Insights on drought and long-term climatic trends: Retrospective analyses of RMA cause of loss data

TitleInsights on drought and long-term climatic trends: Retrospective analyses of RMA cause of loss data
Publication TypeConference Paper
Year of Publication2017
AuthorsReyes JJon T, Eischens A, Shilts M, Elias E, Steele R
Conference NameUniversity Council on Water Resources / National Institute of Water Resources Annual Conference
Date Published06/2017
PublisherUniversity Council on Water Resources / National Institute of Water Resources
Conference LocationFort Collins, CO
ARIS Log Number343472
Abstract

A modern trend among federal agencies, funding streams, and research projects involves the synthesis of existing data to increase the overall collective value and meaning of such knowledge. The creation of the U.S. Department of Agriculture (USDA) Climate Hubs follows this line of thought with information synthesis and tool development as tangible outputs of this new federal coordination network. The Hubs’ 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 stakeholders. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program and works with private insurance companies. The USDA also administers other programs for commodities not insured under the federal program such as for livestock and honey bees. 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), insurance plan code, as well as relevant spatio-temporal information (i.e. state, county, year, month).  The objective of this paper is to link climate information with cause of loss data to potentially shape the development of future RMA programs and provide regionally-relevant information to our stakeholders to effectively manage their lands. We describe an initial retrospective analysis at various spatial scales by land use/land cover, ecoregions, climate zones, and geopolitical boundaries. In addition, we link historical weather data (precipitation and temperature) with causes of loss at multiple time steps: monthly, annual, and decadal. Ultimately this analysis will convey county-level trends to support informed land management decisions and ecosystem resilience.