Articles | Volume 14, issue 3
Geosci. Model Dev., 14, 1295–1307, 2021

Special issue: Fusion of radar polarimetry and numerical atmospheric modelling...

Geosci. Model Dev., 14, 1295–1307, 2021

Development and technical paper 10 Mar 2021

Development and technical paper | 10 Mar 2021

Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07)

Yuefei Zeng et al.

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Cited articles

Aksoy, A., Dowell, D. C., and Snyder, C.: A multiscale comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part I: Storm-scale analyses, Mon. Weather Rev., 137, 1805–1824, 2009. a
Ancell, B. C.: Examination of analysis and forecast errors of high-resolution assimilation, bias removal, and digital filter initialization with an ensemble Kalman filter, Mon. Weather Rev., 140, 3992–4004, 2012. a
Baldlauf, M., Seifert, A., Förstner, J., Majewski, D. M., R., and Reinhardt, T.: Operational convective-scale numerical weather prediciton with the COSMO model: description and sensitivities, Mon. Weather Rev., 139, 3887–3905, 2011. a
Bick, T., Simmer, C., Trömel, S., Wapler, K., Stephan, K., Blahak, U., Zeng, Y., and Potthast, R.: Assimilation of 3D-Radar Reflectivities with an Ensemble Kalman Filter on the Convective Scale, Q. J. Roy. Meteor. Soc., 142, 1490–1504, 2016. a, b
Bloom, S. C., Takacs, L. L., Da Silva, A. M., and Ledvina, D.: Data assimilation using incremental analysis updates, Mon. Weather Rev., 124, 1256–1271, 1996. a
Short summary
A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.