Tropical cyclone risk research: Taking the world by STORM
Nadia Bloemendaal tells the story behind her RDNL Dutch Data Prize winning ‘STORM’ dataset that has been downloaded more than 3,600 times since its publication in 4TU.ResearchData.
Nadia Bloemendaal is a PhD researcher at the Institute of Environmental Studies (IVM) at Vrije Universiteit (VU) in Amsterdam. Her research investigates tropical cyclone risk and how this is impacted by climate change.
Nadia’s childhood dream to study extreme weather began when she was just eight years old after watching the 1996 American epic disaster film, ‘Twister’.
The romantic story of two storm chasers who develop a tornado data-gathering device to protect against one of the world’s most violent tornadoes triggered Nadia’s fascination.
“Ever since watching the film, I wanted to become a meteorologist and study extreme weather. The film inspired me to create some kind of weather alert system that could help to prevent catastrophic storm damage, protect people and save lives,” says Nadia.
To fulfil her lifelong ambition, Nadia studied a Bachelor’s degree in Applied Mathematics at the University of Twente and a Master’s degree in Meteorology at Utrecht University before joining the VU’s Water and Climate Risk group in 2016 to begin her PhD.
Tropical cyclone risk
Every year tropical cyclones (hurricanes and typhoons) bring great devastation to parts of our world, impacting people, economies and the coastal areas where they make landfall. These deadly natural disasters continue to pose a major risk to societies worldwide, and calculating their risk presents a significant challenge due to the lack of historical data.
“There’s only around 40 years of reliable, global-scale satellite data available to study tropical cyclones,” explains Nadia. “What’s more, there are only around 90 cyclone formations on average each year. Of these, only a small proportion make landfall and cause damage. So, there aren’t actually that many tropical cyclones to study.”
She continues, “Tropical cyclone damage typically occurs within 500 km of landfall location which is a very small region relative to the size of a country’s entire coastline. This makes it even more challenging to study risk as there’s an enormous number of locations where a tropical cyclone could hit.”
Making waves with ‘STORM’
In order to overcome the problem of limited data for tropical cyclone risk research, Nadia and her team of collaborators from IVM, Deltares, KNMI and the University of Southampton, developed a mathematical model that can statistically extend the available data to simulate 10,000 years of tropical cyclone activity.
The ‘Synthetic Tropical cyclOne geneRation Model’, otherwise known as ‘STORM’, can extract and amplify data about tropical cyclones from any meteorological dataset to provide information about their possible tracks and intensities. STORM simulations provide the number, geographic location and wind speed of tropical cyclones.
Nadia explains that certain environmental variables must be considered in order to ensure simulation accuracy. “STORM is a Python model that integrates NetCDF meteorological data with the publicly available ERA5 dataset (ECMWF) to adjust for sea surface temperature and atmospheric pressure. This allows STORM to accurately and reliably simulate tropical cyclone activity in susceptible coastal regions based on present-climate conditions.
The winning dataset
Nadia applied STORM to extract 38 years of historical tropical cyclone data from the Best Track Archive for Climate Stewardship (IBTrACS). Since IBTrACS is the most comprehensive dataset from the National Oceanic and Atmospheric Administration, Nadia generated the first global synthetic tropical cyclone risk dataset using STORM.
Her resultant dataset, ‘STORM IBTrACS present climate synthetic tropical cyclone tracks’, caused a big splash!
It won last year’s RDNL Dutch Data Prize and has been downloaded 3,670 times since it was published in 4TU.ResearchData only four months ago. The associated peer-reviewed publication is available in Scientific Data.
Real world applications
“STORM has high value in protecting people’s lives. I made my datasets publicly available in the 4TU.ResearchData repository so that they can benefit others in the field of climate research,” says Nadia.
A variety of stakeholders have shown interest in Nadia’s STORM data, from researchers studying tropical cyclone risk in Tonga in the South Pacific to international insurance company, Allianz.
“Insurance companies can use STORM to model tropical cyclone risk at higher resolution and over longer-time scales, allowing them to perform large-scale risk assessments with greater confidence than ever before.”
Nadia came third in the Allianz Climate Risk Research Award last year. She was awarded this prize for the best climate risk related PhD research.
Apart from improving risk mitigation through insurances, Nadia hopes that her STORM datasets can help construction companies to build houses that can withstand certain wind speeds in tropical cyclone-prone coastal regions.This way, people will have a better chance at protecting themselves from a tropical cyclone, hereby reducing impacts and ultimately saving more lives
As Nadia is set to complete her PhD in May, her final project is to apply STORM to the PRIMAVERA dataset to identify coastal regions that will be at increased risk of tropical cyclones under climate change. Local policymakers and other stakeholders can take appropriate measures to reduce potential future impacts.
And, with her RDNL Dutch Data Prize money, Nadia plans to design an interactive online world map of possible tropical cyclones based on her STORM datasets. Users will be able to search, view and select tropical cyclone tracks to learn about their risk, intensity and shift under climate change.
Nadia is most excited about being able to provide tropical cyclone information at any location. “The website will allow users to navigate any place on earth, let’s say downtown Miami, for example, and see its full tropical cyclone risk profile under present or climate change conditions!”
Nadia hopes that a simple online tool will help the general public to visualise complex meteorological data, understand tropical cyclone risk and act accordingly.
The playlist behind STORM
To be fully transparent about her research, Nadia wants to share the top four songs that she listened to whilst developing STORM:
- Scorpions – Rock you like a hurricane
- The Doors – Riders on the STORM
- Bløf – Harder dan ik hebben kan
- Rammestein – Sonne
Thank you, Nadia, for sharing the story behind ‘STORM’ with 4TU.ResearchData. We wish you all the best for your future career.
Acknowledgements to Nadia’s STORM collaborators; Hans de Moel and Jeroen Aerts (IVM), Sanne Muis (Deltares and IVM), Reindert Haarsma (KNMI) and Ivan Haigh (University of Southampton and IVM)
Written by Connie Clare (4TU.ResearchData)
Cover image illustrated by Connie Clare (4TU.ResearchData)