Articles | Volume 29, issue 4
https://doi.org/10.5194/npg-29-329-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-29-329-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using a hybrid optimal interpolation–ensemble Kalman filter for the Canadian Precipitation Analysis
Dikraa Khedhaouiria
CORRESPONDING AUTHOR
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Stéphane Bélair
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Vincent Fortin
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Guy Roy
Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, QC, Canada
Franck Lespinas
Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, QC, Canada
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Short summary
This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms that has not yet been explored for precipitation analyses. Our approach combined an ensemble-based DA approach with an existing deterministically based DA. Both DA scheme families have desirable aspects that can be leveraged if combined. The DA hybrid method showed better precipitation analyses in regions with a low rate of assimilated surface observations, which is typically the case in winter.
This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms...