Hybridizing Bayesian and variational data assimilation for high-resolution hydrologic forecasting

The Ensemble Variational Assimilation and Bayesian Estimation

The purpose of assimilation can be stated as to determine the probability distribution for the state of the observed system, conditioned by the available data. In the case of linearity and additive Gaussian errors, a sample of independent realizations of the (Gaussian) conditional probability distribution can be obtained by repeating the following process. Perturb the data according to their ow...

A review of operational methods of variational and ensemble-variational data assimilation: Ensemble-variational data assimilation

Variational and ensemble methods have been developed separately by various research and development groups and each brings its own benefits to data assimilation. In the last decade or so, various ways have been developed to combine these methods, especially with the aims of improving the background-error covariance matrices and of improving efficiency. The field has become confusing, even to ma...

Variational Assimilation of Remote Sensing Data for Land Surface Hydrologic Applications

Soil moisture plays a major role in the global hydrologic cycle. Most importantly, soil moisture controls the partitioning of available energy at the land surface into latent and sensible heat fluxes. We investigate the feasibility of estimating large-scale soil moisture profiles and related land surface variables from low-frequency (L-band) passive microwave remote sensing observations using w...

Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly q...

Adjoint sensitivity analysis and variational data assimilation for flash flood forecasting