Applications

Overview: Extreme precipitation events have caused catastrophic flooding throughout West Africa and will continue to wreak havoc over these parts as the climate continues to change. For this project, I am analyzing monthly convective shallow, deep convective and stratiform events over the West Africa region and comparing rainfall totals using GPM DPR data. Mentors: Aaron Funk, Courtney Schumacher

Overview: Argentina has a low-density rain gauge network. As a result, there are often challenges in representing accurate estimates of precipitation. Satellite quantitative precipitation estimates (SQPEs) derived from satellite measurements can help fill these gaps and serve a critical role in hydrological and weather forecasting applications. This project explores different gauge bias correction methods of SQPE products using the IMERG Early Run in Argentina to improve SQPE data products. Mentor: Joe Turk

Overview: This project evaluates the GPM IMERG Late product against ground data to develop applications for a hydrological modelling online platform. Mentor: Mircea Grecu

Super Typhoon Nanmadol became one of the strongest typhoons to threaten Japan since records began in 1951. Nanmadol began as a tropical disturbance, basically an area of active thunderstorms, on September 11th southeast of Iwo Jima about midway between Tokyo and Guam. After moving to the southwest for 2 days, this disturbance became better organized and formed into a depression on the 13th. The system then made a counterclockwise loop, moving first back to the northeast before turning back again towards the west. Over this time, the system slowly intensified, becoming Tropical Storm Nanmadol

Overview: This project works to validate the GPM dual-frequency precipitation radar (DPR) merged scan product against a quality-controlled ground reference data (GV-MRMS) in the continental US. Knowledge from this concept study will be applied to validating/ evaluating and selecting remotely-sensed satellite rainfall products that could be useful for rainfall estimation in data-scarce regions such as West Africa. Mentors: Yagmur Derin, Pierre Kirstetter

Affiliation: Texas A&M University – Corpus Christi, Corpus Christi, Texas, USA Project Mentees: Eva Yamamoto, June Choi; Nimisha Wagle

Affiliation: Goddard Earth Sciences Technology and Research, Morgan State University, and NASA Goddard Space Flight Center, USA Project Mentees: Charlene Gaba, Idelbert Behanzin

Overview: Understanding how the behavior of large-scale precipitating systems is impacted by atmospheric variables can yield important insights about subseasonal variability and predictability across different regions. For this project, we explored the relationship between atmospheric variables and the characteristics of large precipitating systems, such as their size, geographic distribution, volume of rain, and maximum height of the system. Mentor: Chuntao Liu

Overview: This project uses IMERG to characterize the spatial and temporal extreme precipitation events over West Africa. Mentor: Mircea Grecu

Overview: Hydrometeorological natural hazards are on the rise globally, yet in Africa, rainfall data which is crucial in mitigation efforts is lacking. Understanding the amount and distribution of rainfall and how it plays a role in causing these natural hazards is critical to improve disaster response and mitigation efforts. This project uses GPM IMERG data together with resources like NASA's Landslide Viewer to determine a precipitation threshold for landslides in the Mt. Elgon region of Uganda. Mentors: Vasco Mantas, Zhong Liu, Andrea Portier, Dorian Janney