Neglect of irrigation Effects accounts for dry-warm bias in climate model over the Central United States

 

Authors

Yun Qian — Pacific Northwest National Laboratory
Zhao Yang — Pacific Northwest National Laboratory
Ying Liu — Pacific Northwest National Laboratory
William I. Gustafson — Pacific Northwest National Laboratory
Larry Berg — Pacific Northwest National Laboratory
Zhe Feng — Pacific Northwest National Laboratory
Maoyi Huang — National Oceanic and Atmospheric Administration (NOAA)
Ben Yang — Pacific Northwest National Laboratory

Category

Boundary layer structure, including land-atmosphere interactions and turbulence

Description

In spite of continuing improvements in the representation of physical processes and the unrelenting increase in spatial resolution, many climate models still suffer from persistent biases in a number of key variables. One particular bias that is common in a vast number of weather forecast and climate models is a too warm and too dry over the central US. Irrigation, by artificially adding water over pasture or farm land when needed, perturbs the surface water and energy budgets and could possibly modulate local to regional atmospheric processes and land-atmosphere interactions. Irrigation effects, however, are complicated by the complex multi-scale interactions between soil moisture, land-surface heterogeneity, plant phenology and physiology, large scale as well as local secondary circulations. In this study we have conducted convection-permitting simulations with 4-km grid spacing for multiple growing seasons over the Contiguous United States, based on the Weather Research and Forecasting (WRF) model coupled with an operational-like irrigation scheme within the Noah land surface model. Dynamic Recycling Model (DRM) is employed to quantify the impact of irrigation on water budget and precipitation recycling ratio over each irrigated region. The results show that irrigation increases soil moisture, leading to increases in the surface evapotranspiration and precipitation recycling ratio but decreases in the sensible heat and surface temperature. There is an irrigation-induced decrease in both the lifting condensation level (LCL) and mixed-layer depth. The decrease in LCL is larger than the decrease in mixed-layer depth, suggesting an increasing probability of shallow clouds. We also find that including irrigation reduces model dry bias in warm season precipitation contributed by the mesoscale convective systems (MCS) and improves the precipitation diurnal cycle associated with the MCS propagation over Southern Great Plains. We suggest the neglect ion of irrigation effects may account for the well-known warming bias over central US in global climate models. The results demonstrate the importance of irrigation parameterization for Earth system modeling and improve the process-level understanding on the role of human activity in modulating Land–Air–Cloud Interactions.