Joint Seminar: Global highest resolution ensemble weather forecast model for extremes precipitation events and latest model developments initiatives for improved forecasting

Global highest resolution ensemble forecast system have been established based
on NCEP Global Forecast System (GFS) with 21 ensemble members (GEFS)
and probabilistic forecast up to 10 days is issued. Apart from the high resolution
weather forecast system, India also has the highest resolution seasonal forecast
system for dynamical forecast of monsoon with a horizontal resolution of
~38km based on NCEP CFS (coupled forecast system) and also there is an
efficient extended range forecast system (up to 4 pentads) based on GFS and
CFS mostly for agricultural guidance.

The high resolution (12km) ensemble forecast system has efficiently predicted
the monsoon heavy rain events during the monsoon season of 2018. However,
the GFS and CFS systems are known to have some significant bias over land as
well as over Ocean. The coupled CFSv2 model shows significant dry
precipitation bias over global land areas and a wet precipitation bias over global
ocean. Although the high resolution atmospheric model (GFS) does not show
the dry precipitation bias over Indian land mass.

Keeping the biases of CFS and GFS in to account, several latest developments
have been attempted. The Stochastic multi cloud model (SMCM) and another
version of SMCM constrained with DYNMO radar have been implemented. A
holistic approach with convection-cloud micropysics-radiation has been done in
the GFS and CFS and it has improved the model fidelity.

Lastly, keeping the limited scalability of GFS (semi lagrangian) model in to
account, the spectral cubic octahedral (Tco) has been implemented ad a version
of GFS with Tco has been developed and presently under test for various
convective regimes.




13:30 h


Bundesstr. 53, room 022/023
Seminar Room 022/023, Ground Floor, Bundesstrasse 53, 20146 Hamburg, Hamburg


Parthasarathi Mukhopadhyay, Indian Institute of Tropical Meteorology


Bjorn Stevens

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