Using GIS to Analyze New York’s Limited English Proficiency Communities and Improve Multilingual National Weather Service Operations

The United States is known as “The Great Melting Pot”, for the wide variety of communities, cultures and languages from around the world present in the country. This is especially true in the state of New York, home to over 19 million people. While this has many benefits, it also comes with challenges. In the state, approximately 2.5 million (or just over 12% of all) New York residents are considered to have Limited English Proficiency (LEP) (i.e., they speak English less than “very well”). This problem is recognized by leaders in New York, as high up as Attorney General Letitia James, stating that “the next severe weather event is a matter of when, not if. It is critical that this potentially lifesaving information be transmitted to the millions of New Yorkers — and Americans nationwide — who are not proficient in English.” However, knowledge of where these populations are located is quite limited. In the case of the National Weather Service (NWS), removing barriers to messaging is one of the most prevalent challenges in weather operations today. While the NWS translates some weather information from English to Spanish and Samoan, it does not cover all languages and the translation work is done manually. This paradigm leaves the NWS with a substantial service coverage gap. The NWS cannot accomplish its goal of a “Weather-Ready Nation” without understanding the communities they serve and how they utilize information to empower their response.
In our presentation, we will take a closer look at the linguistic representation of the NWS County Warning Areas (CWAs) of New York State in several languages, including but not limited to Spanish, Vietnamese, Mandarin, Tagalog, among others. Using methodologies in GIS, we explore fascinating spatial analysis of multilingual “hot spots” and note regions that are in need of further resources and support due to their higher vulnerability and underserved nature, caused by language barriers as well as other socioeconomic disadvantages. We will also show how the NWS can take advantage of this information for local NWS community engagement and outreach across the country.