Tropical Cyclone Activity and its Effect on Global Averages of Total Precipitable Water

The NASA Water Vapor Project (NVAP) has recently been reprocessed and extended to now span 22 years (1988-2009) while also removing past known biases. The new dataset supersedes its predecessor and makes for a much more accurate and reliable water vapor dataset The NASA Making Earth Science Data Records for Research Environments (MEaSUREs) project released the NVAP-MEaSUREs (NVAP-M) dataset back on April 1, 2013. NVAP-M is broken down into three separate tiers, NVAP-M Climate, Weather, and Ocean, which vary in format based on user needs. The motivation of this study was to observe the effects that tropical cyclones have on current global averages of total precipitable water (TPW). With tropical cyclones being an intense precipitation event, this hinders the ability of currently used instruments, such as the Special Sensor Microwave/Imager (SSMI), to make accurate readings. Consequential to this error is that there is a large amount of missing high TPW values within each tropical cyclone. These missing values are currently not taken into consideration when computing a global TPW average. To proceed with this investigation of this problem, all tropical cyclones over the span of the dataset are located and tracked. Each tropical cyclone that is tracked has a gridded “environment” ranging in three different sizes to account for the differences in tropical cyclone size. The purpose of the environment is to locate the missing TPW data within. Through different methods of interpolation, the missing TPW data is filled in and a reanalysis of the global average is conducted. The results suggest that ignoring the influence of tropical cyclones affects the current averages of TPW in the atmosphere. With water vapor being a principal variable in processes like the Earth Energy Budget, the Global Water Cycle, and energy transport, it is important for atmospheric scientists to have more accurate data to help better understand these processes and avoid any possible implications.