Establishment of an Objective Standard for the Definition of Binary Tropical Cyclones in the Western North Pacific

To develop an objective standard for defining binary tropical cyclones(BTCs)in the western North Pacific(WNP),two best-track datasets,from the China Meteorological Administration and the Joint Typhoon Warning Center,were adopted for statistical analyses on two important characteristics of BTCs-two TCs approaching each other,and counterclockwise spinning.Based on the high consistency between the two datasets,we established an objective standard,which includes a main standard for defining BTCs and a secondary standard for identifying typical/atypical BTCs.The main standard includes two requirements:two coexisting TCs are a pair of BTCs if(i)the separation distance is≤1800 km,and(ii)this separation maintains for at least 12 h.Meanwhile,the secondary standard defines a typical BTC as one for which there is at least one observation when the two TCs approach each other and spin counterclockwise simultaneously.Under the standard,the ratio of typical BTCs increases as the BTC duration increases or the minimum distance between the two TCs decreases.Then,using the JTWC dataset,it was found that there are 505 pairs of BTCs during the period 1951−2014,including 328 typical BTCs and 177 atypical BTCs,accounting for 65.0%and 35.0%of the total,respectively.In addition,a study of two extreme phenomena-the maximum approaching speed and the maximum counterclockwise angular velocity in typical BTCs-shows that the configuration of the circulation conditions and the distribution of the BTCs favor the formation of these extreme phenomena.

ANALYSIS OF THE EFFECT OF 3DVAR AND ENSRF DIRECT ASSIMILATION OF RADAR DATA ON THE FORECAST OF A HEAVY RAINFALL EVENT

The present study designs experiments on the direct assimilation of radial velocity and reflectivity data collected by an S-band Doppler weather radar(CINRAD WSR-98D) at the Hefei Station and the reanalysis data produced by the United States National Centers for Environmental Prediction using the Weather Research and Forecasting(WRF) model,the WRF model with a three-dimensional variational(3DVAR) data assimilation system and the WRF model with an ensemble square root filter(EnSRF) data assimilation system.In addition,the present study analyzes a Meiyu front heavy rainfall process that occurred in the Yangtze-Huaihe River Basin from July 4 to July 5,2003,through numerical simulation.The results show the following.(1) The assimilation of the radar radial velocity data can increase the perturbations in the low-altitude atmosphere over the heavy rainfall region,enhance the convective activities and reduce excessive simulated precipitation.(2) The 3DVAR assimilation method significantly adjusts the horizontal wind field.The assimilation of the reflectivity data improves the microphysical quantities and dynamic fields in the model.In addition,the assimilation of the radial velocity and reflectivity data can better adjust the wind fields and improve the intensity and location of the simulated radar echo bands.(3) The EnSRF assimilation method can assimilate more small-scale wind field information into the model.The assimilation of the reflectivity data alone can relatively accurately forecast the rainfall centers.In addition,the assimilation of the radial velocity and reflectivity data can improve the location of the simulated radar echo bands.(4) The use of the 3DVAR and EnSRF assimilation methods to assimilate the radar radial velocity and reflectivity data can improve the forecast of precipitation,rain-band areal coverage and the center location and intensity of precipitation.