{"id":206248,"date":"2026-04-22T18:00:08","date_gmt":"2026-04-22T18:00:08","guid":{"rendered":"https:\/\/www.newsbeep.com\/us-ny\/206248\/"},"modified":"2026-04-22T18:00:08","modified_gmt":"2026-04-22T18:00:08","slug":"when-the-rain-comes-some-new-york-city-subway-riders-stay-home-scientists-are-now-mapping-exactly-who-and-where","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us-ny\/206248\/","title":{"rendered":"When the Rain Comes, Some New York City Subway Riders Stay Home. Scientists Are Now Mapping Exactly Who, and Where"},"content":{"rendered":"<p dir=\"ltr\">On a sweltering August afternoon or in the teeth of a winter storm, New York City subway riders make a quiet calculation: Is the trip worth it?<\/p>\n<p dir=\"ltr\">A new study published in <a href=\"https:\/\/www.nature.com\/articles\/s44333-026-00094-4\" rel=\"nofollow noopener\" target=\"_blank\">npj Sustainable Mobility and Transport<\/a> takes a detailed look at how those decisions show up in ridership patterns across the system, and how they vary from station to station.<\/p>\n<p dir=\"ltr\">Researchers from NYU Tandon, the University of Louisville, and the University of Hong Kong analyzed hourly ridership at 10 major subway stations between 2023 and 2025. Using a statistical technique called vine copula modeling, they examined how stations\u2019 ridership moves together under different weather conditions rather than treating each station as an isolated case.<\/p>\n<p dir=\"ltr\">\u201cThink about what actually happens when a storm hits,\u201d said <a href=\"https:\/\/engineering.nyu.edu\/faculty\/joseph-chow\" rel=\"nofollow noopener\" target=\"_blank\">Joseph Chow<\/a>, one of the paper\u2019s authors and an NYU Tandon Institute Associate Professor. \u201cThere is structure in how the riders of a system respond to the storm, almost like a unique \u201csignature\u201d of the system to a type of extreme weather event. Understanding these structures and how they evolve can help different cities better prepare their public transit systems to be resilient against extreme weather events.\u201d<\/p>\n<p dir=\"ltr\">Heavy precipitation has the strongest effect during the evening rush hour. As detailed in the appendix, median declines during heavy rain range from nearly 29 percent at Columbus Circle to less than 8 percent at Grand Central. Outer-borough stations such as Flushing\u2013Main Street also show large declines, approaching 26 percent.<\/p>\n<p dir=\"ltr\">Evening travel is more flexible than morning commutes, so heavy rain tends to shift or suppress trips rather than eliminate them entirely. Riders may leave earlier, wait out the storm, or cancel discretionary plans, leading to sharper drops during that specific peak hour even though most still get home, the researchers explained.<\/p>\n<p dir=\"ltr\">Extreme cold tells a different story. Even during the morning rush, when its effects are strongest, ridership declines are modest, generally between about 1 and 2.4 percent across stations. Larger effects appear off-peak, when discretionary trips are more likely to be canceled.<\/p>\n<p dir=\"ltr\">\u201cCommuters maintain their routines even when temperatures plunge,\u201d Chow said, who is also the Deputy Director of <a href=\"https:\/\/c2smart.engineering.nyu.edu\/\" rel=\"nofollow noopener\" target=\"_blank\">C2SMART<\/a>, Tandon\u2019s transportation research center. \u201cIt\u2019s the discretionary traveler, the person heading to a restaurant or a friend\u2019s apartment, who cancels the transit trip or switches to a different mode.\u201d<\/p>\n<p dir=\"ltr\">The study also highlights sharp differences between nearby stations. Columbus Circle emerges as one of the most weather-sensitive locations during heavy rain, while Grand Central, less than two miles away, shows comparatively small declines.<\/p>\n<p dir=\"ltr\">That variation suggests borough location alone does not determine resilience. Infrastructure, station design, connectivity, and surrounding land use all appear to play a role.<\/p>\n<p dir=\"ltr\">\u201cWhat we\u2019re giving planners is a way to see the whole network respond to a storm or a heat wave, not just one station at a time. And this method allows them to generate other plausible ridership scenarios under extreme weather, aiding decision-making,\u201d said <a href=\"https:\/\/engineering.nyu.edu\/faculty\/omar-wani\" rel=\"nofollow noopener\" target=\"_blank\">Omar Wani<\/a>, a NYU Tandon Assistant Professor and a paper author.<\/p>\n<p dir=\"ltr\">The authors emphasize important limitations. The analysis focuses on 10 high-ridership stations, and extreme weather events are relatively rare in the data. To address this, the model generates plausible ridership patterns based on observed relationships across stations.<\/p>\n<p dir=\"ltr\">That means the results should be interpreted as estimates of likely responses, rather than simple averages of past storms.<\/p>\n<p dir=\"ltr\">Even so, a clear pattern emerges. Heavy rain hits hardest during peak hours, while extreme cold has a greater effect off-peak, and the differences between stations are consistent rather than random.<\/p>\n<p dir=\"ltr\">The implications extend beyond operations. Because some neighborhoods rely more heavily on transit, uneven drops in ridership during extreme weather may translate into uneven burdens. As climate change increases the frequency of severe weather, understanding where and when riders stay home could help agencies plan more targeted responses.<\/p>\n<p dir=\"ltr\">In addition to Chow and Wani, the paper\u2019s authors are Yan Guo and Brian Yueshuai He of the University of Louisville; and Zhiya Su of the University of Hong Kong. Funding for the research was provided by the National Science Foundation.<\/p>\n<p>\u00a0<\/p>\n<p>Appendix<\/p>\n<p>\u00a0<\/p>\n<p>The tables below show median declines in ridership at the ten stations studied, compared with normal weather conditions. Each weather type is measured during the peak period when its effects are most pronounced, using the evening commute (4 to 5 p.m.) for heavy rain and the morning commute (8 to 9 a.m.) for extreme cold.<br \/>\u00a0<\/p>\n<p>Station<\/p>\n<p>Borough<\/p>\n<p>Median Decline,<br \/>Heavy Rain Peak Hour<br \/>(4 PM to 5 PM)<\/p>\n<p>Columbus Circle<\/p>\n<p>Manhattan<\/p>\n<p>-28.9%<\/p>\n<p>Flushing-Main St<\/p>\n<p>Queens<\/p>\n<p>-26.4%<\/p>\n<p>Fulton Street<\/p>\n<p>Manhattan<\/p>\n<p>-24.7%<\/p>\n<p>Times Square<\/p>\n<p>Manhattan<\/p>\n<p>-23.9%<\/p>\n<p>Chambers St\/WTC<\/p>\n<p>Manhattan<\/p>\n<p>-21.5%<\/p>\n<p>Atlantic Av-Barclays Center<\/p>\n<p>Brooklyn<\/p>\n<p>-21.4%<\/p>\n<p>Broadway\/Jackson Heights<\/p>\n<p>Queens<\/p>\n<p>-20.4%<\/p>\n<p>Penn Station<\/p>\n<p>Manhattan<\/p>\n<p>-19.3%<\/p>\n<p>Union Square<\/p>\n<p>Manhattan<\/p>\n<p>-10.2%<\/p>\n<p>Grand Central<\/p>\n<p>Manhattan<\/p>\n<p>-7.8%<\/p>\n<p>Columbus Circle<\/p>\n<p>Manhattan<\/p>\n<p>-2.4%<\/p>\n<p>Flushing-Main St<\/p>\n<p>Queens<\/p>\n<p>-2.4%<\/p>\n<p>Fulton Street<\/p>\n<p>Manhattan<\/p>\n<p>-2.0%<\/p>\n<p>Broadway\/Jackson Heights<\/p>\n<p>Queens<\/p>\n<p>-2.0%<\/p>\n<p>Chambers St\/WTC<\/p>\n<p>Manhattan<\/p>\n<p>-1.9%<\/p>\n<p>Penn Station<\/p>\n<p>Manhattan<\/p>\n<p>-1.8%<\/p>\n<p>Atlantic Av-Barclays Center<\/p>\n<p>Brooklyn<\/p>\n<p>-1.8%<\/p>\n<p>Times Square<\/p>\n<p>Manhattan<\/p>\n<p>-1.7%<\/p>\n<p>Grand Central<\/p>\n<p>Manhattan<\/p>\n<p>-1.1%<\/p>\n<p>Union Square<\/p>\n<p>Manhattan<\/p>\n<p>-1.00%<\/p>\n<p>\u00a0<\/p>\n<p>Station<\/p>\n<p>Borough<\/p>\n<p>Median Decline,<br \/>Extreme Cold Peak Hour<br \/>(8 AM to 9 AM)<\/p>\n<p>Flushing-Main St<\/p>\n<p>Queens<\/p>\n<p>-2.4%<\/p>\n<p>Fulton Street<\/p>\n<p>Manhattan<\/p>\n<p>-2.0%<\/p>\n<p>Broadway\/Jackson Heights<\/p>\n<p>Queens<\/p>\n<p>-2.0%<\/p>\n<p>Chambers St\/WTC<\/p>\n<p>Manhattan<\/p>\n<p>-1.9%<\/p>\n<p>Penn Station<\/p>\n<p>Manhattan<\/p>\n<p>-1.8%<\/p>\n<p>Atlantic Av-Barclays Center<\/p>\n<p>Brooklyn<\/p>\n<p>-1.8%<\/p>\n<p>Times Square<\/p>\n<p>Manhattan<\/p>\n<p>-1.7%<\/p>\n<p>Grand Central<\/p>\n<p>Manhattan<\/p>\n<p>-1.1%<\/p>\n<p>Union Square<\/p>\n<p>Manhattan<\/p>\n<p>-1.0%<\/p>\n","protected":false},"excerpt":{"rendered":"On a sweltering August afternoon or in the teeth of a winter storm, New York City subway riders&hellip;\n","protected":false},"author":2,"featured_media":68485,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[9,11,10,278,283,81781],"class_list":{"0":"post-206248","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-new-york","8":"tag-new-york","9":"tag-new-york-headlines","10":"tag-new-york-news","11":"tag-newswise","12":"tag-nyu-tandon-school-of-engineering","13":"tag-subwaynew-york-cityextreme-weatherrainheat"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/posts\/206248","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/comments?post=206248"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/posts\/206248\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/media\/68485"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/media?parent=206248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/categories?post=206248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-ny\/wp-json\/wp\/v2\/tags?post=206248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}