| dc.description.abstract | One of the weather elements that strongly influences human activity is rainfall. RAOB (Rawinsonde Observation Programs) is a tool in analyzing events related to rainfall. This study utilizes observational rainfall data over a period of one year, and radiosonde data series of 3 hours and 6 hours before the occurrence of rain obtained from NOAA (National Oceanic and Atmospheric Administration). This study aims to understand the technique of determining rainfall indicators and analyzed the output of RAOB program to determine RAOB index that affect the most to rainfall. It also aims to further screen the parameters into three main categories of rainfall events, namely, heavy, and light. This study reveals that Cap Strength, Vorticity Generation Parameter, and Total CAPE parameters collected 6 hours prior to the occurrence of heavy rainfall are potentially good predictors. The index of TQ calculated 3 hours prior to the occurrence of heavy rainfall is also a good potential predictor. For the occurrence of light rainfall, K-Index parameter obtained at 6 hours prior to the events is the only significant predictor. Meanwhile, important predictors obtained at 3 hours prior to the events are the Hybrid Microburst Index, Jefferson Index and K-Index. In addition, other potentially prospective indicators include 500 mb Wind speed, Strom Relative Helicity, and SWEAT Index. Mathematical relationships of rainfall data as dependent variable and the selected parameters strongly suggest the existence of linearity component in the relationships. | en |
