data assimilation

He also became much more interested in the science of data assimilation.

Data assimilation is a part of the challenge for every forecasting problem.

Data assimilation is the process by which observations are incorporated into a computer model of a real system.

Basically, the same types of data assimilation methods as those described above are in use there.

Data assimilation plays an increasingly important role in weather forecasting.

The model is kept close to the real atmosphere using 4D-Var data assimilation of observations.

Mars is the first extraterrestrial planet which data assimilation has been applied to, so far.

Dealing with biased data is a serious challenge in data assimilation.

The data assimilation method used is based on a sequential analysis with a 10-day update cycle.

Data assimilation methods allow the models to incorporate later observations to improve the initial conditions.

In data assimilation applications, the analysis and forecasts are best thought of as probability distributions.

Advanced radar data assimilation for thunderstorm prediction is a key part of the system.

It has an automatically generated adjoint that allows the model to be used for data assimilation.

Data quality is always an issue for chemical data assimilation, in particular the presence of biases.

He was in a trance of data assimilation as graphs and maps cascaded past.

They have extensive knowledge on global data assimilation, dynamic core, physics packages, and ocean models.

AutoChem has been used to perform long term chemical data assimilation of atmospheric chemistry.

Data Assimilation - The process of constraining model predictions to be consistent with observations.

This data assimilation method is used operationally at forecast centres such as the Met Office.

The process of creating the analysis in data assimilation often involves minimization of a "cost function."

It was designed primarily for modeling atmospheric chemistry, and in particular, for chemical data assimilation.

In addition, sophisticated techniques such as data assimilation might be used in order to produce more realistic simulations.

His current interests include data assimilation.

Data assimilation brings these together to yield a simulation that is consistent both with theory and with observations.

Data assimilation periodically adjusts the model state to incorporate new data using statistical methods.