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United States Department of Agriculture

Agricultural Research Service

Research Project: INTEGRATION OF CLIMATE VARIABILITY AND FORECASTS INTO RISK-BASED MANAGEMENT TOOLS FOR AGRICULTURE PRODUCTION AND RESOURCE CONSERVATION Title: Working from a faint signal towards climate-informed decision support

Author
item Schneider, Jeanne

Submitted to: USDA-CSREES National Water Quality Conference
Publication Type: Abstract Only
Publication Acceptance Date: January 25, 2009
Publication Date: February 8, 2009
Citation: Schneider, J.M. 2009. Working from a faint signal towards climate-informed decision support[abstract]. USDA-CSREES National Water Quality Conference, Feb. 8-12, 2009, St. Louis, MO. Available: http://www.usawaterquality.org/conferences/2009/abstract_index.html#S

Interpretive Summary: Abstract only.

Technical Abstract: If we have reliable seasonal climate forecasts out to a year ahead, we should be able to incorporate that information and significantly improve our decision support tools for a wide range of agricultural and water resource applications. This opportunity is being realized in some key areas of the U.S., especially the Southeast where the ENSO impact on winter precipitation is strong and skillfully predicted. Unfortunately, for much of the contiguous U.S., and especially in the absence of strong ENSO events, the 3-month precipitation forecasts from NOAA/Climate Prediction Center and Columbia University’s International Research Institute for Climate and Society have close to zero skill by any measure. What should or could we do for locations where the ENSO signal is faint at any time, or any location during those periods when ENSO conditions are moderate or neutral? What do our application communities need to know that we might be able to tell them? Can we rethink standard 30-year climatologies to provide alternative climate-informed guidance? One possible approach will be presented, specifically related to the decision support needs of no-till farmers in northern Oklahoma, derived from decade-scale variations in precipitation.

Last Modified: 10/19/2014
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