This work explores the potential of online parameter estimation as a technique for model error treatment under an imperfect model scenario, in an ensemble-based data assimilation system, using a simple atmospheric general circulation model, and an observing system simulation experiment (OSSE) approach. Model error is introduced in the imperfect model scenario by changing the value of the parameters associated with different schemes. The parameters of the moist convection scheme are the only ones to be estimated in the data assimilation system. In this work, parameter estimation is compared and combined with techniques that account for the lack of ensemble spread and for the systematic model error. The OSSEs show that when parameter estimati...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
© Copyright 2006 American Meteorological Society (AMS). Permission to use figures, tables, and brief...
This thesis studies the benefits of simultaneously considering system information from different sou...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
In this work, various methods for the estimation of the parameter uncertainty and the covariance bet...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
Insufficient model resolution is one source of model error in numerical weather predictions. Meth-od...
Weather forecast and earth system models usually have a number of parameters, which are often optimi...
International audienceA new methodology is proposed to estimate and account for systematic model err...
A new methodology is proposed to estimate and account for systematic model error in linear filtering...
We review the field of data assimilation (DA) from a Bayesian perspective and show that, in addition...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
© Copyright 2006 American Meteorological Society (AMS). Permission to use figures, tables, and brief...
This thesis studies the benefits of simultaneously considering system information from different sou...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
In this work, various methods for the estimation of the parameter uncertainty and the covariance bet...
This study explores the viability of parameter estimation in the comprehensive general circulation m...
Insufficient model resolution is one source of model error in numerical weather predictions. Meth-od...
Weather forecast and earth system models usually have a number of parameters, which are often optimi...
International audienceA new methodology is proposed to estimate and account for systematic model err...
A new methodology is proposed to estimate and account for systematic model error in linear filtering...
We review the field of data assimilation (DA) from a Bayesian perspective and show that, in addition...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
To account for model error on multiple scales in convective‐scale data assimilation, we incorporate ...
© Copyright 2006 American Meteorological Society (AMS). Permission to use figures, tables, and brief...
This thesis studies the benefits of simultaneously considering system information from different sou...