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Abstract Land-use land-cover change affects weather and climate. This paper quantifies land–atmosphere interactions over irrigated and nonirrigated land uses during the Great Plains Irrigation Experiment (GRAINEX). Three coupling metrics were used to quantify land–atmosphere interactions as they relate to convection. They include the convective triggering potential (CTP), the low-level humidity index (HIlow), and the lifting condensation level (LCL) deficit. These metrics were calculated from the rawinsonde data obtained from the Integrated Sounding Systems (ISSs) for Rogers Farm and York Airport along with soundings launched from the three Doppler on Wheels (DOW) sites. Each metric was categorized by intensive observation period (IOP), cloud cover, and time of day. Results show that with higher CTP, lower HIlow, and lower LCL deficit, conditions were more favorable for convective development over irrigated land use. When metrics were grouped and analyzed by IOP, compared to nonirrigated land use, HIlowwas found to be lower for irrigated land use, suggesting favorable conditions for convective development. Furthermore, when metrics were grouped and analyzed by clear and nonclear days, CTP values were higher over irrigated cropland than nonirrigated land use. In addition, compared to nonirrigated land use, the LCL deficit during the peak growing season was lower over irrigated land use, suggesting a favorable condition for convection. It is found that with the transition from the early summer to the mid/peak summer and increased irrigation, the environment became more favorable for convective development over irrigated land use. Finally, it was found that regardless of background atmospheric conditions, irrigated land use provided a favorable environment for convective development.
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This content will become publicly available on June 22, 2027
Irrigation effects on downwind precipitation in different synoptic conditions: a study in the U.S. Central Great Plains
Abstract Irrigation modifies land–atmosphere interactions by altering surface fluxes, boundary-layer thermodynamics, and moisture transport, yet its influence on precipitation remains highly dependent on synoptic influence. Building on recent modeling studies that quantify irrigation impacts within irrigated regions, we investigate how irrigation affects precipitation and its thermodynamic and dynamical controls in downwind areas using convection-permitting WRF simulations. A wind-aligned composite framework is applied to isolate coherent flow-relative responses under three synoptic conditions: quiescent, transitional, and strong synoptic disturbance. Across all regimes, irrigation induces surface cooling, enhanced latent heat flux, and low-level moistening that is advected downwind, yet the precipitation response differs fundamentally across synoptic conditions. Critically, we find that the LFC–LCL deficit, which measures thermodynamic resistance to deep parcel ascent, is a key discriminating variable explaining why irrigation-induced CAPE enhancement under quiescent conditions fails to produce precipitation, while comparable or lesser thermodynamic instability under transitional forcing yields organized downwind rainfall enhancement. These results establish a robust and rigorous regime-dependent framework for understanding how large-scale irrigation modifies downwind hydroclimate. They demonstrate that irrigation can substantially enhance atmospheric instability and reduce thermodynamic resistance to deep parcel ascent, but its impact on precipitation depends on background synoptic conditions. Responses are maximized when irrigation-induced thermodynamic enhancements, including reductions in LFC − LCL deficit, are organized by synoptic-scale flow, highlighting the role of synoptic conditions in modulating land–atmosphere interaction and hydroclimate responses.
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- Award ID(s):
- 2414601
- PAR ID:
- 10698927
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- npj Climate and Atmospheric Science
- ISSN:
- 2397-3722
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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