In 2008, abundant dropwindsonde data were collected during both reconnaissance and surveillance flights in and around tropical cyclones (TCs) in the western North Pacific basin under the framework of The Observing System Research and Predictability Experiment (THORPEX)-Pacific Asian Regional Campaign (T-PARC). The National Centers for Environmental Prediction Global Forecast System (GFS) showed significant track improvements for Typhoon Sinlaku (2008) after the assimilation of dropwindsonde data. For this particular typhoon, the potential vorticity (PV) diagnosis is adopted to understand the key factors affecting the track. A data denial run initialized at 0000 UTC 10 September is examined to evaluate how the extra data collected during T-PARC improve GFS track forecasts.A quantitative analysis of the steering flow based on the PV diagnosis indicates that the Pacific subtropical high to the east of Sinlaku is a primary factor that advects Sinlaku northwestward, while the monsoon trough plays a secondary role. The assimilation of dropwindsonde data improves the structure and intensity of the initial vortex and maintains the forecast vortex structure in the vertical. The difference in the vertical extent of the vortices could be regarded as a cause for the discrepancy in steering flow between runs with and without the dropwindsonde data. This paper highlights the importance of improved analyses of the vertical TC structure, and thus of a representative steering flow in the deep troposphere during the forecasts.
Targeted observation is one of the most important research and forecasting issues for improving tropical cyclone predictability. A new parameter [i.e., the adjoint-derived sensitivity steering vector (ADSSV)] has been proposed and adopted as one of the targeted observing strategies in the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR). The ADSSV identifies the sensitive areas at the observing time to the steering flow at the verifying time through the adjoint calculation. In this study, the ADSSV is calculated from the nonlinear forecast model of the fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5) and its adjoint to interpret the dynamical processes in the interaction between Typhoon Shanshan (2006) and the midlatitude trough. The ADSSV results imply that high-sensitivity regions affecting the motion of Typhoon Shanshan are located at the edge of the subtropical high and the 500-hPa midlatitude trough over northern central China. These ADSSV signals are in very good agreement with the quantitative evaluation based on the potential vorticity (PV) diagnosis. The vertical structure of the ADSSV is also shown for more physical insights into the typhoon-trough interaction. The maximum ADSSV occurs at 800-500 hPa to the southeast of Shanshan (associated with the subtropical high), while distinct ADSSV signals are located upstream of the storm center at about 500-300 hPa (associated with the mid-to upper-tropospheric midlatitude trough). Overall, it is demonstrated that the ADSSV features can well capture the signal of the large-scale trough feature affecting the motion of Shanshan, which can also be well validated from the PV analysis.
This study utilizes data compiled over 21 years (1993–2013) from the Central Weather Bureau of Taiwan to investigate the statistical characteristics of typhoon-induced rainfall for 53 typhoons that have impacted Taiwan. In this work the data are grouped into two datasets: one includes 21 selected conventional weather stations (referred to as Con-ST), and the other contains all the available rain gauges (250–500 gauges, mostly automatic ones; referred to as All-ST). The primary aim of this study is to understand the potential impacts of the different gauge distributions between All-ST and Con-ST on the statistical characteristics of typhoon-induced rainfall. The analyses indicate that although the average rainfall amount calculated with Con-ST is statistically similar to that with All-ST, the former cannot identify the precipitation extremes and rainfall distribution appropriately, especially in mountainous areas. Because very few conventional stations are located over the mountainous regions, the cumulative frequency obtained solely from Con-ST is not representative. As compared to the results from All-ST, the extreme rainfall assessed from Con-ST is, on average, underestimated by 23%–44% for typhoons approaching different portions of Taiwan. The uneven distribution of Con-ST, with only three stations located in the mountains higher than 1000 m, is likely to cause significant biases in the interpretation of rainfall patterns. This study illustrates the importance of the increase in the number of available stations in assessing the long-term rainfall characteristic of typhoon-associated heavy rainfall in Taiwan.
Using special data from the field campaign of 2008 and an ensemble Kalman filter-based vortex initialization method, this study explores the impact of different track clusters categorized under the ensemble simulations of Typhoon Sinlaku (2008) on the associated precipitation. In particular, the distinct pattern of cumulative frequencies in the 28 members is identified to correspond to three types of track clusters. The simulation integrated from the initial ensemble mean slightly underestimates the maximum amount of the observed rainfall in central Taiwan by about 30%. The quantitative evaluation based on the equitable threat score indicates that members with tracks close to the best track produce more consistent rainfall distribution in northern Taiwan although their cumulative frequencies are underestimated. For members with southwestward-biased tracks, although the cumulative frequencies are closer to the observation, the simulated rainfall pattern is less consistent with the observation in northern Taiwan and the maximum rainfall amount is overestimated. The comparison of rainfall simulation during landfall between two representative members shows that the distinct differences in the rainfall amount and distribution are primarily associated with the track differences on the windward side of the mountain. With a finer horizontal grid resolution, the rainfall accumulation becomes greater as a result of the enhancement of updraft from the better-resolved topography, yet the cumulative frequency stays nearly unchanged. Based on ensemble simulations, this study highlights that the uncertainties in rainfall patterns and amounts can be assessed from ensemble track variations, thus providing better insights into the rainfall predictability associated with typhoons near Taiwan.
The adjoint-derived sensitivity steering vector (ADSSV) has been proposed and applied as a guidance for targeted observation in the field programs for improving tropical cyclone predictability, such as The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). The ADSSV identifies sensitive areas at the observing time to the steering flow at the verifying time through adjoint calculation. In addition, the ability of the ADSSV to represent signals of influence from synoptic systems such as the midlatitude trough and the subtropical high prior to the recurvature of Typhoon Shanshan (2006) has also been demonstrated.In this study, the impact of initial perturbations associated with the high or low ADSSV sensitivity on model simulations is investigated by systematically perturbing initial vorticity fields in the case of Shanshan. Results show that experiments with the perturbed initial conditions located in the high ADSSV area (i.e., the midlatitude trough and the subtropical high) lead to more track deflection relative to the unperturbed control run than experiments with perturbations in the low sensitivity area. The evolutions of the deep-layer-mean steering flow and the direction of the ADSSV are compared to provide conceptual interpretation and validation on the physical meaning of the ADSSV. Concerning the results associated with the perturbed regions in high sensitivity regions, the variation of the steering flow within the verifying area due to the initial perturbations is generally consistent with that of the direction of the ADSSV. In addition, the bifurcation between the ADSSV and the steering change becomes larger with the increased integration time. However, the result for the perturbed region in the low-sensitivity region indicates that the steering change does not have good agreement with the ADSSV. The large initial perturbations to the low-sensitivity region may interact with the trough to the north due to the nonlinearity, which may not be accounted for in the ADSSV. Furthermore, the effect of perturbations specifically within the sensitive vertical layers is investigated to validate the vertical structure of the ADSSV. The structure of kinetic energy shows that the perturbation associated with the trough (subtropical high) specifically in the mid-to-upper (mid-to-lower) troposphere evolves similarly to that in the deep-layer troposphere, leading to comparable track changes. A sensitivity test in which perturbations are locally introduced in a higher-sensitivity area is conducted to examine the different impact as compared to that perturbed with the broader synoptic feature.
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