Construction of a new index and its application to forecasting heavy rainfall

Abstract

Heavy rainfall is a severe weather occurring frequently in summer across China. It can not only bring urban waterlogging, landslides, but also cause huge losses of life and property. While it is difficult to forecast depending on the single physical parameters or only based on routine numerical weather prediction. At present the 6-hour-interval TS score of heavy rainfall is just 2. 6% in China, much lower than the scores of the wind and temperature fields, so the forecast accuracy of strong precipitation still needs to be improved. From previous research, the occurrence of heavy rainfall has a very close relationship with convective parameters. Therefore it is of particular importance to find an integrated and convenient parameter to characterize the formation mechanism of heavy rainfall. As the atmosphere is an organic combination of dynamic and thermal fluids, and precipitation is the result of many factors in the atmosphere, so the key of precipitation forecasting is data processing and mining strong signals from various early physical quantities. Base on the Ingredients-Based Methodology (IM), this paper introduces a new physical parameter THP (Temperature, Helicity and Precipitable water), which contains atmospheric thermodynamics, dynamics and moisture factors. Using NCEP/NCAR reanalysis data (time resolution every 6 h, spatial resolution 1 degrees X1 degrees) and ground observational data in China, the THP index was diagnosed and analyzed in two heavy precipitation processes in detail. And then, the universality of THP was tested according to precipitation observational data from July 1 to August 15, 2012. The analysis and comparison show that the THP index can provide good direction to the distribution and the movement of summer heavy precipitation, and heavy rainfall is located in the high value area of THP. The variation of THP is ahead of changes in observational precipitation, so THP index can also give a good reference to the beginning and ending time of heavy rain. The THP value is of certain indicating significance to predication of rainfall intensity. Moreover, judging from the inspection effect, the THP index has a good applicability during summer in China mainland. Because the major affecting factors of rainstorms are considered in THP index, the stability of THP is superior to the method of using single physical parameters in forecasting analysis. And compared with some conventional physical parameters, the THP value shows a better correspondence to the precipitation rainfall area in the following 6 hours. The THP index can reflect the characteristic and mechanism of heavy rainfall, and the bigger of the THP value, the bigger probability of rainstorms. Therefore, as a forecaster parameter, the THP index plays a positive role in forecasting heavy rainfall. Besides, the IM method has a clearly physical meaning, and can be used more widely to forecast the locations of other disasters, such as thunderstorms, wind gusts and hail, so as to improve the forecasting level of severe convective storms.