Kucharik, C.J. and S.P. Serbin.  Climate effects on Wisconsin Corn and Soybean Yields.  Submitted to Agricultural and Forest Meteorology, Feb 2008.

Abstract
 
We combined county level USDA corn and soybean yield data with a gridded 8km daily climate dataset of maximum and minimum temperatures and precipitation across Wisconsin and used regression modeling to study the relationships between monthly average meteorological variables and yield anomalies for the 1950 to 2006 time period. Across southern and western geographic regions, corn yield variability was most influenced (ranked by R2 values) by July maximum temperatures and July precipitation whereas across the northeast, daily high temperatures in September impacted corn yield variability the most. In contrast, soybeans were most affected by precipitation in July and August over the west central and southeast, and by minimum daytime temperatures during May in counties close to Lake Michigan. Corn and soybeans experienced optimal growing conditions contributing to higher than average yields when summertime average high temperatures were in a small range (3 to 4ºC). Small increases in average daily high temperatures during July and August (e.g., 2-4ºC), which are on the same order of magnitude that is projected under future warming scenarios with climate models, were correlated with annual yields that were 10 to 30% lower than the expected, average values.  Surprisingly, summertime precipitation anomalies of +50% translated into only very small increases in corn and soybean yields of 8% and 11%, respectively.  Overall, crop yields were generally favored by cooler than average daytime high temperatures in August, and above normal temperatures in September. Our results suggested that because these crops responded differently to seasonal weather in Wisconsin and the actual responses varied spatially, crop productivity responses to climate and management changes would likely vary spatially, particularly in a north-south gradient across the state.