John Marshall (PI)
Massachusetts Institute of Technology
marshall@gulf.mit.edu
Estimating the Climate and Circulation of the Ocean - ECCO ll: High
Resolution Global-Ocean and Sea-Ice Reanalysis
A consortium of university and national laboratory partners propose
to make a major qualitative improvement in the resolution and accuracy
of estimates of the time-evolving global-ocean and sea-ice circulations
by harnessing the vast computational resources of project Columbia and
follow-ons in order to combine (i) the voluminous new global observations
from satellites and from in-situ instruments with (ii) a general circulation
model that incorporates novel gridding techniques and parallel-computing
technologies using (iii) rigorous state estimation methods at hitherto
unachievable resolutions. Specifically, a mesoscale-eddy-resolving model
will be constrained by all relevant,global-scale, NASA and other data
streams in order to obtain a best-possible reanalysis of the global-ocean
and sea-ice circulations for applications in climate research and forecasting. The
proposed work is made possible by recent advances in ocean state estimation
technology (ECCO: Estimating the Circulation and Climate of the Ocean),
in modeling infrastructure (ESMF: Earth System Modeling Framework), in
computational fluid dynamics (MITgcm: Massachusetts Institute of Technology
general circulation model), and in automatic differentiation (AD). The
following strands will be developed: (i) very high resolution simulations
of ocean circulation and sea-ice distribution using the MITgcm model,
(ii) assimilation of satellite and in-situ global data sets at mesoscale-eddy-resolving
resolution using rigorous state estimation methods, (iii) detailed evaluation
of resulting ocean-circulation and sea-ice estimates, including comparisons
with existing coarse-resolution estimates and quantitative statements
about residual uncertainties, (iv) demonstration science applications,
including analysis of heat budgets, studies of climate variability, sensitivity,
and predictability, and estimates of error covariance matrices for the
Global Modeling and Assimilation Office (GMAO) seasonal-to-interannual
prediction effort, and (v) ground-breaking scientific visualization and
distribution of massive quality-controlled data sets, ocean and sea-ice
state estimates, and ESMF-compliant modeling and estimation software
to the community. The proposed work will strengthen the connection
between NASA's modeling and remote sensing strategies and will enhance
the value of NASA satellite retrievals for studies and discussions about
climate and climate variability
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