The microphysical characteristics of rain may vary in different rain regions of a tropical cyclone (TC), but few studies have demonstrated the differences in raindrop size distributions (RSDs) of convective rain in different rainbands of a specific TC. This study examines the RSD characteristics and evolution of convective rain within outer rainbands and a coastal-front-like rainband associated with Typhoon Fitow, based on observational data from a disdrometer at Shibo station in Shanghai, China, during 6-7 October 2013. Considering the fast passage of convective TC rainbands over the disdrometer and the low rain rate of stratiform rain in the outer area, this study proposes a modified rain-type classification method based on the disdrometer data. This study indicates that convective outer-rainband rain (ORR) and coastal-front rain (CFR) have different rain parameters, three parameters of the gamma model, radar reflectivity-rain rate (Z-R), and shape-slope (μ-Λ) relationships. The convective ORR has higher concentrations at all drop sizes than the convective CFR as well as larger spectral width, leading to the greater rainfall rate. The different Z-R relationships suggest the necessity of a variable relationship for quantitative precipitation estimation (QPE) in different rain regions of the TC. This study also demonstrates for the first time that the RSD evolution with increasing rain rate is different in various convective rainbands associated with Fitow, suggesting that different microphysical parameterization schemes may be required for different rainbands in TC models.Note. The terms R, Z, W, N T , D m , D max , and log 10 N w represent rain rate, radar reflectivity, rain water content, total drop concentration, mass-weighted mean diameter, maximum diameter, and normalized intercept parameter, respectively. The rainfall duration and accumulated amount are also given for the different rain types in each stage. "C," "S," and "T" denote the convective, stratiform, and total rainfall, respectively.

Forecasts of tropical cyclone (TC) intensity from six operational models (three global models and three regional models) during 2010 and 2011 are assessed to study the current capability of model guidance in the western North Pacific. The evaluation is performed on both V max and P min from several aspects, including the relative error, skill assessment, category score, the hitting rate of trend, and so on. It is encouraging to see that the models have had some skills in the prediction of TC intensity, including that two of them are better than a statistical baseline in V max at several lead times and three of them show some skill in intensity change. With dissipated cases included, all the models have skills in category and trend forecasting at lead times longer than 24 h or so. The model forecast errors are found to be significantly correlated with initial error and the observed initial intensity. A statistical calibration scheme for model forecasting is proposed based on such an attribute, which is more effective for P min than V max . The statistically calibrated model forecasts are important in setting up a skillful multimodel consensus, for either the mean or the statistically weighted mean. The V max forecasts converted from the calibrated P min consensus based on a statistical wind-pressure relationship show significant skill over the baseline and a skillful scheme is also proposed to deal with the delay of the model forecasts in operation.