Remote Sensing for Geophysical Fluids
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 2684
Special Issue Editor
2. Institut national de recherche en informatique et en automatique (INRIA), 75589 Paris, France
Interests: computational fluid dynamics, numerical modeling, applied and computational mathematics, remote sensing, atmospheric physics, meteorology, geophysics, climate science, atmospheric pollution, numerical weather prediction, optimization algorithms, ocean modeling, parameter estimation, sensitivity analysis, data assimilation
Special Issue Information
Dear Colleagues,
For more than six decades, our knowledge of the fluid environment of the Earth and of some of the planets of the Solar System has grown considerably, and this mainly due to two factors:
-The development of an important network of sensors for the observation of the Earth, i.e., satellites used in a large domain of wavelengths and used for routine prediction and basic research, lidars, radars, GPS signals, etc.
-The development of HPC has led to the significant development of mathematical modeling for geophysical processes in oceanic-atmospheric sciences in the framework of operational prediction or of impact studies, and also of climatological studies.
These studies inspired two questions:
-For a given model, what is the “optimal” network of sensors?
-For a given network of sensors, what are the “optimal” models that need to be developed?
For these questions, the concept of optimality has to be precisely defined; it is also a question by itself, and it is an important topic to be considered in this Special Issue. In the term “Geophysical Fluids”, we include the ocean, the atmosphere, the cryosphere, and their interfaces, both from the observational and computational viewpoints.
The purpose of this Special Issue is to publish the latest developments in remote sensing and in models for geophysical fluids. We wish to emphasize the link between data and models: what is the best way incorporate data in models? Studies of the impact of errors and error propagation from observation to the solution of numerical models will be encouraged, as well as data assimilation and sensitivity studies.
Prof. Dr. François Xavier Le Dimet
Guest Editor
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Keywords
- Observation of the liquid envelope of the Earth
- Oceanography
- Meteorology
- Hydrology
- Interfaces of geophysical fluids
- Satellites
- Radar
- Lidar
- GPS and other electromagnetic signals
- Chemical components of the environment
- Climatological observations
- Interfaces between the components of the environment
- Network of remote sensors
- Error propagation
- Data assimilation
- Coupled models
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