric and nonatmospheric artifacts. The QC process is largely based on DRWP literature, but two new algorithms have been developed to remove data contaminated by convection and excessive first-guess propagations from the median filter/first-guess algorithm. In addition to describing the automated and manual QC process in detail, this paper describes the extent of the data retained. Roughly 58% of all possible wind observations exist in the database, with approximately 100 times as many complete profile sets existing relative to the EV44 balloon databases. This increased sample of near-continuous wind profile measurements may help increase launch availability by reducing the uncertainty of wind changes during launch countdown.

Impact of assimilating airborne Doppler radar velocity data using the ARPS 3DVAR on the analysis and prediction of Hurricane Ike (2008)

The ARPS 3DVAR data assimilation system is enhanced and used for the first time to assimilate airborne Doppler radar wind observations. It is applied to Hurricane Ike (2008), where radar observations taken along four flight legs through the hurricane vortex 14 to 18 h before it made landfall are assimilated. An optimal horizontal de‐correlation scale for the background error is determined through sensitivity experiments. A comparison is made between assimilating retrieved winds and assimilating radial velocity data directly. The effect of the number of assimilation cycles, each analyzing data from one flight leg, is also examined. The assimilation of retrieved wind data and of radial velocity data produces similar results. However, direct assimilation of radial velocity data is recommended for both theoretical and practical reasons. In both cases, velocity data assimilation improves the analyzed hurricane structure and intensity as well as leads to better prediction of the intensity. Improvement to the track forecasting is also found. The assimilation of radial velocity observations from all four flight legs through intermittent assimilation cycles produces the best analyses and forecasts. The first analysis in the first cycle tends to produce the largest analysis increment. It is through the mutual adjustments among model variables during the forecast periods that a balanced vortex with lowered central pressure is established. The wind speeds extracted from the assimilated model state agree very well with independent surface wind measurements by the stepped‐frequency microwave radiometer onboard the aircraft, and with independent flight‐level wind speeds detected by the NOAA P‐3 aircraft in‐flight measurements. Twenty‐four hour accumulated precipitation is noticeably improved over the case without radar data assimilation.

The accuracy of Doppler radar wind retrievals using insects as targets

AbstractInsect returns from the UK's Doppler weather radars were collected in the summers of 2007 and 2008, to ascertain their usefulness in providing information about boundary layer winds. Such observations could be assimilated into numerical weather prediction models to improve forecasts of convective showers before precipitation begins. Significant numbers of insect returns were observed during daylight hours on a number of days through this period, when they were detected at up to 30 km range from the radars, and up to 2 km above sea level. The range of detectable insect returns was found to vary with time of year and temperature. There was also a very weak correlation with wind speed and direction. Use of a dual‐polarized radar revealed that the insects did not orient themselves at random, but showed distinct evidence of common orientation on several days, sometimes at an angle to their direction of travel. Observation minus model background residuals of wind profiles showed greater bias and standard deviation than that of other wind measurement types, which may be due to the insects' headings/airspeeds and to imperfect data extraction. The method used here, similar to the Met Office's procedure for extracting precipitation returns, requires further development as clutter contamination remained one of the largest error contributors. Wind observations derived from the insect returns would then be useful for data assimilation applications. Copyright © 2010 Royal Meteorological Society and Crown Copyright.

Study of wind fields associated with subtropical squall lines using Envisat Synthetic Aperture Radar images and ground-based weather radar data

Squall lines are lines of organized convective rain cells accompanied by wind shear and high wind gusts. They are usually studied by using ground-based weather radar. In this paper, three squall line events, which occurred over the South China Sea in 2006 and 2007, are investigated by using simultaneously acquired Synthetic Aperture Radar (SAR) images of the European Envisat satellite and ground-based Doppler weather radar data of the Hong Kong Observatory. Both radars yield wind fields: the SAR near-sea surface wind fields and the Doppler radar upper-air wind fields. Both wind fields are of high spatial resolution (sub-kilometre scale), making them useful to study fine-scale features in squall lines. Three squall lines events, each having distinct features, are presented. They show exemplarily the advantage of synergistic use of both SAR and ground-based weather radar in the study of squall lines.

Nocturnal boundary layer characteristics and land breeze development in Houston, Texas during TexAQS II

The nocturnal boundary layer in Houston, Texas was studied using a high temporal and vertical resolution tethersonde system on four nights during the Texas Air Quality Study II (TexAQS II) in August and September 2006. The launch site was on the University of Houston campus located approximately 4 km from downtown Houston. Of particular interest was the evolution of the nocturnal surface inversion and the wind flows within the boundary layer. The land–sea breeze oscillation in Houston has important implications for air quality as the cycle can impact ozone concentrations through pollutant advection and recirculation. The results showed that a weakly stable surface inversion averaging in depth between 145 and 200 m AGL formed on each of the experiment nights, typically within 2–3 h after sunset. Tethersonde vertical winds were compared with two other Houston data sets (High Resolution Doppler Lidar and radar wind profiler) from locations near the coastline and good agreement was found, albeit with a temporal lag at the tethersonde site. This comparison revealed development of a land breeze on three nights which began near the coastline and propagated inland both horizontally and vertically with time. The vertical temperature structure was significantly modified on one night at the tethersonde site after the land breeze wind shift, exhibiting near-adiabatic profiles below 100 m AGL.

The Eyewall-Penetration Reconnaissance Observation of Typhoon Longwang (2005) with Unmanned Aerial Vehicle, Aerosonde

Abstract In this paper, a successful eye-penetration reconnaissance flight by an unmanned aerial vehicle, Aerosonde, into Typhoon Longwang (2005) and the preliminary analyses of the collected data are presented. The 10-h flight is diagnosed through four flight legs. The wind field measured along flight leg 1 provides the tangential and radial wind profiles from the outer perimeter into the eye of the typhoon at the 700-hPa layer. A vertical sounding was taken in the eye along flight leg 2 and the derived surface pressure in the eyewall is close to the estimates made by the local weather agencies. Along flight leg 3, the strongest winds during the whole flight mission were measured. These in situ wind measurements by Aerosonde are consistent with the winds observed by the Hua-lien Doppler weather radar. The maximum 10-min (1 min) wind along flight leg 3 when Aerosonde was flying around the eyewall region is 58.6 m s−1 (62 m s−1). The maximum sustained surface wind derived from this maximum wind speed is also close to the estimates made by the local weather agencies. In conclusion, this successful mission demonstrates that the Aerosonde with a trained crew can play a role in severe weather monitoring and the Aerosonde’s measurement can serve as an independent check for Doppler radar wind retrieval.