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An update on the 4D-LETKF data assimilation system for the whole neutral atmosphere

Dai Koshin, K. Sato, Masashi Kohma, Shingo Watanabe

2022Geoscientific model development17 citationsDOIOpen Access PDF

Abstract

Abstract. The four-dimensional local ensemble transform Kalman filter (4D-LETKF) data assimilation system for the whole neutral atmosphere is updated to better represent disturbances with wave periods shorter than 1 d in the mesosphere and lower thermosphere (MLT) region. First, incremental analysis update (IAU) filtering is introduced to reduce the generation of spurious waves arising from the insertion of the analysis updates. The IAU is better than other filtering methods, and also is commonly used for middle atmospheric data assimilation. Second, the order of horizontal diffusion in the forecast model is changed to reproduce the more realistic tidal amplitudes that were observed by satellites. Third, the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) and Special Sensor Microwave Imager/Sounder (SSMIS) observations in the stratosphere and mesosphere also are assimilated. The performance of the resultant analyses is evaluated by comparing them with the mesospheric winds from meteor radars, which are not assimilated. The representation of assimilation products is greatly improved not only for the zonal mean field but also for short-period and/or horizontally small-scale disturbances.

Topics & Concepts

Data assimilationThermosphereEnvironmental scienceDepth soundingAtmosphere (unit)Microwave Limb SounderMesosphereStratosphereMeteorologyEnsemble Kalman filterSpurious relationshipRemote sensingKalman filterAtmospheric sciencesClimatologyIonosphereGeologyComputer sciencePhysicsGeophysicsExtended Kalman filterArtificial intelligenceMachine learningOceanographyMeteorological Phenomena and SimulationsClimate variability and modelsIonosphere and magnetosphere dynamics
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