Climate Dynamics

, Volume 48, Issue 3–4, pp 1309–1327 | Cite as

The impact of an extreme case of irrigation on the southeastern United States climate

  • Christopher Selman
  • Vasubandhu Misra


The impacts of irrigation on southeast United States diurnal climate are investigated using simulations from a regional climate model. An extreme case is assumed, wherein irrigation is set to 100 % of field capacity over the growing season of May through October. Irrigation is applied to the root zone layers of 10–40 and 40–100 cm soil layers only. It is found that in this regime there is a pronounced decrease in monthly averaged temperatures in irrigated regions across all months. In non-irrigated areas a slight warming is simulated. Diurnal maximum temperatures in irrigated areas warm, while diurnal minimum temperatures cool. The daytime warming is attributed to an increase in shortwave flux at the surface owing to diminished low cloud cover. Nighttime and daily mean cooling result as a consequence repartitioning of energy into latent heat flux over sensible heat flux, and of a higher net downward ground heat flux. Excess heat is transported into the deep soil layer, preventing a rapidly intensifying positive feedback loop. Both diurnal and monthly average precipitations are reduced over irrigated areas at a magnitude and spatial pattern similar to one another. Due to the excess moisture availability, evaporation is seen to increase, but this is nearly balanced by a corresponding reduction in sensible heat flux. Concomitant with additional moisture availability is an increase in both transient and stationary moisture flux convergences. However, despite the increase, there is a large-scale stabilization of the atmosphere stemming from a cooled surface.


Regional climate modeling Irrigation Diurnal climatology Diurnal Southeast United States Southeast US Regional model Agriculture Anthropogenic influences Anthropogenic Climate Climate change Regional Impact Southeast Model Parametrization 



This work was supported by Grants from NOAA (NA12OAR4310078, NA10OAR4310215, NA10OAR4320143) and USGS G13AC00408. All model integrations for this paper were done on the computational resourced provided by the Extreme Science and Engineering Discovery Environment (XSEDE) under TG-ATM120010.

Supplementary material

382_2016_3144_MOESM1_ESM.docx (235 kb)
Supplementary material 1 (DOCX 235 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeUSA
  2. 2.Center for Ocean-Atmospheric Prediction StudiesFlorida State UniversityTallahasseeUSA
  3. 3.Florida Climate InstituteFlorida State UniversityTallahasseeUSA

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