Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions

Numerical 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

Regional Actual Evapotranspiration Estimation with Land and Meteorological Variables Derived from Multi-Source Satellite Data

Evapotranspiration (ET) is one of the components in the water cycle and the surface energy balance systems. It is fundamental information for agriculture, water resource management, and climate change research. This study presents a scheme for regional actual evapotranspiration estimation using multi-source satellite data to compute key land and meteorological variables characterizing land surface, soil, vegetation, and the atmospheric boundary layer. The algorithms are validated using ground observations from the Heihe River Basin of northwest China. Monthly data estimates at a resolution of 1 km from the proposed algorithms compared well with ground observation data, with a root mean square error (RMSE) of 0.80 mm and a mean relative error (MRE) of −7.11%. The overall deviation between the average yearly ET derived from the proposed algorithms and ground-based water balance measurements was 9.44% for a small watershed and 1% for the entire basin. This study demonstrates that both accuracy and spatial depiction of actual evapotranspiration estimation can be significantly improved by using multi-source satellite data to measure the required land surface and meteorological variables. This reduces dependence on spatial interpolation of ground-derived meteorological variables which can be problematic, especially in data-sparse regions, and allows the production of region-wide ET datasets