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The development of spatial weather and climate data and web-based access tools for improved agricultural risk management

TitleThe development of spatial weather and climate data and web-based access tools for improved agricultural risk management
Publication TypeConference Paper
Year of Publication2011
AuthorsDaly, C., C. M. Pancake, and K. Bryant
Conference NameProceedings of American Meteorological Society Applied Climatology Conference
Date Published07/2011
Abstract

Crop insurance is a major industry in the U.S., sold and delivered by private insurance companies in collaboration with the USDA Risk Management Agency (RMA). Currently, federal crop insurance programs cover about $90 billion in crop value. These programs help farmers insure primarily against natural disasters and weather events, such as drought, excessive moisture, heat, cold, and hail, which can partially or totally destroy crops. In an effort to expedite the claims process and save taxpayer money, the RMA has partnered with Oregon State University to provide high-quality spatial weather and climate data for use in substantiating weather events and producer claims. These data sets will also help the RMA determine risk levels more accurately, improving their underwriting capability. With RMA support, PRISM is now being operated on a daily basis, producing grids of precipitation and minimum, maximum, and mean temperature for the conterminous US at 800-m resolution. For each variable, an initial map is produced within 24 hours of the end of the day. The daily map is updated approximately 4 days later, then monthly for the next six months, as additional station data are added and QC is performed. At the same time, an historical time series of daily grids is being developed to allow long-term climatologies to be constructed. Monthly time-step products are also being developed, and are the initial focus for drought and excessive moisture claims. Historical data will provide an important long-term context, i.e., what is the likelihood of a condition occurring? Is it truly unusual, or well within the expected range of events? This is done by ranking the value of a variable for a given time period, (e.g., a day or month) within the 30-year normal period, or within the most recent ten years. A plain-English interpretation of the ranking is assigned, such as “typical,” “dry,” “unusually dry,” or “unusually wet.” A prototype, web-based spatial weather and climate portal is now online, and currently accessible by RMA personnel. The portal is designed to provide a simple, intuitive access point for these complex data sets. The user can view an assessment of current conditions or data for an historical time period, and determine how these conditions relate to long-term, climatic distributions. The user can also ask for a dynamically-produced report with text, tables, and figures describing conditions during a selected period of time; the initial reporting focus is on claims of prevented planting due to excessive moisture.