Abstract
AbstractNumerical climate models have been upgraded by the improved description of terrestrial hydrological processes across different scales. The goal of this study is to explore the role of terrestrial hydrological processes on land–atmosphere interactions within the context of modeling uncertainties related to model physics parameterization. The models applied are the Weather Research and Forecasting (WRF) model and its coupled hydrological modeling system WRF-Hydro, which depicts the lateral terrestrial hydrological processes and further allows their feedback to the atmosphere. We conducted convection-permitting simulations (3 km) over the Heihe River Basin in Northwest China for the period 2008–2010, and particularly focused on its upper reach area of complex high mountains. In order to account for the modeling uncertainties associated with model physics parameterization, an ensemble of simulations is generated by varying the planetary boundary layer (PBL) schemes. We embedded the fully three-dimensional atmospheric water tagging method in both WRF and WRF-Hydro for quantifying the strength of land–atmosphere interactions. The impact of PBL parameterization on land–atmosphere interactions is evaluated through its direct effect on vertical mixing. Results suggest that enabled lateral terrestrial flow in WRF-Hydro distinctly increases soil moisture and evapotranspiration near the surface in the high mountains, thereby modifies the atmospheric condition regardless of the applied PBL scheme. The local precipitation recycling ratio in the study area increases from 1.52 to 1.9% due to the description of lateral terrestrial flow, and such positive feedback processes are irrespective of the modeling variability caused by PBL parameterizations. This study highlights the non-negligible contribution of lateral terrestrial flow to local precipitation recycling, indicating the potential of the fully coupled modeling in land–atmosphere interactions research.
Funder
Bundesministerium für Bildung und Forschung
Chinese Government Scholarship
Karlsruher Institut für Technologie (KIT)
Publisher
Springer Science and Business Media LLC
Cited by
15 articles.
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