地球惑星科学専攻 地球科学輻合部特別講演会

日時: 2010年2月26日(金) 15:00 - 17:00
場所: 京都大学理学部1号館 563号室
題目: Conditional nonlinear optimal perturbation and its applications in predictability studies of weather and climate
講演者: Dr. Mu Mu (LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences)

講演要旨:
Linear singular Vector (LSV) is one of the useful tools in the
predictability studies of weather and climate.
However, the linear approximation required by the approach of LSV has
strong limitations since it ignores
the nonlinear processes. The  author and his colleagues have proposed
a new method  called CNOP
(Conditional Nonlinear Optimal Perturbation), which generalizes LSVs
into the fully nonlinear regime.
CNOP is the initial perturbation whose nonlinear evolution attains the
maximum value of the cost function,
which is constructed according to the problems of interests with
physical constraint conditions. In predictability
study ,CNOP represents the initial error that has largest effect on
the uncertainties at the prediction time.
In sensitivity and stability analysis of fluid motions, CNOP also
describes the most nonlinearly unstable (or most
sensitive) mode.
In this talk, we first review the approach of CNOPs and the algorithms
 to calculate them .Then the applications
of CNOP in the predictability study ,sensitivity analysis will be
briefly introduced . As two examples , we will show
the advantages of CNOPs in the studies of Spring predictability
barrier (SPB) of ENSO prediction , and in the
determination of sensitivity area in targeted observations for
tropical cyclones.
Extensions of conditional nonlinear optimal perturbation of initial
conditions to parameters of numerical model
will be investigated , and prospect and challenge in the future
applications of CNOP are also discussed.

問い合わせ先: 余田成男