UC Irvine

The Labrador Sea is an important deep water formation site where a large fraction of the

ocean's deep waters had their last contact with the atmosphere. Consequently, quantifying the ventilation of the Labrador Sea is crucial for understanding the global ocean circulation. In this study, I use yearly hydrographic measurements of CFC-11 and CFC-12 conducted along WOCE repeat section AR7W from 1991 to 2009. I present improvements to previous application of Bayesian evidence framework to 3-dimensional interpolation of CFC-11, CFC-12, temperature and salinity data. The Bayesian evidence framework is also used to infer the Labrador Sea's climatological and interannual transit-time distribution (TTD) with a maximum entropy deconvolution method. We present improvements to the ventilation problem to allow for measurement errors and to better quantify the uncertainty in the estimated TTDs. These improvements include the introduction of an intrinsic correlation function to explicitly take into account correlations in adjacent portions of the TTD and the choice of hyperparameters in our model. Our results provide a baseline from which changes in the

ventilation of the Labrador Sea can be quantified.