The GPM Applications Team in collaboration with the University of Coimbra created the GPM Mentorship Program to support new users from established and underrepresented communities and provide tailored hands-on learning experiences in using GPM data for applications. The goal of the program is to provide an overview of using state-of-the-art satellite-based precipitation estimates, and to provide users their first experience of applying GPM data to support real-world problems. The 2022 initiative is the first edition of the mentorship program.
The GPM Applications Team in collaboration with the University of Coimbra created the GPM Mentorship Program to support new users from established and underrepresented communities and provide tailored hands-on learning experiences in using GPM data for applications. The goal of the program is to provide an overview of using state-of-the-art satellite-based precipitation estimates, and to provide users their first experience of applying GPM data to support real-world problems. The 2022 initiative is the first edition of the mentorship program.
Statistics from the 2022 GPM Mentorship Program. Credits: NASA
Data and information collected from Earth observing satellites allows us to better understand our planet and make informed decisions that lead to improved outcomes for society. Specifically, the use of high-quality precipitation data from NASA’s Global Precipitation Measurement (GPM) mission has informed decision-making throughout the world, from short-term crises to long-term planning. GPM has supporting planning and decisions related to water resource management, crop forecasting, ecological monitoring, disaster risk reduction and response, public health, aviation, weather forecasting, and climate modeling, among others. A fundamental component of the GPM Applications efforts is to continue to engage new and existing users to help guide the use of GPM data within their systems to address real-world problems and make informed decisions that directly benefit society.
Unlike training programs consisting primarily of passive content consumption – for example, video webinars and tutorials - the GPM Mentorship Program provides both theoretical and practical trainings supported by direct interaction with subject matter experts from NASA’s Precipitation Measurement Mission (PMM) Science Team. Participating in the program helps to consolidate learned skills and promotes interaction with top scientists in the GPM community.
Screenshot of mentors and participants (mentees) during the last session of the 2022 GPM Mentorship Program. Credits: NASA
The program began by selecting a small cohort of participants to partner with PMM mentors, with the goal of developing 2-month projects using GPM data. These projects focused on topics suggested by the mentors that were tailored to the skills and interests of the participants. Participants are expected to become local pivots for the dissemination of PMM products and best practices, laying the foundations for further use of GPM data in their communities.
All training and participation for the 2022 GPM Mentorship Program took place online across a period of three months. Participants spent about 8 hours per month participating in training sessions and working on collaborative projects with PMM scientists, then shared the outcomes of their project and lessons learned during the final session.
Some outcomes from the program include:
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: Understanding the relationship between aerosols and the fuel that govern deep convective storm events can significantly improve meteorologists’ and scientific researchers’ capacity to predict and monitor these severe weather events. For this project, I am analyzing shallow, deep convective and stratiform events over Central Kalimantan using GPM DPR data and comparing it to the amount of atmospheric aerosols using AOD retrievals from ground based measurements provided by AERONET.
Mentors: Aaron Funk, Courtney Schumacher
Overview: This project evaluates the GPM IMERG Late product against ground data to develop applications for a hydrological modelling online platform.
Mentor: Mircea Grecu
Overview: Numerous isolated precipitation features (PFs) can have similar rain intensities as organized ones and thus have potential to cause catastrophic flooding, landslides, and infrastructure damage. Understanding more about the properties of these storm systems can help improve forecast analysis, and improve mitigation and disaster response. For this project, I am doing a global analysis to sort out when and where high intensity isolated PFs were formed using GPM DPR data and indirect measurements of latent heating from GPM.
Mentor: Chuntao Liu
Overview: This project uses IMERG to characterize the spatial and temporal extreme precipitation events over West Africa.
Mentor: Mircea Grecu
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: 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: The Canadian Shield Region (CSR) is the Precambrian rock-dominated, deglaciated region of Northern America. There are more lakes than anywhere else in the world. As projected climate change intensifies the water and energy cycles, understanding fundamental hydrologic changes in these environments will be critical for predicting and managing water resources. In this study, I am using IMERG to find the potential sensitivity of Canadian shield depressions to inundation depth.
Mentor: Chuntao Liu
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
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
Affiliation: Texas A&M University, College Station, Texas, USA
Project Mentees: Armand Kablan, Ayuna Santika
Affiliation: Science Systems and Applications, Inc. and NASA Goddard Space Flight Center, Greenbelt, MD, USA
Project Mentees: Simon Ageet
Affiliation: Texas A&M University – Corpus Christi, Corpus Christi, Texas, USA
Project Mentees: Eva Yamamoto, June Choi; Nimisha Wagle
Affiliation: Texas A&M University, College Station, USA
Project Mentees: Armand Kablan, Ayuna Santika
Affiliation: ADNET Systems, Inc. & NASA Goddard Space Flight Center, Greenbelt, MD, USA
Project Mentees: Simon Ageet
Affiliation: University of Maryland Baltimore County and NASA Goddard Space Flight Center, Greenbelt, MD, USA
Role: GPM Mentorship Session Facilitator
Affiliation: NASA Jet Propulsion Laboratory, California Institute of Technology, USA
Project Mentee: María Paula Hobouchian
Affiliation: Goddard Earth Sciences Technology and Research, Morgan State University, and NASA Goddard Space Flight Center, USA
Project Mentees: Charlene Gaba, Idelbert Behanzin
Affiliation: University of Oklahoma, Norman, OK, USA
Project Mentees: Odinaka Echeta
Affiliation: University of Coimbra, Earth and Space Science Center (CITEUC), Portugal
Project Mentee: Simon Ageet
Affiliation: NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) and George Mason University, Greenbelt, Maryland
Project Mentee: Simon Ageet
