NYC SYEP Internship Project: When it Comes to Climate, What’s “Normal”?
This project was completed in partnership with the NYC Summer Youth Employment Program (SYEP). Linyi completed her internship in Summer 2021.
We hear about climate change all the time…but how do we know if the climate is actually changing? We can track weather changes day-to-day and even seasonally, but when do we know it’s really a different climate and not just an abnormally hot or cold year? To do this, climatologists use metrics called climate normals, which are averages calculated over 30-year ranges. Climate normals are calculated for a variety of factors including temperature, precipitation, even ideal days per year to grow corn! The normals are updated every 10 years. By comparing these larger ranges, we can begin to piece together the story of a changing climate. Climate normals were recently updated in 2021 to include the most recent data from 1991 to 2020.
From climate normals, we can make interesting maps like this one, which compares the past 100 years of data from the 1900s to the most recent 30 years of data. This chart shows that the most recent “normal” temperature is around one degree higher than the average temperature over the last century. Using charts like this one, we can tell that climate change is happening.
These charts are neat, but who really cares about these new normals? Cities care!
Cities can use this data to make informed decisions on potential issues related to water supply, flooding, and infrastructure. For example, if a city sees that their system is starting to struggle a little and maybe just scraping by during storms, and it sees that their area has been getting a bit more rain compared to 50 years ago, that city knows that their stormwater systems need to be expanded to avoid flooding.
StormSensor helps cities track how climate change impacts their community by combining precipitation data with data detailing how water moves through their stormwater systems. Doing this can help cities find areas where their system may be undersized and leading to flooding or impacted by other effects of climate change such as sea level rise. As part of this project, we wanted to see if we could add any more insights to StormSensor’s solutions by looking at climate normals. We chose two cities to focus on, Jersey City, NJ, and North Miami, FL.
The first part of my investigation looked at how NOAA climate normals compared to actual weather data gathered by StormSensor; I compared the historic monthly minimum, maximum, and average temperatures and the total precipitation to the normal for the cities. This example for Jersey City, NJ shows that the average temperature stayed very close to the normal, but the highs are getting higher and the lows are getting lower for every month. The overall temperature has not changed much, but it indicates that temperature swings are getting larger. We saw a similar pattern in North Miami.
Once we saw that there was some evidence of a change in the climate, we wanted to know what that meant for StormSensor® customers! Next step: see if there is a correlation between climate normals and issues in stormwater systems.
StormSensor® has developed real-time alerts to let their customers know when different events occur in their system. Examples include combined sewage overflows, stormwater flows, and critical depth events. We compared records of these events to climate normals and looked for patterns. (During this phase I learned a lot about what it is like to be a data scientist! There were a lot of non-significant findings!) However, we did find a few interesting patterns, even though they were not entirely surprising. For example, in North Miami, we noticed that a lower-than-normal amount of rain was correlated to fewer alert events.
What Happened Next—Data Science Internship
After the data analysis phase of my project, I met with the StormSensor® product team to learn how this kind of research gets turned into a software feature. Developing a feature really makes you walk in the shoes of who would actually want to use it. For example, if I were a stormwater systems manager, I would want to be prepared for unusual weather patterns and make sure that our systems are not overwhelmed. Looking ahead, especially at precipitation, will let me know if our systems will hold up and prevent flooding.
If I were a civil engineer, I would want to look back on previous climate data, so I know how climate change affects my area and keep that in mind when designing infrastructure. For example, I would want to design buildings that are less prone to flooding if I see that my area is getting more severe thunderstorms and blizzards.
I worked with the product team to put together requirements documents for my feature, and I got to be involved in the design selection process. I cannot share everything under development with you here but stay tuned! StormSensor® will be including my research in some upcoming products designed to help communities like the ones I studied better understand climate change and it’s impacts on their systems.
The Summer Youth Employment Program (SYEP) is the nation’s largest youth employment program, connecting NYC youth between the ages of 14 and 24 with career exploration opportunities and paid work experience each summer.
Participants have the opportunity to explore their interests and career pathways, develop workplace skills and engage in learning experiences that help in developing their social, civic and leadership skills.
By participating in structured project and work-based opportunities, NYC youth are better prepared for careers of the future.
Linyi’s project is the third round of remote internships StormSensor has sponsored along with SYEP- past projects included explorations in data science, hydrologic engineering, and marketing.