Simulation of the hydrological cycle over Europe: Model validation and impacts of increasing greenhouse gases

Citation
K. Arpe et E. Roeckner, Simulation of the hydrological cycle over Europe: Model validation and impacts of increasing greenhouse gases, ADV WATER R, 23(2), 1999, pp. 105-119
Citations number
25
Categorie Soggetti
Civil Engineering
Journal title
ADVANCES IN WATER RESOURCES
ISSN journal
03091708 → ACNP
Volume
23
Issue
2
Year of publication
1999
Pages
105 - 119
Database
ISI
SICI code
0309-1708(19991011)23:2<105:SOTHCO>2.0.ZU;2-V
Abstract
Different methods of estimating precipitation area means, based on observat ions, are compared with each other to investigate their usefulness for mode l validation. For the applications relevant to this study the ECMWF reanaly ses provide a good and comprehensive data set for validation. The uncertain ties of precipitation analyses, based on observed precipitation or from num erical weather forecasting schemes, are generally in the range of 20% but r egionally much larger. The MPI atmospheric general circulation model is abl e to reproduce long term means of the main features of the hydrological cyc le within the range of uncertainty of observational data, even for relative ly small areas such as the Rhine river basin. Simulations with the MPI coup led general circulation model, assuming a further increase of anthropogenic greenhouse gases, show clear trends in temperature and precipitation for t he next century which would have significant implications for human activit y, e.g. a further increase of the sea level of the Caspian Sea and less wat er in the Rhine and the Danube. We have gained confidence in these results because trends in the temperature and precipitation in the coupled model si mulations up to the present are partly confirmed by an atmospheric model si mulation forced with observed SSTs and by observational data. We gained fur ther confidence because the simulations with the same coupled model but usi ng constant greenhouse gases do not show such trends. However, doubts arise from the fact that these trends are strong where the systematic errors of the model are large. (C) 1999 Elsevier Science Ltd. All rights reserved.