A51M-0245
Multi-criteria Evaluation of Discharge Simulation in Dynamic Global Vegetation Models
Friday, 18 December 2015
Poster Hall (Moscone South)
Hui Yang1, Shilong Piao1, Zhenzhong Zeng1, Philippe Ciais2, Yi Yin3, Pierre Friedlingstein4, Stephen Sitch5, Anders Ahlström6, Matthieu Guimberteau7, Chris Huntingford8, Sam Levis9, Peter E. Levy10, Mengtian Huang1, Yue Li1, Xiran Li1, Mark Lomas11, Philippe P Peylin12, Ben Poulter13, Nicolas Viovy3, Soenke Zaehle14, Ning Zeng15, Fang Zhao15 and Lei Wang16, (1)Peking University, Beijing, China, (2)CNRS, Paris Cedex 16, France, (3)LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette Cedex, France, (4)University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter, United Kingdom, (5)University of Exeter, Exeter, United Kingdom, (6)Stanford University, Stanford, CA, United States, (7)Institut Pierre Simon Laplace, Laboratoire d'Océanographie et du Climat: expérimentations et approches numériques (LOCEAN), Paris, France, (8)Centre for Ecology and Hydrology, Wallingford, United Kingdom, (9)National Center for Atmospheric Research, Boulder, CO, United States, (10)Center for Ecology and Hydrology Penicuik, Penicuik, United Kingdom, (11)University of Sheffield, Sheffield, United Kingdom, (12)CEA Saclay DSM / LSCE, Gif sur Yvette, France, (13)University of Montana, Missoula, MT, United States, (14)Max Planck Institute for Biogeochemistry, Jena, Germany, (15)University of Maryland College Park, College Park, MD, United States, (16)ITP Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Abstract:
In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modelled well in the low and mid latitudes, but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore the 30-year trend of discharge is also under-estimated. For the inter-annual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e. models account for 50% of observed inter-annual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change, but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modelling capability, a regional-weighted average of multi-model ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.
