Session NP5.1 "Inverse Problems and Data Assimilation'', General Assembly, European Geosciences Union, Vienna, Austria, 17-22 April 2016
We would like to draw your attention to the session 'Inverse Problems and Data Assimilation' (session NP5.1, Programme Group 'Nonlinear Processes in Geosciences') to be held during the upcoming General Assembly of the European Geosciences Union (Vienna, Austria, 17-22 April 2016).
This session will be devoted to all aspects of Inverse Problems and Data Assimilation in Geophysics. A detailed description is given below.
The deadline for receipt of abstracts is 13 January 2016, 13:00 CET. An Abstract Processing Charge (APC) of €40.00 gross must be paid for each abstract submission.
Possibilities of financial support are available for young scientists, as well as for established scientists from low, lower middle, and upper middle income countries. Requests for financial support must be submitted, together with an abstract, by 1 December 2015.
General information on the General Assembly, in particular instructions for submitting abstracts and requests for financial support, is available at the address: http://www.egu2016.eu/
Identification of the session : Programme Group 'Nonlinear Processes in Geosciences', Session NP5.1
Solicited lecturers for the session: Thomas Bodin (ENS Lyon, France) and Marc Bocquet (CEREA, Marne-la-Vallée, France)
Please send this announcement to colleagues you think may be interested.
Alberto Carrassi (MCRN Member)
Description of the session
Inverse Problems are encountered in many fields of Geosciences, for the purpose of either prediction or inference. One class of inverse problems, in the context of predictability, is assimilation of observations in dynamical models of the system under study.
This session will be devoted to the presentation and discussion of methods for inverse problems and data assimilation, in ocean and atmosphere dynamics, solid earth geophysics, atmospheric chemistry, hydrology and, more generally, in all fields of geophysics.
Data assimilation in coupled models (for example ocean/atmosphere models) is an emerging area of development for forecasting and reanalysis at operational centres. We particularly encourage contributions related to research aimed at understanding and developing such coupled data assimilation systems.
We also encourage reports on advanced methods, and related mathematical developments, suitable for situations in which local linear and Gaussian hypotheses are not valid and/or in the presence of model error. Contributions dealing with algorithmic aspects and numerical implementation of the solution of inverse problems are welcome, as well as contributions dealing with quantification of uncertainty in inverse and data assimilation problems.