The quantity, type, and condition of vegetation strongly influence the fluxes of energy, momentum, and moisture in the atmospheric boundary layer. Documented studies highlight that mesoscale areas of vegetation can alter the environment for storm initiation and development. However, these studies are somewhat limited in their real-world applicability. Past observational studies have focused on specific events (i.e., case studies), relatively short time periods, or small regions. Past numerical studies have modeled highly idealized simulations or have lacked an extended set of regional observations for model initialization and verification. In all cases, the authors have acknowledged these shortcomings and attribute the limitations to a lack of long-term, mesoscale observations across a large area. The purpose of the current study is twofold: (1) to examine the impacts of Oklahoma’s winter wheat crop on the mesoscale environment and (2) to offset the limitations of past studies by employing surface data from the Oklahoma Mesonet.

Winter wheat, which accounts for about three-fourths of U.S. wheat production, is sown in the fall and harvested in the late spring or early summer. During early spring, the mature wheat crop forms a swath about 150 km wide that extends from southwest Oklahoma into north central Oklahoma and southern Kansas. On either side of this band is sparse or dormant vegetation, especially in extreme western Oklahoma and the Panhandle. In the late spring or early summer, wheat is harvested and previously dormant grassland has grown, resulting in a band of short stubble and bare soil surrounded by mature prairie grasses. Given these conditions and the extensive set of near-surface measurements from its Mesonet, Oklahoma is an optimal real-world environment to examine mesoscale vegetative influences on the atmosphere.

Evidence that Oklahoma’s winter wheat crop modifies the surface layer has been noted by scientists at the Oklahoma Climatological Survey since 1996. This presentation will document monthly and daily anomalies identified across Oklahoma’s winter wheat belt using data from the Oklahoma Mesonet.