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Evaluation of the hydrological cycle in the ECHAM5 model

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Hagemann,  S.
Terrestrial Hydrology, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Arpe,  K.
The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Roeckner,  E.
Climate Modelling, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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JClim19-16-3810.pdf
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Citation

Hagemann, S., Arpe, K., & Roeckner, E. (2006). Evaluation of the hydrological cycle in the ECHAM5 model. Journal of Climate, 19, 3810-3827. doi:10.1175/JCLI3831.1.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0011-FD68-3
Abstract
This study investigates the impact of model resolution on the hydrological cycle in a suite of model simulations using a new version of the Max Planck Institute for Meteorology atmospheric general circulation model (AGCM). Special attention is paid to the evaluation of precipitation on the regional scale by comparing model simulations with observational data in a number of catchments representing the major river systems on the earth in different climate zones. It is found that an increased vertical resolution, from 19 to 31 atmospheric layers, has a beneficial effect on simulated precipitation with respect to both the annual mean and the annual cycle. On the other hand, the influence of increased horizontal resolution, from T63 to T106, is comparatively small. Most of the improvements at higher vertical resolution, on the scale of a catchment, are due to large-scale moisture transport, whereas the impact of local water recycling through evapotranspiration is somewhat smaller. At high horizontal and vertical resolution (T106L31) the model captures most features of the observed hydrological cycle over land, and also the local and remote precipitation response to El Niño–Southern Oscillation (ENSO) events.

Major deficiencies are the overestimation of precipitation over the oceans, especially at higher vertical resolution, along steep mountain slopes and during the Asian summer monsoon season, whereas a dry bias exists over Australia. In addition, the model fails to reproduce the observed precipitation response to ENSO variability in the Indian Ocean and Africa. This might be related to missing coupled air–sea feedbacks in an AGCM forced with observed sea surface temperatures.