High-resolution decadal prediction - impacts on the predictability of the Pacific variability
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/346252
Tipus de documentText en actes de congrés
Data publicació2021-05
EditorBarcelona Supercomputing Center
Condicions d'accésAccés obert
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Abstract
Decadal prediction is a relatively recent field of research,
attracting growing interest beyond the scientific community
due to its strong potential to provide key information for
decision making in economic sectors (e.g. energy production,
agriculture, insurance) in a context of pressing danger of
climate change. Decadal climate prediction (DCP) skill can
arise from two major sources. The first is related to the external
radiative forcings (such as volcanic eruptions, solar activity or
the anthropogenic greenhouse gases), whose past variations
have caused important climate trends in recent decades. And
the second is the internal low-frequency variability, usually
associated with oceanic processes operating at decadal and
multi-decadal timescales. The premise of DCP is that such
internal variability processes, when adequately modelled and
initialized, can improve our predictive capacity not only on the
oceans but also over the surrounding land areas, such as in the
North Atlantic region [1].
However, one major limitation common to current DCP
systems is the little skill that they present over the continents,
which appears to be connected to an incorrect representation
of the teleconnection mechanisms that, mediated via
the atmosphere, connect the ocean with the neighbouring
continents. There are several indications that the current generation
of models at standard resolution misrepresents those
key teleconnections, and that higher resolution versions might
improve them, decreasing common biases of global models
and improving some regional seasonal prediction skills, e.g.
in tropical sea surface temperature [2]. For decadal prediction,
it is still unclear if similar improvements can be achieved
through increased resolution, as these systems involve many
more simulation years than the seasonal ones, which have
made them computationally unaffordable until now.
In this study, we explore how the forecast skill of the
DCP can be improved by increasing the spatial resolution of
the model. A specific focus on ENSO predictive skill and its
associated climate teleconnections will be given to investigate
the predictability of the Pacific Ocean, given the promising
results of the resolution of oceanic eddies and therefore their
effect on the ocean variability [3].
CitacióCarréric, A.; Ortega, P. High-resolution decadal prediction - impacts on the predictability of the Pacific variability. A: . Barcelona Supercomputing Center, 2021, p. 22-23.
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BSC_DS-2021-02_High-Resolution Decadal.pdf | 410,7Kb | Visualitza/Obre |