4:00 PM - 4:15 PM
[AAS02-09] Inter-comparison of the hybrid variational-ensemble methods
Keywords:variational data assimilation, ensemble Kalman filter, hybrid covariance, hybrid gain
In a hybrid method a specific operator is taken as a linear combination from the corresponding operators in the variational part and the ensemble part. If this operator is the background covariance we have the hybrid covariance method (hybrid B). In case the Kalman gain is chosen we have the hybrid gain method (hybrid K). In some variants of the hybrid covariance method, the operators in the factor form of the background covariance can be used. That means we can take a linear combination between background variances (hybrid V) or background correlations.
In the Strategic Programs for Innovative Research (SPIRE) Field 3, besides the traditional methods like 4DVAR and EnKF, hybrid methods have been implemented in the K Computer under a unified hybrid assimilation system for the Japan Meteorological Agency (JMA) limited-area operational model NHM. The system consisted of two components: the variational one 4DVAR and the ensemble one 4D-LETKF. The variational part was adopted from the JNoVA system developed at JMA. The ensemble part was based on the NHM-LETKF system developed at JMA. There is a two-way interaction between two sub-systems.
Real observation experiments were carried out for the August in 2014. This month was characterized by abnormal rainfall over the western Japan with two tropical cyclones and several heavy rainfall events. To verify performance of three hybrid methods (Hybrid B, Hybrid V, and Hybrid K) the same 50-50 weights were used in all hybrid experiments. In addition to the hybrid experiments, JNoVA and NHM-LETKF were run over the same period. Verification shows that all hybrid methods and JNoVA outperformed NHM-LETKF. Using JNoVA as the control method, Hybrid B and Hybrid K were slightly better than JNoVA. Hybrid V can beat JNoVA at some pressure level but in general Hybrid V was slightly worse than JNoVA. Hybrid B and Hybrid K were comparable in predicting atmospheric variables. Further verification against rainfall analyses points out that Hybrid K was comparable to JNoVA, whereas Hybrid B was better than JNoVA significantly in predicting precipitation especially for rainfall thresholds greater than 20 mm.