Accessibility navigation


The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events

Meng, D., Chen, Y., Wang, H., Gao, Y., Potthast, R. and Wang, Y. (2019) The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events. Atmospheric Research, 219. pp. 1-12. ISSN 0169-8059

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/j.atmosres.2018.12.017

Abstract/Summary

The Weather Research and Forecasting (WRF) model's data assimilation (WRFDA) hybrid ensemble-variational data assimilation (EnVar) system is used to examine the performance of the EnVar method for assimilating cloud liquid/ice water path products. To add flow-dependent features to background error covariance (BEC) of hydrometeors, hydrometeors mixing ratios (Qc, Qi, Qr, Qs) are extended into analysis state vector for the “alpha” control variable. Then the BEC in the updated WRFDA-EnVar system combines the static hydrometeors BEC and flow-dependent hydrometeors BEC derived from ensemble forecasts. The updated system is evaluated by performing a series of single observation tests and two-weeks cycling assimilation and forecasting experiments by assimilating Cloud Liquid/Ice Water Path from NASA. The single observation tests show that the flow-dependent and multivariate BEC is introduced into the updated WRFDA-EnVar system by including extended hydrometeors analysis variables. The cycling assimilation and forecasting experiments demonstrate that by using the updated system included hydrometeors analysis variables, the root mean square errors (RMSEs) of analysis and forecasts are reduced and the Fractions Skill Scores (FSSs) of the precipitation forecasts are increased when compared with 3DVar method and the EnVar method without hydrometeors analysis variables. The diagnostics for a local severe rainfall case in the two-weeks cycling assimilation and forecasting experiments further show that through the application of the EnVar method included hydrometeors analysis variables, the convective available potential energy (CAPE) and humidity are increased effectively, and then better forecasts in terms of spatial distribution and intensity in accumulated precipitation are obtained, as well as cloud component.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
ID Code:82118
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation