Tropical Cyclone Initialization Research Articles

Dynamical Structures of Cross-Domain Forecast Error Covariance of a Simulated Tropical Cyclone in a Convection-Permitting Coupled Atmosphere–Ocean Model

AbstractUnderstanding the dynamics of the flow-dependent forecast error covariance across the air–sea interface is beneficial toward revealing the potential influences of strongly coupled data assimilation on tropical cyclone (TC) initialization in coupled models, and the fundamental dynamics associated with TC air–sea interactions. A 200-member ensemble of convection-permitting forecasts from a coupled atmosphere–ocean regional model is used to investigate the forecast error covariance across the oceanic and atmospheric domains during the rapid intensification of Hurricane Florence (2018). Forecast uncertainties in both atmospheric and oceanic domains, from an Eulerian perspective, increase with forecast lead time, mainly from TC displacement errors. In a storm-relative framework, the ensemble forecast uncertainties in both domains are predominantly caused by differences in the simulated storm intensity and structure. The largest ensemble spread in the atmospheric pressure, temperature, and wind fields can be found within the TC inner-core region. Alternatively, the largest ensemble spread in the upper-ocean currents and temperature fields are located along the cold wake behind the storm. Cross-domain ensemble correlations between simulated atmospheric (oceanic) observations and oceanic (atmospheric) state variables in the storm-relative coordinates are highly anisotropic, variable dependent, and ultimately driven by the dynamics of TC air–sea interactions. Meaningful and dynamically consistent cross-domain ensemble correlations suggest that it is possible to use atmospheric and oceanic observations to simultaneously update state variables associated with the coupled ocean–atmosphere prediction of TCs using strongly coupled data assimilation. Sensitivity experiments demonstrate that at least 60–80 ensemble members are required to represent physically consistent cross-domain correlations and minimize sampling errors.

Impact of Tropical Cyclone Initialization on Its Convection Development and Intensity: A Case Study of Typhoon Megi (2010)

AbstractThis study investigates the impact of tropical cyclone (TC) initialization methods on TC intensity prediction under a framework coupling the Weather Research and Forecasting Model with the TC Centered-Local Ensemble Transform Kalman Filter (WRF TCC-LETKF). While the TC environments are constrained by assimilating the same environmental observations, two different initialization strategies, assimilating real dropsonde observations (the DP experiment) and synthetic axisymmetric surface wind structure (the VT experiment), are employed to construct the TC inner-core structure. These two experiments have distinct results on predicting the rapid intensification (RI) of Typhoon Megi (2010), which can be attributed to their different convective burst (CB) development. In DP, the assimilation of the dropsondes helps establish a realistic TC structure with asymmetry information, leading to scattered CB distribution and persistent RI with abundant moisture supply. In VT, assimilating the axisymmetric surface wind structure spins up the TC efficiently. However, the initially excessive CB coverage causes a too-early high-level warm core, and the reduced moisture supply hinders RI. The forecast results imply that if the TC structure is initialized using a scheme considering only the axisymmetric vortex structure, the RI potential can possibly be underestimated due to the inability to represent the realistic asymmetric structure. Finally, assimilation of both the real and synthetic data can be complementary, giving a strong TC initially that undergoes a longer RI period.

A Tropical Cyclone Initialization in Multi-Scale Localization with Hybrid Four Dimensional Ensemble-Variational System: Preliminary Results

A Tropical Cyclone Initialization in Multi-Scale Localization with Hybrid Four Dimensional Ensemble-Variational System: Preliminary Results

Application of a Typhoon Initialization Scheme Based on the Incremental Analysis Updates Technique in a Rapid Update Cycle System

Initialization of tropical cyclones plays an important role in typhoon numerical prediction. This study applied a typhoon initialization scheme based on the incremental analysis updates (IAU) technique in a rapid refresh system to improve the prediction of Typhoon Lekima (2019). Two numerical sensitivity experiments with or without application of the IAU technique after performing vortex relocation and wind adjustment procedures were conducted for comparison with the control experiment, which did not involve a typhoon initialization scheme. Analysis of the initial fields indicated that the relocation procedure shifted the typhoon circulation to the observed typhoon region, and the wind speeds became closer to the observations following the wind adjustment procedure. Comparison of the results of the sensitivity and control experiments revealed that the vortex relocation and wind adjustment procedures could improve the prediction of typhoon track and intensity in the first 6-h period, and that these improvements were extended throughout the first 12-h period of the prediction by the IAU technique. The new typhoon initialization scheme also improved the simulated typhoon structure in terms of not only the wind speed and warm core prediction but also the organization of the eye of Typhoon Lekima. Diagnosis of the tendencies of variables showed that use of the IAU technique in a typhoon initialization scheme is efficacious in resolving the spurious high-frequency noise problem such that the model is able to reach equilibrium as soon as possible.

Impact of Assimilating Aircraft Reconnaissance Observations on Tropical Cyclone Initialization and Prediction Using Operational HWRF and GSI Ensemble–Variational Hybrid Data Assimilation

Abstract This study evaluates the impact of assimilating high-resolution, inner-core reconnaissance observations on tropical cyclone initialization and prediction in the 2013 version of the operational Hurricane Weather Research and Forecasting (HWRF) Model. The 2013 HWRF data assimilation system is a GSI-based hybrid ensemble–variational system that, in this study, uses the Global Data Assimilation System ensemble to estimate flow-dependent background error covariance. Assimilation of inner-core observations improves track forecasts and reduces intensity error after 18–24 h. The positive impact on the intensity forecast is mainly found in weak storms, where inner-core assimilation produces more accurate tropical cyclone structures and reduces positive intensity bias. Despite such positive benefits, there is degradation in short-term intensity forecasts that is attributable to spindown of strong storms, which has also been seen in other studies. There are several reasons for the degradation of intense storms. First, a newly discovered interaction between model biases and the HWRF vortex initialization procedure causes the first-guess wind speed aloft to be too strong in the inner core. The problem worsens for the strongest storms, leading to a poor first-guess fit to observations. Though assimilation of reconnaissance observations results in analyses that better fit the observations, it also causes a negative intensity bias at the surface. In addition, the covariance provided by the NCEP global model is inaccurate for assimilating inner-core observations, and model physics biases result in a mismatch between simulated and observed structure. The model ultimately cannot maintain the analysis structure during the forecast, leading to spindown.

Assimilation of All-Sky Infrared Radiances from Himawari-8 and Impacts of Moisture and Hydrometer Initialization on Convection-Permitting Tropical Cyclone Prediction

Abstract This study explores the impacts of assimilating all-sky infrared satellite radiances from Himawari-8, a new-generation geostationary satellite that shares similar remote sensing technology with the U.S. geostationary satellite GOES-16, for convection-permitting initialization and prediction of tropical cyclones with an ensemble Kalman filter (EnKF). This case studies the rapid intensification stages of Supertyphoon Soudelor (2015), one of the most intense tropical cyclones ever observed by Himawari-8. It is found that hourly cycling assimilation of the infrared radiance improves not only the estimate of the initial intensity, but also the spatial distribution of essential convective activity associated with the incipient tropical cyclone vortex. Deterministic convection-permitting forecasts initialized from the EnKF analyses are capable of simulating the early development of Soudelor, which demonstrates encouraging prospects for future improvement in tropical cyclone prediction through assimilating all-sky radiances from geostationary satellites such as Himawari-8 and GOES-16. A series of forecast sensitivity experiments are designed to systematically explore the impacts of moisture updates in the data assimilation cycles on the development and prediction of Soudelor. It is found that the assimilation of the brightness temperatures contributes not only to better constraining moist convection within the inner-core region, but also to developing a more resilient initial vortex, both of which are necessary to properly capture the rapid intensification process of tropical cyclones.

Improvements to a Tropical Cyclone Initialization Scheme and Impacts on Forecasts

Abstract This study makes improvements to the tropical cyclone (TC) initialization method introduced by Nguyen and Chen (i.e., the NC2011 scheme). The authors found that prescribing sea level pressure associated with the initial vortex using a modified Fujita formula has very little impact on the vortex structure and intensity during a series of 1-h model integration and relocation. On the other hand, inserting an artificial warm core makes the vortex spin up much faster. When a warm core is inserted during the initial spinup process, the computational time required for model initialization is reduced by ½–⅓. Because prescribed sea level pressure is not required to spin up the vortex, information on vortex size, such as radius of maximum wind, is no longer needed. The performance of the improved NC2011 scheme with an initial prescribed warm core during the initial spinup process is tested for typhoons that made landfall over southern China or Vietnam in 2006. Before landfall, these storms were over the open ocean where conventional data were sparse, without special observations. Two sets of model runs, with (NC2011-CTRL) and without (CTRL) vortex initialization, are performed for comparison. The initial and time-dependent boundary conditions are from the NCEP Final Analyses (FNL). There are twelve 48-h simulations in each run set. Results show that the vortex initialization improves TC track and intensity simulations.

The Spin-up Process of a Cyclone Vortex in a Tropical Cyclone Initialization Scheme and Its Impact on the Initial TC Structure

The scheme developed by Nguyen and Chen (2011) is used to produce 18 TCs (2004−2013) over the Northwestern Pacific that are well adjusted to the environment. The environment, including SST, in which the storm is embedded has a significant effect on the intensity and rainband patterns of these TCs. During the early season, TCs have a tendency to exhibit a “9” type asymmetric structure with an upper-level outflow channel extending southwestward from the southeastern quadrate of the storm. At low levels, the convergence area between the TC circulation and the southwesterly monsoon flow is a favorable location for the development of spiral rainbands. Late season TCs have a tendency to produce a “6” type storm structure with an outflow channel extending northeastward from the northwestern part of the eyewall, especially when an upper-level cold low or trough is present to the northwest of the storm. At low levels, the convergence of the northeasterly monsoon flow and the TC circulation is favorable for the occurrences of spiral rainbands. For intense TCs that underwent an eyewall replacement cycle, the scheme also shows considerable skill in reproducing the concentric eyewall structure. (Citation: Chen, C., Y. Chen, and H. V. Nguyen, 2014: The spin-up process of a cyclone vortex in a tropical cyclone initialization scheme and its impact on the Initial TC structure. SOLA, 10, 93−97, doi:10.2151/sola.2014-019).

An Initialization Scheme for Tropical Cyclone Numerical Prediction by Enhancing Humidity in Deep-Convection Region

AbstractA nudging scheme for humidity fields is implemented in the Advanced Hurricane Weather Research and Forecasting model (WRF) for tropical cyclone (TC) initialization. The scheme improves TC simulation by enhancing the TC humidity profile in deep-convection regions, where it uses satellite Fengyun 2 cloud-top brightness temperatures as a judging criterion. The impacts of the nudging on predicting TC intensity and structure are evaluated through the simulation of TC Khanun (2005) during its movement toward landfall at the coast of Zhejiang Province, China. During the nudging, the humidity distributions at the TC's inner core and along its outer spiral rainbands, where deep convections occur, are both enhanced. As a result, the intensity of the vortex is enhanced, being more consistent to the best-track data from the China Meteorological Administration. Specifically, the nudging modifies the simulated distribution of humidity according to convective activities captured by the satellite and therefore adjusts the development of deep convection in the model, which then influences the intensity and size of TC vortex through diabatic heating. During WRF simulation, the TC vortex initialized from the humidity nudging is dynamically and thermodynamically balanced with the background field, favoring a steady development of the vortex's intensity and structure. Because of the better simulation of TC inner core and outer spiral rainbands, the WRF simulation skills of TC intensity and track are improved.

On the initialization of tropical cyclones with a three dimensional variational analysis

A method of initializing tropical cyclones in high-resolution numerical models is developed by modifying a data assimilation system, the NRL atmospheric variational data assimilation system (NAVDAS), which was designed for general mesoscale weather prediction using a three-dimensional variational (3DVAR) analysis with intermittent updates. The method includes the following three upgrades to overcome difficulties resulting from tropical cyclone initialization with the NAVDAS analysis. First, synthetic observation soundings are generated on 9 vertical levels at 49 points for strong storms (v max > 23.1 m s−1) and 41 points for weak storms around each cyclone center to supplement the observations used by the analysis. Secondly, a vortex relocation method for nested grids is developed to correct the cyclone position in the background fields of the analysis for each nested mesh. Lastly, the 3DVAR analysis is modified to gradually reduce the horizontal length scale and geostrophic coupling constraint near the center of a tropical cyclone for minimizing the problems introduced by improper covariances and coupling constraint used in the analysis. The synthetic observations significantly improve the intensity and structure of the analysis and the track forecast. The vortex relocation significantly improves the first guess background, avoiding the large analysis corrections that would be needed to correct cyclone position, and reducing the imbalance introduced by such large analysis increments. The modifications to the analysis length scale and geostrophic coupling constraint successfully improve the inner core analysis, providing a tighter circulation, and reducing the underestimate of the mass field gradient. Among the three upgrades, the vortex relocation provides the largest improvement to the tropical cyclone initialization and forecast.

Tropical cyclone track and intensity prediction with a structure adjustable balanced vortex

A new Tropical Cyclone (TC) initialization method with the structure adjustable bogus vortex was applied to the forecasts of track, central pressure, and wind intensity for the 417 TCs observed in the Western North Pacific during the 3-year period of 2005–2007. In the simulations the Final Analyses (FNL) with 1° × 1° resolution of National Center for Environmental Prediction (NCEP) were incorporated as initial conditions. The present method was shown to produce improved forecasts over those without the TC initialization and those made by Regional Specialized Meteorological Center Tokyo. The average track (central pressure, wind intensity) errors were as small as 78.0 km (11.4 hPa, 4.9 m s−1) and 139.9 km (12.4 hPa, 5.5 m s−1) for 24-h and 48-h forecasts, respectively. It was found that the forecast errors are almost independent on the size and intensity of the observed TCs because the size and intensity of the bogus vortex can be adjusted to fit the best track data. The results of this study indicate that a bogus method is useful in predicting simultaneously the track, central pressure, and intensity with accuracy using a dynamical forecast model.

High-Order Spectral Filter for the Spherical-Surface Limited Area

Abstract A high-order spectral filter for the spherical-surface limited-area domain, either window or sector type, is presented, where the window domain is finite both in longitude and latitude and the sector domain is finite in longitude, but is ranged from Pole to Pole in latitude. The data given in the physical domain are extended to either extended window or sector domain by padding artificial data that are appropriate for spectral decomposition with half-ranged Fourier series. The high-order filter equation of Laplacian operator type was split into first- or second-order spherical elliptic equations as in the global domain high-order spectral filter. Each low-order elliptic equation is discretized using half-ranged Fourier series both in longitudinal and latitudinal direction. Since the domain is of the spherical geometry, the window domain spectral filter consists of full matrices for each zonal wavenumber and thus performs filtering with O(N3) operation for N × N grids. On the other hand, the sector domain filter performs with efficient O(N2 logN) operation for the same grids, because the matrices can be constructed in tridiagonal form. The error of the filter was analyzed using the eigenfunctions of the filter equation to get insights on data-extension parameters. The limited-area domain filters were tested with localized analytic function and the midlatitude observed data of meteorological variables, and the results were compared to those of the global domain filter. Accuracies of window and sector domain filters were found almost the same, and they turned out to vary with the filter parameters and the location and size of the domain. Application of the limited domain filters to the tropical cyclone initialization scheme showed very close performances to each other for the track and intensity forecasts.

A Vortex Relocation Scheme for Tropical Cyclone Initialization in Advanced Research WRF

Abstract This paper introduces a relocation scheme for tropical cyclone (TC) initialization in the Advanced Research Weather Research and Forecasting (ARW-WRF) model and demonstrates its application to 70 forecasts of Typhoons Sinlaku (2008), Jangmi (2008), and Linfa (2009) for which Taiwan’s Central Weather Bureau (CWB) issued typhoon warnings. An efficient and dynamically consistent TC vortex relocation scheme for the WRF terrain-following mass coordinate has been developed to improve the first guess of the TC analysis, and hence improves the tropical cyclone initialization. The vortex relocation scheme separates the first-guess atmospheric flow into a TC circulation and environmental flow, relocates the TC circulation to its observed location, and adds the relocated TC circulation back to the environmental flow to obtain the updated first guess with a correct TC position. Analysis of these typhoon cases indicates that the relocation procedure moves the typhoon circulation to the observed typhoon position without generating discontinuities or sharp gradients in the first guess. Numerical experiments with and without the vortex relocation procedure for Typhoons Sinlaku, Jangmi, and Linfa forecasts show that about 67% of the first-guess fields need a vortex relocation to correct typhoon position errors while eliminates the topographical effect. As the vortex relocation effectively removes the typhoon position errors in the analysis, the simulated typhoon tracks are considerably improved for all forecast times, especially in the early periods as large adjustments appeared without the vortex relocation. Comparison of the horizontal and vertical vortex structures shows that large errors in the first-guess fields due to an incorrect typhoon position are eliminated by the vortex relocation scheme and that the analyzed typhoon circulation is stronger and more symmetric without distortions, and better agrees with observations. The result suggests that the main difficulty of objective analysis methods [e.g., three-dimensional variational data assimilation (3DVAR)], in TC analysis comes from poor first-guess fields with incorrect TC positions rather than not enough model resolution or observations. In addition, by computing the eccentricity and correlation of the axes of the initial typhoon circulation, the distorted typhoon circulation caused by the position error without the vortex relocation scheme is demonstrated to be responsible for larger track errors. Therefore, by eliminating the typhoon position error in the first guess that avoids a distorted initial typhoon circulation, the vortex relocation scheme is able to improve the ARW-WRF typhoon initialization and forecasts particularly when using data assimilation update cycling.

Tropical Cyclone Initialization with a Spherical High-Order Filter and an Idealized Three-Dimensional Bogus Vortex

Abstract A tropical cyclone initialization method with an idealized three-dimensional bogus vortex of an analytic empirical formula is presented for the track and intensity prediction. The procedure in the new method consists of four steps: the separation of the disturbance from the analysis, determination of the tropical cyclone domain, generation of symmetric bogus vortex, and merging of it with the analysis data. When separating the disturbance field, an efficient spherical high-order filter with the double-Fourier series is used whose cutoff scale can be adjusted with ease to the horizontal scale of the tropical cyclone of interest. The tropical cyclone domain is determined from the streamfunction field instead of the velocities. The axisymmetric vortex to replace the poorly resolved tropical cyclone in the analysis is designed in terms of analytic empirical functions with a careful treatment of the upper-layer flows as well as the secondary circulations. The geopotential of the vortex is given in such a way that the negative anomaly in the lower layer is changed into positive anomaly above the prescribed pressure level, which depends on the intensity of the tropical cyclone. The geopotential is then used to calculate the tangential wind and temperature using the gradient wind balance and the hydrostatic balance, respectively. The inflow and outflow in the tropical cyclone are constructed to resemble closely the observed or simulated structures under the constraint of mass balance. The bogus vortex is merged with the disturbance field with the use of matching principle so that it is not affected except near the boundary of tropical cyclone domain. The humidity of the analysis is modified to be very close to the saturation in the lower layers near the tropical cyclone center. The balanced bogus vortex of the present study is completely specified on the basis of four parameters from the Regional Specialized Meteorological Center (RSMC) report and the additional two parameters, which are derived from the analysis data. The initialization method was applied to the track and the intensity (in terms of central pressure) prediction of the TCs observed in the western North Pacific Ocean and East China Sea in 2007 with the use of the Weather Research and Forecasting (WRF) model. No significant initial jump or abrupt change was seen in either momentum or surface pressure during the time integration, thus indicating a proper tropical cyclone initialization. Relative to the results without the tropical cyclone initialization and the forecast results of RSMC Tokyo, the present method presented a great improvement in both the track and intensity prediction.

Tropical Cyclone Initialization with Dynamical Retrieval from a Modified UWPBL Model

A new scheme, termed Vortex Initialization with the Assimilation of Retrieved Variables (VIRV), is presented to improve the initialization of regional numerical model for Tropical Cyclone (TC) prediction. In this scheme, the horizontal winds in Planetary Boundary Layer (PBL) and the sea level pressure (SLP), retrieved from Quick Scatterometer (QuikSCAT) data obtained using a modified University of Washington Planetary Boundary Layer (UWPBL) model, are assimilated with a cycled three-dimensional variational (3DVAR) technique to produce the initialized analysis. The procedures of retrieval are implemented under the joint dynamical constraints of the gradient wind, secondary circulation, and thermal stratification. Moreover, in order to improve the analysis of TC intensity, the roughness parameterization in the UWPBL model was modified for the case of strong surface wind. The sensitivities of the structure, intensity, and track of TC to the VIRV are then examined by two numerical experiments for TC Bilis (2006) and TC Fung-wong (2008). The maximum Wind Speed (MWS) and minimum Sea Level Pressure (MSLP) retrieved from the QuikSCAT data obtained using the modified UWPBL model show more agreement with the observations relative to those derived from the analysis of the National Center for Environmental Prediction (NCEP global model). The analysis of TC intensity cfm enhanced using VIRV by modifying the low-level (upper-level) convergence (divergence), vertical shear of horizontal wind, transportation of moisture. Significant improvement on 48-h TC simulation is identified in the MWS, with 22.8% error reduction. In particular, the Modification of Roughness Parameterization (MRP) enhanced the simulation of MWS by 6.9%. Finally, the VIRV also reduces the simulation error in the �

Typhoon Initialization in a Mesoscale Model—Combination of the Bogused Vortex and the Dropwindsonde Data in DOTSTAR

Abstract Issues concerning the initialization and simulation of tropical cyclones by integrating both dropwindsonde data and a bogused vortex into a mesoscale model have been studied. A method is proposed to combine dropwindsonde data with a bogused vortex for tropical cyclone initialization and to improve track and intensity prediction. A clear positive impact of this proposed method on both the tropical cyclone track and intensity forecasts in a mesoscale model is demonstrated in three cases of typhoons, including Meari (2004), Conson (2004), and Megi (2004). The effectiveness of the proposed method in improving the track and intensity forecasts is also demonstrated in the evaluation of all 10 cases of Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) missions in 2004. This method provides a useful and practical means to improve operational tropical cyclone prediction with dropwindsonde observations.

Tropical Cyclone Initialization and Prediction Based on Four-Dimensional Variational Data Assimilation

Abstract Issues on the initialization and simulation of tropical cyclones (TCs) have been studied here based on four-dimensional variational data assimilation. In particular, experiments have been carried out to assess 1) what the most critical parameters for the so-called bogus data assimilation are and 2) how the current procedures for the bogus data assimilation can be further improved. It is shown that the assimilation of wind fields is more successful than that of pressure fields in improving the initial structure and prediction of TCs. It is emphasized that the geostrophic adjustment favors the pressure field to adjust to the wind field because the TC vortex is much smaller than the radius of Rossby deformation. The results suggest that a better initial condition in the wind field is critical to the simulation of TCs. Experiments from this study also show that inclusion of the initial TC movement in the data assimilation window can help improve the track prediction, particularly during the early integration period. This method is able to shed light on the improvement of TC simulation based on the bogus data assimilation. In all, the results add a theoretical interpretation of the importance of the wind field to the sea level pressure field in terms of geostrophic adjustment, as well as a time dimension of the bogus data assimilation, by assimilating a movable vortex in the four-dimensional variational data assimilation.

Hurricane Juan (2003). Part II: Forecasting and Numerical Simulation

Abstract The landfall of Hurricane Juan (September 2003) in the Canadian Maritimes represents an ideal case in which to study the performance of operational forecasting of an intense, predominantly tropical feature entering the midlatitudes. A hybrid cyclone during its genesis phase, Juan underwent a tropical transition as it drifted slowly northward 1500 km from the east coast of the United States. Shortly after reaching its peak intensity as a category-2 hurricane, the storm accelerated rapidly northward and made landfall near Halifax, Nova Scotia, Canada, with maximum sustained winds of 44 m s−1. Although the forecasts and warnings produced by the U.S. National Hurricane Center and the Canadian Hurricane Centre were of high quality throughout Hurricane Juan’s life cycle, guidance from numerical weather prediction models became unreliable as the storm accelerated toward the coast. The short-range, near-surface forecasts from eight operational models during the crucial prelandfall portion of Juan’s track are investigated in this study. Despite continued improvements to operational numerical forecasting systems, it is shown that those systems not employing advanced tropical vortex initialization techniques were unable to provide forecasters with credible near-surface guidance in this case. A pair of regional forecasts, one successful and one from the failed model set, are compared in detail. Spurious asymmetries in the initial vortex of the deficient model are shown to hamper structural predictions and to cause nonnegligible track perturbations from the trajectory implied by the well-described deep-layer mean flow. The Canadian Mesoscale Compressible Community model is rerun with an improved representation of the hurricane’s vortex in the initial state. The hindcast produced following the tropical cyclone initialization contains reduced track, structure, and intensity errors compared with those generated by the model in real time. The enhanced initial intensity produces a direct improvement in the forecast storm strength throughout the period, and the symmetrization of the vortex eliminates the interactions that plague the operational system. The southeastward relocation of the implanted vortex to Juan’s observed location eliminates a significant northwestward track bias under the influence of a broad area of southerly steering flow. The study concludes that the initialization of Hurricane Juan’s structure and position adds value to numerical guidance even as the storm accelerates poleward at a latitude where the implantation of a quasi-symmetric vortex may not be generally valid.

GFDL-Type Typhoon Initialization in MM5

Abstract The Geophysical Fluid Dynamics Laboratory (GFDL) hurricane initialization algorithm is implemented in the community fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). This work is applied to the MM5-based Regional Data Assimilation and Prediction System model (RDAPS), the Korea Meteorological Administration's regional forecast model. The bogus procedure starts by initializing the winds within the bogus area. The main difficulty lies in the generation of other variables, such as humidity, temperature, geopotential, etc., which are dynamically consistent with the prescribed wind. However, it was found that there is a simple and practical way of tropical cyclone (TC) initialization. It is achieved by the use of the built-in function of MM5, the four-dimensional data assimilation (FDDA). In order to do so, a miniature RDAPS is constructed. After the initialization of wind within the filter region, all other variables are generated by the mod...