Identifying the environmental conditions that control tropical cyclone (TC) genesis is a challenging problem. This study examines a new method to evaluate the precursors of TC genesis using high-resolution ensemble forecasts and relative operating characteristic (ROC) diagrams.
With an advanced research version of the Weather Research and Forecasting (WRF) model, high-resolution ensemble forecasts (at 5 km horizontal resolution) are conducted in various configurations using a bred vector method to form a set of 140 ensemble members for predicting Hurricane Ernesto’s genesis. Basic evaluation shows that high-resolution ensemble forecasts are able to predict well-developed TCs, whereas the NCEP Global Ensemble Forecast System (GEFS) fails to do so. This set of 140 ensemble members is employed to study the precursors of Hurricane Ernesto’s genesis by contrasting the genesis and nongenesis cases. Specifically, ROC curves, composite figures for genesis and nongenesis cases, and Kolmogorov-Smirnov tests are applied to characterize the relationship between important environmental parameters near the beginning of the simulation and genesis likelihood 15-18 h later. It is found that moist conditions at 850 hPa, vertical wind shear, the strength of the 850 hPa pre existing wave, and upper-level warming play notable roles in Ernesto’s genesis.

Forecasts of tropical cyclone (TC) tracks from six global models during 2010 and 2012 were assessed to study the current capability of track forecast guidance over the western North Pacific. To measure the performance of the global model forecasts, a series of statistical evaluations of track forecasts up to 120 h were carried out, including the mean, median, percentile distribution, regional distribution, relative position, correlation analysis, and binned analysis. Results showed that certain improvements have been made for the six global models in their prediction accuracy and stability in the past three years. Remarkably, stepped decreases in the values of each quantile were found at all lead time levels from 2010 to 2012 for NCEP-GFS. An analysis of the regional distribution of position errors showed that a high-latitude region, low-latitude region (which covers mostly the TC genesis region) and the South China Sea are the three main areas within which large errors tend to concentrate. The majority of the models show their own respective characteristics of systematic bias at each lead time, as established through the relative position analysis results. Only the results of NCEP-GFS and CMA-T639 did not show any obvious systematic bias in the three-year study period. Binned analyses indicated that the prediction accuracy and stability of most of the models were better for strong TCs than for weak TCs at short lead time levels. It was also found that the models tend to perform better for initially large TCs, or for those with weak vertical wind shear at lead times shorter than 48 h. The results demonstrate the heavy reliance of forecast errors upon the initial characteristics of a TC or its environmental conditions.

The cause of the rapid weakening of Typhoon “Bebinca” was analyzed in this paper, by using the NCEP FNL (Final) Operational Global Analysis data on 1°×1° grids and the Tropical Cyclone (TC) Annual Report. The result shows that during the middle to late stage of its life cycle, the meteorological environments did not sustain “Bebinca” to maintain its intensity: the water vapor transport at low level decreased significantly; cold air intruded from north at low to middle level; both the divergence at high level and the convergence at low level reduced at the same time in the late stage. All these above factors restrained the development of “Bebinca”. In particular, the rapid reduction of sea surface temperature (SST) was the main factor that induced the rapid weakening of the Typhoon, which occurred about 6 hour ahead of its weakening. Compared to the 500-850 hPa vertical wind shear, which shows a relatively high correlation with the weakening, the impact of the 200-850 hPa vertical wind shear on the intensity change was not significant. Therefore, the Typhoons in the South China Sea would possibly weaken and disappear rapidly in fall and winter. So we have to pay more attention to the time effectiveness of the forecasting and correct the results in time.

In December, 2011, the world’s second most deadly disaster of the year, Tropical Storm Washi (known as Sendong in the Philippines) landed along the east coast of Mindanao, Philippines, causing 1,292 deaths, 1,049 missing, 2,002 injured, and total 695,195 people (110,806 families) affected. This paper introduced briefly the hydro-meteorological characteristics of Washi, and assessed its devastating impacts on society and economy, and the response and recovery taken by the Philippines government during the whole period of Washi. Based on the assessment of impact of disaster, the paper indicated the gaps and needs on aspects of DRR actions and identified the future challenges on typhoon related disaster preparedness and reduction in the Philippines. Finally, the report provided the recommendations within the framework of the activities of Typhoon Committee to improve and enhance the capacity building on typhoon related disaster reduction in the Philippines.

Using principal component analysis, a new comprehensive assessment index for damage caused by tropical cyclones in mainland China is developed based on data from 1984 to 2008. It is a weighted average of four kinds of damage data: including the deaths and missing, affected crop area, destroyed houses, and rate of direct economic loss. The weighting coefficients are set by principal component analysis. Two indices are derived, which differ in the importance of the deaths and missing in severity assessment according to the sign of the second principal component of damage data. Trends in the damage caused by individual tropical cyclones and in the annual frequencies of the various levels of severity of damage caused by tropical cyclones are analyzed. No clear trend in damage from individual tropical cyclones is found. The annual frequency of tropical cyclones causing heavy and catastrophic damage shows a clear decrease from 1984 to 2008 with no trend in the total number of damaging tropical cyclones.