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Using tracer observations to reduce the uncertainty of ocean diapycnal 3 mixing and climate – carbon cycle projections
| Content Provider | Semantic Scholar |
|---|---|
| Author | Schmittner, Andreas Keller, Klaus Matthews, Damon |
| Copyright Year | 2009 |
| Abstract | 6 [1] What is the uncertainty of climate–carbon cycle projections in response to 7 anthropogenic greenhouse gas emissions, and how can we reduce this uncertainty? We 8 address this question by quantifying the ability of available ocean tracer observations to 9 constrain the values of diapycnal diffusivity in the pelagic ocean (Kv), a key uncertain 10 parameter representing sub-grid-scale diapycnal (vertical) mixing in physical circulation 11 models. We show that model versions with weak mixing (i.e., low Kv) lead to higher 12 projections of atmospheric CO2 and larger global warming than do models with vigorous 13 mixing. Slower heat uptake and slower carbon uptake by the oceans contribute about 14 equally to the accelerated warming in the low-mixing models. A Bayesian data-model 15 fusion method is developed to quantify the likelihood of different structural and 16 parametric model choices given an array of observed 20th century ocean tracer 17 distributions. These spatially resolved observations provide strong limits on the upper 18 value of Kv, whereas global metrics used in previous studies, such as the historical 19 evolution of global average surface air temperature, global ocean heat uptake, or 20 atmospheric CO2 concentration, provide only poor constraints. We compare different 21 methods to quantify the probability of a particular diffusivity value given the 22 observational constraints. One-dimensional, globally horizontally averaged data result in 23 sharper probability density functions compared with the full 3-D fields. This perhaps 24 unexpected result opens up an avenue to objectively determine the optimal degree of 25 aggregation at which model predictions have skill, and at which observations are most 26 helpful in constraining model parameters. Our best estimate for Kv in the pelagic 27 pycnocline is around 0.05–0.2 cm/s, in agreement with earlier independent estimates 28 based on tracer dispersion experiments and turbulence microstructure measurements. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://ir.library.oregonstate.edu/downloads/dj52w623b |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Carbon Cycle Carbon Dioxide Centimeter per Second Data model Emission - Male genitalia finding Estimated Experiment Global Warming How True Feel Vigorous Right Now Large Mixing (mathematics) Parametric model Population Parameter Projections and Predictions Tracer Turbulence Version |
| Content Type | Text |
| Resource Type | Article |
