Nomination for: S. Zhang, M. J. Harrison, A. Rosati and A. Wittenberg,
2007: "System design and evaluation of coupled ensemble data
assimilation for global oceanic climate studies", Mon. Wea. Rev., 135,
3541-3564.

Given the probabilistic nature of climate evolution, a complete solution
of numerical climate prediction is the temporally-varying probability
density function (PDF) of climate states in the future time. One of
major challenges to make numerical climate prediction is how to sample
the initial PDF. Traditional \`\`perturbation\'\' approach \-- imposing
noises on certain components of coupled model \-- only is an artificial
approximation of the initial PDF and the introduced numerical artifacts
may contaminate projections of signal. This study is a pioneering effort
in producing coherent ensemble initial conditions for a fully-coupled
climate system by incorporating observed data into model dynamics. In
the Ensemble Coupled Data Assimilation System (ECDAS) that was designed
and implemented in this study, various historical records about some
aspects of climate states are absorbed into every components of coupled
model by a continuous filtering process using the joint distribution
function derived from coupled dynamics. Within the ECDAS, both the
reconstruction of historical climate states and the production of
numerical climate prediction become a natural process \-- a set of
continuous coupled model simulations with or without constraints of
observed data. In this procedure, the consistent coupled components in
each ensemble member ensure that the model integration is the dynamical
projection of initial signals on the future time.

Not only did this study present extraordinary technical achievement
(super-parallelization, sparse observation processing technique etc.)
but also highlighted the\
importance to the global circulation of maintaining realistic physical
relationships among model variables \-- like water mass properties in
the ocean, and geostrophy in the atmosphere \-- and demonstrated the
ability of the coupled ensemble filter to maintain those relationships. 
The study also performed some clever model experiments to assess the
adequacy of the historical observing system for reconstructing
20th-century variations and trends in ocean heat content.

This study has already had profound and far-reaching impacts on the
field\
of climate research (in the 5 months since its publication in October
2007, this paper has received four citations).  In addition to
pioneering the field of ensemble coupled data assimilation, it has
produced a highly flexible assimilation system that is now being used at
GFDL to generate improved global seasonal-to-interannul forecasts, to
assess climate variability and trends over the 20th century, and to
assess the skill of decadal predictions. One of major applications of
this system in the near future will be to initialize the coupled states
for decadal projections of the meridional overturning circulations which
is an important theme for the next IPCC assessment report. Another
extension of the application of the outlined ECDAS is the initialization
of high-resolution coupled model which may be able to produce the
forecast for the genesis of hurricane. Then, although new challenges
still exist for applying to the new generation coupled model with much
higher resolution and much more complicated physical processes the work
outlined in this paper will have more impacts on numerical weather and
climate predictions in the future.