Assessment of Noah land surface model with various runoff parameterizations over a Tibetan river

Abstract

Runoff parameterizations currently adopted by the (i) Noah‐MP model, (ii) Community Land Model (CLM), and (iii) CLM with variable infiltration capacity hydrology (CLM‐VIC) are incorporated into the structure of Noah land surface model, and the impact of these parameterizations on the runoff simulations is investigated for a Tibetan river. Four numerical experiments are conducted with the default Noah and three aforementioned runoff parameterizations. Each experiment is forced with the same set of atmospheric forcing, vegetation, and soil parameters. In addition, the Community Earth System Model database provides the maximum surface saturated area parameter for the Noah‐MP and CLM parameterizations. A single‐year recurrent spin‐up is adopted for the initialization of each model run to achieve equilibrium states. Comparison with discharge measurements shows that each runoff parameterization produces significant differences in the separation of total runoff into surface and subsurface components and that the soil water storage‐based parameterizations (Noah and CLM‐VIC) outperform the groundwater table‐based parameterizations (Noah‐MP and CLM) for the seasonally frozen and high‐altitude Tibetan river. A parameter sensitivity experiment illustrates that this underperformance of the groundwater table‐based parameterizations cannot be resolved through calibration. Further analyses demonstrate that the simulations of other surface water and energy budget components are insensitive to the selected runoff parameterizations, due to the strong control of the atmosphere on simulated land surface fluxes induced by the diurnal dependence of the roughness length for heat transfer and the large water retention capacity of the highly organic top soils over the plateau.

High‐Resolution Land Surface Modeling of Hydrological Changes Over the Sanjiangyuan Region in the Eastern Tibetan Plateau: 1. Model Development and Evaluation

“…The NSE values range from 0.70 to 0.89 at Yellow River stations, which are better than previous works where NSE values range from 0.49 to 0.85 based on GLDAS1/Variable Infiltration Capacity simulations (Cuo et al, 2013) and 0.31 to 0.89 based on GLDAS1/Noah simulations (Zheng et al, 2017). Bai et al (2016) also evaluated streamflow simulations of GLDAS1 over the TP, and their results showed that Kling-Gupta efficiency values vary from À0.75 to 0.09 at the TNH and ZMD stations, which are much lower than those from CSSPv2 simulations (Table 1).…”

“…For runoff generation, Zheng et al () compared four different schemes over upper Yellow River in the TP and found soil water storage‐based runoff parameterizations outperformed water table‐based runoff schemes for the seasonally frozen and high‐altitude rivers. Thus, we incorporated the Variable Infiltration Capacity (Liang et al, ) runoff parameterization into CSSP following Oleson et al ().…”

Assessment and Reduction of the Physical Parameterization Uncertainty for Noah‐MP Land Surface Model

“…precipitation for the period 1979-2013. CMFD has been widely employed for land surface modeling over China (Chen et al, 2011;Leng et al, 2015;Liu & Xie, 2013;Xue et al, 2013;Zheng et al, 2017).…”

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

“…A six-year-long (2009-2014) experiment was created using version 3.6.1 of the WRF model [42] and the WRFDA data assimilation [43][44][45]. The experiment was started on 1 January 2009; however, that year was used only as a spin-up for the soil system in the model, and it is not included in this paper as is typically done in other literature [46,47]. The WRF model was nested inside ERA-Interim [48].…”