Comparing Precipitation During Typhoons in the Western North Pacific using PERSIANN and TRMM TMPA

A typhoon is an extreme weather event that causes destruction for many Asian-Pacific countries in the Pacific Ocean. Typhoons are known for causing heavy precipitation, very strong winds, and storm surges. These affects then lead to flooding, heavy run-off, and landslides, which often result in water contamination, heavy sedimentation, and building collapse. With climate change, the occurrence, strength, and duration of typhoons are changing, and it is generally acknowledged that typhoons are becoming stronger. The need to better understand these typhoon events in order to predict the outcomes that many Asia-Pacific countries will face is of utmost importance. Our approach to better understand typhoons and the precipitation associated with them is to estimate the precipitation during typhoon events. We compared daily, weekly, and monthly precipitation from in-situ stations apart of the NOAA Global Historical Climatological Network (GHCN) during twenty-five typhoon events in the Western North Pacific from 2000 to 2018 against two widely used and understood datasets, NASAs Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural NetworksClimate Data Record (PERSIANN-CDR). The goals of the research were threefold: 1) develop a better understanding of normal as it relates to precipitation during typhoons in the North Western Pacific, 2) determine whether precipitation estimates from satellites accurately estimate precipitation during normal conditions and during typhoon events, and 3) determine whether in situ precipitation gages provide enough coverage and data to truly understand precipitation patterns during typhoon events. Correlation coefficient, r-squared, and root mean square error were used to analyze precipitation products against in-situ rainfall from stations.