Researcher of the Month
Applied Mathematics & Statistics, Physics majors, Honors College, Class of 2023
Research Mentors: Dr. Kevin Reed, School of Marine & Atmospheric Sciences (current); Dr. Eric Jones,
Laser Teaching Center, Physics & Astronomy (previous)
At this time of year, extreme weather events concern all of us. For Justin Willson, “Examining Future Changes in Tropical Cyclone Intensity Near Landfall” has become a major preoccupation and commitment months in the making — ever since joining the Climate Extremes Modeling Group of Dr. Kevin Reed (SoMAS).
Justin is an Applied Math & Statistics (AMS)/Physics double major in the Honors College whose computational atmospheric science project looking at the intensity of hurricanes near landfall was conducted remotely in summer 2021, and was supported by URECA funding. Through the immersive URECA summer program, Justin sought to gain more experience doing big data analysis, working with complex data files, and developing Python code to analyze data from past and future climate simulations, work that has confirmed for him how much he enjoys working in this field. Justin plans to build on his atmospheric sciences analysis/modeling work with Dr. Reed for his Honors College senior thesis next year, and reflects: “ I have found that I really enjoy working with data. I am fascinated by how data analysis can help answer important questions about the future….I like how it will improve our understanding of the planet and climate change, and potential dangers we could face in the future. ”
Justin first became involved in undergraduate research at SBU during the first semester of his freshman year, doing Light Polarization experiments at the Laser Teaching Center (Physics & Astronomy) under the mentorship of Dr. Eric Jones, and LTC founder, Dr. Harold Metcalf. Although there were disruptions to the research in spring semester 2020, Justin was able to continue his LTC-summer project “ Monte Carlo Simulation of Bell Inequalities ” remotely, with funding through a Simons Foundation-sponsored URECA summer award (2020). Justin presented this project virtually at the Frontiers in Optics plus Laser Science (FiO+ LS) Conference last September and at the 2021 URECA spring symposium.
Justin is a member of the Society of Physics Students (SPS) and Running Club. Outside of research, he enjoys fishing, running and soccer. He is from Massachusetts, and is a graduate of King Philip Regional High School (Wrentham, MA). Below are excerpts of his interview with Karen Kernan, URECA Director.
Karen : What is your summer URECA research project about?
Justin: I’ve been researching trends in tropical cyclone (TC) intensity near landfall under the guidance of Dr Kevin Reed (School of Marine & Atmospheric Sciences). Tropical cyclones are some of the most dangerous weather events in the world, and it is important to understand potential changes in their behavior due to future climate change. In my project, I analyzed the intensities of TCs near landfall by applying statistical methods to TC intensity distributions within 100 km, 200 km, or 300 km of the eastern U.S. coast . In this case, intensity refers to the maximum sustained wind speed at points along the TC’s track. I used several datasets in this analysis including IBTrACS (historical estimation of observed TC tracks and wind speeds from 1985-2014), REF (variable resolution Community Atmosphere Model version -CAM5- simulation of TCs from 1985-2014), RCP4.5 (variable resolution simulation of TCs in a future climate with global warming from 2070-2100), and RCP8.5 (same as RCP4.5 but with a higher rate of warming).
For all datasets, I used Python to create TC intensity distributions and then analyzed them using statistics to see if there were any statistically significant differences in intensity in the future. Specifically, I wanted to do two things: compare the historical simulations to observations and compare the historical and future simulations. The first comparison was important because it allowed me to understand how accurate, in a general sense, the simulations were compared to observed trends. Then, I could compare the historical and future simulations to quantify any differences in intensity.
Did you find anything unexpected?
I had expected the intensity near the coast to increase with global warming, but I actually didn't find that in these simulations. This result was surprising and it definitely warrants more analysis so the next step is to apply the same analysis procedure to different climate models to see if the same trends are observed in those models as well. Also, I am going to refine my analysis to only include TCs at tropical storm strength or greater since the ability to simulate weaker storms near land was identified as a potential problem during the summer. Both of these steps would give us a better indication of whether we would likely see that trend in the future or if it was an inaccuracy in the particular climate model we analyzed.
…and how long have you been working in this area of climate modeling?
I first contacted Dr. Reed at the end of the fall 2020 semester, and did some readings during the winter to get some background information on tropical cyclones. Then , from the readings, we developed a research proposal for my summer 2021 project . I didn't actually start research until the summer. I spent most of the first month learning how to use Python to open the datasets and extract relevant information from them. At the same time, I was continuing to do readings to learn about the climate models, and how different scientists have analyzed different trends, including variables such as precipitation or intensity after landfall. After developing background skills and additional programming knowledge, I spent the rest of the summer writing programs that analyze d data specific to my project .
Did you already have previous programming experience?
Yes . My research project on Monte Carlo simulations for the LTC gave me background knowledge of Python--the syntax of the language , how to make and debug programs, how to think as a programmer , and programming principles that are fundamental to all languages . I learned a lot from that experience which helped me this past summer because it was easier to learn new methods and apply what I already knew to a new problem. I also had some familiarity with statistical analysis and analyzing datasets from my physics labs and AMS courses which made that aspect of the research easier to understand .
In summer 2020, all of the projects had to be done remotely.
Yes, that was unfortunate since I was looking forward to working in the lab however I ended up really enjoying computational analysis. I actually conducted my research remotely this past summer as well. My meeting with Dr. Reed a couple days ago was my first time meeting him in person, although we’ve had a lot of meetings over Zoom. I hope to meet the rest of the Climate Extremes Modeling Group this semester in person too.
Do you work with some of the graduate students in Dr. Reed’s group?
Yes, I worked with one of the graduate students of the group, Alyssa Stansfield, who has done a lot of research in this area and her studies on future changes in precipitation due to TCs provided the inspiration for my own project . She is a great mentor and always helped me with any questions I had about Python or the datasets.
What do you most enjoy about the work that you've done so far?
I have found that I really enjoy working with data. I am fascinated by how data analysis can help answer important questions about the future. Global warming is already becoming a more deadly problem so to be able to look at the outputs from some of the most advanced climate models we have, analyze them , and see what trends could be observed in the future, I think that's really interesting and important….I like how it will improve our understanding of the planet and climate change, and potential dangers we could face in the future.
What has been the most difficult part of being involved in research for you?
The most difficult thing, I would say, is time management. This is the first semester that I’ll be doing research and classwork at the same time. Because my classes are time-consuming, I'll need to figure out a way to do both without affecting my grades or ability to complete my project. I think that's why summer is the best time to do research because in the summer research will most likely be the one and only thing you're focusing on. There's definitely more time in the summer to really explore what you're interested in and complete a project that examines a problem at an advanced level.
Do you have any advice for other students about research?
If you want to get involved in research, don't be afraid to reach out to a lot of different professors and see what types of opportunities they have to offer. They're not usually going to advertise these opportunities; you have to go and find them yourself; but the good thing, in my experience, is that it isn’t too difficult to get started. If professors have space in their research group, they’re usually welcoming and I’ve been fortunate to have two great mentors. Also, I would add: don't be afraid to try different areas to figure out what you like and what topics you’re most interested in.
It’s great that you’ve had two positive research experiences.
Yes, both Dr. Reed and Dr. Jones are excellent mentors. They always put in a lot of effort into helping me to understand what I’m doing and why I am doing it. They're always willing to help with pretty much anything that I might have questions about and overall, they are both very passionate about their work and extend that passion to create a positive research experience for the students.
Also, getting involved in research early on improved my experience because it allowed me to discover new interests . If I were only starting to get involved now in my junior year, I might not have had the time to figure out that I was most fascinated by computational projects. That being said, anytime is a good time to start research and sometimes it helps to start later once you have taken more advanced classes.
It sounds like you’ve learned a lot through your research experiences.
Yes, I have learned a lot through research. Before starting research, I had no programming knowledge and now I feel more comfortable using Python and learning other programming languages. Another thing I have learned through research is how to approach problems in a long term way. In my experience, classes assign work that is due in a week or two so you can’t spend that much time learning one topic before you move on to the next one. But in research, problems can take months to solve and there are always setbacks so it was important that I learned how to break a problem down into specific parts and come up with creative solutions to solve them.