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| Titel |
Model derived uncertainty in observed deep ocean heat content trends |
| VerfasserIn |
Freya Garry, Elaine McDonagh, Damien Desbruyères, Brian King, Adam Blaker, Eleanor Frajka-Williams, Chris Roberts |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250094203
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| Publikation (Nr.) |
 EGU/EGU2014-9601.pdf |
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| Zusammenfassung |
| We subsample a high-resolution ocean-only model to estimate uncertainty associated with
observational estimates of deep ocean heat content. The deep ocean is a potentially vast
reservoir for heat uptake, but the slowdown of surface air temperature warming in the early
twenty-first century suggests that heat uptake is variable. It is therefore necessary to quantify
entire ocean heat content changes to reduce uncertainty in climate projections and sea level
rise estimates. While the Argo network effectively samples the 0-2000m layer, deep
ocean observations are spatially and temporally limited, with our best estimates of
heat content change relying on repeat hydrographic sections. Here we estimate
the uncertainty associated with heat content changes from repeat hydrographic
sections.
We use a historical 1/12° simulation of the eddy permitting ocean model NEMO
between 1980 and 2010, with a focus on the North-East Atlantic. Two types of uncertainty
are considered to address the representativeness of large-scale heat content estimates
generated from observations:
* There are typically 5-year intervals between repeat hydrographic sections, so temporal
uncertainty is concerned with how well observations reflect the true variability or whether a
strongly aliased signal is measured.
* Spatial uncertainty exists because two or three repeated sections in a basin may not be
representative of the heat content variability of the whole basin.
We find that in the sub-2000m North-East Atlantic temperature trends on hydrographic
sections are captured well by typically pentadal sampling. Spatial uncertainty results in a
systematic difference between trends from whole-basin sampling of the model and
those determined from subsampling the hydrographic sections. Warming between
2000-2500m is overestimated by 10%. Between 3000-5000m, on average 67% of a cooling
trend across the basin is captured on subsampled sections, increasing with depth to
5000m where the sub-sampled and whole-basin estimates agree. In this analysis
we use basin average temperatures from 1990 to reduce the influence of model
spin-up.
This analysis implies that repeated hydrographic sections in the North-East Atlantic
capture the sense of trends in deep ocean heat content well, but where a significant trend is
present they systematically over- or under-estimate the trend by up to 100% depending on the
depth. Our model analysis suggests that, in total, subsampling repeat hydrographic sections
underestimates cooling beneath 2000m by 8% between 1990 and 2010 in the North-East
Atlantic. |
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