Increased understanding of the importance of TC structure in dynamical, climatological and prediction studies makes determination of TC size important. A new algorithm for the objective estimation of the radius of outermost closed isobar (r_oci) has been developed. The new method uses storm position and global analyses of mean sea level pressure to compute a mean (axisymmetric) r_oci. This radius can be used, together with the central pressure, for the construction of a synthetic vortex that is initialized in a numerical prediction model. The method also has important applications in dynamical and climatological studies of TC intensity, size and structure. The algorithm is robust and capable of estimating r_oci, even in the case of a weak system that may not have a closed isobar in the global analysis. The values produced by the new method are shown to be more consistent than the corresponding operational estimates which are subjective and produced under strong time constraints. Statistical comparison between subjective and objective estimates gives a mean absolute difference of 110 km, which given the difficulty in making a subjective estimate, is satisfactory. In addition, even though limitations exist with the estimates of vortex parameters like the radius to gales (r₃₄), comparison with estimates from an extended best track data set provides independent evaluation of the scheme. Mean absolute difference for r₃₄ for around 3200 cases is near 80 km, even though the best track estimates are subjective and the objective r₃₄ is estimated only from storm central pressure and the objective r_oci. This validation suggests that the algorithm can be used to obtain useful size estimates of TCs.

Severe typhoon Fitow (1323) brought persistent and heavy rainfall to Zhejiang and the Shanghai area after it made landfall at Fujian Province of China in October 2013, breaking the rainfall records of several counties and districts in Zhejiang. In this paper, we provide an overview of the characteristics of Fitow’s landfall, including its track, intensity, structural evolution, heavy rainfall, and wind. We also describe some of the associated disastrous impacts. Finally, we provide verifications of operational forecasts of its track, intensity and rainfall. Though the track and intensity is well predicted, the rainfall persistence and enhancement in the second stage in Shanghai and north Zhejiang areas are not predicted out at all. The analysis presented in this paper provides forecasters and researchers with some valuable information on Fitow, which could form a useful basis for further studies.

A high-resolution numerical simulation of the extreme rainfall caused by typhoon Morakot (0908) over Taiwan Province, China, was made using the WRF-ARW/NCAR model (Version 3.2), ERA Interim reanalysis data (resolution: 1.5°×1.5°) from the European Centre for Medium-Range Weather Forecasts (ECMWF), and global real-time sea surface temperature analysis data (RTG_SST, 0.5°×0.5°) from NCEP/NOAA. The numerical simulation results showed that the extreme rainfall caused by Morakot over Taiwan was closely related to water vapor transport of the southwesterly flow. However, the effect of a binary typhoon system between Morakot and Severe Tropical Storm Goni (0907) was also an important factor. Goni strengthened the intensity of the southwesterly
flow and the water vapor transport to Morakot and resulted in the heavy rainfall increasing over central and southern mountainous areas of Taiwan. Furthermore, the effect of the binary typhoon system increasing the northward component of the track of Morakot, and the typhoon’s slow translation to Taiwan, caused the longtime and persistent severe rainfall over southern Taiwan. After removing Goni’s circulation in the model initial field, the cumulative precipitation was greatly reduced by 35.78%, 33.03% and 31.5% in the 18-, 6- and 2-km resolution model results, respectively.

Performance of non-hydrostatic Regional Atmospheric Modeling System (RAMS) in simulating the tropical cyclones of different intensities, formed during pre and post monsoon is evaluated. Study is carried out for Orissa, Sidr, Mala, h04B, 01A, and Agni cyclones. The simulated cyclone track, winds at 850 hpa and 200 hpa and other thermodynamical features associated with the development of cyclones such as vertical wind shear and mid tropospheric humidity and sea surface temperature are compared with observations. The tracks of all cyclones are reasonably well simulated by the model except for h04B. The track error increases with the simulation time. The model overestimates the lowest mean sea level pressure as compared to the observations. The model represents the low level circulation and upper air divergence of wind realistic during all the cyclone cases.

A disaster induced by a tropical cyclone (TC) is a complex non-linear process, involving interactions of multiple factors. Assuming that the resilience to TC disasters remains basically unchanged, the disaster-causing risk is usually consistent with intensities of the TC-induced rainstorms and wind. When an area is hit by a low probability TC, the rainstorm and wind intensities are higher, and the likelihood for causing a disaster is greater. Therefore, criteria for the impact of a TC and disaster risk assessments can be established based on the probable intensities of the TC-associated rainstorms and wind. In this study, an AMH Copula-based function is introduced to investigate the joint risk probabilities of TC rainstorms and wind. In line with the equivalence principle of the
distribution of a stochastic atmospheric phenomenon in both time and space, and taking the impact on Shanghai of TC Haikui as an example, the Copula-based joint probability distribution model is developed to assess the impacts of TC rainstorms and wind, based on the marginal distributions of the maximum daily rainfall and extreme gust velocity. The joint exceedance probabilities of TC rainstorms and wind derived from the model can be used as criteria to measure the risk levels. As our findings show, this approach captures the TC risks well, especially in high-risk areas. The aim of the study is to provide a practically useful concept for making more accurate assessments of the risk level of an extreme weather event using observational data, and objective criteria for risk avoidance and transfer.