This paper describes a particle filter in the global NWP at Deutscher
Wetterdienst (DWD). A particle filter (PF) in the global NWP at DWD is
proposed and evaluated its skills in comparison with the operational
system. To alleviate the degeneration, which is the largest issue in PFs
high-dimensional systems, several approaches are effectively
incorporated such as localization, Gaussian mixture approximation in the
prior distribution, adaptive resampling, and so on (See Section 2.3).
Since comprehensive formulations in this system are described, the
readers can totally understand its theoretical aspects.
This paper describe a newly developed operational seasonal forecast
system, JMA/MRI-CPS3. Ocean 4D-Var and sea ice 3D-Var data assimilation
methods are newly
introduced. The errors in the ocean analysis are now represented in the
initial perturbations. Updated physical processes and increased
resolution of the
atmospheric model contribute to the improved climate reproducibility of
the MJO and North Atlantic blocking highs. The introduction of a
0.25-degree-resolution ocean model
provides a realistic representation of tropical instability waves and
contributes to improved ENSO pattern.
This paper proposed a machine learning method as an observation
operator for satellite radiances within a data assimilation system.
Model forecast and satellite microwave radiance observations
are used to train machine learning models to obtain the observation
operator for satellite data assimilation.Data assimilation experiments using the machine learning-based
observation operator show promising results without a separate bias
correction procedure.The machine learning-based observation operator can potentially
accelerate the development of using new satellite observations in
numerical weather prediction.
This paper proposed a new method calculating the threshold wind speed for dust occurrence.
A new method to obtain threshold wind speed that takes account
of the interannual variations of dry vegetation cover is proposed. Dry vegetation coverage is a key factor determining interannual variations in the April dust occurrence. Other land surface factors such as soil freeze-thaw and snow
cover should be considered to explain dust occurrence variations in
Yamaguchi and Maeda (2020) The above paper was press released. (25 Aug. 2020)
Press release document (in Japanese)
Kawabata and Yamaguchi (2020): The above paper was chosen as a JMSJ Editor's Highlight. (13 Jul. 2020)
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Stevens et al. (2020): The above paper was chosen as a JMSJ Editor's Highlight. (5 Mar. 2020)
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Takemura and Mukougawa (2020): The above paper was chosen as a JMSJ Editor's Highlight. (4 Jan. 2020)
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