Abstract

Abstract. A major challenge in the emerging research field of coupling of existing regional climate models (RCMs) and hydrology/land-surface models is the computational interaction between the models. Here we present results from a full two-way coupling of the HIRHAM RCM over a 4000 km × 2800 km domain at 11 km resolution and the combined MIKE SHE-SWET hydrology and land-surface models over the 2500 km2 Skjern River catchment. A total of 26 one-year runs were performed to assess the influence of the data transfer interval (DTI) between the two models and the internal HIRHAM model variability of 10 variables. DTI frequencies between 12 and 120 min were assessed, where the computational overhead was found to increase substantially with increasing exchange frequency. In terms of hourly and daily performance statistics the coupled model simulations performed less accurately than the uncoupled simulations, whereas for longer-term cumulative precipitation the opposite was found, especially for more frequent DTI rates. Four of six output variables from HIRHAM, precipitation, relative humidity, wind speed and air temperature, showed statistically significant improvements in root-mean-square error (RMSE) by reducing the DTI. For these four variables, the HIRHAM RMSE variability corresponded to approximately half of the influence from the DTI frequency and the variability resulted in a large spread in simulated precipitation. Conversely, DTI was found to have only a limited impact on the energy fluxes and discharge simulated by MIKE SHE.

Highlights

  • IntroductionSurface and subsurface processes has been performed in a broad range of studies over the years utilizing increasingly complex model codes

  • Combined modelling of atmospheric, surface and subsurface processes has been performed in a broad range of studies over the years utilizing increasingly complex model codes

  • The HIRHAM root-meansquare error (RMSE) variability corresponded to approximately half of the influence from the data transfer interval (DTI) frequency and the variability resulted in a large spread in simulated precipitation

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Summary

Introduction

Surface and subsurface processes has been performed in a broad range of studies over the years utilizing increasingly complex model codes. It is further argued that the combination of hydrology and vegetation processes may account for rising CO2 levels not simulated using hydrological models alone. Several studies deal with the influence of surface hydrology, vegetation and land use change on atmospheric processes. Zeng et al (2003) highlight the considerable influence of landsurface temperature and moisture heterogeneities on simulations of sensible (H ) and latent heat (LE) fluxes as well as the precipitation pattern, using the RegCM2 regional climate model (RCM). Of these, York et al (2002) use the CLASP II model with coupled aquifer–atmosphere processes for a single grid box to study the response of groundwater levels to climate forcing

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