Prediction and Early Warning Indicators of Short-term Severe Convection Weather in Ulanqab City

Based on the disaster reports,NCEP2.5X2.5 reanalysis data and radiosonde data of 11 national stations in Ulanqab region from June to August during 2012-2017,the weather situation classification and warning indicators of thunderstorm and gale,hail and short-term heavy rainfall were studied.The results show that the cold vortex weather situation was easy to produce hail,and the falling area of severe convection could be found in the downstream of the cold vortex,the intersection area of jet stream at 200 and 500 hPa,and the wet area side of the 700 hPa main line.The cold trough type weather situation was easy to produce thunderstorm and gale,and the falling area of severe convection appeared on the right side of the upper jet stream axis,the left side of the lower jet stream axis,the wet side of the 700 hPa main line,and the east of the shear line at 700 hPa.The weather situation of the low trough and subtropical high type was dominated by short-term rainstorm,and the falling area of severe convection was on the right side of upper jet stream at 200 hPa,the left side of the low southeast jet stream,and the wet side of the 700 hPa main line.The warning index thresholds of the total index,the temperature change at 850-500 hPa with height,the height of 0 and-20℃layer,lifting condensation height,temperature dew point difference and mixing ratio were highly reliable.

A new early warning method for dam displacement behavior based on non-normal distribution function

Traditional methods for early warning of dam displacements usually assume that residual displacements follow a normal distribution.This assumption deviates from the reality,thereby affecting the reliability of early warning results and leading to misjudgments of dam displacement behavior.To solve this problem,this study proposed an early warning method using a non-normal distribution function.A new early warning index was developed using cumulative distribution function(CDF)values.The method of kernel density estimation was used to calculate the CDF values of residual displacements at a single point.The copula function was used to compute the CDF values of residual displacements at multiple points.Numerical results showed that,with residual displacements in a non-normal distribution,the early warning method proposed in this study accurately reflected the dam displacement behavior and effectively reduced the frequency of false alarms.This method is expected to aid in the safe operation of dams.