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Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model
Ist Teil von
Nonlinear processes in geophysics, 2019-08, Vol.26 (3), p.211-225
Ort / Verlag
Gottingen: Copernicus GmbH
Erscheinungsjahr
2019
Link zum Volltext
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
We previously performed local ensemble transform Kalman filter (LETKF)
experiments with up to 10 240 ensemble members using an intermediate
atmospheric general circulation model (AGCM). While the previous study
focused on the impact of localization on the analysis accuracy, the present
study focuses on the probability density functions (PDFs) represented by the
10 240-member ensemble. The 10 240-member ensemble can resolve the detailed
structures of the PDFs and indicates that non-Gaussianity is caused in those
PDFs by multimodality and outliers. The results show that the spatial
patterns of the analysis errors are similar to those of non-Gaussianity.
While the outliers appear randomly, large multimodality corresponds well
with large analysis error, mainly in the tropical regions and storm track
regions where highly nonlinear processes appear frequently. Therefore, we
further investigate the life cycle of multimodal PDFs, and show that they
are mainly generated by the on–off switch of convective
parameterization in the tropical regions and by the instability associated
with advection in the storm track regions. Sensitivity to the ensemble size
suggests that approximately 1000 ensemble members are necessary in the
intermediate AGCM-LETKF system to represent the detailed structures of
non-Gaussian PDFs such as skewness and kurtosis; the higher-order
non-Gaussian statistics are more vulnerable to the sampling errors due to a
smaller ensemble size.