Tropical Cyclone Cases Research Articles

Relationship Between the Change in Size of Tropical Cyclones and Spatial Patterns of Precipitation

AbstractThe relationship between the size change of tropical cyclones (TCs) and radial distribution of precipitation was investigated for TCs occuring over the western North Pacific Ocean with satellite observation data. The size of a TC is defined as the radial extent of 15 m s−1 winds (R15). The spatial distribution of precipitation was investigated by extracting two subperiods, which are the size‐increasing period and the size‐stationary period, as determined from R15 evolution. The results show a contrast that during the size‐increasing period, precipitation falls both inside and outside the R15, whereas during the size‐stationary period, it is concentrated near the center of the TC and falls less around and outside R15. This contrast is also confirmed statistically by composite analysis using 64 TC cases. Further analysis reveals that this contrast does not depend on the intensity or the change in intensity of the TC, which indicates that the area of precipitation related to the intensity or intensity change of TCs is different from that related to the size change of TCs. Finally, we examined the radial distribution of inertial stability in TCs and found that precipitation during the size‐stationary period occurs in a region with a higher inertial stability than that which occurs during the size‐increasing period.

A Three-Dimensional Trajectory Model with Advection Correction for Tropical Cyclones: Algorithm Description and Tests for Accuracy

Abstract When computing trajectories from model output, gridded winds are often temporally interpolated to a time step shorter than model output intervals to satisfy computational stability constraints. This study investigates whether trajectory accuracy may be improved for tropical cyclone (TC) applications by interpolating the model winds using advection correction (AC) instead of the traditional linear interpolation in time (LI) method. Originally developed for Doppler radar processing, AC algorithms interpolate data in a reference frame that moves with the pattern translation, or advective flow velocity. A previously developed trajectory AC implementation is modified here by extending it to three-dimensional (3D) flows, and the advective flows are defined in cylindrical rather than Cartesian coordinates. This AC algorithm is tested on two model-simulated TC cases, Hurricanes Joaquin (2015) and Wilma (2005). Several variations of the AC algorithm are compared to LI on a sample of 10 201 backward trajectories computed from the modeled 5-min output data, using reference trajectories computed from 1-min output to quantify position errors. Results show that AC of 3D wind vectors using advective flows defined as local gridpoint averages improves the accuracy of most trajectories, with more substantial improvements being found in the inner eyewall where the horizontal flows are dominated by rotating cyclonic wind perturbations. Furthermore, AC eliminates oscillations in vertical velocity along LI backward trajectories run through deep convective updrafts, leading to a ~2.5-km correction in parcel height after 20 min of integration.

A Conceptual Framework for the Scale‐Specific Stochastic Modeling of Transitions in Tropical Cyclone Intensities

At any given time, a tropical cyclone (TC) vortex has multiple intensity pathways that are possible. We conceptualize this problem as a scenario where each of the TC's intensity pathways is a distinct attractor basin, and a combination of several external and internal factors across multiple scales dictates as to which of the many pathways the TC vortex actually takes. As with any complex system, it is difficult to know the details of the multiscale processes that cause or initiate the tipping of the TC vortex into an attractor basin. A stochastic shock arising from any of the various scales within a TC vortex and the subsequent cross‐scale energy transactions may rapidly increase the probability of the vortex intensifying or weakening. To address this problem and apply our conceptual framework to actual TC case studies, we formulate a novel scale‐specific stochastic model that examines the multiscale energetics at and across individual wave numbers within the TC vortex. The stochastic term is modeled in a realistic manner in that the lower and higher wave numbers are treated differently. High‐resolution Hurricane Weather and Research Forecast model outputs of two Bay of Bengal TCs, Phailin (intensifying) and Lehar (weakening), are used as case studies. An ensemble of intensity pathways is generated, and the nonstationary probability distributions of the intensity transitions at each time are examined. Our approach is another step toward an improved understanding of the stochastic dynamics of multiscale transitions of a TC vortex.

Quantification and Exploration of Diurnal Oscillations in Tropical Cyclones

AbstractDiurnal oscillations of infrared cloud-top brightness temperatures (Tbs) in tropical cyclones (TCs) as inferred from storm-centered, direction-relative longwave infrared (~11 μm) imagery are quantified for Northern Hemisphere TCs (2005–15) using statistical methods. These methods show that 45%, 54%, and 61% of at least tropical storm-, hurricane-, and major hurricane-strength TC cases have moderate or strong diurnal signals. Principal component analysis–based average behavior of all TCs with intensities of 34 kt (17.5 m s−1) or greater is shown to have a nearly symmetric diurnal signal where Tbs oscillate from warm to cold and cold to warm within and outside of a radius of approximately 220 km, with maximum central cooling occurring in the early morning (0300–0800 local standard time), and a nearly simultaneous maximum warming occurring near the 500-km radius—a radial standing wave with a node near 220-km radius. Amplitude and phase of these diurnal oscillations are quantified for individual 24-h periods (or cases) relative to the mean oscillation. Details of the diurnal behavior of TCs are used to examine preferred storm and environmental characteristics using a combination of spatial, composite, and regression analyses. Results suggest that diurnal, cloud-top Tb oscillations in TCs are strongest and most regular when storm characteristics (e.g., intensity and motion) and environmental conditions (e.g., vertical wind shear and low-level temperature advection) support azimuthally symmetric storm structures and when surrounding mid- and upper-level relative humidity values are greater. Finally, it is hypothesized that larger mid- and upper-level relative humidity values are necessary ingredients for robust, large-amplitude, and regular diurnal oscillations of Tbs in TCs.

Parameterizing Sea Surface Temperature Cooling Induced by Tropical Cyclones: 1. Theory and An Application to Typhoon Matsa (2005)

AbstractSea surface temperature cooling (SSTC) induced by tropical cyclones (TCs) could produce a significant impact on the TC intensity. Although a coupled atmosphere‐ocean model could provide such SSTC, various challenges associated with coupled modeling often lead many TC researchers to continue to use atmosphere‐only models. Therefore, the main goal of this study is to develop a fast, robust, and effective parameterization scheme for TC‐induced SSTC that can be used in atmosphere‐only TC models. The following three steps are taken to achieve this goal: (i) Results from an idealized ocean simulation, together with theoretical and temperature budget analyses, are analyzed to isolate each major mechanism causing TC‐induced SSTC, which is then used as a basis for the parameterization; (ii) building upon the idealized ocean simulation, a new SSTC parameterization scheme including vertical mixing, advection, and SST recovery processes under the influences of sea surface height anomalies and ocean subsurface temperature is developed; and (iii) this SSTC parameterization scheme is evaluated through numerical simulations of Typhoon Matsa (2005) and validated against remote sensing data. Results show significant improvements in the simulated TC intensity and SST changes after applying this parameterization scheme. Although further testing with more TC cases is needed, these results are promising, and the parameterization scheme should be compatible with any TC weather prediction model.

Impact of Vortex Initialization in Prediction of Tropical Cyclones over Bay of Bengal with NCUM Model

The present study evaluates the impact of vortex initialization (VI) scheme within the NCMRWF Global Unified model (NCUM-G) for prediction of tropical cyclones (TCs) formed over Bay of Bengal (BoB). For this purpose, two numerical experiments such as control simulation (CNTL) without using VI scheme and VOTX simulation using the VI scheme in the NCUM-G are performed by considering four landfalling TCs formed over BoB basin during the year 2016–17. The results suggest that even though TCs are large synoptic systems, the introduction of VI scheme has a positive impact on the prediction of the location, movement, intensity and development of rain bands associated with the TCs. The initial vortex position and landfall position errors are reduced by ∼64% and ∼39% in VOTX simulations over CNTL, respectively. The mean track errors of all the four TCs are reasonably improved by ∼58% in VOTX over CNTL. The equitable threat score (ETS) and frequency bias are significantly improved in the VOTX for all the TC cases as compared to CNTL. Study results provide a positive proof of concept that the VI scheme within the NCUM-G can help to improve the simulation of track and intensity of TCs over BoB.

Ensemble Forecasts of Tropical Cyclone Track with Orthogonal Conditional Nonlinear Optimal Perturbations

This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations (CNOPs)–based ensemble forecast technique in MM5 (Fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model). The results show that the ensemble forecast members generated by the orthogonal CNOPs present large spreads but tend to be located on the two sides of real tropical cyclone (TC) tracks and have good agreements between ensemble spreads and ensemble-mean forecast errors for TC tracks. Subsequently, these members reflect more reasonable forecast uncertainties and enhance the orthogonal CNOPs–based ensemble-mean forecasts to obtain higher skill for TC tracks than the orthogonal SVs (singular vectors)–, BVs (bred vectors)–and RPs (random perturbations)–based ones. The results indicate that orthogonal CNOPs of smaller magnitudes should be adopted to construct the initial ensemble perturbations for short lead–time forecasts, but those of larger magnitudes should be used for longer lead–time forecasts due to the effects of nonlinearities. The performance of the orthogonal CNOPs–based ensemble-mean forecasts is case-dependent, which encourages evaluating statistically the forecast skill with more TC cases. Finally, the results show that the ensemble forecasts with only initial perturbations in this work do not increase the forecast skill of TC intensity, which may be related with both the coarse model horizontal resolution and the model error.

Role of Planetary Boundary Layer Processes in the Simulation of Tropical Cyclones Over the Bay of Bengal

The behaviour of planetary boundary layer (PBL) schemes initialized at different life stages of a tropical cyclone (TC) is studied by considering seven Bay of Bengal TC cases. In each TC case, the Advanced Research Weather Research and Forecasting (WRF-ARW) model is initialized at four life stages (depression to very severe cyclone storm) with National Center for Environmental Prediction (NCEP) Global analysis and integrated up to 96 h. A set of six PBL sensitivity experiments are conducted at four stages for all seven TC cases to analyse the impact of the model boundary layer in simulating the TC track and intensity parameters. The model-produced track, intensity and rainfall patterns are evaluated with the best track, intensity and gridded rainfall estimates obtained from the India Meteorological Department (IMD). The spatial and radius/height section simulated fields are evaluated with satellite retrievals. Results depict that the six PBL schemes during model initialization at different stages of a TC have produced sizable differences in the simulation of track and intensity parameters. The local and nonlocal schemes produced different results based on the TC stage at which the model is initialized. The results also suggest that if the model is initialized with a non-organized cyclonic vortex such as depression stage of the storm, PBL schemes exhibit high sensitivity and spread in terms of both track and intensity. While the spread between PBL schemes was significantly reduced and found close to the observed estimates when the model was initialized at the advanced stages of the TC. In addition, the local 1.5-order closure scheme simulated the storm parameters relatively better when the cyclone vortex was not well organized in the model's initial conditions, while the non-local and first-order closure schemes perform better with initial model conditions of a well-defined cyclonic vortex.

A novel approach for solving CNOPs and its application in identifying sensitive regions of tropical cyclone adaptive observations

Abstract. In this paper, a novel approach is proposed for solving conditional nonlinear optimal perturbations (CNOPs), called the adaptive cooperative coevolution of parallel particle swarm optimization (PSO) and the Wolf Search algorithm (WSA) based on principal component analysis (ACPW). Taking Fitow (2013) and Matmo (2014), two tropical cyclone (TC) cases, CNOPs solved by the ACPW algorithm are used to investigate the sensitive regions identified by TC adaptive observations with the fifth-generation Mesoscale Model (MM5). Meanwhile, the 60 and 120 km resolutions are adopted. The adjoint-based method (short for the ADJ method) is also applied to solve CNOPs, and the result is used as a benchmark. To evaluate the advantages of the ACPW algorithm, we run the PSO, WSA and ACPW programs 10 times and then compare the maximum, minimum and mean objective values as well as the RMSEs. The analysis results prove that the hybrid strategy and cooperative coevolution are useful and effective. To validate the ACPW algorithm, the CNOPs obtained from the different methods are compared in terms of the patterns, energies, similarities and simulated TC tracks with perturbations. The results of our study may be summarized as follows: The ACPW algorithm can capture similar CNOP patterns as the ADJ method, and the patterns of TC Fitow are more similar than TC Matmo. At the 120 km resolution, similarities between the CNOPs of the ADJ method and the ACPW algorithm are more than those at the 60 km resolution. Compared to the ADJ method, although the CNOPs of the ACPW method produce lower energies, they can have improved benefits gained from the reduction of the CNOPs not only across the entire domain but also in the identified sensitive regions. The sensitive regions identified by the CNOPs from the ACPW algorithm have the same influence on the improvements of the skill of TC-track forecasting as those identified by the CNOPs from the ADJ method. The ACPW method is more efficient than the ADJ method. All conclusions prove that the ACPW algorithm is a meaningful and effective method for solving CNOPs and can be used to identify sensitive regions of TC adaptive observations.

A tropical cyclone similarity search algorithm based on deep learning method

The tropical cyclone (TC) track forecast is still a challenging problem. For operational TC forecasts, it is useful for forecasters to find the similar TC in history and reference its data to improve TC forecasting. Considering the vast number of historical TC cases, it is necessary to design a suitable search algorithm to help forecasters find similar TC cases. A historical TC similarity search algorithm (named as SA_DBN) used deep learning approaches based on 500-hPa weather patterns was proposed in this study. Various weather features were automatically extracted by a deep belief network (DBN) without subjective influences. The Chebyshev distance was used to measure the similarity between two TCs. In order to show that similar-TCs retrieved by SA_DBN are helpful for forecasting, a modified WPCLPR method based on the standard WPCLPR and similar-TC track is designed. The modified WPCLPR improved the forecast result (at 85% confidence level) when the lead time was 54H, 60H or 66H. These results showed that the proposed algorithm could effectively retrieve similar TCs and be helpful to forecasters.

Environmental conditions regulating the formation of super tropical cyclone during pre-monsoon transition period over Bay of Bengal

Deadliest tropical cyclones (TCs) with category 4 or 5 intensity, which are referred to super TCs (STCs), often take place in Bay of Bengal (BoB) during pre-monsoon transition period. These STCs are often synchronized with the first-branch northward-propagating intraseasonal oscillation (FNISO) over BoB, but not all TCs synchronizing with FNISO were able to develop into STCs. The study analyzes the distinctive environmental conditions for regular and super TC groups. From the intraseasonal background, the most important difference appears in the intensity and relative location of FNISO. A stronger and closer ISO would lead to a colder upper-level air temperature and thus a more unstable stratification which promotes a greater TC intensity. Similar to intraseasonal timescale, upper-level temperature on the interannual timescale is also colder in the STC cases. The combined intraseasonal and interannual environmental temperature difference between lower and upper troposphere are responsible for significant difference between the STC and TC cases.

Reduced Sensitivity of Tropical Cyclone Intensity and Size to Sea Surface Temperature in a Radiative-Convective Equilibrium Environment

It has been challenging to project the tropical cyclone (TC) intensity, structure and destructive potential changes in a warming climate. Here, we compare the sensitivities of TC intensity, size and destructive potential to sea surface warming with and without a pre-storm atmospheric adjustment to an idealized state of Radiative-Convective Equilibrium (RCE). Without RCE, we find large responses of TC intensity, size and destructive potential to sea surface temperature (SST) changes, which is in line with some previous studies. However, in an environment under RCE, the TC size is almost insensitive to SST changes, and the sensitivity of intensity is also much reduced to 3% °C−1–4% °C−1. Without the pre-storm RCE adjustment, the mean destructive potential measured by the integrated power dissipation increases by about 25% °C−1 during the mature stage. However, in an environment under RCE, the sensitivity of destructive potential to sea surface warming does not change significantly. Further analyses show that the reduced response of TC intensity and size to sea surface warming under RCE can be explained by the reduced thermodynamic disequilibrium between the air boundary layer and the sea surface due to the RCE adjustment. When conducting regional-scale sea surface warming experiments for TC case studies, without any RCE adjustment the TC response is likely to be unrealistically exaggerated. The TC intensity–temperature sensitivity under RCE is very similar to those found in coupled climate model simulations. This suggests global mean intensity projections under climate change can be understood in terms of a thermodynamic response to temperature with only a minor contribution from any changes in large-scale dynamics.

Reducing TC Position Uncertainty in an Ensemble Data Assimilation and Prediction System: A Case Study of Typhoon Fanapi (2010)

Abstract Ensemble-based data assimilation (EDA) has been used for tropical cyclone (TC) analysis and prediction with some success. However, the TC position spread determines the structure of the TC-related background error covariance and affects the performance of EDA. With an idealized experiment and a real TC case study, it is demonstrated that observations in the core region cannot be optimally assimilated when the TC position spread is large. To minimize the negative impact from large position uncertainty, a TC-centered EDA approach is implemented in the Weather Research and Forecasting (WRF) Model–local ensemble transform Kalman filter (WRF-LETKF) assimilation system. The impact of TC-centered EDA on TC analysis and prediction of Typhoon Fanapi (2010) is evaluated. Using WRF Model nested grids with 4-km grid spacing in the innermost domain, the focus is on EDA using dropsonde data from the Impact of Typhoons on the Ocean in the Pacific field campaign. The results show that the TC structure in the background mean state is improved and that unrealistically large ensemble spread can be alleviated. The characteristic horizontal scale in the background error covariance is smaller and narrower compared to those derived from the conventional EDA approach. Storm-scale corrections are improved using dropsonde data, which is more favorable for TC development. The analysis using the TC-centered EDA is in better agreement with independent observations. The improved analysis ameliorates model shock and improves the track forecast during the first 12 h and landfall at 72 h. The impact on intensity prediction is mixed with a better minimum sea level pressure and overestimated peak winds.

Objective estimation of tropical cyclone innercore surface wind structure using infrared satellite images

An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.

Forecasting Tropical Cyclone Eye Formation and Dissipation in Infrared Imagery

Abstract The development of an infrared (IR; specifically near 11 μm) eye probability forecast scheme for tropical cyclones is described. The scheme was developed from an eye detection algorithm that used a linear discriminant analysis technique to determine the probability of an eye existing in any given IR image given information about the storm center, motion, and latitude. Logistic regression is used for the model development and predictors were selected from routine information about the current storm (e.g., current intensity), forecast environmental factors (e.g., wind shear, oceanic heat content), and patterns/information (e.g., convective organization, tropical cyclone size) extracted from the current IR image. Forecasts were created for 6-, 12-, 18-, 24-, and 36-h forecast leads. Forecasts were developed using eye existence probabilities from North Atlantic tropical cyclone cases (1996–2014) and a combined North Atlantic and North Pacific (i.e., Northern Hemisphere) sample. The performance of North Atlantic–based forecasts, tested using independent eastern Pacific tropical cyclone cases (1996–2014), shows that the forecasts are skillful versus persistence at 12–36 h, and skillful versus climatology at 6–36 h. Examining the reliability and calibration of those forecasts shows that calibration and reliability of the forecasts is good for 6–18 h, but forecasts become a little overconfident at longer lead times. The forecasts also appear unbiased. The small differences between the Atlantic and Northern Hemisphere formulations are discussed. Finally, and remarkably, there are indications that smaller TCs are more prone to form eye features in all of the TC areas examined.

Kinetic energy flux budget across air-sea interface

The kinetic energy (KE) fluxes into subsurface currents (EFc) is an important boundary condition for ocean circulation models. Traditionally, numerical models assume the KE flux from wind (EFair) is identical to EFc, that is, no net KE is gained (or lost) by surface waves. This assumption, however, is invalid when the surface wave field is not fully developed, and acquires KE when it grows in space or time. In this study, numerical experiments are performed to investigate the KE flux budget across the air-sea interface under both uniform and idealized tropical cyclone (TC) winds. The wave fields are simulated using the WAVEWATCH III model under different wind forcing. The difference between EFair and EFc is estimated using an air-sea KE budget model. To address the uncertainty of these estimates resides in the variation of source functions, two source function packages are used for this study: the ST4 source package (Ardhuin et al, 2010), and the ST6 source package (Babanin, 2011). The modeled EFc is significantly reduced relative to EFair under growing seas for both the uniform and TC experiments. The reduction can be as large as 20%, and the variation of this ratio is highly dependent on the choice of source function for the wave model. Normalized EFc are found to be consistent with analytical expressions by Hwang and Sletten (2008) and Hwang and Walsh (2016) and field observations by Terray et al. (1996) and Drennan et al. (1996), while the scatters are more widely in the TC cases due to the complexity of the associated wave field. The waves may even give up KE to subsurface currents in the left rear quadrant of fast moving storms. Our results also suggest that the normalized KE fluxes may depend on both wave age and friction velocity (u*).

Impact of ocean warming on tropical cyclone track over the western north pacific: A numerical investigation based on two case studies

AbstractThe impact of ocean warming on tropical cyclone (TC) track over the western North Pacific is an open issue. Relatively little is known about possible changes in TC tracks under ocean warming conditions due to both inhomogeneous observation networks and large natural variability over a relatively short observational period. A suite of semiidealized numerical experiments on two TC cases is conducted to investigate the response of TC tracks to increases in sea surface temperature (SST). It is found that the simulated TC track is highly sensitive to underlying SST. Specifically, through its influence on the radial distribution of sea surface enthalpy, ocean warming can lead to changes in the tangential wind profile and thus increase the TC size in terms of the radius of gale force wind, which is attributed to the increase in maximum wind speed, the expansion of the radius of maximum wind, and the additional increase in outer winds. The increased TC size, as suggested by previous studies, further leads to the eastward withdrawal of the western Pacific subtropical high (WPSH) and thus a northward turning of the TC. Results of climate simulations in the present study provide further evidence for the aforementioned impact of ocean warming on TC size and thus the WPSH and TC track. Results of the present study also imply that the threat of storms to countries in East Asia may be reduced due to possible changes in TC tracks if ocean warming continues in the future.

Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm

This study presents an approach to assimilate tropical cyclone (TC) real-time reports and the University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies (CIMSS) Atmospheric Motion Vectors (AMV) data into the Weather Research and Forecasting (WRF) model for TC forecast applications. Unlike current methods in which TC real-time reports are used to either generate a bogus vortex or spin up a model initial vortex, the proposed approach ingests the TC real-time reports through blending a dynamically consistent synthetic vortex structure with the CIMSS-AMV data. The blended dataset is then assimilated into the WRF initial condition, using the local ensemble transform Kalman filter (LETKF) algorithm. Retrospective experiments for a number of TC cases in the northwestern Pacific basin during 2013–2014 demonstrate that this approach could effectively increase both the TC circulation and enhance the large-scale environment that the TCs are embedded in. Further evaluation of track and intensity forecast errors shows that track forecasts benefit more from improvement in the large-scale flow at 4–5-day lead times, whereas the intensity improvement is minimal. While the difference between the track and intensity improvement could be due to a specific model configuration, this result appears to be consistent with the recent reports of insignificant impacts of inner core data assimilation in operational TC models at the long range of 4–5 days. The new approach will be most beneficial for future regional TC models that are directly initialized from very high-resolution global models whose storm initial locations are sufficiently accurate at the initial analysis that there is no need to carry out any artificial vortex removal or filtering steps.

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

AbstractA total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three‐dimensional variational (3D‐Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.

Impact of different climatic flows on typhoon tracks

A tropical cyclone (TC) vortex is considered to be embedded in and steered by a large-scale environmental flow. The environmental flow can be decomposed into two parts: temporal climatic flow and anomaly. The former is defined according to the calendar climatology with a diurnal cycle and a seasonal cycle. Thus, the temporal climatic flow of the atmosphere, which can be estimated using reanalysis data, varies with regions, altitudes, and hours. The impact of different climatic flows on TC tracks in the Northwest Pacific is examined using a simple generalized beta-advection model. Results show that the predicted tracks of two TC cases have large deviations from their best tracks in the following 1–2 days if the temporal climatic wind is replaced by other hourly climatic winds on the same calendar day or by a several-day-mean climatic wind. The track deviation is more significant when the climatic wind difference is larger than 2 m s−1. This experiment reconfirms that a TC track is influenced by temporal climatic flow and interaction with other disturbances in the vicinity.