Weather Data: Virtual, In-Field, or Regional Network—Does It Matter?
Which data source is better?
In the world of specialty crops, there is disagreement on how well weather-driven insect, disease, and frost prediction models actually perform. Dr. Dave Brown, former director of Washington State University’s AgWeatherNet spent years comparing different weather data sources and how those data affect the accuracy of common environmental models used by orchard growers. In this 20-minute webinar, he shares the surprising things he learned.
Decrease chances of crop damage with one simple practice
Find out how you can increase the accuracy of your predictive models and decrease frost, insect, and disease incidents by doing just one thing differently—improving the quality of your weather data. Discover:
- Microclimates: what are the conditions like inside a crop canopy versus outside?
- Virtual data vs. weather station data: Which is better?
- How do site-specific weather data vs. regional network data compare?
- How much does a small decrease in data quality affect the accuracy of your models?
- What’s the value of in-orchard measurements?
- What are some best practices for higher data quality?
For 20 years as a faculty member at Montana State University and Washington State University (WSU) Dr. Dave Brown pursued research on soil sensors, spatial data science, and digital agriculture. At both universities, he served in many leadership roles for major research projects, academic programs, and most recently as Director of the WSU AgWeatherNet program. In this capacity, Dr. Brown hired and supervised a team of meteorologists who pursued research and extension activities focused on evaluating and improving the quality of weather data used for agricultural decisions.