Welcome to our Syracuse Weather Dashboard.

This offers a comprehensive, data-driven look at the key weather variables, such as temperature, snowfall, and storm frequency, that define the academic experience at Syracuse.

This dashboard is to provide current and prospective students, faculty, and local residents with a clear, historical understanding of Syracuse’s renowned winter climate. By analyzing decades of data from the National Centers for Environmental Information (NCEI) and the National Weather Service, we aim to allow users to move beyond anecdotes and utilize verifiable data to prepare for the academic year and the inevitable snowfall.

Question: How do the average temperatures in Syracuse change across the year, and which months are the coldest for students?

Average temperatures in Syracuse reach their lowest point in January, with an average temperature of 24.45°F, and remain cold throughout December (32.03°F) and February (27.31°F). Temperatures warm steadily through spring and peak in July, when the average temperature reaches 72.85°F. This confirms that the coldest period for students is December through February, while the warmest conditions occur in midsummer before temperatures drop again heading into the fall semester.

A month-by-month breakdown of Syracuse’s temperature patterns, highlighting typical average, high, and low conditions for students.

Monthly Temperature Summary
Month Avg Temp (°F) Max Temp (°F) Min Temp (°F)
Jan 24.4 31.5 15.7
Feb 27.3 33.5 16.8
Mar 34.8 42.7 25.1
Apr 46.8 56.6 36.1
May 59.3 68.9 46.7
Jun 67.9 77.7 56.0
Jul 72.9 82.3 61.1
Aug 71.1 80.4 59.5
Sep 64.4 72.9 52.0
Oct 52.8 61.2 41.8
Nov 41.7 48.4 32.9
Dec 32.0 36.4 22.2

Question: What is the average monthly snowfall amount, and during which month are Syracuse students likely to experience the most snow?

Average snowfall in Syracuse peaks in January, when the city receives about 34 inches of snow on average. Snow totals remain high in December and February, creating a long winter season for students. From late spring through early fall, snowfall is close to zero, so most snow days are concentrated in the core winter months.

A month-by-month snapshot of Syracuse’s snowfall, highlighting which parts of the school year are snowiest and which months have little or no snow.

Average Monthly Snowfall in Syracuse Summary
Month Snowfall (in.)
Jan 34.0
Dec 30.6
Feb 30.3
Mar 19.8
Nov 9.8
Apr 3.0
Oct 0.2
May 0.1
Jun 0.0
Jul 0.0
Aug 0.0
Sep 0.0

Question: How often does Syracuse experience blizzards, and what time of year are they most frequent?

Winter storm activity in Onondaga County is concentrated in the core winter months. December and February show the highest and nearly identical number of winter storm events, with January close behind. Storm frequency drops sharply after March, with only isolated storms occurring in early spring and none recorded from late spring through fall. Overall, the data indicate that the peak winter storm period spans December through February.

The bar chart shows that winter storms in Onondaga County occur almost entirely between December and March. February and December have the highest number of storms, followed by January. Storm activity drops sharply after March, with April showing only one event. This pattern reflects the region’s typical winter climate, where the most severe winter weather occurs in mid-winter.

# A tibble: 2 × 2
  season n_storms
  <chr>     <int>
1 Winter       21
2 Spring        3

Question: How many days per semester can Syracuse students typically expect snow, and which semester experiences more snow depth?

The boxplot displays the distribution of snow depth in Syracuse for both Fall and Spring semesters from 2005 to 2025. It shows that Fall has lower snow depths, with a median of around 0 inches, but there are several outliers. In contrast, Spring has a higher median snow depth at around 4 inches. Spring also shows more extreme outliers, reaching up to 25 inches. While both semesters experience snow depth, overall Spring semester has a higher accumulation.

A table of how many days during the past , on average, per semester students at Syracuse University can expect snow.

Snowy Days per Semester (2005–2025)
Year Fall Spring
2005 34 78
2006 7 49
2007 29 72
2008 21 44
2009 17 56
2010 28 67
2011 2 70
2012 11 26
2013 27 64
2014 16 72
2015 2 84
2016 29 53
2017 22 46
2018 34 72
2019 26 66
2020 12 54
2021 8 50
2022 20 64
2023 6 45
2024 16 37
2025 2 68

Question: Over the last 11 years has there been a decrease or increase in average wind speed in Syracuse?

The data indicates that wind speeds were generally higher during the earlier years, particularly from 2015 to 2017, with the most notable increases occurring between January and April. Towards the end of the year, wind speeds appear to stabilize, as shown by the tighter clustering of values, with each year exhibiting relatively similar measurements. Overall, while there is a slight downward trend in wind speed over time, the levels have remained fairly consistent.

Yearly Average Wind Speed
Date MPH
2016 3.48
2017 3.19
2018 2.40
2019 3.44
2020 3.01
2021 2.14
2022 2.38
2023 2.04
2024 2.46
2025 3.48
Monthly Average Wind Speed
Month MPH
Jan 3.23
Feb 3.50
Mar 3.76
Apr 3.66
May 2.90
Jun 2.32
Jul 1.87
Aug 1.74
Sep 1.78
Oct 2.40
Nov 3.22
Dec 3.24

This dashboard was created using Quarto in RStudio, and the R Language and Environment.

The dataset used to create this dashboard was downloaded from

National Centers for Environmental Information. (2025, December 2). Past Weather – Syracuse, NY. https://www.ncei.noaa.gov/access/past-weather/Syracuse,%20NY

Palecki, M., Durre, I., Applequist, S., Arguez, A., & Lawrimore, J. (2021). National Centers for Environmental Information. U.S. Climate Normals 1991–2020: Monthly Climate Normals. https://www.ncei.noaa.gov/access/us-climate-normals/?utm_source=chatgpt.com#dataset=normals-monthly&timeframe=30&location=NY&station=USW00014771

National Centers for Environmental Information. Storm Events Database: Winter Storm events in Onondaga County, NY (1950–2024). https://www.ncei.noaa.gov/stormevents/listevents.jsp?eventType=%28Z%29+Winter+Storm&beginDate_mm=01&beginDate_dd=01&beginDate_yyyy=1950&endDate_mm=11&endDate_dd=12&endDate_yyyy=2024&county=ONONDAGA%3A67&hailfilter=0.00&tornfilter=0&windfilter=000&sort=DT&submitbutton=Search&statefips=36%2CNEW+YORK

National Weather Service. Past weather observations – KSYR (Syracuse Hancock International Airport). https://forecast.weather.gov/data/obhistory/KSYR.html

Software Citations

Allaire J, Dervieux C (2024). quarto: R Interface to ‘Quarto’ Markdown Publishing System. R package version 1.4.4, https://CRAN.R-project.org/package=quarto.

Arnold J (2024). ggthemes: Extra Themes, Scales and Geoms for ‘ggplot2’. R package version 5.1.0, https://github.com/jrnold/ggthemes, https://jrnold.github.io/ggthemes/.

Bache S, Wickham H (2025). magrittr: A Forward-Pipe Operator for R. doi:10.32614/CRAN.package.magrittr https://doi.org/10.32614/CRAN.package.magrittr, R package version 2.0.4, https://CRAN.R-project.org/package=magrittr.

Dancho M, Vaughan D (2025). tidyquant: Tidy Quantitative Financial Analysis. doi:10.32614/CRAN.package.tidyquant https://doi.org/10.32614/CRAN.package.tidyquant, R package version 1.0.11, https://CRAN.R-project.org/package=tidyquant.

Kunst J (2022). highcharter: A Wrapper for the ‘Highcharts’ Library. R package version 0.9.4, https://CRAN.R-project.org/package=highcharter.

Neuwirth E (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3, https://CRAN.R-project.org/package=RColorBrewer.

Posit team (2025). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www.posit.co/.

R Core Team (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.https://www.R-project.org/.

Rinker, T. W. & Kurkiewicz, D. (2017). pacman: Package Management for R. version 0.5.0. Buffalo, New York. http://github.com/trinker/pacman

Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.

Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.50, https://yihui.org/knitr/.

Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963

Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595

Zhu H (2024). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.4.0, https://github.com/haozhu233/kableExtra, http://haozhu233.github.io/kableExtra/.