The role of land-atmosphere interactions in climate predictability is well-recognized at subseasonal-to-seasonal timescales. To an observer, land-atmosphere interactions may become most readily observable during a dry-down or synoptically quiescent postfrontal event sequence, or during leaf-out and snow-on transitions. However, prior studies have underscored the significance of land-atmosphere interactions in the context of their non-local effects. For example, at mesoscale and circumglobal scales, land-atmosphere interactions in the Great Plains and East Asia, respectively, impact the development and character of Great Plains low-level jets, which drive precipitation and wind variability. Coarse spatiotemporal resolutions, parameterized convection, fixed vegetation, single-layer snow, and crude land surface anomaly prescriptions limit the realism of earlier modeling efforts aimed at quantifying impacts of land-atmosphere interactions. Our convection-permitting WRF v4.3.3 simulations with Noah-MP dynamic vegetation and nudged multi-layer snow and soil moisture overcome these limitations. Here, we apply them over CONUS to investigate the extent to which snow and soil moisture anomalies impact the Great Plains low-level jet and hydroclimate. We examine the aggregation of impacts from March-September at regional-to-continental and diurnal-to-monthly scales, specifically in terms of the terrestrial and atmospheric water budgets, cross-Plains wind and temperature profiles, low-level jet tracks, and tropical storm event suppression. By simulating the anomalously wet 2019 year both with and without snow and soil moisture nudged to the anomalously dry 2011 year, we assert that the results approximate the maximum extent of naturally occurring land-atmosphere interactions on central U.S. interannual climate variability.