Rain Nowcasting using Short Range X-Band Radar Observations and Automatic Water Monitoring over User specified Area

Rain nowcasting is an essential part of weather monitoring and it plays a vital role in human life ranging from advanced warning systems to schedule an open air game and planning a trip to a tourist place. A nowcasting system can be divided into three fundamental steps i.e. Storm Identification, Tracking and Nowcasting. The main contribution of this work is to propose procedures for each step of rain nowcasting tool and objectively evaluate the performances of every step, focusing on two-dimension data collected from short range X-band radars installed in different parts of Italy. This work presents the solution to the issues faced by the storm identification step of already developed tools such as TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting) and SCIT(The Storm Cell Identification and Tracking) where a storm is contiguous area in radar observation exceeding in both radar reflectivity and area from certain reflectivity and areal threshold. The first issue is that the existing nowcasting tools are unable to choose a suitable initial reflectivity threshold. The second issue is that some of the nowcasting tools (i.e. TITAN, SCIT) are not able to isolate false merger. A false merger is a weak point which combines two or more storms into one storm. The third issue is that some of these tools (i.e. TITAN) are unable to identify high reflectivity sub-storms within a large storm called cluster of storms. Very little attention has been given to storm identification evaluation. Up to the best of our knowledge, automatic thresholding is introduced for the first time to handle the first issue while the second issue is solved by mathematical erosion. Third issue is solved by multi-thresholding. Up to the best of our knowledge, storm identification evaluation is introduced for the first time. Storm tracking step of the existing tools such as TITAN and SCIT use only up to two storm attributes i.e. center of mass and area, for tracking. There exists a room for the usage of more attributes for tracking. Also, the contribution of each attribute in storm tracking is yet to investigate. This paper presents a novel procedure called SALdEdA (Structure, Amplitude, Location, Eccentricity difference and Areal difference) for storm tracking. This work also presents the contribution of each component of SALdEdA in storm tracking. The second order exponential smoothing strategy is used for storm nowcasting where the growth and decay of each variable of interest is considered to be linear. The obtained results of all three steps are quite promising. The adopted techniques for automatic threshold calculation are assessed with a 97\% goodness. False merger and sub-storms within a cluster of storms are successfully handled. Furthermore storm tracking procedure produced very good results with an accuracy of 99.34% for convective events and 100% for stratiform events. Results of the nowcasting step show that our system is quite good in predicting speed, direction and mean reflectivity of storms.