The topographical variations of the seas around Taiwan are great, which make the tides complicated. Taiwan is located in the juncture of the tropical and subtropical area. Geographically, it is located within the region of northwestern Pacific typhoon path. These seasonal and geographical situations causing Taiwan frequently threaten by typhoons during summer and autumn. In addition to natural disasters, the coastal area is over developed for the last few decades, which destroys the balance between nature and man. Storms and floods constantly threaten the lowland areas along the coast. An accurate and efficient storm surge model can be used to predict tides and storm surges. The model can be calibrated and verified with the field observations. Data measured by instruments at the tidal station constituting daily tidal variations and storm surge influences during typhoons. The model can offer both predictions to the management institutions and to the general public as pre-warning system and thus taking disaster-prevention measures. This study implements the numerical model, developed by Yu (1993) and Yu et al. (1994) to calculate the hydrodynamic in the seas around Taiwan. The main purpose of this study is to make a calibration and sensitivity analysis of the model parameters. Tidal gauge data around Taiwan coastal stations collected from June to October 2005 are used for the analysis and the comparison between the modeled data and the observations. Two steps have been taken for the model calibration and sensitivity analysis. First step is to calibrate the model for accurate prediction of the astronomical tide, and then the compound tide with meteorological influences. For the calibration of the astronomical tides, sensitivity analysis has been carried out by adjusting the horizontal diffusion coefficient and the bottom friction coefficients used in the model. The sensitivity of the time-step size used in the model and model grids fitted to coastlines are also checked. A depth dependent Chézy numbers are used in the model to describe bottom friction. The model has a better result when the Chézy value varied within 65 to 85. Modifying grids fitted to the coastline has improved the model results significantly. By improving the dynamic phenomenon brought about by the land features, the model calculation fits the real tidal phenomenon better. The analysis has shown that the model is less sensitive to the horizontal diffusion coefficient. Data from 22 tidal stations around Taiwan have been used for the comparisons. The maximum RMSE (root-mean-square error) is about 10 cm at WAi-Pu, whereas the minimum RMSE is about 1 cm for the stations along eastern coast. The calibration of the compound tide is divided into three cases. The first case is to calibrate the forecasted wind field. This has been done by comparing the forecasted wind field from the Central Weather Bureau with the satellite data obtained from QuikSCAT¡XLevel 3. The satellite wind speed has been applied to adjust the forecasted wind speed. The adjusted forecast wind field has shown improvement to the model predictions in the tidal stations south of Taichung, slightly improved in the eastern coast. The second case is tuning the drag coefficient on sea surface used by the hydrodynamic model. Several empirical formulas to describe the sea surface drag have been tested. The model result has shown little influence using various drag formulations. The third case is to single the influences by the meteo-inputs, i.e. the wind field and the atmospheric pressure. The tidal level is more sensitive to the variation of the atmospheric pressure through out the tests carried out during typhoon periods. The model simulation for 2006 using the best selected parameters has shown that the model is consisted with good stability and accuracy for both stormy and calm weather conditions.

<p dir="ltr">It is known that tornadic storms favor environments characteristic of high values of thermal instability, adequate vertical wind shear, abundant near-surface moisture supply, and strong storm-relative helicity at the lowest 1-km boundary layer. These mesoscale environmental conditions and associated storm behaviors are strongly governed by large-scale synoptic patterns and sensitive to variabilities in near-surface characteristics, which are less known in the current research community. This study aims to advance the relatively underexplored area regarding the interaction between surface characteristics, mesoscale environmental conditions, and large-scale synoptic patterns driving tornadic storms in the U.S. </p><p dir="ltr">We first investigate the impact of surface drag on the structure and evolution of these boundaries, their associated distribution of near-surface vorticity, and tornadogenesis and maintenance. Comparisons between idealized simulations without and with drag introduced in the mature stage of the storm prior to tornadogenesis reveal that the inclusion of surface drag substantially alters the low-level structure, particularly with respect to the number, location, and intensity of surface convergence boundaries. Substantial drag-generated horizontal vorticity induces rotor structures near the surface associated with the convergence boundaries in both the forward and rear flanks of the storm. Stretching of horizontal vorticity and subsequent tilting into the vertical along the convergence boundaries lead to elongated positive vertical vorticity sheets on the ascending branch of the rotors and the opposite on the descending branch. The larger near-surface pressure deficit associated with the faster development of the near-surface cyclone when drag is active creates a downward dynamic vertical pressure gradient force that suppresses vertical growth, leading to a weaker and wider tornado detached from the surrounding convergence boundaries. A conceptual model of the low-level structure of the tornadic supercell is presented that focuses on the contribution of surface drag, with the aim of adding more insight and complexity to previous conceptual models.</p><p dir="ltr">We then examine the behaviors and dynamics of TLVs in response to a range of surface drag strengths in idealized simulations and explore their sensitivities to different storm environments. We find that the contribution of surface drag on TLV development is strongly governed by the interaction between surface rotation, surface convergence boundaries, and the low-level mesocyclone. Surface drag facilitates TLV formation by enhancing near-surface vortices and low-level lifting, mitigating the need for an intense updraft gradient developing close to the ground. As surface drag increases, a wider circulation near the surface blocks the inflow from directly reaching the rotating core, leading to a less tilted structure that allows the TLV position beneath the pressure minima aloft. Further increase in drag strength discourages TLV intensification by suppressing vertical stretching due to a negative vertical pressure perturbation gradient force, and it stops benefiting from the support of surrounding convergence boundaries and the overlying low-level updraft, instead becoming detached from them. We hence propose a favorable condition for TLV formation and duration where a TLV forms a less tilted structure directly beneath the low-level mesocyclone but also evolves near surrounding surface boundaries, which scenario strongly depends on underlying surface drag strength. </p><p dir="ltr">Beyond near-surface characteristics, we further explore how these storm-favorable environmental conditions may interact with the larger-scale synoptic patterns and how these interactions may affect the tornadic storm potential in the current warming climate. We employ hierarchical clustering analysis to classify the leading synoptic patterns driving tornadic storms across different geographic regions in the U.S. We find that the primary synoptic patterns are distinguishable across geographic regions and seasonalities. The intense upper-level jet streak described by the high values of eddy kinetic energy (EKE) associated with the dense distribution of Z500 contours dominates the tornado events in the southeast U.S. in the cold season (November-March). Late Spring and early Summer Tornado events in the central and south Great Plains are dominated by deep trough systems to the west axes of the tornado genesis position, while more summer events associated with weak synoptic forcing are positioned closer to the lee side of Rocky Mountain. Moreover, the increasing trend in tornado frequency in the southeastern U.S. is mainly driven by synoptic patterns with intense forcing, and the decreasing trends in portions of the Great Plains are associated with weak synoptic forcing. This finding indicates that the physical mechanisms driving the spatial trends of tornado occurrences differ across regions in the U.S.</p>