@conference {JRN54919,
	title = {Toward Accessible, Discoverable, and Usable Crop Insurance Data: Multi-scale Analysis and Visualization of Cause of Loss},
	booktitle = {16th Annual Climate Prediction Applications Science Workshop (CPASW)},
	year = {2018},
	month = {05/2018},
	publisher = {16th Annual Climate Prediction Applications Science Workshop (CPASW)},
	organization = {16th Annual Climate Prediction Applications Science Workshop (CPASW)},
	address = {Fargo, ND},
	abstract = {<p>The synthesis and analysis of existing {\textquoteleft}big data{\textquoteright} can increase the overall collective value and yield additional insight of such knowledge. The creation of the U.S. Department of Agriculture (USDA) Climate Hub network prioritizes this with information synthesis and tool development as tangible outputs. The Hubs{\textquoteright} mission is to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this, Hubs work across USDA agencies to synthesize existing information to meet the needs of our ultimate stakeholders - farmers, ranchers, and land managers. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program and works with private insurance companies. RMA has collected annual cause of loss data since the mid-1900s with monthly data beginning in 1989. These data describe the reason for loss (e.g., drought, wind, irrigation failure), indemnity amount (i.e., total cost of loss), as well as relevant spatio-temporal information (i.e., state, county, year, month). We describe an initial retrospective analysis at multiple spatial and temporal scales over the United States. Drought and excess moisture were the top two causes of loss since 2001, and were responsible for over 70\% of nationwide climate-related crop loss payments. Regional differences in top causes of loss demonstrate the complex interactions of biophysical, climatic, socio-economic, and geo-political factors. Causes of loss over time show distinct trends as a function of major weather disasters and long-term climate events, such as drought. A web-based tool was then developed to deliver these crop insurance data to our partners and stakeholders for increased accessibility, discoverability, and usability. Ultimately, we envision the project supporting land management decisions and ecosystem resilience.</p>
},
	author = {J.T. Reyes and Andrew Eischens and Shilts, Mark and Jebediah C. Williamson and Emile H. Elias}
}
