Detecting historical ocean climate variability
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While ocean observations of temperature and salinity extend back to the 19th century, their observation count, as well as geographical and vertical distributions all changed dramatically between successive decades. Similarly, atmospheric observations were unevenly distributed in space and time. This study explores the usefulness of past oceanic and atmospheric observing systems to detect extreme climate events through a set of observing system simulation experiments. In these experiments an initial simulation of the evolving ocean state during 1995-1998 (Nature Run) is sub-sampled using the same distribution of surface and subsurface observations as exists in successive decades. The result is a set of synthetic ocean observation re-samples of the massive mainly tropical/subtropical climate anomalies of the 1995-1998 years. These synthetic observation re-samples are then assimilated into a general circulation ocean model using a conventional assimilation scheme. In one set of experiments the model used in data assimilation is driven with climatological forcing to mimic the effects of poorly specified surface forcing. The results indicate that prior to the 1940s the historical observing network alone was only able to resolve limited aspects of tropical/subtropical variability. In contrast, by the 1960s the observing system was sufficient to resolve variability without additional wind information. In a second set of assimilation experiments surface meteorological forcing is improved to an extent consistent with meteorological error estimates for past decades. When this historical surface forcing is also included the results suggest that this extreme climate variability is reproducible even back to the early years of the 20th century. The paper concludes with a discussion of the implications of several simplifying assumptions used to obtain these optimistic results. Copyright 2012 by the American Geophysical Union.
author list (cited authors)
Carton, J. A., Seidel, H. F., & Giese, B. S.