Atmospheric data assimilation is a class of techniques used for producing descriptions of fields of air temperature, pressure, humidity, wind, etc. on a spatial grid or in terms of a finite functional representation. These are then used to initialize numerical weather forecasts or to analyze the atmosphere for other purposes. The techniques combine past, present, and even future observations in an approximate statistically optimal way. Various types of statistical or physically-based models and their corresponding adjoints are employed to relate diverse fields in both time and space and to relate what is observed to what is being analyzed. Computationally, the problem is very demanding and onstraining on the techniques that can be employed ...
International audienceWe commonly refer to state estimation theory in geosciences as data assimilati...
This thesis studies the benefits of simultaneously considering system information from different sou...
Data Assimilation: From an Eventful Past to a Bright Future Michael Ghil, Ecole Normale Supérieure ...
The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly fla...
The seamless integration of large data sets into sophisticated computational models provides one ...
When you describe a physical process, for example, the weather on Earth, or an engineered system, su...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceData assimilation aims at determining as accurately as possible the state of a...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
none4siWe commonly refer to state estimation theory in geosciences as data assimilation (DA). This t...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
International audienceData assimilation aims at determining as accurately as possible the state of a...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceWe commonly refer to state estimation theory in geosciences as data assimilati...
This thesis studies the benefits of simultaneously considering system information from different sou...
Data Assimilation: From an Eventful Past to a Bright Future Michael Ghil, Ecole Normale Supérieure ...
The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly fla...
The seamless integration of large data sets into sophisticated computational models provides one ...
When you describe a physical process, for example, the weather on Earth, or an engineered system, su...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceData assimilation aims at determining as accurately as possible the state of a...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
none4siWe commonly refer to state estimation theory in geosciences as data assimilation (DA). This t...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
International audienceData assimilation aims at determining as accurately as possible the state of a...
We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term enc...
International audienceData assimilation aims at determining as accurately as possible the state of a...
International audienceWe commonly refer to state estimation theory in geosciences as data assimilati...
This thesis studies the benefits of simultaneously considering system information from different sou...
Data Assimilation: From an Eventful Past to a Bright Future Michael Ghil, Ecole Normale Supérieure ...