Combined evaluation of MPI‐ESM land surface water and energy fluxes. (17th May 2013)

• Record Type: Journal Article
• Authors: Hagemann, Stefan; Loew, Alexander; Andersson, A.
• Is Part Of: Journal of advances in modeling earth systems. Volume 5:Number 2(2013:Jun.)
• Page Start: 259
• Page End: 286
• Publication Date: 2013-05-17
• Subjects: Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2012MS000173
• Languages: English
• ISSNs: 1942-2466

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>[1] To assess the robustness of projected changes of the hydrological cycle simulated by an Earth system model (ESM), it is fundamental to validate the ESM and to characterize its major deficits. As the hydrological cycle is closely coupled to the energy cycle, a common large‐scale evaluation of these fundamental components of the Earth system is highly beneficial, even though this has been rarely done up to now. Consequently, the purpose of the present study is the combined evaluation of land surface water and energy fluxes from the newest ESM version of the Max Planck Institute for Meteorology (MPI‐ESM), which was used to produce an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. With regard to energy fluxes, we especially make use of recent satellite data sets. Additionally, MPI‐ESM results are compared with CMIP3 results from the predecessor of MPI‐ESM, ECHAM5/MPIOM, as well as to results from the atmosphere/land part of MPI‐ESM (ECHAM6/JSBACH) forced by observed sea surface temperature (SST). Analyses focus on regions where notable differences occur between the two ESM versions as well as between the fully coupled and the uncoupled SST‐driven simulations. In general, our results show a considerable improvement of MPI‐ESM in simulating surface shortwave radiation fluxes. The precipitation of the fully coupled simulations notably differs from those of the SST‐forced simulations over a few river catchments. Over the Amazon catchment, the coupling to the ocean leads to a large negative precipitation bias, while for the Ganges/Brahmaputra, the coupling significantly improves the simulated precipitation.</p> </abstract>