Effects of the wind–mass balance constraint on ensemble forecasts in the hybrid‐4DEnVar
Ensemble forecast covariance plays an important role in the hybridized background error covariance framework to improve the resultant analysis quality. However, a localization of ensemble samples is needed to fully take advantage of flow‐dependent error modes. In this regard, it is an interesting an...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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Main Authors: | , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2019
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Subjects: | |
Online Access: | http://dx.doi.org/10.1002/qj.3440 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.3440 https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3440 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.3440 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3440 |
Summary: | Ensemble forecast covariance plays an important role in the hybridized background error covariance framework to improve the resultant analysis quality. However, a localization of ensemble samples is needed to fully take advantage of flow‐dependent error modes. In this regard, it is an interesting and practical issue as to which variables, composing the ensemble perturbation, the localization should be applied to. This study examines this issue in a boreal‐summer month by comparing two experimental sets: (a) a set of model variables, and (b) another set of model wind variables and unbalanced dry mass (temperature and surface pressure) used for the control variables. In the comparison, it is shown that imposing the wind–mass balance on the ensemble perturbation improves the Antarctic lower‐stratospheric temperature and tropical mid‐/lower‐tropospheric humidity. The nonlinear wind–mass balance relationship smooths an evolution of humidity forecast forced by the resultant analysis increments. |
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