Newswise — ALBANY, N.Y. (Sept. 3, 2024) — A new partnership between the New York State Mesonet at the University at Albany and New York State Integrated Pest Management Program (NYSIPM) at Cornell University is helping farmers and agricultural producers across the state optimize crop management.

NYSIPM’s Network for Environment and Weather Applications (NEWA), operated by Cornell, and the NYS Mesonet, operated by UAlbany, recently combined efforts to bring real-time, localized weather data and products to farmers and growers in every county of New York.

NEWA is a weather and pest management decision support system that leverages data from a network of weather stations to deliver accurate and precise short-term insect pest, plant disease, crop production risk forecasts. Growers use the data to make key decisions on issues like pest control, irrigation management and planting schedules.

NYS Mesonet is the nation’s most advanced and largest early warning weather detection network, designed to provide meteorological data, products and services that help save lives and property while building a smart weather economy.

Each of the Mesonet’s standard 127 stations, including 50 located at farms, orchards or vineyards, are equipped with automated sensors that measure weather information in real-time, such as temperature, humidity, wind speed and direction, pressure, precipitation, solar radiation, snow depth and soil information. The sites also have cameras that photograph current conditions.

“The collaboration between the New York State Integrated Pest Management Program at Cornell University, and our colleagues at the University at Albany, has effectively doubled the number of weather stations providing information to New York farmers, resulting in more accurate data in more areas of the state,” said Dan Olmstead, NYSIPM’s digital outreach and development coordinator.

“Localized weather information is critical for local farmers to remain competitive and profitable,” said Chris Thorncroft, NYS Mesonet executive director. “This collaboration between the Mesonet and Cornell’s Integrated Pest Management Program is distributing advanced real-time weather data to hundreds of farmers statewide to optimize pest management and maximize crop yields.”

Through the partnership, more than 1,200 registered NEWA users now have access to hyper-localized information from more than 285 combined weather stations, including those located in previously underserved, rural areas of the state.

Olmstead, who has overseen the NEWA platform for seven years, worked with Thorncroft, along with NYS Mesonet Director June Wang and Art Degaetano, director of the NOAA-funded Northeast Regional Climate Center at Cornell, to bring the NEWA/Mesonet partnership to fruition last spring.

“By assimilating Mesonet data with NEWA’s disease and pest management models, farmers now have access to more frequent and localized weather data and agriculture products,” said Wang. “I’m really excited to see how this partnership directly benefits farmers and other sectors across New York.”

The enhanced system’s capabilities were put to the test during a late-season frost in April. Data from NEWA and NYS Mesonet were used to generate summary statistics on the geographic extent and severity of the damage, helping growers and researchers understand the impact of frost events and access visualizations and site-specific data summaries for more streamlined crop insurance claims.

“This partnership equitably equips farmers with the tools and data needed to adapt to changing climate conditions by enhancing their ability to withstand extreme weather events,” Olmstead said. “Improved understanding of short-term forecasts of insect pest and plant disease pressure, crop production conditions, and adverse weather events helps farmers develop long-term strategies to mitigate risks.”

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Agriculture Climate Science Environmental Science
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Weather Climate Agriculture Farmers pest management Crops Agricultural weather data New York State Mesonet University at Albany Cornell University Climate Change
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