Introduction to Data Assimilation: Lecture 1 Saroja Polavarapu Meteorological Research Division Environment Canada PIMS Summer School, Victoria. July 14-18,
Sensitivity Studies (1): Motivation Theoretical background. Sensitivity of the Lorenz model. Thomas Jung ECMWF, Reading, UK ([email protected])
Robin Hogan, Nicola Pounder, Chris Westbrook University of Reading, UK Julien Delanoë LATMOS, France Alessandro Battaglia University of Leicester, UK Retrieving.
13 th EMS Annual Meeting & 11 th European Conference on Applications of Meteorology 9 th – 13 th September 2013Reading, UK Ensemble prediction as a tool.
Impacts of Improved Error Analysis on the Assimilation of Polar Satellite Passive Microwave Precipitation Estimates into the NCEP Global Data Assimilation.
1 Accomplishments: * Nested ROMS in larger domain forward simulation (MABGOM-ROMS) with configuration suitable for IS4DVAR experimentation. Considerations:
1 Hans Huang: WRF 4D-Var Seminar at UCD 5th October 2006 WRF 4D-Var The Weather Research and Forecasting model based 4-Dimensional Variational data assimilation.
(Inverse) Multiscale Modelling Martin Burger Institut für Numerische und Angewandte Mathematik Westfälische Willhelms-Universität Münster.
Sensitivity Analysis of SST along NJ coast with ADROMS Weifeng (Gordon) Zhang John Wilkin Julia Levin Hernan Arango Institute of Marine and Coastal Sciences,
Bob Yantosca Philippe Le Sager Claire Carouge Atmospheric Chemistry Modeling Group School of Engineering & Applied Sciences Harvard University [email protected].
Forecast Sensitivity to Observations & Observation Impact Tom Auligné
Observation Targeting Andy Lawrence Predictability and Diagnostics Section, ECMWF Acknowledgements: Martin Leutbecher, Carla Cardinali, Alexis Doerenbecher,