Miguel Laverde Barajas earns PhD for research on rainstorm analysis

My thesis in a nutshell

I developed a method that makes it possible to better analyse the structure of rainstorm events in space and time. My method looks at the rainstorm as object describing its main physical features  – such as volume, intensity, duration, extension,  orientation, speed and more.  This method is called Spatiotemporal Contiguous Object-based Rainfall Analysis (ST-CORA), and it can be used to correct systematic errors in rainfall measurements captured by satellites.

I applied the method in two monsoon-affected areas in Brazil and Thailand, where the results helped local authorities improve their forecasts for extreme scenarios such as flooding. Later, I implemented the method to introduce an operational rainstorm monitoring and alert system for the Lower Mekong basin, called the Rainstorm Tracker System.

Lower Mekong countries suffer from the effects of seasonal flooding and flash flooding caused by monsoon rains and tropical storms. The tool aims to decrease risk by helping regional authorities to prepare for, monitor, issue warnings, and respond to flood risk.

Memorable moments

The most memorable moment was when the SERVIR-Mekong program used my method ST-CORA to develop the Rainstorm Tracker system for the Lower Mekong region . This program, a joint initiative by NASA and USAID implemented by the Asian Disaster Preparedness Center in Thailand, supports local and regional organizations in the Mekong area in using satellite data to address challenges on the ground. This great leap from academic research to implementation showed how my research impacts society and how hydro informatics technologies can be used in real applications.

Challenges during my PhD studies

The most challenging part was the conclusion of the chapters. Each chapter was designed to answer a particular research question. However, in reality, every answer always leads to further questions for development, and for me, it was difficult to say done it's done. This part was amazing, but at the same time very challenging.

The influence of my PhD research

I hope my research will contribute to both fundamental and applied science. In fundamental science, my research contributes to a better understanding of errors in space and time derived from satellites for extreme event prediction. This can lead to more accurate measurements in multiple hydrological applications and more detailed rainstorm characterization, which in turn can be used to improve data-driven models for flood-related disaster response applications.

In applied science, my PhD research, specifically the Rainstorm tracker, improves the ability of multiple local and regional organizations in the Lower Mekong region to predict and respond to rainstorms.

Next steps

I am planning to work with the SERVIR-Mekong program supporting organizations such as the Mekong River Commission and the World Food Program in improving their decision-making process for water disaster management through the Rainstorm Tracker system.

An important lesson

You can find important findings in your research in places that you never expect. The best ideas may pop up while you are going for a walk or even taking a shower!

Research summary

Title of thesis: Improving satellite-based precipitation estimates: A spatiotemporal object-oriented approach to error analysis and correction.

Satellite Precipitation Products (SPP) have been revolutionary in water resources management and flood-related disaster response. However, estimating extreme rainfall is subject to multiple systematic and aleatory errors that need to be corrected. This dissertation addresses errors in satellite data to estimate extreme rainfall events in space and time beyond the pixel. The Spatiotemporal Contiguous Object-based Rainfall Analysis method (ST-CORA) is developed to analyse errors in SPP for rainstorm estimations based on their main physical features in space and time (volume, intensity, duration, extension, orientation, speed, among others). Using ST-CORA, systematic errors due to volume and displacement in space and time are corrected in a novel bias-corrected method called ST-CORAbico. Case studies in two monsoonal areas in South America and Southeast Asia have been used to analyse the hydrological response of systematic errors in flood predictions and evaluate error reduction in non-operational and operational bias correction applications. Finally, the dissertation describes further implementations of ST-CORA in developing an operational system for rainstorm monitoring called Rainstorm tracker. This web-based platform is designed to monitor and alert decision-makers about the severity of rainstorm events over the Lower Mekong basin in near-real and real-time.