The Effects of Realistic Irrigation on the Great Plains Low-Level Jet

Low-level jets (LLJs) are relatively fast moving streams of air that form in the lower troposphere and are a common phenomenon across the Great Plains. Southerly LLJs over the Great Plains play an important role in northward moisture transport as well as initiation and sustainment of nocturnal convection in the spring and summer. Because processes within the planetary boundary layer (PBL) contribute to the development of LLJs, alterations to surface moisture and energy fluxes influence PBL development and thus LLJs. One important anthropogenic process that has been shown to affect the surface energy budget is irrigation. In this study, we investigate the effects of irrigation on LLJ development across the Great Plains by incorporating a dynamic and realistic irrigation scheme into the Weather Research and Forecasting (WRF) model. This scheme is specifically calibrated for the real-world irrigation practice over southern Great Plains in terms of irrigation water use. Two WRF simulations were conducted with and without the irrigation scheme over the exceptionally dry summer of 2012 over the Great Plains. Irrigation is expected to significantly alter surface energy partitioning and thus PBL evolution over irrigated regions during the dry summer. The results show changes to LLJ features both over and downstream of the most heavily irrigated regions in the Great Plains. At the surface the mean temperature across the central United States had increased by about 1 °C with irrigation. There were statistically significant increases to LLJ speeds in the irrigated simulations of just under 2 m/s. Changes to the mean jet core height on the order of 50 m were also simulated. The overall frequency of jet occurrences increased over the irrigated regions by 5-10%. These changes are weaker than what had been reported in earlier studies based on simple assumptions to represent irrigation, which highlights the importance and necessity to represent human activity more accurately in modeling studies.