Original paper

Influence of monthly varying vegetation on the simulated climate in Europe

Rechid, Diana; Jacob, Daniela

Meteorologische Zeitschrift Vol. 15 No. 1 (2006), p. 99 - 116

published: Feb 27, 2006

DOI: 10.1127/0941-2948/2006/0091

BibTeX file

O

Open Access (paper may be downloaded free of charge)

Download paper for free

Abstract

In this study the regional climate model of the German Max-Planck-Institute for Meteorology (REMO) is used to analyse the effect of monthly varying vegetation on the simulated climate in Europe. For this investigation the annual cycle of vegetation is implemented in the land surface parameterization scheme of REMO. As input data source a new global dataset of land surface parameters is used. It contains monthly varying vegetation parameter values for leaf area index, fractional vegetation cover and background surface albedo. This dataset is adapted to both standard REMO model domains at 0.5 degree and 0.l6 degree horizontal resolution focusing Europe. For both resolutions present-day climate simulations are performed to examine the sensitivity of REMO to the modified vegetation parameterization. The simulation results are compared to corresponding reference simulations where vegetation parameter values are held constant in time. A validation is done by the comparison of the model results with several gridded observational datasets. A significant influence of monthly varying vegetation on the regional climate can be demonstrated. Vertical surface fluxes, near surface temperature and precipitation are strongly affected. The temporal analysis of the results reveals that the vegetation effect on the simulated climate occurs mainly in the summer season. In general, the simulated near-surface climate becomes cooler and wetter during the growing season. Concerning the spatial resolution, main effects can be detected in eastern Europe and the Hungarian lowlands. In these regions the more realistic vegetation treatment improves the simulated mean annual cycles of 2 m temperature and precipitation with respect to the observations.