Extended Abstract (336K)JP4.3
Hydrological variability and trends in global reanalyses
Junye Chen, Univ. of Maryland/ESSIC & NASA/GSFC/GMAO, Greenbelt, MD; and M. G. Bosilovich
A reanalysis is an integration of historical observations and model simulations using data assimilation techniques. Ideally, a long term reanalysis should provide an accurate and comprehensive reconstruction of the history of the climate change. But because of changes of the observation systems and the possible biases in the model and observations, the long term climate variation in the reanalysis data could be contaminated by artificial signals. In this study, the long term variations in the hydrological fields from the existing reanalyses and independent observations are investigated and intercompared. It is found that the hydrological trends can be very different in different datasets. These differences can be attributed to the different model/observation biases and the different assimilated observational data. The hydrological trends based on more recent reanalyses in which more moisture data are assimilated are not necessarily more accurate than those derived from earlier reanalyses with less moisture data assimilated, because of the changes of observation systems and no moisture conservation constraint in the reanalysis system. The consequent energy budgets and large-scale circulation variations are also addressed.
Joint Poster Session 4, Joint Poster: Climate & Extremes, Linking Weather and Climate (Joint with Second Symposium on Policy and Socio-economic Research, Symposium on Connections Between Mesoscale Processes and Climate Variability, 19th Conference on Climate Variability and Change, and Climate Change Manifested by Changes in Weather)
Wednesday, 17 January 2007, 2:30 PM-4:00 PM, Exhibit Hall C
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