The drop size distribution (DSD) and drop shape relation (DSR) characteristics that were observed by a ground-based 2D video disdrometer and retrieved from a C-band polarimetric radar in the typhoon systems during landfall in the western Pacific, near northern Taiwan, were analyzed. The evolution of the DSD and its relation with the vertical development of the reflectivity of two rainband cases are fully illustrated. Three different types of precipitation systems were classified—weak stratiform, stratiform, and convective—according to characteristics of the mass-weighted diameter Dm, the maximum diameter, and the vertical structure of reflectivity. Further study of the relationship between the height H of the 15-dBZ contour of the vertical reflectivity profile, surface reflectivity Z, and the mass-weighted diameter Dm showed that Dm increased with a corresponding increase in the system depth H and reflectivity Z. An analysis of DSDs retrieved from the National Central University (NCU) C-band polarimetric radar and disdrometer in typhoon cases indicates that the DSDs from the typhoon systems on the ocean were mainly a maritime convective type. However, the DSDs collected over land tended to uniquely locate in between the continental and maritime clusters. The average mass-weighted diameter Dm was about 2 mm and the average logarithmic normalized intercept Nw was about 3.8 log10 mm−1 m−3 in typhoon cases. The unique terrain-influenced deep convective systems embedded in typhoons in northern Taiwan might be the reason for these characteristics. The “effective DSR” of typhoon systems had an axis ratio similar to that found by E. A. Brandes et al. when the raindrops were less than 1.5 mm. Nevertheless, the axis ratio tended to be more spherical with drops greater than 1.5 mm and under higher horizontal winds (maximum wind speed less than 8 m s−1). A fourth-order fitting DSR was derived for typhoon systems and the value was also very close to the estimated DSR from the polarimetric measurements in Typhoon Saomai (2006).

Raindrop size distribution (RSD) characteristics of summer and winter seasons over north Taiwan are analyzed by using long-term (~12 years) raindrop spectra from Joss-Waldvogel disdrometer located at National Central University (24°58 0 N, 121°10 0 E), Taiwan. Along with the disdrometer data, radar reflectivity mosaic from six ground-based radars, Tropical Rainfall Measuring Mission, Moderate Resolution Imaging Spectroradiometer, and ERA-Interim data sets are used to establish the dynamical and microphysical characteristics of summer and winter rainfall. Significant differences in raindrop spectra of summer and winter rainfall are noticed. Winter rainfall has a higher concentration of small drops and a lower concentration of midsize and large drops when compared to summer rainfall. RSD stratified on the basis of rain rate showed a higher mass-weighted mean diameter (D m ) and a lower normalized intercept parameter (log 10 N w ) in summer than winter. Similarly, diurnal variation of RSD showed higher D m and lower log 10 N w values in summer as compared to winter rainfall. In addition, for both seasons, the mean value of D m is higher in convective precipitation than stratiform. Radar reflectivity (Z) and rain rate (R) relations (Z = A*R b ) showed a clear demarcation between summer and winter rainfall. Higher ground temperatures, deeply extended clouds with intense convective activity in summer modified the RSD through evaporation, drop sorting, and collision-coalescence processes resulting with higher D m and lower log 10 N w values in summer as compared to winter rainfall. Plain Language SummaryThis study details about the raindrop size distribution characteristics variations between summer and winter seasons of north Taiwan using long-term (12 years) disdrometer data and the possible reasons for the raindrop size distribution variations are also detailed. -T. (2018). Raindrop size distribution characteristics of summer and winter season rainfall over north Taiwan. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.Following this introduction, a brief explanation of data and methodology used in the present study is provided in section 2. RSD variations of summer and winter rainfall are detailed in section 3 and followed by section 4, which includes the possible reasons for the RSD variations in summer and winter seasons. Conclusions drawn from the observational results are provided in section 5.

Raindrop size distribution (RSD) characteristics in summer season rainfall of two observational sites (Taiwan (24°58′N, 121°10′E) and Palau (7°20′N, 134°28′E)) in western Pacific are studied by using five years of impact type disdrometer data. In addition to disdrometer data, Tropical Rainfall Measuring Mission, Moderate Resolution Imaging Spectroradiometer, and ERA‐Interim data sets are used to illustrate the dynamical and microphysical characteristics associated with summer season rainfall of Taiwan and Palau. Taiwan and Palau's raindrop spectra showed a significant difference, with a higher concentration of middle and large drops in Taiwan than Palau rainfall. RSD stratified on the basis of rain rate showed a higher mass‐weighted mean diameter (Dm) and a lower normalized intercept parameter (log10Nw) in Taiwan than Palau rainfall. Precipitation classification into stratiform and convective regimes showed higher Dm values in Taiwan than Palau. Furthermore, for both the locations, the convective precipitation has a higher Dm value than stratiform precipitation. The radar reflectivity‐rain rate relations (Z = A*Rb) of Taiwan and Palau showed a clear variation in the coefficient and a less variation in exponent values. Terrain‐influenced clouds extended to higher altitudes over Taiwan resulted with higher Dm and lower log10Nw values as compared to Palau.

During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, there are many differences between the different modeling studies, which are identified and discussed.

The U.S. Geological Survey (USGS) land use (LU) data employed in the Weather Research and Forecasting (WRF) model classify most LU types in Taiwan as mixtures of irrigated cropland and forest, which is not an accurate representation of current conditions. The WRF model released after version 3.1 provides an alternative LU dataset retrieved from 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products. The MODIS data correctly identify most LU-type distributions, except that they represent western Taiwan as being extremely urbanized. A new LU dataset, obtained using 2007 Système Probatoire d’Observation de la Terre (SPOT) satellite imagery [from the National Central University of Taiwan (NCU)], accurately shows the major metropolitan cities as well as other land types. Three WRF simulations were performed, each with a different LU dataset. Owing to the overestimation of urban area in the MODIS data, WRF-MODIS overpredicts daytime temperatures in western Taiwan. Conversely, WRF-USGS underpredicts daytime temperatures. The temperature variation estimated by WRF-NCU falls between those estimated by the other two simulations. Over the ocean, WRF-MODIS predicts the strongest onshore sea breezes, owing to the enhanced temperature gradient between land and sea, while WRF-USGS predicts the weakest onshore flow. The intensity of the onshore breeze predicted by WRF-NCU is between those predicted by WRF-MODIS and WRF-USGS. Over Taiwan, roughness length is the key parameter influencing wind speed. WRF-USGS significantly overpredicts the surface wind speed owing to the shorter roughness length of its elements, while the surface wind speeds estimated by WRF-NCU and WRF-MODIS are in better agreement with the observed data.