Stronger correlation in the model relative to observations is expected because of the reduced variability. Despite the low signal to noise ratio, the ocean buoy data may still have the potential to provide some constraint on KPP parameters, however it may be important to include other constraints in the cost function, in addition to correlation. Alternatively, more nuanced approaches to working with

the correlation metric might yield a stronger signal to noise ratio. We have seen that certain parameters have spatially-varying sensitivity across the equatorial Pacific, e.g. Ri0 ( Fig. 12) because they relate to well-understood FDA approval PARP inhibitor processes of spatially-varying importance. However, our method of summing costs across the entire domain reduces signal in the sensitive regions by combining it with the costs from the insensitive regions. A regionally-specific approach, different for each parameter, could potentially be used ( Mu and Jackson, 2004). The analysis could also be confined to buoys where

the mismatch between modeled and observed τ is smallest, since errors in τ correlate strongly with errors in τ-SST correlation (not shown). Finally, including more wind products, perhaps scatterometer data that has not been blended with reanalysis, could PD-1/PD-L1 phosphorylation potentially reduce the noise in forcing. This work was funded by a Grant from The King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. MITgcm modeling was conducted by Sarah Zedler1,2 and Ibrahim Hoteit.1

Fengchao Yao1 provided a preliminary investigation into correlation in the TAO/TRITON array in cooperation with Charles Jackson.2 1King Abdullah University of Science and Technology, Saudi Arabia. 2Institute for Geophysics, The University of Texas at Austin, USA. “
“The oceans play a critical role in the global carbon cycle. More than 90% of the active non-geological carbon pool resides in the oceans (Kaufman et al., 1998). Orotidine 5′-phosphate decarboxylase Estimates of global primary production suggest that the oceans contribute about half (Field et al., 1998). One quarter (Le Quéré et al., 2010) of the carbon emitted by anthropogenic sources is thought to be sequestered in the oceans, annually. Understanding the role of the ocean in the global carbon cycle is a driving question in modern Earth science. It requires foremost a geographically-distributed, well-maintained observational capability. We are fortunate that such a capability exists or is in development, and that global data sets of ocean carbon inventories (Key et al., 2004), partial pressure of CO2 (Takahashi et al., 2006 and Takahashi et al., 2009) and ocean-atmospheric exchange (Takahashi et al., 2006 and Takahashi et al., 2009) are publicly available.