Observed tropical cyclone wind flow characteristics

This study projects the changes in tropical cyclone (TC) landfalls in the western North Pacific under shared socioeconomic pathway (SSPs) scenarios during the TC peak season by using low‐resolution global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). Projections are based on the relationship between mid‐ and lower‐level atmospheric circulation and TC landfall frequency during the historical period from 1985 to 2014 and the future climate period from 2015 to 2100. The landfall areas for TCs are divided into northern East Asia (NEA), middle East Asia (MEA) and southern East Asia (SEA); the TC peak seasons are July–September for NEA and MEA, and July–November for SEA. To evaluate reproducibility, both ensemble and individual model outputs for mid‐ and lower‐level atmospheric circulations associated with TC landfall in each East Asian subregion are compared to the reanalysis. An ensemble of seven models with stable results for all three regions is more reasonable in simulating atmospheric circulation patterns than an ensemble of all CMIP6 models. The findings suggest that TC landfall is projected to increase by about 12% and 32% in NEA and MEA, respectively, in the late 21st century under the SSP5‐8.5 scenario compared to the historical period, while decreasing by 13% in SEA. These changes are consistent under both warming scenarios, and are more pronounced in the SSP5‐8.5 scenario compared to SSP1‐2.6, particularly in the later period of this century. An analysis of future atmospheric circulations suggests that global warming will weaken the western North Pacific subtropical high and cause its boundary to retreat eastward. This will lead to changes in the steering flow, which is closely related to TC tracks, resulting in TC landfalls to increase or decrease depending on the East Asian subregion.

The existence of large errors in precipitation products delivered by the network of Weather Surveillance Radar, 1988 Doppler (WSR‐88D) radars is broadly recognized. However, their quantitative characteristics remain poorly understood. Recently, the authors developed a functional‐statistical model that quantifies the relation between radar rainfall and the corresponding true rainfall in a way that is applicable to the probabilistic quantitative precipitation estimation planned for future use by the U.S. National Weather Service. The model consists of a deterministic distortion function and a random uncertainty factor, both conditioned on given radar rainfall values. It also accounts for the spatiotemporal correlations in the random uncertainty factor. The model components were estimated on the basis of a 6‐year‐long data sample that considers the effects of seasons, range from radar, and time scales. In this study, the authors present two different applications of the aforementioned uncertainty model: (1) the estimation of rainfall probability maps and (2) the generation of radar rainfall ensembles. In the former, maps of the rainfall exceedance probability for any threshold are produced, given a radar rainfall map. We also present the analytical derivation of the exceedance probability maps at coarser spatial scales. In the latter, the users can generate ensembles of probable true rainfall fields that are consistent with the observed radar rainfall and its error structure. Simulation of the random component is based on the Cholesky decomposition method. Finally, the authors discuss possible uses of these applications in hydrology and hydroclimatology.

This study investigates how tropical cyclone (TC) tracks and landfalls are modulated by the two major components of the intraseasonal oscillation (ISO), the 30–60-day Madden–Julian oscillation (MJO) and the 10–20-day quasi-biweekly oscillation (QBWO). In the convective phases of the MJO (phases 7 + 8 and 1 + 2), the western North Pacific Ocean (WNP) is mainly clustered with westward- and northwestward-moving TCs. The strong easterlies (southeasterlies) in the southern flank of the subtropical high lead to an increase in TC activity and landfalls in the Philippines and Vietnam (China and Japan) in phase 7 + 8 (phase 1 + 2). In the nonconvective phases (phases 3 + 4 and 5 + 6), TCs change from the original straight-moving type to the recurving type, such that the tendency for landfalls is significantly reduced. The QBWO, on the other hand, has a significant influence on TC landfalls in the Philippines and Japan. The strengthening of the subtropical high in phase 1 + 2 favors the development of westward-moving TCs and results in an increase in landfalls in the Philippines, while in phase 3 + 4 (phase 5 + 6), there is an increase (decrease) in TC activity and landfalls in Japan because of changes in genesis locations and large-scale circulations. The results herein suggest that both the MJO and QBWO exert distinctive impacts on TCs in the WNP.

Numerous studies focus on the impacts of ENSO diversity on tropical cyclone (TC) activities in the western North Pacific (WNP). In recent years, there is a growing threat of landfalling and northward-moving TCs in East Asia, accompanying an increase in central Pacific (CP) El Niño. Here, we aim to discover variations in landfalling TCs during various types of CP El Niño (CP-I and CP-II El Niño). It is found that significant changes in landfalling and going northward TCs over East Asia north 20°N are modulated by CP-I El Niño. During CP-I El Niño, TCs tend to landfall more often over the mainland of China with longer duration, moving distance, and stronger power dissipation index (PDI) after landfall and increased TC-induced rainfall, due to favorable conditions (beneficial steering flow, weak vertical wind shear, increased specific humidity, increased soil moisture, and temperature), especially significant over the northeastern part. The situation over the mainland of China is reversed during eastern Pacific (EP) El Niño and CP-II El Niño, with a significant decrease in the characteristics with corresponding unfavorable environments. Over the Korean Peninsula and Japan, the frequency of TC landfalls, as well as the duration and the moving distance after landfall, exhibits greater levels during CP-I and CP-II El Niño than during EP El Niño due to favorable steering flow, and thus, TC-induced rainfall enhances correspondingly. Regarding the PDI over the Korean Peninsula and Japan, it remains relatively consistent across all El Niño types. However, a notable increase in the PDI during EP El Niño could be attributed to the higher intensity of TCs prior to landfall.

This study develops a statistical‐dynamical seasonal typhoon forecast model (SDTFM) that utilizes the statistical correlation between East Asia (EA) tropical cyclone (TC) landfall and atmospheric circulation predicted by a coupled general circulation model for seasonal prediction and its predictability is verified. A total of 40 ensemble members produced through different data assimilation and time‐lag methods introduced as a way to reduce the initial condition error and model uncertainty enabled the development of the new SDTFM. According to the results, the SDTFM developed in this study showed significant predictability in TC landfall prediction when using the month of May for the initial conditions for the entire East Asia (EEA) and its three sub‐domains: Northern East Asia (NEA), Middle East Asia (MEA), and Southern East Asia (SEA). The predicted TC season is July–September (JAS), and only for SEA, including South China, the Philippines, and Vietnam, it is July–November (JASON) considering the relatively long landfall period. The models developed for each domain significantly predict the interannual variability of TC landfall at the 99% confidence level. The cross‐validated results are still significant at the 99% confidence level in NEA and SEA and the 95% confidence level in MEA and EEA.

The Next Generation Weather Radar (NEXRAD) program is a joint effort of the U.S. Departments of Commerce, Defense, and Transportation to develop, deploy, and support a network of over 135 Doppler weather radars called the Weather Surveillance Radar-1988 Doppler (WSR-88D). The WSR-88D will replace the present aging weather radars (circa, 1957 or 1974). These new Doppler weather radars will allow the identification and forecasting of aviation weather hazards with more accuracy and in more detail than was previously possible. This article focuses on how these Doppler radars will be used to identify and warn of aviation weather hazards. Benefits of the WSR-88D include much higher resolution data, the capability to measure velocities in storms and often in the clear air boundary layer, and the built-in capability to run computer programs (called algorithms) to detect storms automatically and identify potential severe weather associated with them. This article describes the WSR-88D system and characteristics of the data, some of the products produced by the system to meet aviation needs, issues that are related to the resolution of the base reflectivity data, and potential data artifacts that should be removed before the data are displayed on any air traffic control displays. © 1995 John Wiley & Sons, Inc. **This article is a US Government work and, as such, is the public domain in the United States of America.

Spatial patterns of tropical cyclone tornadoes (TCTs), and their relationship to patterns of mesoscale predictors within U.S. landfalling tropical cyclones (LTCs) are investigated using multicase composites from 27 years of reanalysis data (1995–2021). For 72 cases of LTCs with wide-ranging TC intensities at landfall, daytime TCT frequency maxima are found in the northeast, right-front, and downshear-right quadrants when their composites are constructed in ground-relative, TC-heading relative, and environmental shear relative coordinates, respectively. TCT maxima are located near maxima of 10-m–700-hPa bulk wind difference (BWD), which are enhanced by the TC circulation. This proxy for bulk vertical shear in roughly the lowest 3 km is among the best predictors of maximum TCT frequency. Relative to other times, the position of maximum TCT frequency during the afternoon shifts ∼100 km outward from the LTC center toward larger MLCAPE values. Composites containing the strongest LTCs have the strongest maximum 10-m–700-hPa and 10-m–500-hPa BWDs (∼20 m s−1) with nearby maximum frequencies of TCTs. Corresponding composites containing weaker LTCs but still many TCTs, had bulk vertical shear values that were ∼20% smaller (∼16 m s−1). Additional composites of cases having similarly weak average LTC strength at landfall, but few or no TCTs, had both maximum bulk vertical shears that were an additional ∼20% lower (∼12 m s−1) and smaller MLCAPE. TCT environments occurring well inland are distinguished from others by having stronger westerly shear and a west–east-oriented baroclinic zone (i.e., north–south temperature gradient) that enhances mesoscale ascent and deep convection on the LTC’s east side.

A possible world record peak 3-sec wind gust measurement of 220 kt (253 mph; 408 kph) was recorded on Barrow Island, Australia during the passage of Tropical Cyclone Olivia on April 10, 1996. This measurement was one of five extreme 3-sec gusts during a series of 5-min time periods. Gusts of 199, 220 and 202 kt were measured followed by a series of four lower values (minimum of 114 kt) which were then followed by two more extreme gusts of 187 and 161 kt in the 5-min time intervals. The elapsed time between gust maxima was 30 min, representing a scale of 8 nm (15 km) compared to the eye diameter of 40 nm (75 km). The 5-min average winds showed maxima and a minimum at the same time periods as the gusts. The pattern and scales suggests that a mesovortex was imbedded in the already strong eyewall mean winds (5-min mean maximum wind = 95 kt; 1-min mean maximum winds = 106 kt). The extreme gusts represented extreme gust factors of 2.27-2.75, nearly twice the average gust factor throughout the storm of 1.33. This clearly suggests that some process other than mechanical turbulence is important during this period. Radar images from the Bureau of Meteorology radar at Learmonth showed that this event took place at the maximum reflectivity gradient at the inner edge of the eyewall as it passed over the Barrow Island observing station. Eyewall mesovortices occur only at the inner eyewall edge. The observations also show it occurred just after the minimum pressure of 930 mb was observed, as the mean winds were increasing rapidly. In the previous hour, BoM instruments on nearby Varanus Island showed the minimum pressure to be 927 mb, also suggesting Barrow was at the edge of the eye. Varanus measured an extreme gust of 144 kt as a weaker section of the eyewall passed. Additional evidence for the mesovortex theory was seen in the relative humidity measurements. A sudden dip occurred in the near-saturated relative humidity at Barrow at the time of the lull between the two sets of extreme gusts. This may have been caused by a sudden subsidence such as would be expected to occur within the core of a mesovortex. These observations are consistent with the 180 kt flight level wind measured by research aircraft flying through an eyewall mesovortex in Hurricane Hugo (1989) northeast of Barbados and the 190 kt peak gust winds estimated from damage surveys in Hurricane Andrew (1992) in Florida and Tropical Cyclone Tracy (1974) in Darwin, Australia. Introduction During the landfall of intense tropical cyclones with surface 1-minute sustained winds in excess of 130 kt, it has frequently been difficult to obtain actual wind measurements since most instruments are distroyed. The landfall of Cyclone Tracy in December, 1974 in Darwin, Australia and Hurricane Andrew in August, 1992 in South Florida, USA created unprecedented distruction 1,2,3,4. Wind estimates were possible only by indirect means such as damage surveys 5, satellite estimation, ground-based radar data and composites of sparse available surface observations and high-level aircraft observations. Inferences concerning the physical mechansims responsible for the anomalous devastation in these storms has been suggested 2. The primary mechanism proposed has centered on the growth of intense convection in the hurricane's eyewall, convection generated by enhance surface convergence of air at the land-sea boundary. Intense convection in the strong shear region of the eyewall's inner edge is further hypothesized to spin up a convective scale mesovortex at the edge of the eyewall which grows quickly with time, on order of ten minutes, the convective cell lifetime.

For effective forecasting of tropical cyclone (TC) it is very important to have accurate initial structure of cyclone in numerical models. Assimilation of local data such as Doppler Weather Radar (DWR) data in numerical weather prediction (NWP) models has potential to improve the initial and boundary condition for the prediction of land falling cyclones. Xiao et al. (2005, 2007) carried out study on the assimilation of DWR radial wind and reflectivity into NWP model using the 3-dimensional variational data assimilation (3DVAR) system for the heavy rainfall events. A number of case studies on the positive impact of DWR radial wind and reflectivity observations in the assimilation cycle of Advanced Regional Prediction System (ARPS) were documented by Xue et al. (2003). Kun Zhao and Ming Xue (2009) studied the impact of radar data on the analysis and prediction of the structure, intensity and track of land falling Hurricane Ike-2008, at a cloud-resolving resolution. The hurricane landfall, intensification and weakening during the simulation period are well captured by assimilating both airborne Doppler radar reflectivity and wind data (Zhaoxia et al., 2009). The Bratseth successive correction technique and cloud analysis are part of ARPS Model developed by Center for Analysis and Prediction of Storms (CAPS), Oklahoma University, USA (Bratseth, 1986; Brewster, 1996). The ARPS data assimilation system (ADAS) and cloud analysis technique have capability to be applied for assimilation of radar data in Weather Research and Forecasting (WRF) Model.

In this study, several analyses were conducted that were aimed at improving sustained wind speed and gust forecasts for tropical cyclones (TCs) affecting coastal regions. An objective wind speed forecast analysis of recent TCs affecting the mid-Atlantic region was first conducted to set a benchmark for improvement. Forecasts from the National Digital Forecast Database were compared to observations and surface wind analyses in the region. The analysis suggests a general overprediction of sustained wind speeds, especially for areas affected by the strongest winds. Currently, National Weather Service Weather Forecast Offices use a software tool known as the Tropical Cyclone Forecast/Advisory (TCM) wind tool (TCMWindTool) to develop their wind forecast grids. The tool assumes linear decay in the sustained wind speeds when interpolating the National Hurricane Center 12–24-hourly TCM product to hourly grids. An analysis of postlandfall wind decay for recent TCs was conducted to evaluate this assumption. Results indicate that large errors in the forecasted wind speeds can emerge, especially for stronger storms. Finally, an analysis of gust factors for recent TCs affecting the region was conducted. Gust factors associated with weak sustained wind speeds are shown to be highly variable but average around 1.5. The gust factors decrease to values around 1.2 for wind speeds above 40 knots (kt; 1 kt = 0.51 m s−1) and are in general insensitive to the wind direction, suggesting local rather than upstream surface roughness largely dictates the gust factor at a given location. Forecasters are encouraged to increase land reduction factors used in the TCMWindTool and to modify gust factors to account for factors including the sustained wind speed and local surface roughness.

In this study, a practical typhoon effective rainfall nowcasting (TERN) model was developed for use in real‐time forecasting. The TERN model was derived from a data‐driven adaptive network‐based fuzzy inference system (ANFIS). The model inputs include meteorological data and radar reflectivity data. The model simulation process begins with an online typhoon warning issued by the Central Weather Bureau (CWB) of Taiwan. It is then determined whether the typhoon approaches the study area according to the typhoon track predicted by the CWB. When a typhoon hits Taiwan, various data are received from sensor instruments, including the ground precipitation data, typhoon climatological data, and radar reflectivity factor by using Weather Surveillance Radar, 1988, Doppler (WSR‐88D) products. The study site was Shihmen Catchment. A maximum of 10 typhoon events from 2000 to 2010 were collected. Regarding the model construction, the input combinations of the ground precipitations and reflectivity factors over the catchment functioned as optimal input variables. To verify the practicability of the ANFIS‐based TERN model, Typhoon Krosa, which hit Taiwan in 2007, was simulated. The results demonstrated that the proposed methodology of real‐time rainfall forecasts during typhoon warning periods yielded favorable performance levels, reliably predicting results regarding 1 h to 6 h forecasting horizons.

Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

The National Weather Service (NWS) is in the process of developing and testing the initial implementation of the Advanced Weather Information Processing System (AWIPS). AWIPS will provide an expandable processing system capable of acquiring observational data from a variety of central and local sources, and including its manipulation and display as part of the end-to-end forecast process. The accessability of basic Weather Surveillance Radar-1988 Doppler (WSR-88D) products at each forecaster workstation is one of the earliest benefits AWIPS will provide. As the products and capabilities of the WSR-88D evolve, the need in the algorithm calculations for external data, available through AWIPS, will increase. At the same time, AWIPS will provide the core capabilities for NWS forecasters to see the improved WSR-88D products in ways never before possible. The evolutionary path of both these technologies must be carefully coordinated to enhance their benefits to forecast operations. This paper provides an early look at the impacts expected from this symbiotic development.

Polarimetric weather radars, such as the Weather Surveillance Radar-1988 Doppler (WSR-88D), improve weather forecasts and provide valuable data for operational and scientific applications. The polarimetric capability adds additional insight into storm microphysics and greatly improves precipitation estimates. Nevertheless, fast-evolving weather events require high-temporal resolution data, which conventional radar systems (mechanical and dish-based) cannot provide. Phased array radar (PAR) offers superior observation capabilities with electronic beam steering and enhanced scanning agility. Furthermore, digital PAR enables 1-D (space and time) processing and overcomes limitations in clutter mitigation compared with the traditional radar systems that only use Doppler processing. Doppler processing is traditionally used to effectively filtering out ground clutter with zero mean velocity. In contrast, space-time processing (STP) enhances clutter mitigation to filter out both stationary and moving clutter through the joint spatial and temporal spectrum. This study aims to apply STP (nonadaptive) and space-time adaptive processing (STAP) to weather radar data and explore their benefits to improve Doppler velocity estimation of meteorological returns. Furthermore, the performance of STP and STAP for different digital PAR back ends, including fully digital and subarray systems, is investigated. Preliminary findings underscore the critical role of radar scanning parameters and environmental conditions, such as sample quantity, clutter-to-signal ratio (CSR), and signal-to-noise ratio (SNR), in the Doppler velocity estimation. Data collected with the recently completed Horus radar system are evaluated using STP and STAP. Results demonstrate the potential for improving data quality, particularly in Doppler velocity estimation within cluttered environments, through the application of STP and STAP techniques. The filtering algorithm with STAP demonstrates a substantial reduction in error within the Doppler velocity estimation, achieving approximately an eightfold improvement compared with the estimation derived from STP with filtering.

The mean kinematic and thermodynamic structures of tropical cyclones (TCs) making landfall in mainland China are examined by using sounding data from 1998 to 2009. It is found that TC landfall is usually accompanied with a decrease in low-level wind speed, an expansion of the radius of strong wind, weakening of the upper-level warm core, and drying of the mid-tropospheric air. On average, the warm core of the TCs dissipates 24 h after landfall. The height of the maximum low-level wind and the base of the stable layer both increase with the increased distance to the TC center; however, the former is always higher than the latter. In particular, an asymmetric structure of the TC after landfall is found. The kinematic and thermodynamic structures across various areas of TC circulation differ, especially over the left-front and right-rear quadrants (relative to the direction of TC motion). In the left-front quadrant, strong winds locate at a smaller radius, the upper-level temperature is warmer with the warm core extending into a deep layer, while the wet air occupies a shallow layer. In the right-rear quadrant, strong wind and wet air dwell in an area that is broader and deeper, and the warmest air is situated farther away from the TC center.