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Evaluating Extreme Precipitation Events in New York City and Sub-urbans Using Weather Station Data

Undergraduate #109
Discipline: Data Science
Subcategory: Climate Change
Session: 3
Room: Exhibit Hall

Sameeha Malikah - The City College of New York
Co-Author(s): Stephanie Avila, The City College of New York, New York, NY; Gabriella Garcia, The City College of New York, New York, NY; Veebhu Shah, Eleanor Roosevelt High School, New York, NY; Kaylen James, Brooklyn Prospect High School, Brooklyn, NY; Dr. Tarendra Lakhankar, The City College of New York, New York, NY



Throughout the past several decades, precipitation rates have been rising in several regions throughout the world. Increased precipitation is a hazard for people residing in coastal regions, and allows greater amounts of area to be at risk of flooding. Not only does flooding cause structural damage, but saltwater intrusion from floods caused by rising sea levels also damages fertile soil, destroying the agriculture of a region. Increased precipitation also leads to sewage overflow, as was observed when the remnants of Hurricane Ida hit New York City in the Summer of 2021. The goal of this project is to determine the trends in historical precipitation records for New York City, New Jersey, and Connecticut to help make better predictions for extreme precipitation events in the near future. It also aims to get an understanding of the trends in snowfall and extreme precipitation for these locations. Using Python and arcGIS software, this project analyzes precipitation and snowfall measurement data from 44 weather stations located throughout the tri-state area. While most of these stations had data available starting from the 20th century, a few had data available starting from as early as 1869. Statistical methods were used to determine extreme precipitation thresholds for each of the three states.After analyzing the trends in the number of snowfall days in New York City, a decreasing trend of three to four days of annual snowfall per century was observed for a time period of about 150 years. Unlike snowfall, analysis of the precipitation data showed that there has been an increase in the annual count of days with extreme precipitation. The same was observed for rainfall, which indicates an increase by 0.2 to 0.5 inches per century. As research is being continued for the New Jersey and Connecticut weather stations, it is hypothesized that these regions will have similar trends in snowfall, rainfall, and number of days with extreme precipitation. In the comparison between weather stations, it is hypothesized that urban regions will have a larger value for average rainfall and lower value for snow count days compared to suburban areas due to the presence of the Urban Heat Island Effect.

Funder Acknowledgement(s): This research was funded by NSF REU Grant #1950629.

Faculty Advisor: Dr. Tarendra Lakhankar, tlakhankar@ccny.cuny.edu

Role: For this research project, I participated in collecting the weather station data, formulating research questions, writing the base codes for the analysis, analyzing the trends, mentoring my team members, and creating the poster.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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