[Stoch] Abstract submission deadline for Stochastics session NP8.2 at EGU 2012 is Tue. Jan 17

BALASUBRAMANYA Nadiga btnadiga at gmail.com
Fri Jan 13 17:05:48 MST 2012

Dear Colleague,

With the abstract submission deadline of* Tue, Jan 17 *fast approaching,
pls. consider submitting an abstract to
NP8.2 Stochastic Approaches for Multiscale Modelling in Geosciences
at  the EGU General Assembly, being held 22-27 April 2012 in Vienna
The description of the session is attached below.

We would appreciate if you could also bring this session to the attention
of other interested researchers and students.

You may submit an abstract at

Balu Nadiga, Daniel Schertzer, Jinqiao Duan, Christian Franzke

NP8.2 Stochastic Approaches for Multiscale Modelling in Geosciences

Session Description: The myriad physical processes that occur over a wide
range of spatial and temporal scales in geophysical systems give rise to
complex behavior and low frequency variability.  Neither the importance of
understanding the low frequency variability nor the difficulty of being
able to appropriately model it can be over-emphasized. Indeed, several
deficiencies in predicting such systems (e.g., climate) can be traced back
to a misrepresentation of scale interactions. The latter, in turn, leads to
systematic biases in resolved-scale processes.

>From the modeling point of view, given the nonuniqueness of small scales
with respect to large scales and possible separation of scales between
those explicitly modeled and those studied, stochastic approaches can
provide more realistic representations of the multiscale variability and
allow transitions between attractors.  On the other hand, such approaches
also allow for a quantification of uncertainties that are inherent in the
modeling of these multiscale systems. It is important to note that such
quantification of uncertainty is directly linked to the ability to compare
models and observations, and combine them as in data assimilation

We invite contributions spanning fundamental studies of stochastic
approaches, stochastic modelling of geophysical systems, stochastic
parameterisations,  data assimilation using stochastic methods and extreme
value studies using a stochastic framework.
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