Numerical Prediction Development Center, Japan Meteorological Agency, Tsukuba, Ibaraki 305-0052, Japan
Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Ibaraki 305-0052, Japan
Miodrag Rancic
NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland 20740, USA
Lynker, College Park, Maryland 20740, USA
Ting Lei
NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland 20740, USA
Lynker, College Park, Maryland 20740, USA
R. James Purser
NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland 20740, USA
Lynker, College Park, Maryland 20740, USA
Manuel S. F. V. De Pondeca
NOAA/NWS/NCEP/Environmental Modeling Center, College Park, Maryland 20740, USA
Lynker, College Park, Maryland 20740, USA
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Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 6,936 (including HTML, PDF, and XML)
Thereof 6,914 with geography defined
and 22 with unknown origin.
Total article views: 900 (including HTML, PDF, and XML)
Thereof 881 with geography defined
and 19 with unknown origin.
Total article views: 6,036 (including HTML, PDF, and XML)
Thereof 6,033 with geography defined
and 3 with unknown origin.
Covariance localization to mitigate sampling error of ensemble-based forecast error covariances is one of the main parts of the calculation in ensemble-variational data assimilation for the atmosphere. This study clarifies that the multigrid beta filter-based localization makes it several times faster than the conventional recursive filter-based one without significantly changing the analysis if a coarser filter grid is applied and filters except for the coarsest resolution are omitted.
Covariance localization to mitigate sampling error of ensemble-based forecast error covariances...