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A Study On The Characteristics And Prediction Methods Of Short-time Heavy Rainfall In The East Of Northwest China

Posted on:2015-02-13Degree:MasterType:Thesis
Country:ChinaCandidate:X P BaiFull Text:PDF
GTID:2250330431450912Subject:Science of meteorology
Abstract/Summary:PDF Full Text Request
The short-time heavy rainfall is one of the important incentives of meteorological disasters; its prediction has always been a difficult problem. In recent years, the short-time heavy rainfall frequency increased significantly in the east of northwest China.In this paper, it has been by using the rainfall observation data of136meteorological stations in the east of northwest China from2001to2012, the1674automatic weather station hourly precipitation data from2009to2011, NCEP/NCAR1°1°reanalysis data and the MICAPS system of each meteorological stations sounding data. Firstly, in method of the Climatic Statistical Analysis, Linear Trend Analysis, Normalization Analysis, Regional Statistics, Degree Concentration and Concentration Period Analysis, dose detailed research of the spatial and temporal distribution characteristics of short-time heavy rainfall in the east of northwest China. Secondly, be classified of the weather situation in the east of northwest China, have been statistical analyzed the probability of various weather type short-time heavy rainfall; and the circulation state as the starting point, using the mesoscale analysis, combined with the features of upper and lower air circulation configuration and energy weather theory, be established the4kinds of scales short-time heavy rainfall weather conceptual model in the east of northwest China; according to the different conceptual model, by using the Correlation Analysis and t test for significance of selected sensitive physical parameters, and be identified the threshold of each sensitive physical parameters. Finally, its has been respectively using the improved binary Logistic regression analysis method and the improved comprehensive multi index superposition method, through the conceptual model recognition and classification, the water vapor content screening, and sensitive physical parameters diagnosis stepwise discriminate, be established the test model of short-time heavy rainfall in the east of northwest China, and test forecast verification.The main results are as follows:(1) The analysis on distribution characteristics of short-time heavy rainfall in the east of northwest China:The total rainfall over the east of northwest China increased, while the total precipitation frequency was decreased. The main contribution of rainfall concentrated from April to October, the cumulative rainfall throughout the year accounted for more than91%of the total cumulative precipitation, precipitation frequency precipitation throughout the year accounted for more than77%of the total frequency; duration of precipitation is mainly concentrated in6hours, accounted for more than88%of the total precipitation frequency. Short-time heavy rainfall days interannual changes a little, but the number of short-time heavy rainfall process of regional showed an obvious increasing trend. The short-time heavy rainfall mainly occurs in late July to early August, and has obvious diurnal variation; in the evening, midnight and each has a peak, showing the "night rain in Sichuan" feature. Spatial distribution of the total frequency of the short-time heavy rainfall and the terrain distribution is consistent, near the windward slope high value area located in the summer half year circulation prevailing southwest airflow, show that the forced lifting effect of special terrain on airflow obviously. Short-time heavy rainfall years concentration increased gradually from southeast to northwest, concentrated period from east to west gradually postponed; the northeast slope area of interannual central Qinghai Tibet Plateau and Qinling Mountains in the South increased, indicating that the region the next stage flood control task may be more difficult. These results can be as the short-time heavy rainfall disaster to provide reference basis for the prevention and treatment.(2) The analysis of Eastern northwest weather situation display:The weather of the area can be divided into the vortex type, the low trough, the two high variant, the northwest air current, the high pressure ridge control type and the southwest airflow type, the weather caused heavy rainfall in the vortex type, the low trough, the two high variant and the southwest airflow type, and there are seasonal and regional differences. Among them, the late spring and early summer and autumn is mainly in the lower groove precipitation, while the summer season is mainly for the southwest airflow pattern and the two high variant strong precipitation; Gobi desert area is dominated by the low trough heavy rainfall, slope area of the Qinghai Tibet Plateau northeast to the southwest air current heavy rainfall, while the Loess Plateau and Qinling Mountains in the south by the southwest airflow type and the trough type heavy rainfall.(3) On the east of northwest China heavy rainfall sensitive physical quantity diagnosis and prediction study display:The whole layer of specific humidity integral (IQ), the warm dry lid index (Ls), the microburst down wash Potential index (MDPI), the severe weather threat index (SWEAT), the storm relative helicity (SRH), the shear of coarse Richardson number (Shr) and other physical parameters are good indication of the short-time heavy rainfall events. Weather type and moisture elimination can effectively reduce the false alarm rate of the short-time heavy rainfall forecasting (elimination rate of40.2%); on the whole, the two kinds of short-time heavy rainfall forecasting model superposition method on the binary Logistic regression analysis method and the comprehensive index method, test results are obviously increased, and the former TS score is higher than the latter, it can provide new technologies for the prediction of short-time heavy rainfall.
Keywords/Search Tags:short-time heavy rainfall, the east of northwest China, spatial andtemporal characteristics, weather conceptual model, sensitive physical parameters, theimproved binary Logistic regression analysis method
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