Articles | Volume 34, issue 2
https://doi.org/10.5194/angeo-34-187-2016
https://doi.org/10.5194/angeo-34-187-2016
Regular paper
 | 
09 Feb 2016
Regular paper |  | 09 Feb 2016

Impact of variational assimilation using multivariate background error covariances on the simulation of monsoon depressions over India

M. Dhanya and A. Chandrasekar

Viewed

Total article views: 1,465 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
851 560 54 1,465 82 70
  • HTML: 851
  • PDF: 560
  • XML: 54
  • Total: 1,465
  • BibTeX: 82
  • EndNote: 70
Views and downloads (calculated since 09 Feb 2016)
Cumulative views and downloads (calculated since 09 Feb 2016)

Cited

Latest update: 21 Nov 2024
Download
Short summary
The three-dimensional variational technique (3DVar) is a popular technique used for data assimilation. Background error covariance (BEC) influences the performance of 3DVar technique. In this study, two formulations of BEC, namely the cv5 and cv6 options in the 3DVar assimilation in the Weather Research and Forecasting (WRF) model, are compared. It is found that the formulation of BEC impacts the analysis. Utilising the cv6 option moderately improves the simulation of monsoon depressions.