2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

摘要

Most land surface hydrological models (LSHMs) consider land surface processes(e.g. soil–plant–atmosphere interactions, lateral water flows, snow andice) in a spatially detailed manner. The atmosphere is considered asexogenous driver, neglecting feedbacks between the land surface and theatmosphere. On the other hand, regional climate models (RCMs) generallysimulate land surface processes through coarse descriptions and spatialscales but include land–atmosphere interactions. What is the impact of thedifferently applied model physics and spatial resolution of LSHMs on theperformance of RCMs? What feedback effects are induced by different landsurface models? This study analyses the impact of replacing the land surfacemodule (LSM) within an RCM with a high resolution LSHM.A 2-way coupling approach was applied using the LSHM PROMET(1 × 1 km2)and the atmospheric part of the RCM MM5 (45 × 45 km2).The scaling interface SCALMET is used for down- and upscalingthe linear and non-linear fluxes between the model scales.The change in the atmospheric response by MM5 using the LSHM is analysed, andits quality is compared to observations of temperature and precipitation for a4 yr period from 1996 to 1999 for the Upper Danube catchment. Bysubstituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses whencompared to measurements from 277 meteorological weather stations within theUpper Danube catchment. The mean annual bias was improved from ?0.85 to?0.13 K. In particular, the improved afternoon heating from May to Septemberis caused by increased sensible heat flux and decreased latent heat flux aswell as more incoming solar radiation in the fully coupled PROMET/MM5 incomparison to the NOAH/MM5 simulation. Triggered by the LSM replacement,precipitation overall is reduced; however simulated precipitation amountsare still of high uncertainty, both spatially and temporally. Thedistribution of precipitation follows the coarse topography representationin MM5, resulting in a spatial shift of maximum precipitation northwards ofthe Alps. Consequently, simulation of river runoff inherits precipitationbiases from MM5. However, by comparing the water balance, the bias of annualaverage runoff was improved from 21.2% (NOAH/MM5) to 4.4%(PROMET/MM5) when compared to measurements at the outlet gauge of theUpper Danube watershed in Achleiten.