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  • Author or Editor: Thomas Rummler x
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Joel Arnault
,
Sven Wagner
,
Thomas Rummler
,
Benjamin Fersch
,
Jan Bliefernicht
,
Sabine Andresen
, and
Harald Kunstmann

Abstract

The analysis of land–atmosphere feedbacks requires detailed representation of land processes in atmospheric models. The focus here is on runoff–infiltration partitioning and resolved overland flow. In the standard version of WRF, runoff–infiltration partitioning is described as a purely vertical process. In WRF-Hydro, runoff is enhanced with lateral water flows. The study region is the Sissili catchment (12 800 km2) in West Africa, and the study period is from March 2003 to February 2004. The WRF setup here includes an outer and inner domain at 10- and 2-km resolution covering the West Africa and Sissili regions, respectively. In this WRF-Hydro setup, the inner domain is coupled with a subgrid at 500-m resolution to compute overland and river flow. Model results are compared with TRMM precipitation, model tree ensemble (MTE) evapotranspiration, Climate Change Initiative (CCI) soil moisture, CRU temperature, and streamflow observation. The role of runoff–infiltration partitioning and resolved overland flow on land–atmosphere feedbacks is addressed with a sensitivity analysis of WRF results to the runoff–infiltration partitioning parameter and a comparison between WRF and WRF-Hydro results, respectively. In the outer domain, precipitation is sensitive to runoff–infiltration partitioning at the scale of the Sissili area (~100 × 100 km2), but not of area A (500 × 2500 km2). In the inner domain, where precipitation patterns are mainly prescribed by lateral boundary conditions, sensitivity is small, but additionally resolved overland flow here clearly increases infiltration and evapotranspiration at the beginning of the wet season when soils are still dry. The WRF-Hydro setup presented here shows potential for joint atmospheric and terrestrial water balance studies and reproduces observed daily discharge with a Nash–Sutcliffe model efficiency coefficient of 0.43.

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Joël Arnault
,
Thomas Rummler
,
Florian Baur
,
Sebastian Lerch
,
Sven Wagner
,
Benjamin Fersch
,
Zhenyu Zhang
,
Noah Kerandi
,
Christian Keil
, and
Harald Kunstmann

Abstract

Precipitation is affected by soil moisture spatial variability. However, this variability is not well represented in atmospheric models that do not consider soil moisture transport as a three-dimensional process. This study investigates the sensitivity of precipitation to the uncertainty in the representation of terrestrial water flow. The tools used for this investigation are the Weather Research and Forecasting (WRF) Model and its hydrologically enhanced version, WRF-Hydro, applied over central Europe during April–October 2008. The model grid is convection permitting, with a horizontal spacing of 2.8 km. The WRF-Hydro subgrid employs a 280-m resolution to resolve lateral terrestrial water flow. A WRF/WRF-Hydro ensemble is constructed by modifying the parameter controlling the partitioning between surface runoff and infiltration and by varying the planetary boundary layer (PBL) scheme. This ensemble represents terrestrial water flow uncertainty originating from the consideration of resolved lateral flow, terrestrial water flow uncertainty in the vertical direction, and turbulence parameterization uncertainty. The uncertainty of terrestrial water flow noticeably increases the normalized ensemble spread of daily precipitation where topography is moderate, surface flux spatial variability is high, and the weather regime is dominated by local processes. The adjusted continuous ranked probability score shows that the PBL uncertainty improves the skill of an ensemble subset in reproducing daily precipitation from the E-OBS observational product by 16%–20%. In comparison to WRF, WRF-Hydro improves this skill by 0.4%–0.7%. The reproduction of observed daily discharge with Nash–Sutcliffe model efficiency coefficients generally above 0.3 demonstrates the potential of WRF-Hydro in hydrological science.

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