Abstract

The Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment (LIAISE) campaign examined the impact of anthropization on the water cycle in terms of land-atmosphere-hydrology interactions. The objective of this study is to assess the effects of irrigation on the atmosphere and on precipitation in WRF model simulations during the LIAISE Special Observation Period in July 2021 (LIAISE-2021 SOP). Comparisons between simulations and observations show better verification scores for air temperature, humidity and wind speed and direction when the model included the irrigation parameterization, improving the model warm and dry bias at 2 m over irrigated areas. Other changes found are the weakening of the sea breeze circulation and a more realistic surface energy partitioning representation, where the latent heat flux is prevailing over the sensible heat flux. The boundary layer height is lowered in the vicinity of irrigated areas, causing a decrease in the lifting condensation level and the level of free convection, which induce increases in convective available potential energy (CAPE) and convective inhibition (CIN).Precipitation differences between simulations become relevant for smaller areas, close to the irrigated land. When convection is parameterized, simulations including irrigation tend to produce a decrease in rainfall (negative feedback) while convection-permitting simulations produce an increase (positive feedback), although the latter underestimates substantially the observed precipitation field. In addition, irrigation activation decreases the areas exceeding moderate hourly precipitation intensities in all simulations. There is a local impact of irrigated land on model-resolved precipitation accumulations and intensities, although including the irrigation parameterization did not improve the representation of the observed precipitation field, as probably the precipitation systems during LIAISE-2021 SOP were mostly driven by larger scale perturbations or mesoscale systems, more than by local processes. Results reported here not only contribute to enhance our understanding of irrigation effects upon precipitation but also demonstrate the need to include irrigation parameterizations in numerical forecasts to overcome the biases found.This research has been funded by projects WISE-PreP (RTI2018-098693-B-C32), ARTEMIS (PID2021-124253OB-I00) and the Institute for Water Research (IdRA) of the University of Barcelona.

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